کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6026773 1580906 2014 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Comparing voxel-based iterative sensitivity and voxel-based morphometry to detect abnormalities in T2-weighted MRI
موضوعات مرتبط
علوم زیستی و بیوفناوری علم عصب شناسی علوم اعصاب شناختی
پیش نمایش صفحه اول مقاله
Comparing voxel-based iterative sensitivity and voxel-based morphometry to detect abnormalities in T2-weighted MRI
چکیده انگلیسی
This study aimed to test the superiority proposed by Abbott et al. (2011) of their Voxel based iterative sensitivity (VBIS) method over Voxel Based Morphometry using T2-weighted images (T2-VBM), in detecting intensity changes in Alzheimer's disease (AD). A comparison was made first in simulated intensity lesions and then in AD patients. Intensity changes were evaluated in the whole-brain with VBIS and with a simple intensity-based approach and in specific tissue classes with the conventional VBM method of using tissue probability segments. Results showed that VBIS performed well in the simulated environment though it showed no superiority in detecting the lesion compared to the much simpler VBM approach. The VBIS method, however, failed to detect any meaningful signal intensity reduction in AD patient data. Moreover, its whole brain approach was contaminated by the excess cerebrospinal fluid signal (very bright on T2-weighted scans) in areas of maximal measurable atrophy (mesial temporal lobes); this gave rise to spurious signal intensity increases in these regions in AD. The same artefact was observed for both intensity-based methods but not with the conventional VBM approach of performing statistics on grey matter segments. In conclusion, no evidence was found to indicate that VBIS offers benefits over T2-VBM in AD, nor in simulation intensity lesions. The study highlights the necessity of empirically testing voxel-based analysis techniques rather than merely claiming superiority of one method over another on theoretical grounds.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: NeuroImage - Volume 100, 15 October 2014, Pages 379-384
نویسندگان
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