Penn Image Computing and Science Laboratory (PICSL), Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania.
Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania.
Hum Brain Mapp. 2019 Aug 15;40(12):3431-3451. doi: 10.1002/hbm.24607. Epub 2019 Apr 29.
Medial temporal lobe (MTL) substructures are the earliest regions affected by neurofibrillary tangle pathology-and thus are promising biomarkers for Alzheimer's disease (AD). However, automatic segmentation of the MTL using only T1-weighted (T1w) magnetic resonance imaging (MRI) is challenging due to the large anatomical variability of the MTL cortex and the confound of the dura mater, which is commonly segmented as gray matter by state-of-the-art algorithms because they have similar intensity in T1w MRI. To address these challenges, we developed a novel atlas set, consisting of 15 cognitively normal older adults and 14 patients with mild cognitive impairment with a label explicitly assigned to the dura, that can be used by the multiatlas automated pipeline (Automatic Segmentation of Hippocampal Subfields [ASHS-T1]) for the segmentation of MTL subregions, including anterior/posterior hippocampus, entorhinal cortex (ERC), Brodmann areas (BA) 35 and 36, and parahippocampal cortex on T1w MRI. Cross-validation experiments indicated good segmentation accuracy of ASHS-T1 and that the dura can be reliably separated from the cortex (6.5% mislabeled as gray matter). Conversely, FreeSurfer segmented majority of the dura mater (62.4%) as gray matter and the degree of dura mislabeling decreased with increasing disease severity. To evaluate its clinical utility, we applied the pipeline to T1w images of 663 ADNI subjects and significant volume/thickness loss is observed in BA35, ERC, and posterior hippocampus in early prodromal AD and all subregions at later stages. As such, the publicly available new atlas and ASHS-T1 could have important utility in the early diagnosis and monitoring of AD and enhancing brain-behavior studies of these regions.
内侧颞叶(MTL)亚区是最早受到神经原纤维缠结病理影响的区域,因此是阿尔茨海默病(AD)的有前途的生物标志物。然而,由于 MTL 皮质的解剖结构变化较大,以及硬脑膜的混杂,仅使用 T1 加权(T1w)磁共振成像(MRI)对 MTL 进行自动分割是具有挑战性的,因为硬脑膜在 T1w MRI 中的强度与灰质相似,因此最先进的算法通常将其分割为灰质。为了解决这些挑战,我们开发了一个新的图谱集,其中包含 15 名认知正常的老年人和 14 名轻度认知障碍患者,这些图谱集明确标记了硬脑膜,可以由多图谱自动管道(海马亚区自动分割[ASHS-T1])用于 MTL 亚区的分割,包括前/后海马、内嗅皮质(ERC)、Brodmann 区(BA)35 和 36 以及 T1w MRI 上的旁海马皮质。交叉验证实验表明,ASHS-T1 的分割准确性较高,硬脑膜可以可靠地与皮质分离(6.5%错误标记为灰质)。相反,FreeSurfer 将大部分硬脑膜(62.4%)标记为灰质,并且随着疾病严重程度的增加,硬脑膜的错误标记程度降低。为了评估其临床应用价值,我们将该管道应用于 663 名 ADNI 受试者的 T1w 图像,在早期前驱 AD 中观察到 BA35、ERC 和后海马的体积/厚度明显丢失,并且在后期所有亚区都存在这种情况。因此,新的公共图谱和 ASHS-T1 可以在 AD 的早期诊断和监测以及增强这些区域的脑行为研究中具有重要的应用价值。