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分割方法对衰老内侧颞叶亚区体积的影响。

The Effect of Segmentation Method on Medial Temporal Lobe Subregion Volumes in Aging.

机构信息

Department of Psychology, University of Toronto, Toronto, Ontario, Canada.

Rotman Research Institute, Baycrest Academy for Research and Education, Toronto, Ontario, Canada.

出版信息

Hum Brain Mapp. 2024 Oct 15;45(15):e70054. doi: 10.1002/hbm.70054.

Abstract

Early stages of Alzheimer's disease (AD) are associated with volume reductions in specific subregions of the medial temporal lobe (MTL). Using a manual segmentation method-the Olsen-Amaral-Palombo (OAP) protocol-previous work in healthy older adults showed that reductions in grey matter volumes in MTL subregions were associated with lower scores on the Montreal Cognitive Assessment (MoCA), suggesting atrophy may occur prior to diagnosis of mild cognitive impairment, a condition that often progresses to AD. However, current "gold standard" manual segmentation methods are labour intensive and time consuming. Here, we examined the utility of Automatic Segmentation of Hippocampal Subfields (ASHS) to detect volumetric differences in MTL subregions of healthy older adults who varied in cognitive status as determined by the MoCA. We trained ASHS on the OAP protocol to create the ASHS-OAP atlas and then examined how well automated segmentation replicated manual segmentation. Volumetric measures obtained from the ASHS-OAP atlas were also contrasted against those from the ASHS-PMC atlas, a widely used atlas provided by the ASHS team. The pattern of volumetric results was similar between the ASHS-OAP atlas and manual segmentation for anterolateral entorhinal cortex and perirhinal cortex, suggesting that ASHS-OAP is a viable alternative to current manual segmentation methods for detecting group differences based on cognitive status. Although ASHS-OAP and ASHS-PMC produced varying volumes for most regions of interest, they both identified early signs of neurodegeneration in CA/CA/DG and identified marginal differences in entorhinal cortex. Our findings highlight the utility of automated segmentation methods but still underscore the need for a unified and harmonized MTL segmentation atlas.

摘要

阿尔茨海默病(AD)的早期阶段与内侧颞叶(MTL)特定亚区的体积减少有关。使用手动分割方法——Olsen-Amaral-Palombo(OAP)方案——先前在健康老年人中的研究表明,MTL 亚区灰质体积的减少与蒙特利尔认知评估(MoCA)得分较低有关,这表明萎缩可能发生在轻度认知障碍的诊断之前,这种情况常常发展为 AD。然而,目前的“金标准”手动分割方法既费时又费力。在这里,我们研究了自动海马亚区分割(ASHS)在认知状态不同的健康老年人的 MTL 亚区检测体积差异的有效性,这些老年人的认知状态是通过 MoCA 确定的。我们在 OAP 方案上对 ASHS 进行了训练,以创建 ASHS-OAP 图谱,然后检查自动分割对人工分割的复制程度。从 ASHS-OAP 图谱获得的体积测量值也与 ASHS-PMC 图谱(ASHS 团队提供的广泛使用的图谱)进行了对比。ASHS-OAP 图谱和手动分割的体积结果在外侧内嗅皮质和旁嗅皮质的模式相似,这表明 ASHS-OAP 是一种可行的替代当前手动分割方法的方法,可根据认知状态检测组间差异。尽管 ASHS-OAP 和 ASHS-PMC 为大多数感兴趣区域产生了不同的体积,但它们都在 CA/CA/DG 中发现了神经退行性病变的早期迹象,并在内嗅皮质中发现了边缘差异。我们的研究结果强调了自动分割方法的实用性,但仍强调需要一个统一和协调的 MTL 分割图谱。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/50e6/11502966/48a151f991f0/HBM-45-e70054-g004.jpg

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