Literature DB >> 23286142

Cortical folding analysis on patients with Alzheimer's disease and mild cognitive impairment.

David M Cash1, Andrew Melbourne, Marc Modat, M Jorge Cardoso, Matthew J Clarkson, Nick C Fox, Sebastien Ourselin.   

Abstract

Cortical thinning is a widely used and powerful biomarker for measuring disease progression in Alzheimer's disease (AD). However, there has been little work on the effect of atrophy on the cortical folding patterns. In this study, we examined whether the cortical folding could be used as a biomarker of AD. Cortical folding metrics were computed on 678 patients from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. For each subject, the boundary between grey matter and white matter was extracted using a level set technique. At each point on the boundary two metrics characterising folding, curvedness and shape index, were generated. Joint histograms using these metrics were calculated for five regions of interest (ROIs): frontal, temporal, occipital, and parietal lobes as well as the cingulum. Pixelwise statistical maps were generated from the joint histograms using permutations tests. In each ROI, a significant reduction was observed between controls and AD in areas associated with the sulcal folds, suggesting a sulcal opening associated with neurodegeneration. When comparing to MCI patients, the regions of significance were smaller but overlapping with those regions found comparing controls to AD. It indicates that the differences in cortical folding are progressive and can be detected before formal diagnosis of AD. Our preliminary analysis showed a viable signal in the cortical folding patterns for Alzheimer's disease that should be explored further.

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Year:  2012        PMID: 23286142     DOI: 10.1007/978-3-642-33454-2_36

Source DB:  PubMed          Journal:  Med Image Comput Comput Assist Interv


  5 in total

1.  Local curvature analysis for classifying breast tumors: Preliminary analysis in dedicated breast CT.

Authors:  Juhun Lee; Robert M Nishikawa; Ingrid Reiser; John M Boone; Karen K Lindfors
Journal:  Med Phys       Date:  2015-09       Impact factor: 4.071

2.  Neutrosophic segmentation of breast lesions for dedicated breast computed tomography.

Authors:  Juhun Lee; Robert M Nishikawa; Ingrid Reiser; John M Boone
Journal:  J Med Imaging (Bellingham)       Date:  2018-03-06

Review 3.  2014 Update of the Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception.

Authors:  Michael W Weiner; Dallas P Veitch; Paul S Aisen; Laurel A Beckett; Nigel J Cairns; Jesse Cedarbaum; Robert C Green; Danielle Harvey; Clifford R Jack; William Jagust; Johan Luthman; John C Morris; Ronald C Petersen; Andrew J Saykin; Leslie Shaw; Li Shen; Adam Schwarz; Arthur W Toga; John Q Trojanowski
Journal:  Alzheimers Dement       Date:  2015-06       Impact factor: 21.566

Review 4.  Multimodal neuroimaging computing: the workflows, methods, and platforms.

Authors:  Sidong Liu; Weidong Cai; Siqi Liu; Fan Zhang; Michael Fulham; Dagan Feng; Sonia Pujol; Ron Kikinis
Journal:  Brain Inform       Date:  2015-09-04

5.  Differential Diagnosis of Frontotemporal Dementia, Alzheimer's Disease, and Normal Aging Using a Multi-Scale Multi-Type Feature Generative Adversarial Deep Neural Network on Structural Magnetic Resonance Images.

Authors:  Da Ma; Donghuan Lu; Karteek Popuri; Lei Wang; Mirza Faisal Beg
Journal:  Front Neurosci       Date:  2020-10-22       Impact factor: 4.677

  5 in total

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