Real-time intraoperative ultrasound registration for accurate surgical navigation in patients with pelvic malignancies.

IF 2.3 3区 医学 Q3 ENGINEERING, BIOMEDICAL
M A J Hiep, W J Heerink, H C Groen, L Aguilera Saiz, B A Grotenhuis, G L Beets, A G J Aalbers, K F D Kuhlmann, T J M Ruers
{"title":"Real-time intraoperative ultrasound registration for accurate surgical navigation in patients with pelvic malignancies.","authors":"M A J Hiep, W J Heerink, H C Groen, L Aguilera Saiz, B A Grotenhuis, G L Beets, A G J Aalbers, K F D Kuhlmann, T J M Ruers","doi":"10.1007/s11548-024-03299-5","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>Surgical navigation aids surgeons in localizing and adequately resecting pelvic malignancies. Accuracy of the navigation system highly depends on the preceding registration procedure, which is generally performed using intraoperative fluoroscopy or CT. However, these ionizing methods are time-consuming and peroperative updates of the registration are cumbersome. In this present clinical study, several real-time intraoperative ultrasound (iUS) registration methods have been developed and evaluated for accuracy.</p><p><strong>Methods: </strong>During laparotomy in prospectively included patients, sterile electromagnetically tracked iUS acquisitions of the pelvic vessels and bones were collected. An initial registration and five other rigid iUS registration methods were developed including real-time deep learning bone and artery segmentation of 2D ultrasound. For each registration method, the accuracy was computed as the target registration error (TRE) using pelvic lymph nodes (LNs) as targets.</p><p><strong>Results: </strong>Thirty patients were included. The mean ± SD ultrasound acquisition time was 4.2 ± 1.4 min for the pelvic bone and 4.0 ± 1.1 min for the arteries. Deep learning bone and artery ultrasound segmentation resulted in an average (centerline)Dice of 0.85 and a mean surface distance below 2 mm. In 21 patients with visible LNs, initial registration resulted in a median (interquartile range [IQR]) TRE of 7.4 (5.9-10.9) mm. For the other five methods, 2D and 3D bone registration resulted in significantly lower TREs than 2D artery, 3D artery and bifurcation registration (two-sided Wilcoxon rank-sum test p < 0.01). The real-time 2D bone registration method was most accurate with a median (IQR) TRE of 2.6 (1.3-5.7) mm.</p><p><strong>Conclusion: </strong>Real-time 2D iUS bone registration is a fast and accurate method for patient registration prior to surgical navigation and has advantages over current registration techniques. Because of the user dependency of iUS, intuitive software is crucial for optimal clinical implementation. Trial registration number ClinicalTrials.gov (No. NCT05637346).</p>","PeriodicalId":51251,"journal":{"name":"International Journal of Computer Assisted Radiology and Surgery","volume":" ","pages":"249-258"},"PeriodicalIF":2.3000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Computer Assisted Radiology and Surgery","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1007/s11548-024-03299-5","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/12/4 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}
引用次数: 0

Abstract

Purpose: Surgical navigation aids surgeons in localizing and adequately resecting pelvic malignancies. Accuracy of the navigation system highly depends on the preceding registration procedure, which is generally performed using intraoperative fluoroscopy or CT. However, these ionizing methods are time-consuming and peroperative updates of the registration are cumbersome. In this present clinical study, several real-time intraoperative ultrasound (iUS) registration methods have been developed and evaluated for accuracy.

Methods: During laparotomy in prospectively included patients, sterile electromagnetically tracked iUS acquisitions of the pelvic vessels and bones were collected. An initial registration and five other rigid iUS registration methods were developed including real-time deep learning bone and artery segmentation of 2D ultrasound. For each registration method, the accuracy was computed as the target registration error (TRE) using pelvic lymph nodes (LNs) as targets.

Results: Thirty patients were included. The mean ± SD ultrasound acquisition time was 4.2 ± 1.4 min for the pelvic bone and 4.0 ± 1.1 min for the arteries. Deep learning bone and artery ultrasound segmentation resulted in an average (centerline)Dice of 0.85 and a mean surface distance below 2 mm. In 21 patients with visible LNs, initial registration resulted in a median (interquartile range [IQR]) TRE of 7.4 (5.9-10.9) mm. For the other five methods, 2D and 3D bone registration resulted in significantly lower TREs than 2D artery, 3D artery and bifurcation registration (two-sided Wilcoxon rank-sum test p < 0.01). The real-time 2D bone registration method was most accurate with a median (IQR) TRE of 2.6 (1.3-5.7) mm.

Conclusion: Real-time 2D iUS bone registration is a fast and accurate method for patient registration prior to surgical navigation and has advantages over current registration techniques. Because of the user dependency of iUS, intuitive software is crucial for optimal clinical implementation. Trial registration number ClinicalTrials.gov (No. NCT05637346).

盆腔恶性肿瘤患者术中实时超声定位准确手术导航。
目的:手术导航辅助外科医生定位和充分切除盆腔恶性肿瘤。导航系统的准确性高度依赖于之前的注册程序,这通常是通过术中透视或CT进行的。然而,这些电离方法是费时的,操作更新注册是麻烦的。在目前的临床研究中,几种实时术中超声(iUS)登记方法已经开发并评估其准确性。方法:在前瞻性纳入的患者剖腹手术期间,收集无菌电磁跟踪骨盆血管和骨骼的iUS获取。开发了初始配准和其他五种刚性iu配准方法,包括实时深度学习二维超声骨和动脉分割。对于每种配准方法,以骨盆淋巴结(LNs)为目标,计算精度为目标配准误差(TRE)。结果:纳入30例患者。平均±SD超声采集时间盆腔骨为4.2±1.4 min,动脉为4.0±1.1 min。深度学习骨和动脉超声分割的平均(中心线)Dice为0.85,平均表面距离小于2mm。在21例可见LNs患者中,初始配准的中位(四分位间距[IQR]) TRE为7.4 (5.9-10.9)mm。对于其他五种方法,2D和3D骨配准的TREs明显低于2D动脉、3D动脉和分叉配准(双侧Wilcoxon秩和检验p)。实时二维iUS骨配准是一种快速准确的手术导航前患者配准方法,与目前的配准技术相比具有优势。由于用户对iu的依赖性,直观的软件对于优化临床实施至关重要。试验注册号:ClinicalTrials.gov (NCT05637346)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
International Journal of Computer Assisted Radiology and Surgery
International Journal of Computer Assisted Radiology and Surgery ENGINEERING, BIOMEDICAL-RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
CiteScore
5.90
自引率
6.70%
发文量
243
审稿时长
6-12 weeks
期刊介绍: The International Journal for Computer Assisted Radiology and Surgery (IJCARS) is a peer-reviewed journal that provides a platform for closing the gap between medical and technical disciplines, and encourages interdisciplinary research and development activities in an international environment.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信