کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8688563 | 1580952 | 2017 | 39 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Machine-learning classification of 22q11.2 deletion syndrome: A diffusion tensor imaging study
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کلمات کلیدی
(ROI)Structured Interview for Prodromal SyndromesExtreme capsule(AD) - (آگهی)axial diffusivity - diffusivity محوریradial diffusivity - انتشار شعاعیDiffusion weighted image - تصویر توزیع شده وزنdiffusion tensor imaging - تصویربرداری تانسور انتشارsuperior temporal gyrus - جورج جادویی عالی22q11.2 deletion syndrome - سندرم حذف 22q11.2inferior longitudinal fasciculus - فسیکولوس طولی پایین ترUnscented Kalman filter - فیلتر Kalman بی معنیSupport vector machine - ماشین بردار پشتیبانیSocial Responsiveness Scale - مقیاس پاسخگویی اجتماعیregion of interest - منطقه مورد نظرField of view - میدان دیدfractional anisotropy - ناپیوستگی کسری
موضوعات مرتبط
علوم زیستی و بیوفناوری
علم عصب شناسی
روانپزشکی بیولوژیکی
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
Chromosome 22q11.2 deletion syndrome (22q11.2DS) is a genetic neurodevelopmental syndrome that has been studied intensively in order to understand relationships between the genetic microdeletion, brain development, cognitive function, and the emergence of psychiatric symptoms. White matter microstructural abnormalities identified using diffusion tensor imaging methods have been reported to affect a variety of neuroanatomical tracts in 22q11.2DS. In the present study, we sought to combine two discovery-based approaches: (1) white matter query language was used to parcellate the brain's white matter into tracts connecting pairs of 34, bilateral cortical regions and (2) the diffusion imaging characteristics of the resulting tracts were analyzed using a machine-learning method called support vector machine in order to optimize the selection of a set of imaging features that maximally discriminated 22q11.2DS and comparison subjects. With this unique approach, we both confirmed previously-recognized 22q11.2DS-related abnormalities in the inferior longitudinal fasciculus (ILF), and identified, for the first time, 22q11.2DS-related anomalies in the middle longitudinal fascicle and the extreme capsule, which may have been overlooked in previous, hypothesis-guided studies. We further observed that, in participants with 22q11.2DS, ILF metrics were significantly associated with positive prodromal symptoms of psychosis.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: NeuroImage: Clinical - Volume 15, 2017, Pages 832-842
Journal: NeuroImage: Clinical - Volume 15, 2017, Pages 832-842
نویسندگان
Daniel S. Tylee, Zora Kikinis, Thomas P. Quinn, Kevin M. Antshel, Wanda Fremont, Muhammad A. Tahir, Anni Zhu, Xue Gong, Stephen J. Glatt, Ioana L. Coman, Martha E. Shenton, Wendy R. Kates, Nikos Makris,