Evidence map›Paper›PMID 42115951›Full record

ArticleBMC medical imaging2026

A longitudinal analysis of T1-weighted MRI features associated with progression from mild cognitive impairment to Alzheimer's disease.

Yanxia Wang, Wangchen Song, Xinyu Yang, Weijing Meng, Yonghua Ma, Aimin Wang, Guiya Guo, Zhaoxue Zhang, Zihui Li, Hairui Han and 2 more

Abstract read
In one paragraph

Article in BMC medical imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Yanxia Wang *Department of Health Statistics, School of Public Health, Shandong Second Medical University, Weifang, Shandong, 261053, China.
Wangchen Song *Department of Health Statistics, School of Public Health, Shandong Second Medical University, Weifang, Shandong, 261053, China.
Xinyu Yang *Department of Health Statistics, School of Public Health, Shandong Second Medical University, Weifang, Shandong, 261053, China.
Weijing Meng *Experimental Teaching Center for Public Health and Preventive Medicine, School of Public Health, Shandong Second Medical University, Weifang, Shandong, 261053, China.
Yonghua MaDepartment of Health Statistics, School of Public Health, Shandong Second Medical University, Weifang, Shandong, 261053, China.
Aimin WangDepartment of Health Statistics, School of Public Health, Shandong Second Medical University, Weifang, Shandong, 261053, China.
Guiya GuoDepartment of Health Statistics, School of Public Health, Shandong Second Medical University, Weifang, Shandong, 261053, China.
Zhaoxue ZhangDepartment of Health Statistics, School of Public Health, Shandong Second Medical University, Weifang, Shandong, 261053, China.
Zihui LiDepartment of Health Statistics, School of Public Health, Shandong Second Medical University, Weifang, Shandong, 261053, China.
Hairui HanDepartment of Health Statistics, School of Public Health, Shandong Second Medical University, Weifang, Shandong, 261053, China.
Suzhen Wang *Department of Health Statistics, School of Public Health, Shandong Second Medical University, Weifang, Shandong, 261053, China. wangsz@sdsmu.edu.cn.
Fuyan Shi *Department of Health Statistics, School of Public Health, Shandong Second Medical University, Weifang, Shandong, 261053, China. shifuyan@sdsmu.edu.cn.

Funding

National Natural Science Foundation of China 81803337National Natural Science Foundation of China 81872719Shandong Provincial Youth Innovation Team Development Plan of Colleges and Universities No. 2019-6-156, Lu-Jiaothe Shandong Provincial Natural Science Foundation No. ZR2023MH313)
6 · The paper itself

Abstract

objectiveOur study aimed to systematically identify T1-weighted MRI-derived brain structural features associated with progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD).

methodsWe utilized the data from the Alzheimer's Disease Neuroimaging Initiative (ADNI). A total of 947 participants with MCI at baseline were included. All participants underwent a neuropsychological assessment and clinical diagnosis every 6 months. The longest follow-up period was 15.5 years, with a median follow-up time of 3.0 years (range: 0-15.5 years). During the follow-up period, 314 (33.16%) individuals progressed to AD, while 633 (66.84%) remained stable or reverted to normal cognition. After ComBat-based harmonization to reduce scanner-related batch effects, 192 high-dimensional T1-magnetic resonance imaging (MRI)-derived morphometric and volumetric measures were analyzed. To identify the characteristics associated with AD progression from MCI, we employed a comprehensive analysis framework. Firstly, we applied the penalized generalized estimating equations (PGEE) and mixed effects random forest (MERF) models for feature screening. Based on the union features obtained from these two methods, a high-dimensional joint model (HDJM) was further used to select the key brain structural features. Lastly, a multivariate joint model was employed to capture the influence of the longitudinal MRI trajectories on the MCI-to-AD conversion.

resultsWe identified 8 brain structural features from 192 MRI features that were associated with the risk of MCI progressing to AD, including: left hippocampus, left inferior lateral ventricle, left amygdala, right middle temporal gyrus, left fusiform gyrus, right amygdala, left cortical total volume, and brain parenchyma total volume. In the multivariate joint model, the atrophy of left hippocampus volume (α = -0.0009, P = 0.0010), the expansion of left lateral inferior ventricle volume (α = 0.0003, P = 0.0238), the atrophy of right middle temporal gyrus volume (α = -0.0002, P = 0.0036), and the accelerated atrophy of brain parenchyma total volume (α = 0.000005, P = 0.0008) were all significantly associated with the risk of disease transformation. Additionally, the covariate APOE ε4 allele remained a significant independent risk factor (γ = 0.6930, P < 0.0001).

conclusionLeft hippocampal atrophy, left inferior lateral ventricular enlargement, right middle temporal gyrus atrophy, and brain parenchyma total volume atrophy were independently associated with the risk of progression from MCI to AD, alongside the established genetic risk factor APOE ε4.

Indexed as

Alzheimer DiseaseBrainCognitive DysfunctionMagnetic Resonance ImagingAgedAged, 80 and overDisease ProgressionFemaleHumansLongitudinal StudiesMaleAlzheimer's diseaseHigh-dimensional joint modelImaging dataMixed effects random forestPenalized generalized estimating equation

Identifiers

PMID42115951
PMCPMC13340103

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Registered trials

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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.