references.bib

% Centiloid

@article{klunk2015centiloid,
  title      = {The Centiloid Project: standardizing quantitative amyloid plaque estimation by PET},
  author     = {William E Klunk and Robert A Koeppe and Julie C Price and Tammie L Benzinger and Michael D Devous and William J Jagust and Keith A Johnson and Chester A Mathis and Davneet Minhas and Michael J Pontecorvo and Christopher C Rowe and Daniel M Skovronsky and Mark A Mintun},
  year       = {2015},
  month      = {Jan},
  journal    = {Alzheimer's & dementia : the journal of the Alzheimer's Association},
  volume     = {11},
  number     = {1},
  pages      = {1-15.e1-4},
  eprint     = {25443857},
  doi        = {10.1016/j.jalz.2014.07.003},
  language   = {eng},
  issn       = {1552-5279},
  abstract   = {Although amyloid imaging with PiB-PET ([C-11]Pittsburgh Compound-B positron emission tomography), and now with F-18-labeled tracers, has produced remarkably consistent qualitative findings across a large number of centers, there has been considerable variability in the exact numbers reported as quantitative outcome measures of tracer retention. In some cases this is as trivial as the choice of units, in some cases it is scanner dependent, and of course, different tracers yield different numbers. Our working group was formed to standardize quantitative amyloid imaging measures by scaling the outcome of each particular analysis method or tracer to a 0 to 100 scale, anchored by young controls (≤ 45 years) and typical Alzheimer's disease patients. The units of this scale have been named "Centiloids." Basically, we describe a "standard" method of analyzing PiB PET data and then a method for scaling any "nonstandard" method of PiB PET analysis (or any other tracer) to the Centiloid scale.},
  eprinttype = {pubmed}
}
@article{keator2020down,
  title      = {Down syndrome: Distribution of brain amyloid in mild cognitive impairment},
  author     = {David B Keator and Michael J Phelan and Lisa Taylor and Eric Doran and Sharon Krinsky-McHale and Julie Price and Erin E Ballard and William C Kreisl and Christy Hom and Dana Nguyen and Margaret Pulsifer and Florence Lai and Diana H Rosas and Adam M Brickman and Nicole Schupf and Michael A Yassa and Wayne Silverman and Ira T Lott},
  year       = {2020},
  month      = {04},
  journal    = {Alzheimer's & dementia (Amsterdam, Netherlands)},
  volume     = {12},
  number     = {1},
  pages      = {e12013},
  eprint     = {32435685},
  doi        = {10.1002/dad2.12013},
  language   = {eng},
  issn       = {2352-8729},
  abstract   = {INTRODUCTION: Down syndrome (DS) is associated with a higher risk of dementia. We hypothesize that amyloid beta (Aβ) in specific brain regions differentiates mild cognitive impairment in DS (MCI-DS) and test these hypotheses using cross-sectional and longitudinal data.
                METHODS: 18F-AV-45 (florbetapir) positron emission tomography (PET) data were collected to analyze amyloid burden in 58 participants clinically classified as cognitively stable (CS) or MCI-DS and 12 longitudinal CS participants.
                RESULTS: The study confirmed our hypotheses of increased amyloid in inferior parietal, lateral occipital, and superior frontal regions as the main effects differentiating MCI-DS from the CS groups. The largest annualized amyloid increases in longitudinal CS data were in the rostral middle frontal, superior frontal, superior/middle temporal, and posterior cingulate cortices.
                DISCUSSION: This study helps us to understand amyloid in the MCI-DS transitional state between cognitively stable aging and frank dementia in DS. The spatial distribution of Aβ may be a reliable indicator of MCI-DS in DS.},
  eprinttype = {pubmed}
}
@article{navitsky2018standardization,
  title      = {Standardization of amyloid quantitation with florbetapir standardized uptake value ratios to the Centiloid scale},
  author     = {Michael Navitsky and Abhinay D Joshi and Ian Kennedy and William E Klunk and Christopher C Rowe and Dean F Wong and Michael J Pontecorvo and Mark A Mintun and Michael D Devous},
  year       = {2018},
  month      = {Dec},
  journal    = {Alzheimer's & dementia : the journal of the Alzheimer's Association},
  volume     = {14},
  number     = {12},
  pages      = {1565-1571},
  eprint     = {30006100},
  doi        = {10.1016/j.jalz.2018.06.1353},
  language   = {eng},
  issn       = {1552-5279},
  abstract   = {INTRODUCTION: Klunk et al. recently proposed a means of standardizing quantitation of amyloid burden from positron emission tomography scans to a common Centiloid scale, and we have applied that method to florbetapir.
                METHODS: Florbetapir and Pittsburgh compound B scans were acquired for 46 mixed clinical presentation subjects within 18 ± 20 days. Florbetapir and Pittsburgh compound B cortical standardized uptake value ratio (SUVr) values were well correlated for both standard Centiloid (R2 = 0.894) and Avid (R2 = 0.901) volume of interests (VOIs). The methods of Klunk et al. were applied to establish a conversion first from florbetapir SUVr values obtained using standard Centiloid VOIs to Centiloids and then from Avid VOIs (Joshi et al.) to Centiloids.
                RESULTS: The equation for conversion of florbetapir SUVr from Avid VOIs to the Centiloid scale was as follows: Florbetapir Centiloids = 183 × SUVrAvid - 177. The threshold that discriminated neuropathologically verified none or sparse versus moderate to frequent plaques in autopsy-confirmed data is 24.1 Centiloids.
                DISCUSSION: These findings may allow improved tracer-independent amyloid quantitation.},
  eprinttype = {pubmed}
}
@article{landau2015measurement,
  title      = {Measurement of longitudinal β-amyloid change with 18F-florbetapir PET and standardized uptake value ratios},
  author     = {Susan M Landau and Allison Fero and Suzanne L Baker and Robert Koeppe and Mark Mintun and Kewei Chen and Eric M Reiman and William J Jagust},
  year       = {2015},
  month      = {Apr},
  journal    = {Journal of nuclear medicine : official publication, Society of Nuclear Medicine},
  volume     = {56},
  number     = {4},
  pages      = {567-74},
  eprint     = {25745095},
  doi        = {10.2967/jnumed.114.148981},
  language   = {eng},
  issn       = {1535-5667},
  abstract   = {UNLABELLED: The accurate measurement of β-amyloid (Aβ) change using amyloid PET imaging is important for Alzheimer disease research and clinical trials but poses several unique challenges. In particular, reference region measurement instability may lead to spurious changes in cortical regions of interest. To optimize our ability to measure (18)F-florbetapir longitudinal change, we evaluated several candidate regions of interest and their influence on cortical florbetapir change over a 2-y period in participants from the Alzheimer Disease Neuroimaging Initiative (ADNI).
                METHODS: We examined the agreement in cortical florbetapir change detected using 6 candidate reference regions (cerebellar gray matter, whole cerebellum, brain stem/pons, eroded subcortical white matter [WM], and 2 additional combinations of these regions) in 520 ADNI subjects. We used concurrent cerebrospinal fluid Aβ1-42 measurements to identify subgroups of ADNI subjects expected to remain stable over follow-up (stable Aβ group; n = 14) and subjects expected to increase (increasing Aβ group; n = 91). We then evaluated reference regions according to whether cortical change was minimal in the stable Aβ group and cortical retention increased in the increasing Aβ group.
                RESULTS: There was poor agreement across reference regions in the amount of cortical change observed across all 520 ADNI subjects. Within the stable Aβ group, however, cortical florbetapir change was 1%-2% across all reference regions, indicating high consistency. In the increasing Aβ group, cortical increases were significant with all reference regions. Reference regions containing WM (as opposed to cerebellum or pons) enabled detection of cortical change that was more physiologically plausible and more likely to increase over time.
                CONCLUSION: Reference region selection has an important influence on the detection of florbetapir change. Compared with cerebellum or pons alone, reference regions that included subcortical WM resulted in change measurements that are more accurate. In addition, because use of WM-containing reference regions involves dividing out cortical signal contained in the reference region (via partial-volume effects), use of these WM-containing regions may result in more conservative estimates of actual change. Future analyses using different tracers, tracer-kinetic models, pipelines, and comparisons with other biomarkers will further optimize our ability to accurately measure Aβ changes over time.},
  eprinttype = {pubmed}
}

@article{mclachlan2024comparison,
  title     = {Comparison of reference region stability for longitudinal amyloid PET in Down syndrome},
  author    = {McLachlan, Max and Rouanet, Jeremy P and Garimella, Arun and Price, Julie C and Tudorascu, Dana and Laymon, Charles M and Keator, David B and Betthauser, Tobey J and Kreisl, William Charles and Lao, Patrick J and others},
  journal   = {Alzheimer's \& Dementia},
  volume    = {20},
  pages     = {e092918},
  year      = {2024},
  publisher = {Wiley Online Library}
}

@article{luo2025development,
  title      = {Development and evaluation of image preprocessing pipelines for the Centiloid method on Down Syndrome data},
  author     = {Weiquan Luo and Davneet S Minhas and Ethan D Rubenstein and David N Situ and Sarah K Royse and Beau M Ances and Bradley T Christian and Ann D Cohen and Benjamin L Handen and William E Klunk and Dana L Tudorascu and Shahid Zaman and Charles M Laymon},
  year       = {2025},
  month      = {Oct},
  journal    = {Alzheimer's & dementia : the journal of the Alzheimer's Association},
  volume     = {21},
  number     = {10},
  pages      = {e70712},
  eprint     = {41074907},
  doi        = {10.1002/alz.70712},
  language   = {eng},
  issn       = {1552-5279},
  abstract   = {BACKGROUND: Centiloid provides a standardized process to quantify brain amyloid in which a subject's T1 magnetic resonance imaging (MRI) and amyloid positron emission tomography (PET) scans are registered and warped to Montreal Neurological Institute 152 space using prescribed procedures. The method has a high failure rate in Down syndrome (DS) subjects from the Neurodegeneration in Aging Down Syndrome (NiAD) project. We evaluate imaging preprocessing methods (PMs) to improve the DS success rate.
                METHODS: PMs were constructed from combinations of image origin reset, filtering, MRI bias correction, and MRI skull stripping. Centiloid results were evaluated for adherence to standards using The Global Alzheimer's Association Interactive Network dataset. PMs were also evaluated using the NiAD dataset to judge their suitability for the DS population. DS PM evaluation procedures were developed corresponding to those specified for non-DS populations.
                RESULTS: Five accepted PMs improved the Centiloid-processing success rate in the DS cohort from 61.3% to 95.6%.
                DISCUSSION: The identified combinations of preprocessing steps substantially improved the success rate of Centiloid processing in DS.
                HIGHLIGHTS: Image preprocessing pipeline is proposed for Centiloid analysis of DS. Preprocessing pipelines are evaluated for adherence to Centiloid standards. Pipelines are evaluated for improvement in yield of usable imaging data. Preprocessing of amyloid imaging data resulted in a large yield improvement.},
  eprinttype = {pubmed}
}

% Clinical Core Methods

@article{haxby1989neuropsychological,
  title     = {Neuropsychological evaluation of adults with Down's syndrome: patterns of selective impairment in non-demented old adults},
  author    = {Haxby, James V},
  journal   = {Journal of Intellectual Disability Research},
  volume    = {33},
  number    = {3},
  pages     = {193--210},
  year      = {1989},
  publisher = {Wiley Online Library}
}

@book{mccarthy1972msca,
  title     = {MSCA: McCarthy Scales of Children's Abilities},
  author    = {McCarthy, Dorothea},
  year      = {1972},
  publisher = {Psychological Corporation}
}

@misc{korkman2007nepsy,
  title     = {Nepsy-(nepsy-ii)},
  author    = {Korkman, Marit and Kirk, Ursula and Kemp, Sally},
  year      = {2007},
  publisher = {Harcourt Assessment San Antonio, TX}
}

@article{kaufman2004kaufman,
  title   = {Kaufman brief intelligence test--second edition (KBIT-2)},
  author  = {Kaufman, Alan S},
  journal = {Circle Pines, MN: American Guidance Service},
  year    = {2004}
}

@misc{wechsler2003wisc,
  title     = {WISC-IV. Wechsler intelligence scale for children--fourth UK edition. Administration and scoring manual},
  author    = {Wechsler, D},
  year      = {2003},
  publisher = {Harcourt Assessment, London.(tr. it.: WISC-IV. Wechsler Intelligence Scale~…}
}

@article{haxby1989neuropsychological,
  title     = {Neuropsychological evaluation of adults with Down's syndrome: patterns of selective impairment in non-demented old adults},
  author    = {Haxby, James V},
  journal   = {Journal of Intellectual Disability Research},
  volume    = {33},
  number    = {3},
  pages     = {193--210},
  year      = {1989},
  publisher = {Wiley Online Library}
}

@article{beery2004beery,
  title   = {Beery VMI: The Beery-Buktenica developmental test of visual-motor integration},
  author  = {Beery, Keith E},
  journal = {Minneapolis, MN: Pearson},
  year    = {2004}
}

@article{devenny2002cued,
  title     = {Cued recall in early-stage dementia in adults with Down's syndrome},
  author    = {Devenny, DA and Zimmerli, EJ and Kittler, P and Krinsky-McHale, SJ},
  journal   = {Journal of Intellectual Disability Research},
  volume    = {46},
  number    = {6},
  pages     = {472--483},
  year      = {2002},
  publisher = {Wiley Online Library}
}

@article{ball2008executive,
  title     = {Executive dysfunction and its association with personality and behaviour changes in the development of Alzheimer's disease in adults with Down syndrome and mild to moderate learning disabilities},
  author    = {Ball, Sarah L and Holland, Anthony J and Treppner, Peter and Watson, Peter C and Huppert, Felicia A},
  journal   = {British Journal of Clinical Psychology},
  volume    = {47},
  number    = {1},
  pages     = {1--29},
  year      = {2008},
  publisher = {Wiley Online Library}
}

@article{tiffin1948purdue,
  title     = {The Purdue Pegboard: norms and studies of reliability and validity.},
  author    = {Tiffin, Joseph and Asher, Eston Jackson},
  journal   = {Journal of applied psychology},
  volume    = {32},
  number    = {3},
  pages     = {234},
  year      = {1948},
  publisher = {American Psychological Association}
}

@article{krinsky2008selective,
  title   = {Selective attention deficits associated with mild cognitive impairment and early stage Alzheimer's disease in adults with Down syndrome},
  author  = {Krinsky-McHale, Sharon J and Devenny, Darlynne A and Kittler, Phyllis and Silverman, Wayne},
  journal = {American Journal on Mental Retardation},
  volume  = {113},
  number  = {5},
  pages   = {369--386},
  year    = {2008}
}

@article{tinetti1986performance,
  title     = {Performance-oriented assessment of mobility problems in elderly patients.},
  author    = {Tinetti, Mary E},
  journal   = {Journal of the American Geriatrics Society},
  year      = {1986},
  publisher = {Blackwell Publishing}
}

@article{eurlings2006dementia,
  title   = {Dementia Questionnaire for People with Learning Disabilities (DLD)},
  author  = {Eurlings, H and Evenhuis, H and Kenegen, M},
  journal = {UK adaptation},
  year    = {2006}
}

@incollection{esralew2017national,
  title     = {National task group early detection screen for dementia (NTG-EDSD)},
  author    = {Esralew, Lucille and Janicki, Matthew P and Keller, Seth M},
  booktitle = {Neuropsychological assessments of dementia in down syndrome and intellectual disabilities},
  pages     = {197--213},
  year      = {2017},
  publisher = {Springer}
}

@misc{sparrow2016vineland,
  title     = {Vineland adaptive behavior scales (3rd ed.)},
  author    = {Sparrow, SS and Saulnier, CA and Cicchetti, DC},
  year      = {2016},
  publisher = {Bloomington, MN: Pearson}
}

@book{reiss1994handbook,
  title     = {Handbook of challenging behavior: Mental health aspects of mental retardation},
  author    = {Reiss, Steven},
  year      = {1994},
  publisher = {Ids Pub.}
}

@article{cummings1994neuropsychiatric,
  title     = {The Neuropsychiatric Inventory: comprehensive assessment of psychopathology in dementia},
  author    = {Cummings, Jeffrey L and Mega, Michael and Gray, Katherine and Rosenberg-Thompson, Susan and Carusi, Daniela Anne and Gornbein, Jeffrey},
  journal   = {Neurology},
  volume    = {44},
  number    = {12},
  pages     = {2308--2308},
  year      = {1994},
  publisher = {Lippincott Williams \& Wilkins}
}

@article{galvin2005ad8,
  title     = {The AD8: a brief informant interview to detect dementia},
  author    = {Galvin, JE and Roe, CM and Powlishta, KK and Coats, MA and Muich, SJ and Grant, E and Miller, JP and Storandt, M and Morris, JC},
  journal   = {Neurology},
  volume    = {65},
  number    = {4},
  pages     = {559--564},
  year      = {2005},
  publisher = {Lippincott Williams \& Wilkins}
}

@article{nasreddine2005montreal,
  title     = {The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment},
  author    = {Nasreddine, Ziad S and Phillips, Natalie A and B{\'e}dirian, Val{\'e}rie and Charbonneau, Simon and Whitehead, Victor and Collin, Isabelle and Cummings, Jeffrey L and Chertkow, Howard},
  journal   = {Journal of the American Geriatrics Society},
  volume    = {53},
  number    = {4},
  pages     = {695--699},
  year      = {2005},
  publisher = {Wiley Online Library}
}

% Cerebrospinal Fluid

@manual{fujirebio2019_abeta42_ircs,
  title        = {Lumipulse G β-Amyloid 1-42 IRCs},
  organization = {Fujirebio Inc.},
  number       = {231463},
  edition      = {v4},
  note         = {Document code: 2019-06.27Z04TU},
  month        = jun,
  year         = {2019}
}

@manual{fujirebio2019_abeta40_ircs,
  title        = {Lumipulse G β-Amyloid 1-40 IRCs},
  organization = {Fujirebio Inc.},
  number       = {231685},
  edition      = {v1},
  note         = {Document code: 2019-02.24Y01TU},
  month        = feb,
  year         = {2019}
}

@manual{fujirebio2019_ptau181_ircs,
  title        = {Lumipulse G pTau 181 IRCs},
  organization = {Fujirebio Inc.},
  number       = {231654},
  edition      = {v1},
  note         = {Document code: 2019-02.25D01TU},
  month        = feb,
  year         = {2019}
}

@manual{fujirebio2017_totaltau_ircs,
  title        = {Lumipulse G Total Tau IRCs},
  organization = {Fujirebio Inc.},
  number       = {231302},
  edition      = {v1},
  note         = {Document code: 2017-08.26B01TU},
  month        = aug,
  year         = {2017}
}

@manual{fujirebio2019_abeta_controls,
  title        = {Lumipulse β-Amyloid Controls},
  organization = {Fujirebio Inc.},
  number       = {231708},
  edition      = {v1},
  note         = {Document code: 2019-02.23C01TU},
  month        = feb,
  year         = {2019},
  url          = {https://www.fujirebio.com/en-us/products-solutions/lumipulse-g-beta-amyloid-1-42}
}

@manual{fujirebio2018_ptau181_controls,
  title        = {Lumipulse pTau 181 Controls},
  organization = {Fujirebio Inc.},
  number       = {231678},
  edition      = {v1},
  note         = {Document code: 2018-12.25H01TU},
  month        = dec,
  year         = {2018},
  url          = {https://www.fujirebio.com/en-us/products-solutions/lumipulse-g-ptau-181}
}

@manual{fujirebio2017_totaltau_controls,
  title        = {Lumipulse G Total Tau Controls},
  organization = {Fujirebio Inc.},
  number       = {231319},
  edition      = {v1},
  note         = {Document code: 2017-08.25G01TU},
  month        = aug,
  year         = {2017},
  url          = {https://www.fujirebio.com/en-us/products-solutions/lumipulse-g-total-tau}
}

@manual{microvue_ykl40_eia,
  title        = {MicroVue Bone YKL-40 EIA},
  organization = {Quidel Corporation},
  note         = {Enzyme Immunoassay Kit Instructions for Use}
}

@article{stergaard2002elevated,
  title      = {YKL-40 is elevated in cerebrospinal fluid from patients with purulent meningitis},
  author     = {Christian \O{}stergaard and Julia S Johansen and Thomas Benfield and Paul A Price and Jens D Lundgren},
  year       = {2002},
  month      = {May},
  journal    = {Clinical and diagnostic laboratory immunology},
  volume     = {9},
  number     = {3},
  pages      = {598-604},
  eprint     = {11986266},
  doi        = {10.1128/cdli.9.3.598-604.2002},
  language   = {eng},
  issn       = {1071-412X},
  abstract   = {YKL-40, a member of the family 18 glycosyl hydrolases, is secreted by activated neutrophils and macrophages. It is a growth factor for connective tissue cells and a potent migration factor for endothelial cells and may function in inflammation and tissue remodeling. YKL-40 was determined in 134 cerebrospinal fluid (CSF) samples taken on admission from patients suspected of having meningitis (48 with purulent meningitis, 49 with lymphocytic meningitis, 5 with encephalitis, and 32 without evidence of meningitis). YKL-40 levels in CSF were significantly higher in patients with purulent meningitis (median, 663 microg/liter [range, 20 to 8,960]) and encephalitis (5,430 microg/liter [620 to 11,600]) than in patients with lymphocytic meningitis (137 microg/liter [41 to 1,865]) or patients without meningitis (167 microg/liter [24 to 630]) (Kruskal-Wallis and Dunn multiple comparison tests, P < 0.001). CSF YKL-40 levels were also determined for 26 patients with purulent meningitis having a repuncture, and patients who died (n = 5) had significantly higher YKL-40 levels than patients who survived (n = 21) (2,100 microg/liter [1,160 to 7,050] versus 885 microg/liter [192 to 15,400], respectively; Mann-Whitney test, P = 0.018). YKL-40 was most likely locally produced, since patients with infections of the central nervous system had CSF YKL-40 levels that were at least 10-fold higher than the corresponding levels in serum (2,033 microg/liter [470 to 11,600] versus 80 microg/liter [19 to 195]). The CSF neopterin level was the biochemical parameter in CSF and blood that correlated best with CSF YKL-40 levels, indicating that YKL-40 may be produced by activated macrophages within the central nervous system. In conclusion, high levels of YKL-40 in CSF are found in patients with purulent meningitis.},
  eprinttype = {pubmed}
}

@manual{ibl2019_nflight_elisa,
  title        = {{NF-Light\textsuperscript{\textregistered}} (Neurofilament Light) ELISA Instructions for Use},
  organization = {IBL International GmbH},
  month        = feb,
  year         = {2019},
  url          = {https://www.ibl-international.com/en_us/neurofilament-light-elisa-ruo},
  note         = {Research Use Only (RUO)}
}

@article{norgren2002monoclonal,
  title      = {Monoclonal antibodies selective for low molecular weight neurofilaments},
  author     = {Niklas Norgren and Jan-Erik Karlsson and Lars Rosengren and Torgny Stigbrand},
  year       = {2002},
  month      = {Feb},
  journal    = {Hybridoma and hybridomics},
  volume     = {21},
  number     = {1},
  pages      = {53-9},
  eprint     = {11991817},
  doi        = {10.1089/15368590252917647},
  language   = {eng},
  issn       = {1536-8599},
  abstract   = {Neurofilaments are necessary for the maintenance of axonal caliber and structural organization of nerve cells. The low molecular weight form of neurofilament, the neurofilament light protein, which serves as the core of the filament, was used as immunogen for generation of hybridomas with selective reactivity with this form of the filament. Six hybridomas, out of approximately 100 tested clones, were highly discriminatory. All involved epitopes were localized to the rod region of the antigen, as determined by alpha-chymotrypsin digestion of the purified filament and enzymatic peptide mapping. Synthetic peptides (20 mers) covering the entire rod region did not react with the antibodies. A phage display peptide library was used to identify four consensus sequences for the antibodies. The results indicate that all epitopes were of conformational type. Pair-wise BIAcore data furthermore indicated that the epitopes were independent. The access to such specific reagents is a prerequisite for further elucidation of the biology of the low molecular weight form of neurofilaments proteins.},
  eprinttype = {pubmed}
}

@article{norgren2003elevated,
  title      = {Elevated neurofilament levels in neurological diseases},
  author     = {Niklas Norgren and Lars Rosengren and Torgny Stigbrand},
  year       = {2003},
  month      = {Oct},
  journal    = {Brain research},
  volume     = {987},
  number     = {1},
  pages      = {25-31},
  eprint     = {14499942},
  doi        = {10.1016/s0006-8993(03)03219-0},
  language   = {eng},
  issn       = {0006-8993},
  abstract   = {Neurofilaments, a major cytoskeletal constituent of neuronal cells, can be released into the cerebrospinal fluid during several neurodegenerative diseases. By means of a new sensitive ELISA capable of measuring 60 ng/l of neurofilament light, significant elevations were observed for different neurological disorders. Cerebral infarction presented levels of 19800+/-9100 ng/l, amyothropic lateral sclerosis 3600+/-1200 ng/l, 'relapsing-remitting' MS 2500+/-1500 ng/l, extrapyramidal symptoms 1100+/-300 ng/l, late onset AD 300+/-100 ng/l and vascular dementia 1400+/-800 ng/l. In patients with no signs of neurological diseases the upper normal level and cut-off values was determined to be below 100 ng/l. NF-L determinations will be a valuable complement in identifying neuronal degradation and can be used clinically for diagnostic and monitoring purposes.},
  eprinttype = {pubmed}
}

@article{norgren2004neurofilament,
  title      = {Neurofilament and glial fibrillary acidic protein in multiple sclerosis},
  author     = {N Norgren and P Sundstr\"{o}m and A Svenningsson and L Rosengren and T Stigbrand and M Gunnarsson},
  year       = {2004},
  month      = {Nov},
  journal    = {Neurology},
  volume     = {63},
  number     = {9},
  pages      = {1586-90},
  eprint     = {15534240},
  doi        = {10.1212/01.wnl.0000142988.49341.d1},
  language   = {eng},
  issn       = {1526-632X},
  abstract   = {OBJECTIVE: To evaluate levels of neurofilament light (NFL) and glial fibrillary acidic protein (GFAP) in CSF from patients with multiple sclerosis (MS) in relation to clinical progress of the disease.
                METHODS: CSF levels of NFL and GFAP were determined by sensitive ELISAs in 99 patients with different subtypes of MS, classified in terms of "ongoing relapse" or "clinically stable disease," and 25 control subjects. Levels were compared with paraclinical data such as immunoglobulin G index and inflammatory cell count in the CSF, and the levels were related to Expanded Disability Status Scale score and progression index at clinical follow-up evaluations later in the disease course.
                RESULTS: NFL and GFAP levels were elevated in MS patients as compared with control subjects (p < 0.001). The NFL levels were higher at relapses, whereas GFAP levels were unaffected. High NFL levels correlated with progression in patients with an active relapse (r = 0.49; p < 0.01) and in clinically stable patients (r = 0.29; p < 0.05). GFAP correlated to progression in the total patient cohort (r = 0.24; p < 0.05). Moreover, a strong correlation between NFL levels and inflammatory cell counts was evident in the group of patients with an ongoing relapse (r = 0.52; p = 0.001).
                CONCLUSIONS: CSF levels of neurofilament light and glial fibrillary acidic protein may have prognostic value in multiple sclerosis.},
  eprinttype = {pubmed}
}

@article{crimmins2017double,
  title      = {Double Monoclonal Immunoassay for Quantifying Human Visinin-Like Protein-1 in CSF},
  author     = {Daniel L Crimmins and Elizabeth M Herries and Matthew F Ohlendorf and Nancy A Brada and Nichola C Garbett and Gregory J Zipfel and Suzanne E Schindler and Jack H Ladenson},
  year       = {2017},
  month      = {Feb},
  journal    = {Clinical chemistry},
  volume     = {63},
  number     = {2},
  pages      = {603-604},
  eprint     = {27986783},
  doi        = {10.1373/clinchem.2016.263236},
  language   = {eng},
  issn       = {1530-8561},
  eprinttype = {pubmed}
}

@article{sutphen2018longitudinal,
  title      = {Longitudinal decreases in multiple cerebrospinal fluid biomarkers of neuronal injury in symptomatic late onset Alzheimer's disease},
  author     = {Courtney L Sutphen and Lena McCue and Elizabeth M Herries and Chengjie Xiong and Jack H Ladenson and David M Holtzman and Anne M Fagan},
  year       = {2018},
  month      = {Jul},
  journal    = {Alzheimer's & dementia : the journal of the Alzheimer's Association},
  volume     = {14},
  number     = {7},
  pages      = {869-879},
  eprint     = {29580670},
  doi        = {10.1016/j.jalz.2018.01.012},
  language   = {eng},
  issn       = {1552-5279},
  abstract   = {INTRODUCTION: Individuals in early stages of Alzheimer's disease are a targeted population for secondary prevention trials aimed at preserving normal cognition. Understanding within-person biomarker(s) change over time is critical for trial enrollment and design.
                METHODS: Longitudinal cerebrospinal fluid samples from the Alzheimer's Disease Neuroimaging Initiative were assayed for novel markers of neuronal/synaptic injury (visinin-like protein 1, Ng, and SNAP-25) and neuroinflammation (YKL-40) and compared with β amyloid 42, tau, and phospho-tau181. General linear mixed models were used to compare within-person rates of change in three clinical groups (cognitively normal, mild cognitive impairment, and Alzheimer's disease) further defined by β amyloid status.
                RESULTS: Levels of injury markers were highly positively correlated. Despite elevated baseline levels as a function of clinical status and amyloid-positivity, within-person decreases in these measures were observed in the early symptomatic, amyloid-positive Alzheimer's disease group.
                DISCUSSION: Knowledge of within-person biomarker change will impact interpretation of biomarker outcomes in clinical trials that are dependent on disease stage.},
  eprinttype = {pubmed}
}

@article{willemse2018neurogranin,
  title      = {Neurogranin as Cerebrospinal Fluid Biomarker for Alzheimer Disease: An Assay Comparison Study},
  author     = {Eline A J Willemse and Ann {De Vos} and Elizabeth M Herries and Ulf Andreasson and Sebastiaan Engelborghs and Wiesje M {van der Flier} and Philip Scheltens and Dan Crimmins and Jack H Ladenson and Eugeen Vanmechelen and Henrik Zetterberg and Anne M Fagan and Kaj Blennow and Maria Bjerke and Charlotte E Teunissen},
  year       = {2018},
  month      = {Jun},
  journal    = {Clinical chemistry},
  volume     = {64},
  number     = {6},
  pages      = {927-937},
  eprint     = {29523639},
  doi        = {10.1373/clinchem.2017.283028},
  language   = {eng},
  issn       = {1530-8561},
  abstract   = {BACKGROUND: Neurogranin in cerebrospinal fluid (CSF) correlates with cognitive decline and is a potential novel biomarker for Alzheimer disease (AD) dementia. We investigated the analytical and diagnostic performance of 3 commonly used neurogranin assays in the same cohort of patients to improve the interpretability of CSF neurogranin test results.
                METHODS: The neurogranin Erenna® assay from Washington University, St. Louis, MO (WashU); ELISA from ADx Neurosciences; and ELISA from Gothenburg University, Mölndal, Sweden (UGot), were compared using silver staining and Western blot after gel electrophoresis. Clinical performance of the 3 assays was compared in samples from individuals diagnosed with subjective cognitive decline (n = 22), and in patients with AD (n = 22), frontotemporal dementia (n = 22), dementia with Lewy bodies (n = 22), or vascular dementia (n = 20), adjusted for sex and age.
                RESULTS: The assays detected different epitopes of neurogranin: the WashU assay detected the N-terminal part of neurogranin (S10-D23) and a C-terminal part (G49-G60), the ADx assay detected C-terminal neurogranin truncated at P75, and the UGot assay detected the C-terminal neurogranin with intact ending (D78). Spearman ρ was 0.95 between ADx and WashU, 0.87 between UGot and WashU, and 0.81 between UGot and ADx. ANCOVA (analysis of covariance) showed group differences for ranked neurogranin concentrations in each assay (all P < 0.05), with specific increases in AD.
                CONCLUSIONS: Although the 3 assays target different epitopes on neurogranin and have different calibrators, the high correlations and the similar group differences suggest that the different forms of neurogranin in CSF carry similar diagnostic information, at least in the context of neurodegenerative diseases.},
  eprinttype = {pubmed}
}

@article{westgard1981multi,
  title      = {A multi-rule Shewhart chart for quality control in clinical chemistry},
  author     = {J O Westgard and P L Barry and M R Hunt and T Groth},
  year       = {1981},
  month      = {Mar},
  journal    = {Clinical chemistry},
  volume     = {27},
  number     = {3},
  pages      = {493-501},
  eprint     = {7471403},
  language   = {eng},
  issn       = {0009-9147},
  eprinttype = {pubmed}
}

% Genomics Data

@misc{illumina2020genomestudio,
  author = {{Illumina, Inc.}},
  title  = {GenomeStudio},
  year   = {2020},
  url    = {https://www.illumina.com/techniques/microarrays/array-data-analysis-experimental-design/genomestudio.html},
  note   = {Accessed: 2026-06-29}
}

@misc{illumina2020plugins,
  author = {{Illumina, Inc.}},
  title  = {GenomeStudio 2.0 Plug-In},
  year   = {2020},
  url    = {https://support.illumina.com/downloads/genomestudio-2-0-plug-ins.html},
  note   = {Accessed: 2026-06-29}
}

@article{chang2015plink2,
  author  = {Chang, Christopher C. and Chow, Carson C. and Tellier, Laurent C. A. M. and Vattikuti, Sriram and Purcell, Shaun M. and Lee, James J.},
  title   = {Second-generation PLINK: Rising to the Challenge of Larger and Richer Datasets},
  journal = {GigaScience},
  year    = {2015},
  volume  = {4},
  pages   = {7},
  doi     = {10.1186/s13742-015-0047-8}
}

@article{manichaikul2010relationship,
  author  = {Manichaikul, Ani and Mychaleckyj, Josyf C. and Rich, Stephen S. and Daly, Kathy and Sale, Mich{\`e}le and Chen, Wei-Min},
  title   = {Robust Relationship Inference in Genome-Wide Association Studies},
  journal = {Bioinformatics},
  year    = {2010},
  volume  = {26},
  number  = {22},
  pages   = {2867--2873},
  doi     = {10.1093/bioinformatics/btq559}
}

% Frequently Asked Questions

@article{torbati2021multi,
  title     = {A multi-scanner neuroimaging data harmonization using RAVEL and ComBat},
  author    = {Torbati, Mahbaneh Eshaghzadeh and Minhas, Davneet S and Ahmad, Ghasan and O’Connor, Erin E and Muschelli, John and Laymon, Charles M and Yang, Zixi and Cohen, Ann D and Aizenstein, Howard J and Klunk, William E and others},
  journal   = {Neuroimage},
  volume    = {245},
  pages     = {118703},
  year      = {2021},
  publisher = {Elsevier}
}

@article{fortin2016removing,
  title     = {Removing inter-subject technical variability in magnetic resonance imaging studies},
  author    = {Fortin, Jean-Philippe and Sweeney, Elizabeth M and Muschelli, John and Crainiceanu, Ciprian M and Shinohara, Russell T and Alzheimer's Disease Neuroimaging Initiative and others},
  journal   = {NeuroImage},
  volume    = {132},
  pages     = {198--212},
  year      = {2016},
  publisher = {Elsevier}
}

@article{fortin2018harmonization,
  title     = {Harmonization of cortical thickness measurements across scanners and sites},
  author    = {Fortin, Jean-Philippe and Cullen, Nicholas and Sheline, Yvette I and Taylor, Warren D and Aselcioglu, Irem and Cook, Philip A and Adams, Phil and Cooper, Crystal and Fava, Maurizio and McGrath, Patrick J and others},
  journal   = {Neuroimage},
  volume    = {167},
  pages     = {104--120},
  year      = {2018},
  publisher = {Elsevier}
}

% Plasma NT1-tau

@article{chhatwal2020plasma,
  title      = {Plasma N-terminal tau fragment levels predict future cognitive decline and neurodegeneration in healthy elderly individuals},
  author     = {Jasmeer P Chhatwal and Aaron P Schultz and Yifan Dang and Beth Ostaszewski and Lei Liu and Hyun-Sik Yang and Keith A Johnson and Reisa A Sperling and Dennis J Selkoe},
  year       = {2020},
  month      = {Nov},
  journal    = {Nature communications},
  volume     = {11},
  number     = {1},
  pages      = {6024},
  eprint     = {33247134},
  doi        = {10.1038/s41467-020-19543-w},
  language   = {eng},
  issn       = {2041-1723},
  abstract   = {The availability of blood-based assays detecting Alzheimer's disease (AD) pathology should greatly accelerate AD therapeutic development and improve clinical care. This is especially true for markers that capture the risk of decline in pre-symptomatic stages of AD, as this would allow one to focus interventions on participants maximally at risk and at a stage prior to widespread synapse loss and neurodegeneration. Here we quantify plasma concentrations of an N-terminal fragment of tau (NT1) in a large, well-characterized cohort of clinically normal elderly who were followed longitudinally. Plasma NT1 levels at study entry (when all participants were unimpaired) were highly predictive of future cognitive decline, pathological tau accumulation, neurodegeneration, and transition to a diagnosis of MCI/AD. These predictive effects were particularly strong in participants with even modestly elevated brain β-amyloid burden at study entry, suggesting plasma NT1 levels capture very early cognitive, pathologic and neurodegenerative changes along the AD trajectory.},
  eprinttype = {pubmed}
}
@article{chen2019learnings,
  title      = {Learnings about the complexity of extracellular tau aid development of a blood-based screen for Alzheimer's disease},
  author     = {Zhicheng Chen and David Mengel and Ashvini Keshavan and Robert A Rissman and Andrew Billinton and Michael Perkinton and Jennifer Percival-Alwyn and Aaron Schultz and Michael Properzi and Keith Johnson and Dennis J Selkoe and Reisa A Sperling and Purvish Patel and Henrik Zetterberg and Douglas Galasko and Jonathan M Schott and Dominic M Walsh},
  year       = {2019},
  month      = {Mar},
  journal    = {Alzheimer's & dementia : the journal of the Alzheimer's Association},
  volume     = {15},
  number     = {3},
  pages      = {487-496},
  eprint     = {30419228},
  doi        = {10.1016/j.jalz.2018.09.010},
  language   = {eng},
  issn       = {1552-5279},
  abstract   = {INTRODUCTION: The tau protein plays a central role in Alzheimer's disease (AD), and there is huge interest in measuring tau in blood and cerebrospinal fluid (CSF).
                METHODS: We developed a set of immunoassays to measure tau in specimens from humans diagnosed based on current best clinical and CSF biomarker criteria.
                RESULTS: In CSF, mid-region- and N-terminal-detected tau predominated and rose in disease. In plasma, an N-terminal assay (NT1) detected elevated levels of tau in AD and AD-mild cognitive impairment (MCI). Plasma NT1 measurements separated controls from AD-MCI (area under the curve [AUC] = 0.88) and AD (AUC = 0.96) in a discovery cohort and in a Validation Cohort (with AUCs = 0.79 and 0.75, respectively).
                DISCUSSION: The forms of tau in CSF and plasma are distinct, but in each specimen type, the levels of certain fragments are increased in AD. Measurement of plasma NT1 tau should be aggressively pursued as a potential blood-based screening test for AD/AD-MCI.},
  eprinttype = {pubmed}
}
@article{mengel2020plasma,
  title      = {Plasma NT1 Tau is a Specific and Early Marker of Alzheimer's Disease},
  author     = {David Mengel and Shorena Janelidze and Robert J Glynn and Wen Liu and Oskar Hansson and Dominic M Walsh},
  year       = {2020},
  month      = {Nov},
  journal    = {Annals of neurology},
  volume     = {88},
  number     = {5},
  pages      = {878-892},
  eprint     = {32829532},
  doi        = {10.1002/ana.25885},
  language   = {eng},
  issn       = {1531-8249},
  abstract   = {OBJECTIVE: There is an urgent need for sensitive, widely available, blood-based screening tests to identify presymptomatic individuals destined to develop Alzheimer's disease (AD). We investigated whether tau detected in plasma by our in-house NT1 assay is specifically altered in AD, and when applied to patients with subjective cognitive decline (SCD) or mild cognitive impairment (MCI) can serve to predict progression to AD dementia. The predictive value of NT1 versus tau measured using assays from Quanterix and Roche, and the specificity of NT1 for AD versus a nonspecific marker of neurodegeneration (neurofilament light [NfL]) were also examined.
                METHODS: NT1 tau and NfL were measured in plasma from prospectively followed patients with SCD or MCI who remained cognitively stable, converted to AD dementia, or converted to non-AD dementias, and in cognitively unimpaired participants. Tau was measured using Quanterix and Roche assays in baseline subjects with SCD and MCI.
                RESULTS: Plasma NT1 tau was specifically elevated in AD, but not in non-AD dementia compared with controls, whereas NfL was increased in both AD and non-AD dementias. Baseline specimens from individuals who had SCD or MCI revealed that NT1 tau, but not tau measured using Quanterix or Roche assays, is elevated in subjects who progress to AD dementia. As expected, baseline plasma NfL is elevated in those who progress to AD and non-AD dementias.
                INTERPRETATION: Plasma NT1 tau is a specific marker of AD, which is elevated early in disease and may prove useful as a first round screen to identify individuals at risk of developing AD. ANN NEUROL 2020;88:878-892.},
  eprinttype = {pubmed}
}
@article{mengel2020dynamics,
  title      = {Dynamics of plasma biomarkers in Down syndrome: the relative levels of Aβ42 decrease with age, whereas NT1 tau and NfL increase},
  author     = {David Mengel and Wen Liu and Robert J Glynn and Dennis J Selkoe and Andre Strydom and Florence Lai and H Diana Rosas and Amy Torres and Vasiliki Patsiogiannis and Brian Skotko and Dominic M Walsh},
  year       = {2020},
  month      = {Mar},
  journal    = {Alzheimer's research & therapy},
  volume     = {12},
  number     = {1},
  pages      = {27},
  eprint     = {32192521},
  doi        = {10.1186/s13195-020-00593-7},
  language   = {eng},
  issn       = {1758-9193},
  abstract   = {BACKGROUND: Down syndrome (DS) is the most common genetic cause of Alzheimer's disease (AD), but diagnosis of AD in DS is challenging due to the intellectual disability which accompanies DS. When disease-modifying agents for AD are approved, reliable biomarkers will be required to identify when and how long people with DS should undergo treatment. Three cardinal neuropathological features characterize AD, and AD in DS-Aβ amyloid plaques, tau neurofibrillary tangles, and neuronal loss. Here, we quantified plasma biomarkers of all 3 neuropathological features in a large cohort of people with DS aged from 3 months to 68 years. Our primary aims were (1) to assess changes in the selected plasma biomarkers in DS across age, and (2) to compare biomarkers measured in DS plasma versus age- and sex-matched controls.
                METHODS: Using ultra-sensitive single molecule array (Simoa) assays, we measured 3 analytes (Aβ42, NfL, and tau) in plasmas of 100 individuals with DS and 100 age- and sex-matched controls. Tau was measured using an assay (NT1) which detects forms of tau containing at least residues 6-198. The stability of the 3 analytes was established using plasma from ten healthy volunteers collected at 6 intervals over a 5-day period.
                RESULTS: High Aβ42 and NT1 tau and low NfL were observed in infants. Across all ages, Aβ42 levels were higher in DS than controls. Levels of Aβ42 decreased with age in both DS and controls, but this decrease was greater in DS than controls and became prominent in the third decade of life. NT1 tau fell in adolescents and young adults, but increased in older individuals with DS. NfL levels were low in infants, children, adolescents, and young adults, but thereafter increased in DS compared to controls.
                CONCLUSIONS: High levels of Aβ42 and tau in both young controls and DS suggest these proteins are produced by normal physiological processes, whereas the changes seen in later life are consistent with emergence of pathological alterations. These plasma biomarker results are in good agreement with prior neuropathology studies and indicate that the third and fourth decades (i.e., 20 to 40 years of age) of life are pivotal periods during which AD processes manifest in DS. Application of the assays used here to longitudinal studies of individuals with DS aged 20 to 50 years of age should further validate the use of these biomarkers, and in time may allow identification and monitoring of people with DS best suited for treatment with AD therapies.},
  eprinttype = {pubmed}
}

% P-tau217

@article{janelidze2022detecting,
  title      = {Detecting amyloid positivity in early Alzheimer's disease using combinations of plasma Aβ42/Aβ40 and p-tau},
  author     = {Shorena Janelidze and Sebastian Palmqvist and Antoine Leuzy and Erik Stomrud and Inge M W Verberk and Henrik Zetterberg and Nicholas J Ashton and Pedro Pesini and Leticia Sarasa and Jos\'{e} Antonio Allu\'{e} and Charlotte E Teunissen and Jeffrey L Dage and Kaj Blennow and Niklas Mattsson-Carlgren and Oskar Hansson},
  year       = {2022},
  month      = {Feb},
  journal    = {Alzheimer's & dementia : the journal of the Alzheimer's Association},
  volume     = {18},
  number     = {2},
  pages      = {283-293},
  eprint     = {34151519},
  doi        = {10.1002/alz.12395},
  language   = {eng},
  issn       = {1552-5279},
  abstract   = {INTRODUCTION: We studied usefulness of combining blood amyloid beta (Aβ)42/Aβ40, phosphorylated tau (p-tau)217, and neurofilament light (NfL) to detect abnormal brain Aβ deposition in different stages of early Alzheimer's disease (AD).
                METHODS: Plasma biomarkers were measured using mass spectrometry (Aβ42/Aβ40) and immunoassays (p-tau217 and NfL) in cognitively unimpaired individuals (CU, N = 591) and patients with mild cognitive impairment (MCI, N = 304) from two independent cohorts (BioFINDER-1, BioFINDER-2).
                RESULTS: In CU, a combination of plasma Aβ42/Aβ40 and p-tau217 detected abnormal brain Aβ status with area under the curve (AUC) of 0.83 to 0.86. In MCI, the models including p-tau217 alone or Aβ42/Aβ40 and p-tau217 had similar AUCs (0.86-0.88); however, the latter showed improved model fit. The models were implemented in an online application providing individualized risk assessments (https://brainapps.shinyapps.io/PredictABplasma/).
                DISCUSSION: A combination of plasma Aβ42/Aβ40 and p-tau217 discriminated Aβ status with relatively high accuracy, whereas p-tau217 showed strongest associations with Aβ pathology in MCI but not in CU.},
  eprinttype = {pubmed}
}
@article{palmqvist2020discriminative,
  title      = {Discriminative Accuracy of Plasma Phospho-tau217 for Alzheimer Disease vs Other Neurodegenerative Disorders},
  author     = {Sebastian Palmqvist and Shorena Janelidze and Yakeel T Quiroz and Henrik Zetterberg and Francisco Lopera and Erik Stomrud and Yi Su and Yinghua Chen and Geidy E Serrano and Antoine Leuzy and Niklas Mattsson-Carlgren and Olof Strandberg and Ruben Smith and Andres Villegas and Diego Sepulveda-Falla and Xiyun Chai and Nicholas K Proctor and Thomas G Beach and Kaj Blennow and Jeffrey L Dage and Eric M Reiman and Oskar Hansson},
  year       = {2020},
  month      = {Aug},
  journal    = {JAMA},
  volume     = {324},
  number     = {8},
  pages      = {772-781},
  eprint     = {32722745},
  doi        = {10.1001/jama.2020.12134},
  language   = {eng},
  issn       = {1538-3598},
  abstract   = {IMPORTANCE: There are limitations in current diagnostic testing approaches for Alzheimer disease (AD).
                OBJECTIVE: To examine plasma tau phosphorylated at threonine 217 (P-tau217) as a diagnostic biomarker for AD.
                DESIGN, SETTING, AND PARTICIPANTS: Three cross-sectional cohorts: an Arizona-based neuropathology cohort (cohort 1), including 34 participants with AD and 47 without AD (dates of enrollment, May 2007-January 2019); the Swedish BioFINDER-2 cohort (cohort 2), including cognitively unimpaired participants (n = 301) and clinically diagnosed patients with mild cognitive impairment (MCI) (n = 178), AD dementia (n = 121), and other neurodegenerative diseases (n = 99) (April 2017-September 2019); and a Colombian autosomal-dominant AD kindred (cohort 3), including 365 PSEN1 E280A mutation carriers and 257 mutation noncarriers (December 2013-February 2017).
                EXPOSURES: Plasma P-tau217.
                MAIN OUTCOMES AND MEASURES: Primary outcome was the discriminative accuracy of plasma P-tau217 for AD (clinical or neuropathological diagnosis). Secondary outcome was the association with tau pathology (determined using neuropathology or positron emission tomography [PET]).
                RESULTS: Mean age was 83.5 (SD, 8.5) years in cohort 1, 69.1 (SD, 10.3) years in cohort 2, and 35.8 (SD, 10.7) years in cohort 3; 38% were women in cohort 1, 51% in cohort 2, and 57% in cohort 3. In cohort 1, antemortem plasma P-tau217 differentiated neuropathologically defined AD from non-AD (area under the curve [AUC], 0.89 [95% CI, 0.81-0.97]) with significantly higher accuracy than plasma P-tau181 and neurofilament light chain (NfL) (AUC range, 0.50-0.72; P < .05). The discriminative accuracy of plasma P-tau217 in cohort 2 for clinical AD dementia vs other neurodegenerative diseases (AUC, 0.96 [95% CI, 0.93-0.98]) was significantly higher than plasma P-tau181, plasma NfL, and MRI measures (AUC range, 0.50-0.81; P < .001) but not significantly different compared with cerebrospinal fluid (CSF) P-tau217, CSF P-tau181, and tau-PET (AUC range, 0.90-0.99; P > .15). In cohort 3, plasma P-tau217 levels were significantly greater among PSEN1 mutation carriers, compared with noncarriers, from approximately 25 years and older, which is 20 years prior to estimated onset of MCI among mutation carriers. Plasma P-tau217 levels correlated with tau tangles in participants with (Spearman ρ = 0.64; P < .001), but not without (Spearman ρ = 0.15; P = .33), β-amyloid plaques in cohort 1. In cohort 2, plasma P-tau217 discriminated abnormal vs normal tau-PET scans (AUC, 0.93 [95% CI, 0.91-0.96]) with significantly higher accuracy than plasma P-tau181, plasma NfL, CSF P-tau181, CSF Aβ42:Aβ40 ratio, and MRI measures (AUC range, 0.67-0.90; P < .05), but its performance was not significantly different compared with CSF P-tau217 (AUC, 0.96; P = .22).
                CONCLUSIONS AND RELEVANCE: Among 1402 participants from 3 selected cohorts, plasma P-tau217 discriminated AD from other neurodegenerative diseases, with significantly higher accuracy than established plasma- and MRI-based biomarkers, and its performance was not significantly different from key CSF- or PET-based measures. Further research is needed to optimize the assay, validate the findings in unselected and diverse populations, and determine its potential role in clinical care.},
  eprinttype = {pubmed}
}

% Proteomics

@article{petersen2020proteomicA,
  title      = {Proteomic profiles of prevalent mild cognitive impairment and Alzheimer's disease among adults with Down syndrome},
  author     = {Melissa Petersen and Fan Zhang and Sharon J Krinsky-McHale and Wayne Silverman and Joseph H Lee and Deborah Pang and James Hall and Nicole Schupf and Sid E O\textquotesingle{}Bryant},
  year       = {2020},
  month      = {04},
  journal    = {Alzheimer's & dementia (Amsterdam, Netherlands)},
  volume     = {12},
  number     = {1},
  pages      = {e12023},
  eprint     = {32435687},
  doi        = {10.1002/dad2.12023},
  language   = {eng},
  issn       = {2352-8729},
  abstract   = {INTRODUCTION: We sought to determine if a proteomic profile approach developed to detect Alzheimer's disease (AD) in the general population would apply to adults with Down syndrome (DS).
                METHODS: Plasma samples were obtained from 398 members of a community-based cohort of adults with DS. A total of n = 186 participants were determined to be non-demented and without mild cognitive impairment (MCI) at baseline and throughout follow-up; n = 50 had prevalent MCI; n = 42 had prevalent AD.
                RESULTS: The proteomic profile yielded an area under the curve (AUC) of 0.92, sensitivity (SN) = 0.80, and specificity (SP) = 0.98 detecting prevalent MCI. For detecting prevalent AD, the proteomic profile yielded an AUC of 0.89, SN = 0.81, and SP = 0.97. The overall profile closely resembled our previously published profile of AD in the general population.
                DISCUSSION: These data provide evidence of the applicability of our blood-based algorithm for detecting MCI/AD among adults with DS.},
  eprinttype = {pubmed}
}
@article{petersen2020proteomicB,
  title      = {Proteomic profiles for Alzheimer's disease and mild cognitive impairment among adults with Down syndrome spanning serum and plasma: An Alzheimer's Biomarker Consortium-Down Syndrome (ABC-DS) study},
  author     = {Melissa E Petersen and Fan Zhang and Nicole Schupf and Sharon J Krinsky-McHale and James Hall and Mark Mapstone and Amrita Cheema and Wayne Silverman and Ira Lott and Michael S Rafii and Benjamin Handen and William Klunk and Elizabeth Head and Brad Christian and Tatiana Foroud and Florence Lai and H Diana Rosas and Shahid Zaman and Beau M Ances and Mei-Cheng Wang and Benjamin Tycko and Joseph H Lee and Sid O\textquotesingle{}Bryant},
  year       = {2020},
  month      = {06},
  journal    = {Alzheimer's & dementia (Amsterdam, Netherlands)},
  volume     = {12},
  number     = {1},
  pages      = {e12039},
  eprint     = {32626817},
  doi        = {10.1002/dad2.12039},
  language   = {eng},
  issn       = {2352-8729},
  abstract   = {INTRODUCTION: Previously generated serum and plasma proteomic profiles were examined among adults with Down syndrome (DS) to determine whether these profiles could discriminate those with mild cognitive impairment (MCI-DS) and Alzheimer's disease (DS-AD) from those cognitively stable (CS).
                METHODS: Data were analyzed on n = 305 (n = 225 CS; n = 44 MCI-DS; n = 36 DS-AD) enrolled in the Alzheimer's Biomarker Consortium-Down Syndrome (ABC-DS).
                RESULTS: Distinguishing MCI-DS from CS, the serum profile produced an area under the curve (AUC) = 0.95 (sensitivity [SN] = 0.91; specificity [SP] = 0.99) and an AUC = 0.98 (SN = 0.96; SP = 0.97) for plasma when using an optimized cut-off score. Distinguishing DS-AD from CS, the serum profile produced an AUC = 0.93 (SN = 0.81; SP = 0.99) and an AUC = 0.95 (SN = 0.86; SP = 1.0) for plasma when using an optimized cut-off score. AUC remained unchanged to slightly improved when age and sex were included. Eotaxin3, interleukin (IL)-10, C-reactive protein, IL-18, serum amyloid A , and FABP3 correlated fractions at r2 > = 0.90.
                DISCUSSION: Proteomic profiles showed excellent detection accuracy for MCI-DS and DS-AD.},
  eprinttype = {pubmed}
}

% MRI Imaging

@article{collins1994automatic,
  title      = {Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space},
  author     = {D L Collins and P Neelin and T M Peters and A C Evans},
  year       = {1994},
  month      = {3},
  journal    = {Journal of computer assisted tomography},
  volume     = {18},
  number     = {2},
  pages      = {192-205},
  eprint     = {8126267},
  language   = {eng},
  issn       = {0363-8715},
  abstract   = {OBJECTIVE: In both diagnostic and research applications, the interpretation of MR images of the human brain is facilitated when different data sets can be compared by visual inspection of equivalent anatomical planes. Quantitative analysis with predefined atlas templates often requires the initial alignment of atlas and image planes. Unfortunately, the axial planes acquired during separate scanning sessions are often different in their relative position and orientation, and these slices are not coplanar with those in the atlas. We have developed a completely automatic method to register a given volumetric data set with Talairach stereotaxic coordinate system.
                MATERIALS AND METHODS: The registration method is based on multi-scale, three-dimensional (3D) cross-correlation with an average (n > 300) MR brain image volume aligned with the Talariach stereotaxic space. Once the data set is re-sampled by the transformation recovered by the algorithm, atlas slices can be directly superimposed on the corresponding slices of the re-sampled volume. the use of such a standardized space also allows the direct comparison, voxel to voxel, of two or more data sets brought into stereotaxic space.
                RESULTS: With use of a two-tailed Student t test for paired samples, there was no significant difference in the transformation parameters recovered by the automatic algorithm when compared with two manual landmark-based methods (p > 0.1 for all parameters except y-scale, where p > 0.05). Using root-mean-square difference between normalized voxel intensities as an unbiased measure of registration, we show that when estimated and averaged over 60 volumetric MR images in standard space, this measure was 30% lower for the automatic technique than the manual method, indicating better registrations. Likewise, the automatic method showed a 57% reduction in standard deviation, implying a more stable technique. The algorithm is able to recover the transformation even when data are missing from the top or bottom of the volume.
                CONCLUSION: We present a fully automatic registration method to map volumetric data into stereotaxic space that yields results comparable with those of manually based techniques. The method requires no manual identification of points or contours and therefore does not suffer the drawbacks involved in user intervention such as reproducibility and interobserver variability.},
  eprinttype = {pubmed}
}
@article{dale1999cortical,
  title      = {Cortical surface-based analysis. I. Segmentation and surface reconstruction},
  author     = {A M Dale and B Fischl and M I Sereno},
  year       = {1999},
  month      = {Feb},
  journal    = {NeuroImage},
  volume     = {9},
  number     = {2},
  pages      = {179-94},
  eprint     = {9931268},
  doi        = {10.1006/nimg.1998.0395},
  language   = {eng},
  issn       = {1053-8119},
  abstract   = {Several properties of the cerebral cortex, including its columnar and laminar organization, as well as the topographic organization of cortical areas, can only be properly understood in the context of the intrinsic two-dimensional structure of the cortical surface. In order to study such cortical properties in humans, it is necessary to obtain an accurate and explicit representation of the cortical surface in individual subjects. Here we describe a set of automated procedures for obtaining accurate reconstructions of the cortical surface, which have been applied to data from more than 100 subjects, requiring little or no manual intervention. Automated routines for unfolding and flattening the cortical surface are described in a companion paper. These procedures allow for the routine use of cortical surface-based analysis and visualization methods in functional brain imaging.},
  eprinttype = {pubmed}
}
@article{fischl1999cortical,
  title      = {Cortical surface-based analysis. II: Inflation, flattening, and a surface-based coordinate system},
  author     = {B Fischl and M I Sereno and A M Dale},
  year       = {1999},
  month      = {Feb},
  journal    = {NeuroImage},
  volume     = {9},
  number     = {2},
  pages      = {195-207},
  eprint     = {9931269},
  doi        = {10.1006/nimg.1998.0396},
  language   = {eng},
  issn       = {1053-8119},
  abstract   = {The surface of the human cerebral cortex is a highly folded sheet with the majority of its surface area buried within folds. As such, it is a difficult domain for computational as well as visualization purposes. We have therefore designed a set of procedures for modifying the representation of the cortical surface to (i) inflate it so that activity buried inside sulci may be visualized, (ii) cut and flatten an entire hemisphere, and (iii) transform a hemisphere into a simple parameterizable surface such as a sphere for the purpose of establishing a surface-based coordinate system.},
  eprinttype = {pubmed}
}
@article{fischl1999high,
  title      = {High-resolution intersubject averaging and a coordinate system for the cortical surface},
  author     = {B Fischl and M I Sereno and R B Tootell and A M Dale},
  year       = {1999},
  month      = {1},
  journal    = {Human brain mapping},
  volume     = {8},
  number     = {4},
  pages      = {272-84},
  eprint     = {10619420},
  doi        = {10.1002/(sici)1097-0193(1999)8:4<272::aid-hbm10>3.0.co;2-4},
  language   = {eng},
  issn       = {1065-9471},
  abstract   = {The neurons of the human cerebral cortex are arranged in a highly folded sheet, with the majority of the cortical surface area buried in folds. Cortical maps are typically arranged with a topography oriented parallel to the cortical surface. Despite this unambiguous sheetlike geometry, the most commonly used coordinate systems for localizing cortical features are based on 3-D stereotaxic coordinates rather than on position relative to the 2-D cortical sheet. In order to address the need for a more natural surface-based coordinate system for the cortex, we have developed a means for generating an average folding pattern across a large number of individual subjects as a function on the unit sphere and of nonrigidly aligning each individual with the average. This establishes a spherical surface-based coordinate system that is adapted to the folding pattern of each individual subject, allowing for much higher localization accuracy of structural and functional features of the human brain.},
  eprinttype = {pubmed}
}
@article{fischl2000measuring,
  title      = {Measuring the thickness of the human cerebral cortex from magnetic resonance images},
  author     = {B Fischl and A M Dale},
  year       = {2000},
  month      = {Sep},
  journal    = {Proceedings of the National Academy of Sciences of the United States of America},
  volume     = {97},
  number     = {20},
  pages      = {11050-5},
  eprint     = {10984517},
  doi        = {10.1073/pnas.200033797},
  language   = {eng},
  issn       = {0027-8424},
  abstract   = {Accurate and automated methods for measuring the thickness of human cerebral cortex could provide powerful tools for diagnosing and studying a variety of neurodegenerative and psychiatric disorders. Manual methods for estimating cortical thickness from neuroimaging data are labor intensive, requiring several days of effort by a trained anatomist. Furthermore, the highly folded nature of the cortex is problematic for manual techniques, frequently resulting in measurement errors in regions in which the cortical surface is not perpendicular to any of the cardinal axes. As a consequence, it has been impractical to obtain accurate thickness estimates for the entire cortex in individual subjects, or group statistics for patient or control populations. Here, we present an automated method for accurately measuring the thickness of the cerebral cortex across the entire brain and for generating cross-subject statistics in a coordinate system based on cortical anatomy. The intersubject standard deviation of the thickness measures is shown to be less than 0.5 mm, implying the ability to detect focal atrophy in small populations or even individual subjects. The reliability and accuracy of this new method are assessed by within-subject test-retest studies, as well as by comparison of cross-subject regional thickness measures with published values.},
  eprinttype = {pubmed}
}
@article{fischl2001automated,
  title      = {Automated manifold surgery: constructing geometrically accurate and topologically correct models of the human cerebral cortex},
  author     = {B Fischl and A Liu and A M Dale},
  year       = {2001},
  month      = {Jan},
  journal    = {IEEE transactions on medical imaging},
  volume     = {20},
  number     = {1},
  pages      = {70-80},
  eprint     = {11293693},
  doi        = {10.1109/42.906426},
  language   = {eng},
  issn       = {0278-0062},
  abstract   = {Highly accurate surface models of the cerebral cortex are becoming increasingly important as tools in the investigation of the functional organization of the human brain. The construction of such models is difficult using current neuroimaging technology due to the high degree of cortical folding. Even single voxel misclassifications can result in erroneous connections being created between adjacent banks of a sulcus, resulting in a topologically inaccurate model. These topological defects cause the cortical model to no longer be homeomorphic to a sheet, preventing the accurate inflation, flattening, or spherical morphing of the reconstructed cortex. Surface deformation techniques can guarantee the topological correctness of a model, but are time-consuming and may result in geometrically inaccurate models. In order to address this need we have developed a technique for taking a model of the cortex, detecting and fixing the topological defects while leaving that majority of the model intact, resulting in a surface that is both geometrically accurate and topologically correct.},
  eprinttype = {pubmed}
}

@misc{n3_nonuniform_intensity_correction,
  title  = {Non-Uniform Intensity Correction},
  author = {{McConnell Brain Imaging Centre}},
  year   = {n.d.},
  url    = {http://www.bic.mni.mcgill.ca/software/N3/node6.html},
  note   = {Accessed: 2026-07-22}
}

@article{fischl2002whole,
  title      = {Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain},
  author     = {Bruce Fischl and David H Salat and Evelina Busa and Marilyn Albert and Megan Dieterich and Christian Haselgrove and Andre {van der Kouwe} and Ron Killiany and David Kennedy and Shuna Klaveness and Albert Montillo and Nikos Makris and Bruce Rosen and Anders M Dale},
  year       = {2002},
  month      = {Jan},
  journal    = {Neuron},
  volume     = {33},
  number     = {3},
  pages      = {341-55},
  eprint     = {11832223},
  doi        = {10.1016/s0896-6273(02)00569-x},
  language   = {eng},
  issn       = {0896-6273},
  abstract   = {We present a technique for automatically assigning a neuroanatomical label to each voxel in an MRI volume based on probabilistic information automatically estimated from a manually labeled training set. In contrast to existing segmentation procedures that only label a small number of tissue classes, the current method assigns one of 37 labels to each voxel, including left and right caudate, putamen, pallidum, thalamus, lateral ventricles, hippocampus, and amygdala. The classification technique employs a registration procedure that is robust to anatomical variability, including the ventricular enlargement typically associated with neurological diseases and aging. The technique is shown to be comparable in accuracy to manual labeling, and of sufficient sensitivity to robustly detect changes in the volume of noncortical structures that presage the onset of probable Alzheimer's disease.},
  eprinttype = {pubmed}
}
@article{fischl2004automatically,
  title      = {Automatically parcellating the human cerebral cortex},
  author     = {Bruce Fischl and Andr\'{e} {van der Kouwe} and Christophe Destrieux and Eric Halgren and Florent S\'{e}gonne and David H Salat and Evelina Busa and Larry J Seidman and Jill Goldstein and David Kennedy and Verne Caviness and Nikos Makris and Bruce Rosen and Anders M Dale},
  year       = {2004},
  month      = {Jan},
  journal    = {Cerebral cortex (New York, N.Y. : 1991)},
  volume     = {14},
  number     = {1},
  pages      = {11-22},
  eprint     = {14654453},
  doi        = {10.1093/cercor/bhg087},
  language   = {eng},
  issn       = {1047-3211},
  abstract   = {We present a technique for automatically assigning a neuroanatomical label to each location on a cortical surface model based on probabilistic information estimated from a manually labeled training set. This procedure incorporates both geometric information derived from the cortical model, and neuroanatomical convention, as found in the training set. The result is a complete labeling of cortical sulci and gyri. Examples are given from two different training sets generated using different neuroanatomical conventions, illustrating the flexibility of the algorithm. The technique is shown to be comparable in accuracy to manual labeling.},
  eprinttype = {pubmed}
}
@article{reuter2011avoiding,
  title      = {Avoiding asymmetry-induced bias in longitudinal image processing},
  author     = {Martin Reuter and Bruce Fischl},
  year       = {2011},
  month      = {Jul},
  journal    = {NeuroImage},
  volume     = {57},
  number     = {1},
  pages      = {19-21},
  eprint     = {21376812},
  doi        = {10.1016/j.neuroimage.2011.02.076},
  language   = {eng},
  issn       = {1095-9572},
  abstract   = {Longitudinal image processing procedures frequently transfer or pool information across time within subject, with the dual goals of reducing the variability and increasing the accuracy of the derived measures. In this note, we discuss common difficulties in longitudinal image processing, focusing on the introduction of bias, and describe the approaches we have taken to avoid them in the FreeSurfer longitudinal processing stream.},
  eprinttype = {pubmed}
}

@article{edwards2025alzheimer,
  title      = {Alzheimer Disease, Vascular Disease, and Blood-Brain Barrier Permeability Biomarkers in Middle-Aged Adults},
  author     = {Natalie C Edwards and Patrick Lao and Mohamad J Alshikho and Jessica Mazen and Benjamin Huber and Christiane Hale and Joncarlos Berroa and Natalie Morel and Alicia Pacheco and Sara Walker and Mathieu Herman and Jose Gutierrez and Donna M Wilcock and Sabrina Simoes and Jennifer J Manly and Adam M Brickman},
  year       = {2025},
  month      = {Nov},
  journal    = {Neurology},
  volume     = {105},
  number     = {9},
  pages      = {e214220},
  eprint     = {41052375},
  doi        = {10.1212/WNL.0000000000214220},
  language   = {eng},
  issn       = {1526-632X},
  abstract   = {BACKGROUND AND OBJECTIVES: Cerebrovascular disease (CVD) influences Alzheimer disease (AD) risk and progression, but the link between vascular disease and AD pathophysiology remains unclear, particularly in midlife when the impact of CVD on AD risk may be strongest. This study examined the relationship of recently validated vascular cognitive impairment (VCI) plasma biomarker concentrations that reflect aspects of blood-brain barrier dysfunction with MRI markers of CVD and AD plasma biomarker concentrations.
                METHODS: The study included middle-aged participants from the Offspring Study of Racial and Ethnic Disparities in AD who had MRI and plasma biomarker data available. Biomarker concentrations of vascular endothelial growth factor (VEGF) family members (VEGF-D, placental growth factor [PlGF], and basic fibroblast growth factor [bFGF]) were measured using the Meso Scale Discovery platform. β-Amyloid (Aβ42, Aβ40), phosphorylated tau 181 (p-tau181), astrocytosis (glial fibrillary acidic protein [GFAP]), and neurodegeneration (neurofilament light chain [NfL]) biomarkers were measured with Simoa immunoassays. White matter hyperintensity (WMH) volumes were derived from T2-weighted MRI scans. Bivariate relationships of WMH, Aβ42/Aβ40 ratio, p-tau181, GFAP, and NfL with VEGF biomarkers were tested, and path analyses examined potential causal pathways linking each VEGF biomarker concentration to WMH and GFAP, as well as their downstream associations with tau pathology and neurodegeneration.
                RESULTS: We analyzed data from 488 participants (mean [SD] age = 54.3 [10.5]; 66.8% women). Higher PlGF levels were associated with older age (R [CI] = 0.25 [0.17-0.33]); greater WMH volume (R [CI] = 0.2 [0.11-0.29]); and higher levels of GFAP (R [CI] = 0.11 [0.02-0.2]), p-tau181 (R [CI] = 0.12 [0.03-0.21]), and NfL (R [CI] = 0.19 [0.1-0.27]). Higher VEGF-D was associated with increased GFAP (R [CI] = 0.11 [0.02-0.19]) and NfL (R [CI] = 0.16 [0.07-0.25]) levels. bFGF concentration was associated with a lower Aβ42/40 ratio (R [CI] = -0.1 [-0.19 to -0.02]) and higher p-tau181 levels (R [CI] = 0.13 [0.04-0.21]). The best fitting path model showed that PlGF had an indirect effect on GFAP levels mediated by WMH. GFAP subsequently had a direct positive effect on p-tau181, which in turn had a positive effect on NfL levels. VEGF-D and bFGF levels also had a positive direct effect on NfL.
                DISCUSSION: The findings suggest that permeability of the blood-brain barrier is linked to AD pathophysiology, contributes to cerebrovascular lesions observed on MRI, and is associated with neuroinflammation in middle age.},
  eprinttype = {pubmed}
}
@article{hoopes2022synthstrip,
  title      = {SynthStrip: skull-stripping for any brain image},
  author     = {Andrew Hoopes and Jocelyn S Mora and Adrian V Dalca and Bruce Fischl and Malte Hoffmann},
  year       = {2022},
  month      = {Oct},
  journal    = {NeuroImage},
  volume     = {260},
  pages      = {119474},
  eprint     = {35842095},
  doi        = {10.1016/j.neuroimage.2022.119474},
  language   = {eng},
  issn       = {1095-9572},
  abstract   = {The removal of non-brain signal from magnetic resonance imaging (MRI) data, known as skull-stripping, is an integral component of many neuroimage analysis streams. Despite their abundance, popular classical skull-stripping methods are usually tailored to images with specific acquisition properties, namely near-isotropic resolution and T1-weighted (T1w) MRI contrast, which are prevalent in research settings. As a result, existing tools tend to adapt poorly to other image types, such as stacks of thick slices acquired with fast spin-echo (FSE) MRI that are common in the clinic. While learning-based approaches for brain extraction have gained traction in recent years, these methods face a similar burden, as they are only effective for image types seen during the training procedure. To achieve robust skull-stripping across a landscape of imaging protocols, we introduce SynthStrip, a rapid, learning-based brain-extraction tool. By leveraging anatomical segmentations to generate an entirely synthetic training dataset with anatomies, intensity distributions, and artifacts that far exceed the realistic range of medical images, SynthStrip learns to successfully generalize to a variety of real acquired brain images, removing the need for training data with target contrasts. We demonstrate the efficacy of SynthStrip for a diverse set of image acquisitions and resolutions across subject populations, ranging from newborn to adult. We show substantial improvements in accuracy over popular skull-stripping baselines - all with a single trained model. Our method and labeled evaluation data are available at https://w3id.org/synthstrip.},
  eprinttype = {pubmed}
}
@article{billot2023synthseg,
  title      = {SynthSeg: Segmentation of brain MRI scans of any contrast and resolution without retraining},
  author     = {Benjamin Billot and Douglas N Greve and Oula Puonti and Axel Thielscher and Koen {Van Leemput} and Bruce Fischl and Adrian V Dalca and Juan Eugenio Iglesias},
  year       = {2023},
  month      = {May},
  journal    = {Medical image analysis},
  volume     = {86},
  pages      = {102789},
  eprint     = {36857946},
  doi        = {10.1016/j.media.2023.102789},
  language   = {eng},
  issn       = {1361-8423},
  abstract   = {Despite advances in data augmentation and transfer learning, convolutional neural networks (CNNs) difficultly generalise to unseen domains. When segmenting brain scans, CNNs are highly sensitive to changes in resolution and contrast: even within the same MRI modality, performance can decrease across datasets. Here we introduce SynthSeg, the first segmentation CNN robust against changes in contrast and resolution. SynthSeg is trained with synthetic data sampled from a generative model conditioned on segmentations. Crucially, we adopt a domain randomisation strategy where we fully randomise the contrast and resolution of the synthetic training data. Consequently, SynthSeg can segment real scans from a wide range of target domains without retraining or fine-tuning, which enables straightforward analysis of huge amounts of heterogeneous clinical data. Because SynthSeg only requires segmentations to be trained (no images), it can learn from labels obtained by automated methods on diverse populations (e.g., ageing and diseased), thus achieving robustness to a wide range of morphological variability. We demonstrate SynthSeg on 5,000 scans of six modalities (including CT) and ten resolutions, where it exhibits unparallelled generalisation compared with supervised CNNs, state-of-the-art domain adaptation, and Bayesian segmentation. Finally, we demonstrate the generalisability of SynthSeg by applying it to cardiac MRI and CT scans.},
  eprinttype = {pubmed}
}
@article{rorden2024improving,
  title      = {Improving 3D edge detection for visual inspection of MRI coregistration and alignment},
  author     = {Chris Rorden and Taylor Hanayik and Daniel R Glen and Roger Newman-Norlund and Chris Drake and Julius Fridriksson and Paul A Taylor},
  year       = {2024},
  month      = {Jun},
  journal    = {Journal of neuroscience methods},
  volume     = {406},
  pages      = {110112},
  eprint     = {38508496},
  doi        = {10.1016/j.jneumeth.2024.110112},
  language   = {eng},
  issn       = {1872-678X},
  abstract   = {BACKGROUND: Visualizing edges is critical for neuroimaging. For example, edge maps enable quality assurance for the automatic alignment of an image from one modality (or individual) to another.
                NEW METHOD: We suggest that using the second derivative (difference of Gaussian, or DoG) provides robust edge detection. This method is tuned by size (which is typically known in neuroimaging) rather than intensity (which is relative).
                RESULTS: We demonstrate that this method performs well across a broad range of imaging modalities. The edge contours produced consistently form closed surfaces, whereas alternative methods may generate disconnected lines, introducing potential ambiguity in contiguity.
                COMPARISON WITH EXISTING METHODS: Current methods for computing edges are based on either the first derivative of the image (FSL), or a variation of the Canny Edge detection method (AFNI). These methods suffer from two primary limitations. First, the crucial tuning parameter for each of these methods relates to the image intensity. Unfortunately, image intensity is relative for most neuroimaging modalities making the performance of these methods unreliable. Second, these existing approaches do not necessarily generate a closed edge/surface, which can reduce the ability to determine the correspondence between a represented edge and another image.
                CONCLUSION: The second derivative is well suited for neuroimaging edge detection. We include this method as part of both the AFNI and FSL software packages, standalone code and online.},
  eprinttype = {pubmed}
}

@article{rohlfing2013incorrect,
  title      = {Incorrect ICBM-DTI-81 atlas orientation and white matter labels},
  author     = {T Rohlfing},
  year       = {2013},
  month      = {01},
  journal    = {Frontiers in neuroscience},
  volume     = {7},
  pages      = {4},
  eprint     = {23355801},
  doi        = {10.3389/fnins.2013.00004},
  language   = {eng},
  issn       = {1662-4548},
  eprinttype = {pubmed}
}
@article{chappell2008variational,
  title     = {Variational Bayesian inference for a nonlinear forward model},
  author    = {Chappell, Michael A and Groves, Adrian R and Whitcher, Brandon and Woolrich, Mark W},
  journal   = {IEEE Transactions on Signal Processing},
  volume    = {57},
  number    = {1},
  pages     = {223--236},
  year      = {2008},
  publisher = {IEEE}
}

@article{groves2009combined,
  title      = {Combined spatial and non-spatial prior for inference on MRI time-series},
  author     = {Adrian R Groves and Michael A Chappell and Mark W Woolrich},
  year       = {2009},
  month      = {Apr},
  journal    = {NeuroImage},
  volume     = {45},
  number     = {3},
  pages      = {795-809},
  eprint     = {19162204},
  doi        = {10.1016/j.neuroimage.2008.12.027},
  language   = {eng},
  issn       = {1095-9572},
  abstract   = {When modelling FMRI and other MRI time-series data, a Bayesian approach based on adaptive spatial smoothness priors is a compelling alternative to using a standard generalized linear model (GLM) on presmoothed data. Another benefit of the Bayesian approach is that biophysical prior information can be incorporated in a principled manner; however, this requirement for a fixed non-spatial prior on a parameter would normally preclude using spatial regularization on that same parameter. We have developed a Gaussian-process-based prior to apply adaptive spatial regularization while still ensuring that the fixed biophysical prior is correctly applied on each voxel. A parameterized covariance matrix provides separate control over the variance (the diagonal elements) and the between-voxel correlation (due to off-diagonal elements). Analysis proceeds using evidence optimization (EO), with variational Bayes (VB) updates used for some parameters. The method can also be applied to non-linear forward models by using a linear Taylor expansion centred on the latest parameter estimates. Applying the method to FMRI with a constrained haemodynamic response function (HRF) shape model shows improved fits in simulations, compared to using either the non-spatial or spatial-smoothness prior alone. We also analyse multi-inversion arterial spin labelling data using a non-linear perfusion model to estimate cerebral blood flow and bolus arrival time. By combining both types of prior information, this new prior performs consistently well across a wider range of situations than either prior alone, and provides better estimates when both types of prior information are relevant.},
  eprinttype = {pubmed}
}

@article{chappell2010separation,
  title      = {Separation of macrovascular signal in multi-inversion time arterial spin labelling MRI},
  author     = {Michael A Chappell and Bradley J MacIntosh and Manus J Donahue and Matthias G\"{u}nther and Peter Jezzard and Mark W Woolrich},
  year       = {2010},
  month      = {May},
  journal    = {Magnetic resonance in medicine},
  volume     = {63},
  number     = {5},
  pages      = {1357-65},
  eprint     = {20432306},
  doi        = {10.1002/mrm.22320},
  language   = {eng},
  issn       = {1522-2594},
  abstract   = {Arterial spin labeling (ASL) provides a noninvasive method to measure brain perfusion and is becoming an increasingly viable alternative to more invasive MR methods due to improvements in acquisition, such as the use of a three-dimensional GRASE readout. A potential source of error in ASL measurements is signal arising from intravascular blood that is destined for more distal tissue. This is typically suppressed using diffusion gradients in many ASL sequences. However, several problems exist with this approach, such as the choice of cutoff velocity and gradient direction and incompatibility with certain readout modules. An alternative approach is to explicitly model the intravascular signal. This study exploits this approach by using multi-inversion time ASL data with a recently developed model-fitting method. The method employed permits the intravascular contribution to be discarded in voxels where there is no support in the data for its inclusion, thereby addressing the issue of overfitting. It is shown by comparing data with and without flow suppression, and by comparing the intravascular contribution in GRASE ASL data to MR angiographic images, that the model-fitting approach can provide a viable alternative to flow suppression in ASL where suppression is either not feasible or not desirable.},
  eprinttype = {pubmed}
}

@article{chappell2011partial,
  title      = {Partial volume correction of multiple inversion time arterial spin labeling MRI data},
  author     = {M A Chappell and A R Groves and B J MacIntosh and M J Donahue and P Jezzard and M W Woolrich},
  year       = {2011},
  month      = {Apr},
  journal    = {Magnetic resonance in medicine},
  volume     = {65},
  number     = {4},
  pages      = {1173-83},
  eprint     = {21337417},
  doi        = {10.1002/mrm.22641},
  language   = {eng},
  issn       = {1522-2594},
  abstract   = {The accuracy of cerebral blood flow (CBF) estimates from arterial spin labeling (ASL) is affected by the presence of both gray matter (GM) and white matter within any voxel. Recently a partial volume (PV) correction method for ASL has been demonstrated (Asllani et al. Magn Reson Med 2008; 60:1362-1371), where PV estimates were used with a local linear regression to separate the GM and white matter ASL signal. Here a new PV correction method for multi-inversion time ASL is proposed that exploits PV estimates within a spatially regularized kinetic curve model analysis. The proposed method exploits both PV estimates and the different kinetics of the ASL signal arising from GM and white matter. The new correction method is shown, on both simulated and real data, to provide correction of GM CBF comparable to a linear regression approach, whilst preserving greater spatial detail in the CBF image. On real data corrected GM CBF values were found to be largely independent of GM PV, implying that the correction had been successful. Increases of mean GM CBF after correction of 69-80% were observed.},
  eprinttype = {pubmed}
}

@article{chappell2013comparing,
  title      = {Comparing model-based and model-free analysis methods for QUASAR arterial spin labeling perfusion quantification},
  author     = {Michael A Chappell and Mark W Woolrich and Esben T Petersen and Xavier Golay and Stephen J Payne},
  year       = {2013},
  month      = {May},
  journal    = {Magnetic resonance in medicine},
  volume     = {69},
  number     = {5},
  pages      = {1466-75},
  eprint     = {22711674},
  doi        = {10.1002/mrm.24372},
  language   = {eng},
  issn       = {1522-2594},
  abstract   = {Amongst the various implementations of arterial spin labeling MRI methods for quantifying cerebral perfusion, the QUASAR method is unique. By using a combination of labeling with and without flow suppression gradients, the QUASAR method offers the separation of macrovascular and tissue signals. This permits local arterial input functions to be defined and "model-free" analysis, using numerical deconvolution, to be used. However, it remains unclear whether arterial spin labeling data are best treated using model-free or model-based analysis. This work provides a critical comparison of these two approaches for QUASAR arterial spin labeling in the healthy brain. An existing two-component (arterial and tissue) model was extended to the mixed flow suppression scheme of QUASAR to provide an optimal model-based analysis. The model-based analysis was extended to incorporate dispersion of the labeled bolus, generally regarded as the major source of discrepancy between the two analysis approaches. Model-free and model-based analyses were compared for perfusion quantification including absolute measurements, uncertainty estimation, and spatial variation in cerebral blood flow estimates. Major sources of discrepancies between model-free and model-based analysis were attributed to the effects of dispersion and the degree to which the two methods can separate macrovascular and tissue signal.},
  eprinttype = {pubmed}
}

@article{alsop2015recommended,
  title      = {Recommended implementation of arterial spin-labeled perfusion MRI for clinical applications: A consensus of the ISMRM perfusion study group and the European consortium for ASL in dementia},
  author     = {David C Alsop and John A Detre and Xavier Golay and Matthias G\"{u}nther and Jeroen Hendrikse and Luis Hernandez-Garcia and Hanzhang Lu and Bradley J MacIntosh and Laura M Parkes and Marion Smits and Matthias J P {van Osch} and Danny J J Wang and Eric C Wong and Greg Zaharchuk},
  year       = {2015},
  month      = {Jan},
  journal    = {Magnetic resonance in medicine},
  volume     = {73},
  number     = {1},
  pages      = {102-16},
  eprint     = {24715426},
  doi        = {10.1002/mrm.25197},
  language   = {eng},
  issn       = {1522-2594},
  abstract   = {This review provides a summary statement of recommended implementations of arterial spin labeling (ASL) for clinical applications. It is a consensus of the ISMRM Perfusion Study Group and the European ASL in Dementia consortium, both of whom met to reach this consensus in October 2012 in Amsterdam. Although ASL continues to undergo rapid technical development, we believe that current ASL methods are robust and ready to provide useful clinical information, and that a consensus statement on recommended implementations will help the clinical community to adopt a standardized approach. In this review, we describe the major considerations and trade-offs in implementing an ASL protocol and provide specific recommendations for a standard approach. Our conclusion is that as an optimal default implementation, we recommend pseudo-continuous labeling, background suppression, a segmented three-dimensional readout without vascular crushing gradients, and calculation and presentation of both label/control difference images and cerebral blood flow in absolute units using a simplified model.},
  eprinttype = {pubmed}
}

@article{almeida2018test,
  title      = {Test-retest reliability of cerebral blood flow in healthy individuals using arterial spin labeling: Findings from the EMBARC study},
  author     = {Jorge R C Almeida and Tsafrir Greenberg and Hanzhang Lu and Henry W Chase and Jay C Fournier and Crystal M Cooper and Thilo Deckersbach and Phil Adams and Thomas Carmody and Maurizio Fava and Benji Kurian and Patrick J McGrath and Melvin G McInnis and Maria A Oquendo and Ramin Parsey and Myrna Weissman and Madhukar Trivedi and Mary L Phillips},
  year       = {2018},
  month      = {Jan},
  journal    = {Magnetic resonance imaging},
  volume     = {45},
  pages      = {26-33},
  eprint     = {28888770},
  doi        = {10.1016/j.mri.2017.09.004},
  language   = {eng},
  issn       = {1873-5894},
  abstract   = {INTRODUCTION: Previous investigations of test-retest reliability of cerebral blood flow (CBF) at rest measured with pseudo-continuous Arterial Spin Labeling (pCASL) demonstrated good reliability, but are limited by the use of similar scanner platforms. In the present study we examined test-retest reliability of CBF in regions implicated in emotion and the default mode network.
                MATERIAL AND METHODS: We measured absolute and relative CBF at rest in thirty-one healthy subjects in two scan sessions, one week apart, at four different sites and three different scan platforms. We derived CBF from pCASL images with an automated algorithm and calculated intra-class correlation coefficients (ICCs) across sessions for regions of interest. In addition, we investigated site effects.
                RESULTS: For both absolute and relative CBF measures, ICCs were good to excellent (i.e. >0.6) in most brain regions, with highest values observed for the subgenual anterior cingulate cortex and ventral striatum. A leave-one-site-out cross validation analysis did not show a significant effect for site on whole brain CBF and there was no proportional bias across sites. However, a significant site effect was present in the repeated measures ANOVA.
                CONCLUSIONS: The high test-retest reliability of CBF measured with pCASL in a range of brain regions implicated in emotion and salience processing, emotion regulation, and the default mode network, which have been previously linked to depression symptomatology supports its use in studies that aim to identify neuroimaging biomarkers of treatment response.},
  eprinttype = {pubmed}
}

@article{chesebro2021automated,
  title      = {Automated detection of cerebral microbleeds on T2*-weighted MRI},
  author     = {Anthony G Chesebro and Erica Amarante and Patrick J Lao and Irene B Meier and Richard Mayeux and Adam M Brickman},
  year       = {2021},
  month      = {Feb},
  journal    = {Scientific reports},
  volume     = {11},
  number     = {1},
  pages      = {4004},
  eprint     = {33597663},
  doi        = {10.1038/s41598-021-83607-0},
  language   = {eng},
  issn       = {2045-2322},
  abstract   = {Cerebral microbleeds, observed as small, spherical hypointense regions on gradient echo (GRE) or susceptibility weighted (SWI) magnetic resonance imaging (MRI) sequences, reflect small hemorrhagic infarcts, and are associated with conditions such as vascular dementia, small vessel disease, cerebral amyloid angiopathy, and Alzheimer's disease. The current gold standard for detecting and rating cerebral microbleeds in a research context is visual inspection by trained raters, a process that is both time consuming and subject to poor reliability. We present here a novel method to automate microbleed detection on GRE and SWI images. We demonstrate in a community-based cohort of older adults that the method is highly sensitive (greater than 92% of all microbleeds accurately detected) across both modalities, with reasonable precision (fewer than 20 and 10 false positives per scan on GRE and SWI, respectively). We also demonstrate that the algorithm can be used to identify microbleeds over longitudinal scans with a higher level of sensitivity than visual ratings (50% of longitudinal microbleeds correctly labeled by the algorithm, while manual ratings was 30% or lower). Further, the algorithm identifies the anatomical localization of microbleeds based on brain atlases, and greatly reduces time spent completing visual ratings (43% reduction in visual rating time). Our automatic microbleed detection instrument is ideal for implementation in large-scale studies that include cross-sectional and longitudinal scanning, as well as being capable of performing well across multiple commonly used MRI modalities.},
  eprinttype = {pubmed}
}
@article{lao2020alzheimer,
  title      = {Alzheimer-Related Cerebrovascular Disease in Down Syndrome},
  author     = {Patrick J Lao and Jos\'{e} Gutierrez and David Keator and Batool Rizvi and Arit Banerjee and Kay C Igwe and Krystal K Laing and Mithra Sathishkumar and Fahmida Moni and Howard Andrews and Sharon Krinsky-McHale and Elizabeth Head and Joseph H Lee and Florence Lai and Michael A Yassa and H Diana Rosas and Wayne Silverman and Ira T Lott and Nicole Schupf and Adam M Brickman},
  year       = {2020},
  month      = {Dec},
  journal    = {Annals of neurology},
  volume     = {88},
  number     = {6},
  pages      = {1165-1177},
  eprint     = {32944999},
  doi        = {10.1002/ana.25905},
  language   = {eng},
  issn       = {1531-8249},
  abstract   = {OBJECTIVE: Adults with Down syndrome (DS) develop Alzheimer disease (AD) pathology by their 5th decade. Compared with the general population, traditional vascular risks in adults with DS are rare, allowing examination of cerebrovascular disease in this population and insight into its role in AD without the confound of vascular risk factors. We examined in vivo magnetic resonance imaging (MRI)-based biomarkers of cerebrovascular pathology in adults with DS, and determined their cross-sectional relationship with age, beta-amyloid pathology, and mild cognitive impairment or clinical AD diagnostic status.
                METHODS: Participants from the Biomarkers of Alzheimer's Disease in Down Syndrome study (n = 138, 50 ± 7 years, 39% women) with MRI data and a subset (n = 90) with amyloid positron emission tomography (PET) were included. We derived MRI-based biomarkers of cerebrovascular pathology, including white matter hyperintensities (WMH), infarcts, cerebral microbleeds, and enlarged perivascular spaces (PVS), as well as PET-based biomarkers of amyloid burden. Participants were characterized as cognitively stable (CS), mild cognitive impairment-DS (MCI-DS), possible AD dementia, or definite AD dementia based on in-depth assessments of cognition, function, and health status.
                RESULTS: There were detectable WMH, enlarged PVS, infarcts, and microbleeds as early as the 5th decade of life. There was a monotonic increase in WMH volume, enlarged PVS, and presence of infarcts across diagnostic groups (CS < MCI-DS < possible AD dementia < definite AD dementia). Higher amyloid burden was associated with a higher likelihood of an infarct.
                INTERPRETATION: The findings highlight the prevalence of cerebrovascular disease in adults with DS and add to a growing body of evidence that implicates cerebrovascular disease as a core feature of AD and not simply a comorbidity. ANN NEUROL 2020;88:1165-1177.},
  eprinttype = {pubmed}
}
@article{lao2024cerebrovascular,
  title      = {Cerebrovascular disease emerges with age and Alzheimer's disease in adults with Down syndrome},
  author     = {Patrick Lao and Natalie Edwards and Lisi Flores-Aguilar and Mohamad Alshikho and Batool Rizvi and Dana Tudorascu and H Diana Rosas and Michael Yassa and Bradley T Christian and Mark Mapstone and Benjamin Handen and Molly E Zimmerman and Jose Gutierrez and Donna Wilcock and Elizabeth Head and Adam M Brickman},
  year       = {2024},
  month      = {May},
  journal    = {Scientific reports},
  volume     = {14},
  number     = {1},
  pages      = {12334},
  eprint     = {38811657},
  doi        = {10.1038/s41598-024-61962-y},
  language   = {eng},
  issn       = {2045-2322},
  abstract   = {Adults with Down syndrome have a genetic form of Alzheimer's disease (AD) and evidence of cerebrovascular disease across the AD continuum, despite few systemic vascular risk factors. The onset and progression of AD in Down syndrome is highly age-dependent, but it is unknown at what age cerebrovascular disease emerges and what factors influence its severity. In the Alzheimer's Biomarker Consortium-Down Syndrome study (ABC-DS; n = 242; age = 25-72), we estimated the age inflection point at which MRI-based white matter hyperintensities (WMH), enlarged perivascular spaces (PVS), microbleeds, and infarcts emerge in relation to demographic data, risk factors, amyloid and tau, and AD diagnosis. Enlarged PVS and infarcts appear to develop in the early 30s, while microbleeds, WMH, amyloid, and tau emerge in the mid to late 30s. Age-residualized WMH were higher in women, in individuals with dementia, and with lower body mass index. Participants with hypertension and APOE-ε4 had higher age-residualized PVS and microbleeds, respectively. Lifespan trajectories demonstrate a dramatic cerebrovascular profile in adults with Down syndrome that appears to evolve developmentally in parallel with AD pathophysiology approximately two decades prior to dementia symptoms.},
  eprinttype = {pubmed}
}
@article{ramirez2016imaging,
  title      = {Imaging the Perivascular Space as a Potential Biomarker of Neurovascular and Neurodegenerative Diseases},
  author     = {Joel Ramirez and Courtney Berezuk and Alicia A McNeely and Fuqiang Gao and JoAnne McLaurin and Sandra E Black},
  year       = {2016},
  month      = {Mar},
  journal    = {Cellular and molecular neurobiology},
  volume     = {36},
  number     = {2},
  pages      = {289-99},
  eprint     = {26993511},
  doi        = {10.1007/s10571-016-0343-6},
  language   = {eng},
  issn       = {1573-6830},
  abstract   = {Although the brain lacks conventional lymphatic vessels found in peripheral tissue, evidence suggests that the space surrounding the vasculature serves a similar role in the clearance of fluid and metabolic waste from the brain. With aging, neurodegeneration, and cerebrovascular disease, these microscopic perivascular spaces can become enlarged, allowing for visualization and quantification on structural MRI. The purpose of this review is to: (i) describe some of the recent pre-clinical findings from basic science that shed light on the potential neurophysiological mechanisms driving glymphatic and perivascular waste clearance, (ii) review some of the pathobiological etiologies that may lead to MRI-visible enlarged perivascular spaces (ePVS), (iii) describe the possible clinical implications of ePVS, (iv) evaluate existing qualitative and quantitative techniques used for measuring ePVS burden, and (v) propose future avenues of research that may improve our understanding of this potential clinical neuroimaging biomarker for fluid and metabolic waste clearance dysfunction in neurodegenerative and neurovascular diseases.},
  eprinttype = {pubmed}
}
@article{zhu2010severity,
  title      = {Severity of dilated Virchow-Robin spaces is associated with age, blood pressure, and MRI markers of small vessel disease: a population-based study},
  author     = {Yi-Cheng Zhu and Christophe Tzourio and A\"{\i}cha Soumar\'{e} and Bernard Mazoyer and Carole Dufouil and Hugues Chabriat},
  year       = {2010},
  month      = {Nov},
  journal    = {Stroke},
  volume     = {41},
  number     = {11},
  pages      = {2483-90},
  eprint     = {20864661},
  doi        = {10.1161/STROKEAHA.110.591586},
  language   = {eng},
  issn       = {1524-4628},
  abstract   = {BACKGROUND AND PURPOSE: Little is known about the risk factors of dilated Virchow-Robin spaces (dVRS) and their relation with other markers of brain small vessel disease. We investigated both issues in a large population-based sample of elderly individuals.
                METHODS: Severity of dVRS was semiquantitatively graded in both white matter and basal ganglia using high-resolution 3-dimensional MRI images taken from 1818 stroke- and dementia-free subjects enrolled in the Three-City Dijon MRI study. Multinomial logistic regression models were used to model the association of cardiovascular risk factors, APOE genotype, brain atrophy, and MRI markers of small vessel disease with the degree of dVRS.
                RESULTS: Severity of dVRS was found to be strongly associated with age in both basal ganglia (degree 4 versus 1: OR, 2.1; 95% CI, 1.4 to 3.2) and white matter (OR, 1.5; 95% CI, 1.2 to 1.9). The proportion of hypertensive subjects increased with the degrees of dVRS in both basal ganglia (P = 0.02) and white matter (P = 0.048). Men presented a higher risk of severe dVRS in basal ganglia than women, particularly degree 4 (OR, 6.0; 95% CI, 1.8 to 19.8). The degree of dVRS was associated with the volume of white matter hyperintensities and the prevalence of lacunes, but not with brain atrophy.
                CONCLUSIONS: In this large cohort study of elderly subjects, the degree of dVRS appears independently associated with age, hypertension, volume of white matter hyperintensities, and lacunar infarctions. dVRS should be considered as another MRI marker of cerebral small vessel disease in the elderly with regional variations in their severity.},
  eprinttype = {pubmed}
}