Lu Fang, Ma Qing, Shi Cailing, Yue Wenjun
Department of Radiology, Affiliated Hospital of North Sichuan Medical College, 637000 Nanchong, Sichuan, China.
Department of Neurology, North Sichuan Medical College, 637000 Nanchong, Sichuan, China.
J Integr Neurosci. 2025 Jan 21;24(1):25991. doi: 10.31083/JIN25991.
Volume alterations in the parietal subregion have received less attention in Alzheimer's disease (AD), and their role in predicting conversion of mild cognitive impairment (MCI) to AD and cognitively normal (CN) to MCI remains unclear. In this study, we aimed to assess the volumetric variation of the parietal subregion at different cognitive stages in AD and to determine the role of parietal subregions in CN and MCI conversion.
We included 662 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, including 228 CN, 221 early MCI (EMCI), 112 late MCI (LMCI), and 101 AD participants. We measured the volume of the parietal subregion based on the Human Brainnetome Atlas (BNA-246) using voxel-based morphometry among individuals at various stages of AD and the progressive and stable individuals in CN and MCI. We then calculated the area under the curve (AUC) of the receiver operating characteristic (ROC) curve to test the ability of parietal subregions to discriminate between different cognitive groups. The Cox proportional hazard model was constructed to determine which specific parietal subregions, alone or in combination, could be used to predict progression from MCI to AD and CN to MCI. Finally, we examined the relationship between the cognitive scores and parietal subregion volume in the diagnostic groups.
The left inferior parietal lobule (IPL)_6_5 (rostroventral area 39) showed the best ability to discriminate between patients with AD and those with CN (AUC = 0.688). The model consisting of the left IPL_6_4 (caudal area 40) and bilateral IPL_6_5 showed the best combination for predicting the CN progression to MCI. The left IPL_6_1 (caudal area 39) showed the best predictive power in predicting the progression of MCI to AD. Certain subregions of the volume correlated with cognitive scales.
Subregions of the angular gyrus are essential in the early onset and subsequent development of AD, and early detection of the volume of these regions may be useful in identifying the tendency to develop the disease and its treatment.
顶叶亚区的体积变化在阿尔茨海默病(AD)中受到的关注较少,其在预测轻度认知障碍(MCI)向AD转化以及认知正常(CN)向MCI转化中的作用仍不明确。在本研究中,我们旨在评估AD不同认知阶段顶叶亚区的体积变化,并确定顶叶亚区在CN和MCI转化中的作用。
我们纳入了来自阿尔茨海默病神经影像倡议(ADNI)数据库的662名参与者,包括228名CN、221名早期MCI(EMCI)、112名晚期MCI(LMCI)和101名AD参与者。我们基于人类脑图谱(BNA - 246),使用基于体素的形态测量法测量了AD各阶段个体以及CN和MCI中病情进展和稳定个体的顶叶亚区体积。然后,我们计算了受试者工作特征(ROC)曲线的曲线下面积(AUC),以测试顶叶亚区区分不同认知组的能力。构建Cox比例风险模型,以确定哪些特定的顶叶亚区单独或联合使用可用于预测MCI向AD以及CN向MCI的进展。最后,我们研究了诊断组中认知分数与顶叶亚区体积之间的关系。
左侧顶下小叶(IPL)_6_5(嘴侧腹侧39区)在区分AD患者和CN患者方面表现出最佳能力(AUC = 0.688)。由左侧IPL_6_4(尾侧40区)和双侧IPL_6_5组成的模型在预测CN向MCI进展方面表现出最佳组合。左侧IPL_6_1(尾侧39区)在预测MCI向AD进展方面表现出最佳预测能力。体积的某些亚区与认知量表相关。
角回亚区在AD的早期发病及后续发展中至关重要,早期检测这些区域的体积可能有助于识别疾病发展趋势及其治疗。