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Objective <p>Our 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).</p> Methods <p>We 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.</p> Results <p>We 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 (<i>α</i> = -0.0009, <i>P</i> = 0.0010), the expansion of left lateral inferior ventricle volume (<i>α</i> = 0.0003, <i>P</i> = 0.0238), the atrophy of right middle temporal gyrus volume (<i>α</i> = -0.0002, <i>P</i> = 0.0036), and the accelerated atrophy of brain parenchyma total volume (<i>α</i> = 0.000005, <i>P</i> = 0.0008) were all significantly associated with the risk of disease transformation. Additionally, the covariate APOE ε4 allele remained a significant independent risk factor (<i>γ</i> = 0.6930, <i>P</i> &lt; 0.0001).</p> Conclusion <p>Left 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. </p>

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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月11日

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  • Yanxia Wang,
  • Wangchen Song,
  • Xinyu Yang,
  • Weijing Meng,
  • Yonghua Ma,
  • Aimin Wang,
  • Guiya Guo,
  • Zhaoxue Zhang,
  • Zihui Li,
  • Hairui Han,
  • Suzhen Wang,
  • Fuyan Shi

摘要

Objective

Our 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).

Methods

We 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.

Results

We 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).

Conclusion

Left 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.