Evidence map›Paper›PMID 41966233›Full record

ArticleNeuroImage2026

Test-retest reliability of FreeSurfer measures of neurodegeneration.

Henry Rusinek, Louisa Bokacheva, Haiyun Chen, Arjun Masurkar, Ricardo Osorio, Rebecca Betensky, Alok Vedvyas, Joshua Chodosh, Yongzhao Shao, Timothy Shepherd and 2 more

Abstract read
In one paragraph

Article in NeuroImage, 2026. 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

12 authors.

Henry RusinekDepartment of Radiology and Psychiatry, NYU Grossman School of Medicine, 660 First Ave, New York, NY 10016, USA; Department of Psychiatry, NYU Grossman School of Medicine, 145 East 32nd Street, New York, NY 10016, USA. Electronic address: hr18@nyu.edu.
Louisa BokachevaDepartment of Neurology, NYU Grossman School of Medicine, 145 East 32nd Street, New York, NY 10016, USA. Electronic address: Louisa.Bokacheva@nyulangone.org.
Haiyun ChenDepartment of Neurology, NYU Grossman School of Medicine, 145 East 32nd Street, New York, NY 10016, USA. Electronic address: Haiyun.Chen@nyulangone.org.
Arjun MasurkarDepartment of Neurology, NYU Grossman School of Medicine, 145 East 32nd Street, New York, NY 10016, USA. Electronic address: Arjun.Masurkar@nyulangone.org.
Ricardo OsorioDepartment of Psychiatry, NYU Grossman School of Medicine, 145 East 32nd Street, New York, NY 10016, USA. Electronic address: Ricardo.Osorio@nyulangone.org.
Rebecca BetenskyDepartment of Biostatistics, NYU School of Global Public Health, 708 Broadway, New York, NY 10003, USA. Electronic address: Rebecca.Betensky@nyu.edu.
Alok VedvyasDepartment of Neurology, NYU Grossman School of Medicine, 145 East 32nd Street, New York, NY 10016, USA. Electronic address: Alok.Vedvyas@nyulangone.org.
Joshua ChodoshDepartment of Medicine, NYU Grossman School of Medicine, 550 First Ave, New York, NY 10016, USA. Electronic address: Joshua.Chodosh@nyulangone.org.
Yongzhao ShaoDepartment of Population Health, NYU Grossman School of Medicine, 550 First Ave, New York, NY 10016, USA. Electronic address: Yongzhao.Shao@nyulangone.org.
Timothy ShepherdDepartment of Radiology and Psychiatry, NYU Grossman School of Medicine, 660 First Ave, New York, NY 10016, USA. Electronic address: Timothy.Shepherd@nyulangone.org.
Karyn MarshDepartment of Neurology, NYU Grossman School of Medicine, 145 East 32nd Street, New York, NY 10016, USA. Electronic address: Karyn.Marsh@nyulangone.org.
Thomas WisniewskiDepartment of Neurology, NYU Grossman School of Medicine, 145 East 32nd Street, New York, NY 10016, USA. Electronic address: Thomas.Wisniewski@nyulangone.org.

Funding

Research Education ComponentP30AG066512 · NIA · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Mary Sherman Mittelman · 2020 to 2026
$28.4M
ARIA Pathophysiology Characterized by in vivo Neuroimaging, Plasma Biomarkers and Post-Mortem ProteomicsU24NS141774 · NINDS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI GE, YULIN, LU, HANZHANG · 2025 to 2025
$3.3M
NIA NIH HHS P30 AG066512NINDS NIH HHS U24 NS141774
6 · The paper itself

Abstract

Reliable structural brain measurements are essential for studying neurodegeneration and for designing adequately powered aging and Alzheimer's disease (AD) research. We evaluated the test-retest reliability of FreeSurfer 7.1 morphometric measures in 100 older adults (mean age 73.5 years) ranging from cognitively unimpaired to dementia. Each participant underwent two T1-weighted 3T MRI scans on the same scanner within a short interval (mean 5.5 weeks), minimizing biological change. Segmentation was performed in both standard cross-sectional and longitudinal FreeSurfer modes, focusing on AD-relevant volumes of entorhinal cortex, hippocampus, lateral ventricles, choroid plexus, and the AD cortical thickness signature. Reliability was quantified using absolute and root-mean-square test-retest differences, standard deviation of differences, and intraclass correlation coefficients. Longitudinal processing improved precision by 15-50% across most measures compared with cross-sectional processing, with the largest gain observed for entorhinal thickness. Larger, anatomically well-defined regions (e.g., hippocampus, AD signature) demonstrated higher reliability than small structures or those with complex geometry (e.g., entorhinal cortex, choroid plexus). Image quality, indexed by the Euler characteristic, was the only factor significantly associated with measurement variability; reliability was unrelated to age, sex, cognitive status, inter-scan interval, or amyloid/tau PET burden. Power analyses indicated that detecting a 1% within-individual change requires sample sizes ranging from 36 (AD signature) to >300 (entorhinal cortex). We observed low reliability of choroid plexus volumetry by FreeSurfer 7. These results provide practical benchmarks for expected FreeSurfer measurement variability in older adults. They highlight the advantages of longitudinal processing and rigorous quality control for research on brain aging and AD.

Indexed as

Alzheimer DiseaseBrainMagnetic Resonance ImagingAgedAged, 80 and overAgingFemaleHumansMaleReproducibility of Results

Identifiers

PMID41966233
PMCPMC13293555

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.