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Automated segmentation of medial temporal lobe subregions on in vivo T1-weighted MRI in early stages of Alzheimer's disease.
Xie, Long; Wisse, Laura E M; Pluta, John; de Flores, Robin; Piskin, Virgine; Manjón, Jose V; Wang, Hongzhi; Das, Sandhitsu R; Ding, Song-Lin; Wolk, David A; Yushkevich, Paul A.
Affiliation
  • Xie L; Penn Image Computing and Science Laboratory (PICSL), Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania.
  • Wisse LEM; Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania.
  • Pluta J; Penn Image Computing and Science Laboratory (PICSL), Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania.
  • de Flores R; Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania.
  • Piskin V; Penn Memory Center, University of Pennsylvania, Philadelphia, Pennsylvania.
  • Manjón JV; Penn Image Computing and Science Laboratory (PICSL), Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania.
  • Wang H; Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania.
  • Das SR; Penn Memory Center, University of Pennsylvania, Philadelphia, Pennsylvania.
  • Ding SL; Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania.
  • Wolk DA; Penn Image Computing and Science Laboratory (PICSL), Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania.
  • Yushkevich PA; Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA), Universidad Politécnica de Valencia, Valencia, Spain.
Hum Brain Mapp ; 40(12): 3431-3451, 2019 08 15.
Article in En | MEDLINE | ID: mdl-31034738
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.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Temporal Lobe / Magnetic Resonance Imaging / Alzheimer Disease / Cognitive Dysfunction Type of study: Screening_studies Limits: Aged / Aged80 / Female / Humans / Male / Middle aged Language: En Journal: Hum Brain Mapp Journal subject: CEREBRO Year: 2019 Document type: Article Country of publication: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Temporal Lobe / Magnetic Resonance Imaging / Alzheimer Disease / Cognitive Dysfunction Type of study: Screening_studies Limits: Aged / Aged80 / Female / Humans / Male / Middle aged Language: En Journal: Hum Brain Mapp Journal subject: CEREBRO Year: 2019 Document type: Article Country of publication: United States