https://scholars.lib.ntu.edu.tw/handle/123456789/581022
標題: | Presurgical resting-state functional MRI language mapping with seed selection guided by regional homogeneity | 作者: | JYH-HORNG CHEN | 關鍵字: | Magnetic resonance imaging; Tumors; Clinical practices; Data-driven approach; Functional connectivity; Functional magnetic resonance imaging; Regional homogeneity; Resting state; Resting state functional mris; Task based approach; Mapping; adult; aged; Article; brain mapping; brain tumor; clinical article; controlled study; female; functional connectivity; functional magnetic resonance imaging; functional neuroimaging; human; language; male; preoperative period; retrospective study; task performance; brain cortex; brain mapping; brain tumor; diagnostic imaging; meta analysis; nuclear magnetic resonance imaging; Brain Mapping; Brain Neoplasms; Cerebral Cortex; Humans; Language; Magnetic Resonance Imaging | 公開日期: | 2020 | 卷: | 84 | 期: | 1 | 起(迄)頁: | 375-383 | 來源出版物: | Magnetic Resonance in Medicine | 摘要: | Purpose: Resting-state functional MRI (rs-FMRI) has shown potential for presurgical mapping of eloquent cortex when a patient’s performance on task-based FMRI is compromised. The seed-based analysis is a practical approach for detecting rs-FMRI functional networks; however, seed localization remains challenging for presurgical language mapping. Therefore, we proposed a data-driven approach to guide seed localization for presurgical rs-FMRI language mapping. Methods: Twenty-six patients with brain tumors located in left perisylvian regions had undergone task-based FMRI and rs-FMRI before tumor resection. For the seed-based rs-FMRI language mapping, a seeding approach that integrates regional homogeneity and meta-analysis maps (RH+MA) was proposed to guide the seed localization. Canonical and task-based seeding approaches were used for comparison. The performance of the 3 seeding approaches was evaluated by calculating the Dice coefficients between each rs-FMRI language mapping result and the result from task-based FMRI. Results: With the RH+MA approach, selecting among the top 6 seed candidates resulted in the highest Dice coefficient for 81% of patients (21 of 26) and the top 9 seed candidates for 92% of patients (24 of 26). The RH+MA approach yielded rs-FMRI language mapping results that were in greater agreement with the results of task-based FMRI, with significantly higher Dice coefficients (P <.05) than that of canonical and task-based approaches within putative language regions. Conclusion: The proposed RH+MA approach outperformed the canonical and task-based seed localization for rs-FMRI language mapping. The results suggest that RH+MA is a robust and feasible method for seed-based functional connectivity mapping in clinical practice. ? 2019 International Society for Magnetic Resonance in Medicine |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85076112512&doi=10.1002%2fmrm.28107&partnerID=40&md5=ebb65e7113960a56490d4cc5572c309b https://scholars.lib.ntu.edu.tw/handle/123456789/581022 |
ISSN: | 07403194 | DOI: | 10.1002/mrm.28107 |
顯示於: | 電機工程學系 |
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