Evidence map›Paper›PMID 40083197›Full record

ArticleHuman brain mapping2025

Brain Morphometrics Correlations With Age Among 350 Participants Imaged With Both 3T and 7T MRI: 7T Improves Statistical Power and Reduces Required Sample Size.

Cong Chu, Tales Santini, Jr-Jiun Liou, Ann D Cohen, Pauline M Maki, Anna L Marsland, Rebecca C Thurston, Peter J Gianaros, Tamer S Ibrahim

Abstract read
In one paragraph

Article in Human brain mapping, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Cong ChuDepartment of Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.ORCID 0009-0005-0205-105X
Tales SantiniDepartment of Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.ORCID 0000-0003-4533-9190
Jr-Jiun LiouDepartment of Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.ORCID 0000-0002-8800-9557
Ann D CohenDepartment of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.ORCID 0000-0001-7395-9624
Pauline M MakiDepartments of Psychiatry, Psychology and Obstetrics & Gynecology, University of Illinois Chicago, Chicago, Illinois, USA.ORCID 0000-0002-8443-3430
Anna L MarslandDepartment of Psychology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.ORCID 0000-0001-8951-7513
Rebecca C ThurstonDepartments of Psychiatry, Clinical and Translational Science, Epidemiology and Psychology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.ORCID 0000-0001-6580-1202
Peter J GianarosDepartments of Psychology and Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.ORCID 0000-0003-2313-5277
Tamer S IbrahimDepartments of Bioengineering, Psychiatry, and Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.ORCID 0000-0001-6738-5855

Funding

Vascular Moderators of the Impact of Alzheimer's Pathology in the Young-OldP01AG025204 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI HOWARD J AIZENSTEIN, Ann D. Cohen · 2005 to 2026
$56.5M
Substrates of Threat and Reward Sensitivity and CVD RiskP01HL040962 · NHLBI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI GIANAROS, PETER J · 1988 to 2022
$31.1M
Menopausal Vasomotor Symptoms and Brain Aging in WomenRF1AG053504 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI MAKI, PAULINE M, THURSTON, REBECCA C · 2016 to 2019
$4.1M
Menopausal Vasomotor Symptoms and Brain Aging in WomenR01AG053504 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI MAKI, PAULINE M, THURSTON, REBECCA C · 2021 to 2025
$3.8M
High Performance Imaging for Assessment of Small Vessel Disease in Older Adults with DepressionR01MH111265 · NIMH · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI AIZENSTEIN, HOWARD J, IBRAHIM, TAMER S · 2016 to 2020
$3.6M
SARS-CoV-2 and Precursors of Alzheimer's Disease and Related Dementias: An Ultrahigh Field (7T) MRI Study in a Diverse Multinational CohortR56AG074467 · NIA · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI GIRARD, TIMOTHY D, HOSSEINI, AKRAM A. · 2021 to 2021
$3.5M
Metabolic and Inflammatory Pathways of Midlife Neurocognitive DisparitiesR01DK110041 · NIDDK · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI GIANAROS, PETER J, MARSLAND, ANNA L · 2017 to 2021
$3.3M
Mechanisms linking hot flashes to cardiovascular riskR01HL105647 · NHLBI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI THURSTON, REBECCA C · 2011 to 2015
$3.2M
Interdisciplinary Mentoring and Research in Womens Cardiovascular HealthK24HL123565 · NHLBI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI THURSTON, REBECCA C · 2014 to 2023
$1.0M
High-Throughput Computing for Genomics and Bioinformatics ResearchS10OD028483 · OD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI LEE, ADRIAN V · 2021 to 2021
$574k
NHLBI NIH HHS K24 HL123565NHLBI NIH HHS P01 HL040962NHLBI NIH HHS R01 HL105647NIA NIH HHS P01 AG025204NIA NIH HHS R01 AG053504NIA NIH HHS R56 AG074467NIA NIH HHS RF1 AG053504NIDDK NIH HHS R01 DK110041NIH HHS P01AG025204NIH HHS P01HL040962NIH HHS R01AG053504NIH HHS R01DK110041NIH HHS R01MH111265NIH HHS R56AG074467NIH HHS RF1AG053504NIH HHS S10 OD028483NIMH NIH HHS R01 MH111265
6 · The paper itself

Abstract

Magnetic resonance imaging (MRI) at 7T has a superior signal-to-noise ratio to 3T but also presents higher signal inhomogeneities and geometric distortions. A key knowledge gap is to robustly investigate the sensitivity and accuracy of 3T and 7T MRI in assessing brain morphometrics. This study aims to (a) aggregate a large number of paired 3T and 7T scans to evaluate their differences in quantitative brain morphological assessment using a widely available brain segmentation tool, FreeSurfer, as well as to (b) examine the impact of normalization methods for subject variability and smaller sample sizes on data analysis. A total of 401 healthy participants aged 29-68 were imaged at both 3T and 7T. Structural T1-weighted magnetization-prepared rapid gradient-echo (MPRAGE) images were processed and segmented using FreeSurfer. To account for head size variability, the brain volumes underwent intracranial volume (ICV) correction using the Residual (regression model) and Proportional (simple division to ICV) methods. The resulting volumes and thicknesses were correlated with age using Pearson's correlation and false discovery rate correction. The correlations were also calculated in increasing sample size from three to the whole sample to estimate the sample size required to detect aging-related brain variation. Three hundred and fifty subjects (208 females) passed the image quality control, with 51 subjects excluded due to excessive motion artifacts on 3T, 7T, or both. 7T MRI showed an overall stronger correlation between morphometrics and age and a larger number of significantly correlated brain volumes and cortical thicknesses. While the ICV is consistent between both field strengths, the Residual normalization method shows markedly higher correlation with age for 3T when compared with the Proportional normalization method. The 7T results are consistent regardless of the normalization method used. In a large cohort of healthy participants with paired 3T and 7T scans, we compared the statistical performance in assessing age-related brain morphological changes. Our study reaffirmed the inverse correlation between brain volumes and cortical thicknesses and age and highlighted varying correlations in different brain regions and normalization methods at 3T and 7T. 7T imaging significantly improves statistical power and thus reduces the required sample size.

Indexed as

AgingBrainMagnetic Resonance ImagingNeuroimagingAdultAgedFemaleHumansImage Processing, Computer-AssistedMaleMiddle AgedSample Size3T7Tagingbrain morphometricsmagnetic resonance imaging

Identifiers

PMID40083197
PMCPMC11907059

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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.