Literature DB >> 29305751

Volumetric comparison of hippocampal subfields extracted from 4-minute accelerated vs. 8-minute high-resolution T2-weighted 3T MRI scans.

Shan Cong1,2,3, Shannon L Risacher1, John D West1, Yu-Chien Wu1, Liana G Apostolova1,4,5, Eileen Tallman1, Maher Rizkalla3, Paul Salama3, Andrew J Saykin6,7, Li Shen8,9.   

Abstract

The hippocampus has been widely studied using neuroimaging, as it plays an important role in memory and learning. However, hippocampal subfield information is difficult to capture by standard magnetic resonance imaging (MRI) techniques. To facilitate morphometric study of hippocampal subfields, ADNI introduced a high resolution (0.4 mm in plane) T2-weighted turbo spin-echo sequence that requires 8 min. With acceleration, the protocol can be acquired in 4 min. We performed a comparative study of hippocampal subfield volumes using standard and accelerated protocols on a Siemens Prisma 3T MRI in an independent sample of older adults that included 10 cognitively normal controls, 9 individuals with subjective cognitive decline, 10 with mild cognitive impairment, and 6 with a clinical diagnosis of Alzheimer's disease (AD). The Automatic Segmentation of Hippocampal Subfields (ASHS) software was used to segment 9 primary labeled regions including hippocampal subfields and neighboring cortical regions. Intraclass correlation coefficients were computed for reliability tests between 4 and 8 min scans within and across the four groups. Pairwise group analyses were performed, covaried for age, sex and total intracranial volume, to determine whether the patterns of group differences were similar using 4 vs. 8 min scans. The 4 and 8 min protocols, analyzed by ASHS segmentation, yielded similar volumetric estimates for hippocampal subfields as well as comparable patterns of differences between study groups. The accelerated protocol can provide reliable imaging data for investigation of hippocampal subfields in AD-related MRI studies and the decreased scan time may result in less vulnerability to motion.

Entities:  

Keywords:  Alzheimer’s disease; Hippocampal subfields; Magnetic resonance imaging; Segmentation; Volumetric analysis

Mesh:

Year:  2018        PMID: 29305751      PMCID: PMC6033688          DOI: 10.1007/s11682-017-9819-3

Source DB:  PubMed          Journal:  Brain Imaging Behav        ISSN: 1931-7557            Impact factor:   3.978


  34 in total

1.  Mild cognitive impairment: clinical characterization and outcome.

Authors:  R C Petersen; G E Smith; S C Waring; R J Ivnik; E G Tangalos; E Kokmen
Journal:  Arch Neurol       Date:  1999-03

2.  Conversion of mild cognitive impairment to Alzheimer disease predicted by hippocampal atrophy maps.

Authors:  Liana G Apostolova; Rebecca A Dutton; Ivo D Dinov; Kiralee M Hayashi; Arthur W Toga; Jeffrey L Cummings; Paul M Thompson
Journal:  Arch Neurol       Date:  2006-05

3.  Structural changes in hippocampal subfields in major depressive disorder: a high-field magnetic resonance imaging study.

Authors:  Yushan Huang; Nicholas J Coupland; R Marc Lebel; Rawle Carter; Peter Seres; Alan H Wilman; Nikolai V Malykhin
Journal:  Biol Psychiatry       Date:  2013-02-16       Impact factor: 13.382

4.  A learning-based wrapper method to correct systematic errors in automatic image segmentation: consistently improved performance in hippocampus, cortex and brain segmentation.

Authors:  Hongzhi Wang; Sandhitsu R Das; Jung Wook Suh; Murat Altinay; John Pluta; Caryne Craige; Brian Avants; Paul A Yushkevich
Journal:  Neuroimage       Date:  2011-01-13       Impact factor: 6.556

Review 5.  Staging of Alzheimer's disease-related neurofibrillary changes.

Authors:  H Braak; E Braak
Journal:  Neurobiol Aging       Date:  1995 May-Jun       Impact factor: 4.673

6.  Hippocampal atrophy patterns in mild cognitive impairment and Alzheimer's disease.

Authors:  Susanne G Mueller; Norbert Schuff; Kristine Yaffe; Catherine Madison; Bruce Miller; Michael W Weiner
Journal:  Hum Brain Mapp       Date:  2010-09       Impact factor: 5.038

7.  Measurement of hippocampal subfields and age-related changes with high resolution MRI at 4T.

Authors:  S G Mueller; L Stables; A T Du; N Schuff; D Truran; N Cashdollar; M W Weiner
Journal:  Neurobiol Aging       Date:  2006-05-19       Impact factor: 4.673

8.  Histology-derived volumetric annotation of the human hippocampal subfields in postmortem MRI.

Authors:  Daniel H Adler; John Pluta; Salmon Kadivar; Caryne Craige; James C Gee; Brian B Avants; Paul A Yushkevich
Journal:  Neuroimage       Date:  2013-09-12       Impact factor: 6.556

9.  Hippocampal subfield volumetry in mild cognitive impairment, Alzheimer's disease and semantic dementia.

Authors:  Renaud La Joie; Audrey Perrotin; Vincent de La Sayette; Stéphanie Egret; Loïc Doeuvre; Serge Belliard; Francis Eustache; Béatrice Desgranges; Gaël Chételat
Journal:  Neuroimage Clin       Date:  2013-08-14       Impact factor: 4.881

10.  A semi-automated pipeline for the segmentation of rhesus macaque hippocampus: validation across a wide age range.

Authors:  Michael R Hunsaker; David G Amaral
Journal:  PLoS One       Date:  2014-02-24       Impact factor: 3.240

View more
  8 in total

1.  MIND food and speed of processing training in older adults with low education, the MINDSpeed Alzheimer's disease prevention pilot trial.

Authors:  Daniel O Clark; Huiping Xu; Lyndsi Moser; Philip Adeoye; Annie W Lin; Christy C Tangney; Shannon L Risacher; Andrew J Saykin; Robert V Considine; Frederick W Unverzagt
Journal:  Contemp Clin Trials       Date:  2019-07-18       Impact factor: 2.226

2.  Structural connectivity mapping in human hippocampal-subfields using super-resolution hybrid diffusion imaging: a feasibility study.

Authors:  Nahla M H Elsaid; Pierrick Coupé; Andrew J Saykin; Yu-Chien Wu
Journal:  Neuroradiology       Date:  2022-05-13       Impact factor: 2.995

3.  Volumetric GWAS of medial temporal lobe structures identifies an ERC1 locus using ADNI high-resolution T2-weighted MRI data.

Authors:  Shan Cong; Xiaohui Yao; Zhi Huang; Shannon L Risacher; Kwangsik Nho; Andrew J Saykin; Li Shen
Journal:  Neurobiol Aging       Date:  2020-07-14       Impact factor: 4.673

4.  Genetic Influence Underlying Brain Connectivity Phenotype: A Study on Two Age-Specific Cohorts.

Authors:  Shan Cong; Xiaohui Yao; Linhui Xie; Jingwen Yan; Li Shen
Journal:  Front Genet       Date:  2022-02-07       Impact factor: 4.599

5.  Grey matter changes on brain MRI in subjective cognitive decline: a systematic review.

Authors:  Pablo Arrondo; Óscar Elía-Zudaire; Gloria Martí-Andrés; María A Fernández-Seara; Mario Riverol
Journal:  Alzheimers Res Ther       Date:  2022-07-22       Impact factor: 8.823

6.  Future research directions to identify risks and mitigation strategies for neurostructural, ocular, and behavioral changes induced by human spaceflight: A NASA-ESA expert group consensus report.

Authors:  Rachael D Seidler; Claudia Stern; Mathias Basner; Alexander C Stahn; Floris L Wuyts; Peter Zu Eulenburg
Journal:  Front Neural Circuits       Date:  2022-08-04       Impact factor: 3.342

Review 7.  Neuroimaging in aging and neurologic diseases.

Authors:  Shannon L Risacher; Andrew J Saykin
Journal:  Handb Clin Neurol       Date:  2019

8.  Hippocampal Subregion and Gene Detection in Alzheimer's Disease Based on Genetic Clustering Random Forest.

Authors:  Jin Li; Wenjie Liu; Luolong Cao; Haoran Luo; Siwen Xu; Peihua Bao; Xianglian Meng; Hong Liang; Shiaofen Fang
Journal:  Genes (Basel)       Date:  2021-05-01       Impact factor: 4.096

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.