دورية أكاديمية
(TS)2WM: Tumor Segmentation and Tract Statistics for Assessing White Matter Integrity with Applications to Glioblastoma Patients
| العنوان: | (TS)2WM: Tumor Segmentation and Tract Statistics for Assessing White Matter Integrity with Applications to Glioblastoma Patients |
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| المؤلفون: | Liming Zhong, Tengfei Li, Hai Shu, Chao Huang, Jason Michael Johnson, Donald F Schomer, Ho-Ling Liu, Qianjin Feng, Wei Yang, Hongtu Zhu |
| المصدر: | NeuroImage, Vol 223, Iss , Pp 117368- (2020) |
| بيانات النشر: | Elsevier |
| سنة النشر: | 2020 |
| المجموعة: | Directory of Open Access Journals: DOAJ Articles |
| مصطلحات موضوعية: | Diffusion tensor imaging, Glioblastoma, Tract statistics, Tumor segmentation, White matter integrity, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571 |
| الوصف: | Glioblastoma (GBM) brain tumor is the most aggressive white matter (WM) invasive cerebral primary neoplasm. Due to its inherently heterogeneous appearance and shape, previous studies pursued either the segmentation precision of the tumors or qualitative analysis of the impact of brain tumors on WM integrity with manual delineation of tumors. This paper aims to develop a comprehensive analytical pipeline, called (TS)2WM, to integrate both the superior performance of brain tumor segmentation and the impact of GBM tumors on the WM integrity via tumor segmentation and tract statistics using the diffusion tensor imaging (DTI) technique. The (TS)2WM consists of three components: (i) A dilated densely connected convolutional network (D2C2N) for automatically segment GBM tumors. (ii) A modified structural connectome processing pipeline to characterize the connectivity pattern of WM bundles. (iii) A multivariate analysis to delineate the local and global associations between different DTI-related measurements and clinical variables on both brain tumors and language-related regions of interest. Among those, the proposed D2C2N model achieves competitive tumor segmentation accuracy compared with many state-of-the-art tumor segmentation methods. Significant differences in various DTI-related measurements at the streamline, weighted network, and binary network levels (e.g., diffusion properties along major fiber bundles) were found in tumor-related, language-related, and hand motor-related brain regions in 62 GBM patients as compared to healthy subjects from the Human Connectome Project. |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| تدمد: | 1095-9572 |
| العلاقة: | http://www.sciencedirect.com/science/article/pii/S1053811920308545Test; https://doaj.org/toc/1095-9572Test; https://doaj.org/article/a089a9ad44e640cba6e270aefd130fd6Test |
| DOI: | 10.1016/j.neuroimage.2020.117368 |
| الإتاحة: | https://doi.org/10.1016/j.neuroimage.2020.117368Test https://doaj.org/article/a089a9ad44e640cba6e270aefd130fd6Test |
| رقم الانضمام: | edsbas.13D41432 |
| قاعدة البيانات: | BASE |
Full Text Finder | تدمد: | 10959572 |
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| DOI: | 10.1016/j.neuroimage.2020.117368 |