ID | 117636 |
Title Alternative | Virtual imaging-guided RAPN
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Author |
Shiozaki, Keito
Tokushima University
Kawanishi, Yasuo
Takamatsu Red Cross Hospital
Daizumoto, Kei
Tokushima University
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Izumi, Kazuyoshi
Takamatsu Red Cross Hospital
Kusuhara, Yoshito
Tokushima University
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Fukawa, Tomoya
Tokushima University
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Yamamoto, Yasuyo
Tokushima University
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Yamaguchi, Kunihisa
Tokushima University
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Keywords | imaging
partial nephrectomy
robot-assisted surgery
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Content Type |
Journal Article
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Description | Objectives : To evaluate whether virtual partial nephrectomy images could help surgeons identify vascular and collecting system around tumors during actual surgery. Materials & methods : We retrospectively analyzed 36 patients who underwent robot-assisted partial nephrectomy (RAPN) between 2016 and 2017. Virtual partial nephrectomy images were created from preoperative CT images using computer software, and then analyzed. For analysis, blood vessels and collecting system portions within a 5-mm-thick safety margin around the tumor were examined. During analysis, we predicted whether targeted vasculature around the tumor would require clipping or suturing during surgery, and also whether the collecting system would require opening during resection. Surgical outcomes for virtual partial nephrectomy analyses and actual RAPNs were compared and analyzed for sensitivity and specificity. Results : In 36 cases, 119 arteries and 100 veins were targeted on virtual partial nephrectomy images. Arterial suturing or clipping for hemostasis showed a sensitivity and specificity of 83.3% and 84.5%, respectively. For veins, the sensitivity and specificity were 39.1% and 92.2%, respectively. Collecting system opening prediction sensitivity was 85.7%, and specificity was 65.2%. Conclusion : Virtual partial nephrectomy imaging is useful for RAPN planning, particularly regarding arteries and the collecting system. It is hoped that techniques for visualizing veins will improve.
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Journal Title |
The Journal of Medical Investigation
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ISSN | 13496867
13431420
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NCID | AA11166929
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Publisher | Tokushima University Faculty of Medicine
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Volume | 69
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Issue | 3-4
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Start Page | 237
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End Page | 243
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Sort Key | 237
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Published Date | 2022-08
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DOI (Published Version) | |
URL ( Publisher's Version ) | |
FullText File | |
language |
eng
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TextVersion |
Publisher
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departments |
University Hospital
Medical Sciences
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