Evidence map›Paper›PMID 42339065›Full record

ArticleAlzheimer's & dementia (Amsterdam, Netherlands)

Features predicting data exclusion in imaging studies of Alzheimer's disease.

Shaney Flores, Jalen Scott, Ruijin Lu, Yi Su, Sarah J Keefe, T Hunter Smith, Russ C Hornbeck, Nicole S McKay, Jeremy F Strain, Ashlee Simmons and 18 more

Abstract read
In one paragraph

Article in Alzheimer's & dementia (Amsterdam, Netherlands). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

28 authors.

Shaney FloresMallinckrodt Institute of Radiology Washington University in St. Louis School of Medicine St. Louis Missouri USA.ORCID https://orcid.org/0000-0003-2726-8704
Jalen ScottMallinckrodt Institute of Radiology Washington University in St. Louis School of Medicine St. Louis Missouri USA.
Ruijin LuCharles F. and Joanne Knight Alzheimer's Disease Research Center Washington University in St. Louis School of Medicine St. Louis Missouri USA.
Yi SuBanner Alzheimer's Institute Phoenix Arizona USA.
Sarah J KeefeMallinckrodt Institute of Radiology Washington University in St. Louis School of Medicine St. Louis Missouri USA.
T Hunter SmithMallinckrodt Institute of Radiology Washington University in St. Louis School of Medicine St. Louis Missouri USA.
Russ C HornbeckMallinckrodt Institute of Radiology Washington University in St. Louis School of Medicine St. Louis Missouri USA.
Nicole S McKayMallinckrodt Institute of Radiology Washington University in St. Louis School of Medicine St. Louis Missouri USA.
Jeremy F StrainDepartment of Neurology Washington University in St. Louis School of Medicine St. Louis Missouri USA.
Ashlee SimmonsMallinckrodt Institute of Radiology Washington University in St. Louis School of Medicine St. Louis Missouri USA.
Kaitlyn DombrowskiMallinckrodt Institute of Radiology Washington University in St. Louis School of Medicine St. Louis Missouri USA.
Jacqueline RizzoMallinckrodt Institute of Radiology Washington University in St. Louis School of Medicine St. Louis Missouri USA.
Hope ShimonyMallinckrodt Institute of Radiology Washington University in St. Louis School of Medicine St. Louis Missouri USA.
Randall J BatemanDepartment of Neurology Washington University in St. Louis School of Medicine St. Louis Missouri USA.
Ganesh M BabulalDepartment of Neurology Washington University in St. Louis School of Medicine St. Louis Missouri USA.
Susan M LandauDepartment of Neuroscience University of California Berkeley Berkeley California USA.
William JagustDepartment of Neuroscience University of California Berkeley Berkeley California USA.
David A WolkDeparment of Neurology University of Pennsylvania Perelman School of Medicine Philadelphia Pennsylvania USA.
James LahDepartment of Neurology Emory University School of Medicine Atlanta Georgia USA.
Carey GleasonWisconsin Alzheimer's Disease Research Center University of Wisconsin-Madison Madison Wisconsin USA.
Sterling JohnsonWisconsin Alzheimer's Disease Research Center University of Wisconsin-Madison Madison Wisconsin USA.
Erik D RobersonUniversity of Alabama at Birmingham Alzheimer's Disease Research Center Birmingham Alabama USA.
Reisa SperlingMassachusetts Alzheimer's Research Center Massachusetts General Hospital Charlestown Massachusetts USA.
Keith JohnsonMassachusetts Alzheimer's Research Center Massachusetts General Hospital Charlestown Massachusetts USA.
John C MorrisCharles F. and Joanne Knight Alzheimer's Disease Research Center Washington University in St. Louis School of Medicine St. Louis Missouri USA.
Chengjie XiongCharles F. and Joanne Knight Alzheimer's Disease Research Center Washington University in St. Louis School of Medicine St. Louis Missouri USA.
Brian A GordonMallinckrodt Institute of Radiology Washington University in St. Louis School of Medicine St. Louis Missouri USA.
Tammie L S BenzingerMallinckrodt Institute of Radiology Washington University in St. Louis School of Medicine St. Louis Missouri USA.

Funding

Smartphone-Based "Burst" Cognitive AssessmentsP01AG003991 · NIA · WASHINGTON UNIVERSITY · PI Tammie Lee Smith Benzinger · 1985 to 2026
$69.5M
The natural history of AB accumulation in preclinical ADP01AG026276 · NIA · WASHINGTON UNIVERSITY · PI SCHINDLER, SUZANNE ELIZABETH · 2005 to 2025
$49.5M
Research Education ComponentP30AG066444 · NIA · WASHINGTON UNIVERSITY · PI DAVID M. HOLTZMAN · 2020 to 2026
$28.7M
NIA NIH HHS P01 AG003991NIA NIH HHS P01 AG026276NIA NIH HHS P30 AG066444
6 · The paper itself

Abstract

introductionPositron emission tomography (PET) without usable or accompanying magnetic resonance imaging (MRI) is typically excluded in quantitative analyses of Alzheimer's disease, potentially limiting study generalizability. We investigated participant features predicting data exclusion in magnetic resonance (MR)-dependent analyses and evaluated an existing MR-free PET pipeline to quantify these missing data.

methodsImaging, clinical, cognitive, and sociodemographic data were analyzed for 2119 individuals in a multi-site cohort. Agreement between MR-dependent and MR-free Centiloids (CL) assessed using intra-class correlations and features predicting data exclusion were examined using logistic regressions.

resultsMR-free and MR-dependent CLs generally agreed, but MR-free CLs underestimated MR-dependent cross-sectionally and longitudinally. Approximately 19.5% ( DISCUSSION: Data exclusion in imaging studies is not entirely random. Flexible quantification methods like MR-free PET could supplement traditional methods to improve generalizability in large, multi-site studies.

Indexed as

amyloid positron emission tomography (PET)Centiloiddata exclusiongeneralizabilitymagnetic resonance (MR)‐free

Identifiers

PMID42339065
PMCPMC13283902

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.