Usefulness of the Multimodal Fusion Image for Visualization of Deep Sylvian Veins

• Material Type: 博士論文
• Title: Usefulness of the Multimodal Fusion Image for Visualization of Deep Sylvian Veins
• Author/Editor: Nakase, Kenta; Takeshima, Yasuhiro; Konishi, Kengo; Matsuda, Ryosuke; Tamura, Kentaro; Yamada, Shuichi; Nishimura, Fumihiko; Nakagawa, Ichiro; Young-Soo, Park; Nakase, Hiroyuki
• Author Heading: Nakase, Kenta; Takeshima, Yasuhiro; Konishi, Kengo; Matsuda, Ryosuke; Tamura, Kentaro; Yamada, Shuichi; Nishimura, Fumihiko; Nakagawa, Ichiro; Young-Soo, Park; Nakase, Hiroyuki
• Publication, Distribution, etc.: Japan Neurosurgical Society
• Publication Date: 2022-10-15
• Publication Date (W3CDTF): 2022-10-15
• Periodical title: Neurologia medico-chirurgica
• No. or year of volume/issue: 62 10
• Volume: 62
• Issue: 10
• Pages: 475-482
• ISSN (Periodical Title): ISSN : 0470-8105
• Degree grantor/type: 奈良県立医科大学
• Date Granted: 2023-03-15
• Dissertation Number: 甲第864号
• Degree Type: 博士（医学）
• Text Language Code: eng
• Subject Heading: cerebral aneurysm; common vertical trunk; computed tomography venography; multimodal fusion image; deep Sylvian veins
• Target Audience: 一般
• Note (General): type:Thesis; The preoperative assessment of cerebral veins is important to avoid unexpected cerebral venous infarction in the neurosurgical setting. However, information is particularly limited regarding deep Sylvian veins, which occasionally disturb surgical procedures for cerebral anterior circulation aneurysms. The predictability of detecting deep Sylvian veins and their tributaries using a modern multimodal fusion image was aimed to be evaluated. Moreover, 51 patients who underwent microsurgery for unruptured cerebral aneurysms with Sylvian fissure dissection were retrospectively reviewed. The visualization of the four components of the deep Sylvian veins in conventional computed tomography (CT) venography and multimodal fusion images was evaluated. To compare the detection accuracy among these radiological images, the sensitivity and specificity for the detection of each of the four venous structures were calculated in comparison with those of intraoperative inspections. The kappa coefficients were also measured and the inter-rater agreement for each venous structure in each radiological image was examined. In all veins, the multimodal fusion image exhibited a high detection rate without statistical difference from intraoperative inspections (P = 1.0). However, CT venography exhibited a low detection rate with a significant difference from intraoperative inspections in the common vertical trunk (P = 0.006) and attached vein (P = 0.008). The kappa coefficients of the fusion image ranged from 0.73 to 0.91 and were superior to those of CT venography for all venous structures. This is the first report to indicate the usefulness of a multimodal fusion image in evaluating deep Sylvian veins, especially for the detection of nontypical, relatively small veins with large individual variability.; 博士（医学）・甲第864号・令和5年3月15日; Ⓒ 2022 The Japan Neurosurgical Society This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives International License.; identifier:Neurologia medico-chirurgica Vol.62 No.10 p.475-482 (2022 Oct); identifier:04708105; identifier:http://ginmu.naramed-u.ac.jp/dspace/handle/10564/4096; identifier:Neurologia medico-chirurgica, 62(10): 475-482
• Source: fulltext; http://ginmu.naramed-u.ac.jp/dspace/bitstream/10564/4096/1/01%e7%94%b2864%e6%9c%ac%e6%96%87%e3%81%ae%e8%a6%81%e6%97%a8.pdf; http://ginmu.naramed-u.ac.jp/dspace/bitstream/10564/4096/6/02%e7%94%b2864%e5%af%a9%e6%9f%bb%e8%a6%81%e6%97%a8.pdf; http://ginmu.naramed-u.ac.jp/dspace/bitstream/10564/4096/7/03%e7%94%b2864%e6%9c%ac%e6%96%87.pdf
• Access Restrictions: インターネット公開
• Related Material (DOI): 10.2176/jns-nmc.2022-0206
• Periodical Title (NCID): AN00358613; https://ci.nii.ac.jp/ncid/AN00358613
• Data Provider (Database): 国立情報学研究所 : 学術機関リポジトリデータベース（IRDB）（機関リポジトリ）; https://irdb.nii.ac.jp
• Original Data Provider (Database): 奈良県立医科大学 : 奈良県立医科大学機関リポジトリ GINMU