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<p>Early diagnosis of Alzheimer’s disease (AD) remains a significant challenge due to the lack of objective biomarkers. Accurate identification of morphological and metabolic alterations during the different stages of AD is crucial for timely intervention and effective management of the disease. Surface-based morphometry (SBM) and amide proton transfer (APT) imaging are innovative techniques that offer the potential to visualize these changes in the brain. By leveraging these advanced imaging modalities, this study aims to investigate the specific alterations that occur in AD, thereby exploring potential imaging biomarkers that could facilitate early and precise diagnosis of the condition. The identification of such biomarkers is essential for improving the diagnostic accuracy and efficacy of therapeutic strategies for Alzheimer’s disease. In this prospective study, we enrolled 26 patients with AD, thirty-six patients with amnestic mild cognitive impairment (aMCI), and 32 healthy controls (HCs). All participants underwent 3D T1-weighted imaging (T1WI) and 3D-APT imaging. Morphological parameters, including cortical thickness (CTh), sulcal depth (SD), fractal dimension (FD), and gyrification index (GI), were calculated using the SBM algorithm. Magnetization transfer ratio asymmetry (MTR<sub>asym</sub>) values were computed for 106 brain regions utilizing the vendor’s post-processing workstation. AD Patients exhibited cortical thinning in the frontal, temporal, parietal lobes, and cingulate gyrus, along with a decrease in GI in the left parietal lobe. MCI patients showed a reduction in GI in the left parietal and temporal lobes. Multivariate logistic regression analysis identified widespread increased MTR<sub>asym</sub> values in AD patients, affecting the frontal, temporal, parietal, occipital, cingulate, basal ganglia regions, and white matter. The right amygdala shows the highest diagnostic performance. Additionally, a negative correlation was observed between MTR<sub>asym</sub> values and clinical assessments. SBM analysis revealed morphological changes in the brain across different stages of AD, while APT imaging identified metabolic alterations in AD patients. These findings suggest that the combination of SBM and APT imaging may hold potential as a non-invasive diagnostic and monitoring approach for AD.</p>

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Morphological and metabolic alterations in different stages of Alzheimer’s diseases: a study using surface-based morphometry (SBM) and amide proton transfer (APT) imaging

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月1日

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  • Meimeng Zhong,
  • Qingwei Song,
  • Shuo Zhang,
  • Zhewei Liu,
  • Chang Yuan,
  • Peixue Li,
  • Nan Wang,
  • Dan Yu,
  • Kewei Wang,
  • Chunbo Dong,
  • Jie Zhao,
  • Jing Liu,
  • Chao Yang

摘要

Early diagnosis of Alzheimer’s disease (AD) remains a significant challenge due to the lack of objective biomarkers. Accurate identification of morphological and metabolic alterations during the different stages of AD is crucial for timely intervention and effective management of the disease. Surface-based morphometry (SBM) and amide proton transfer (APT) imaging are innovative techniques that offer the potential to visualize these changes in the brain. By leveraging these advanced imaging modalities, this study aims to investigate the specific alterations that occur in AD, thereby exploring potential imaging biomarkers that could facilitate early and precise diagnosis of the condition. The identification of such biomarkers is essential for improving the diagnostic accuracy and efficacy of therapeutic strategies for Alzheimer’s disease. In this prospective study, we enrolled 26 patients with AD, thirty-six patients with amnestic mild cognitive impairment (aMCI), and 32 healthy controls (HCs). All participants underwent 3D T1-weighted imaging (T1WI) and 3D-APT imaging. Morphological parameters, including cortical thickness (CTh), sulcal depth (SD), fractal dimension (FD), and gyrification index (GI), were calculated using the SBM algorithm. Magnetization transfer ratio asymmetry (MTRasym) values were computed for 106 brain regions utilizing the vendor’s post-processing workstation. AD Patients exhibited cortical thinning in the frontal, temporal, parietal lobes, and cingulate gyrus, along with a decrease in GI in the left parietal lobe. MCI patients showed a reduction in GI in the left parietal and temporal lobes. Multivariate logistic regression analysis identified widespread increased MTRasym values in AD patients, affecting the frontal, temporal, parietal, occipital, cingulate, basal ganglia regions, and white matter. The right amygdala shows the highest diagnostic performance. Additionally, a negative correlation was observed between MTRasym values and clinical assessments. SBM analysis revealed morphological changes in the brain across different stages of AD, while APT imaging identified metabolic alterations in AD patients. These findings suggest that the combination of SBM and APT imaging may hold potential as a non-invasive diagnostic and monitoring approach for AD.