Fully automated image updating for brain shift compensation after dural opening.

IF 3.6 2区 医学 Q1 CLINICAL NEUROLOGY
Chengpei Li, Linton T Evans, Jennifer Hong, Scott C Davis, David W Roberts, Keith D Paulsen, Xiaoyao Fan
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引用次数: 0

Abstract

Objective: In open cranial procedures, intraoperative brain shift can degrade the accuracy of surgical navigation on the basis of preoperative MR (pMR) images as soon as the cortical surface is exposed. The aim of this study was to develop a fully automated image updating system to address brain shift at the start of open cranial surgery and to evaluate its accuracy and efficiency.

Methods: This study included patients undergoing open cranial procedures at a single center. Intraoperative stereovision (iSV) images of the surgical field were acquired as an easily integrated nondisruptive source of high-resolution image data on surgical surface deformation and were integrated with a computational model to compensate for volumetric brain shift after dural opening by updating the coregistered preoperative images. A Fast Segment Anything Model algorithm segmented the exposed cortical surface on iSV images automatically. Vessel and sulcus features were also segmented automatically from both iSV and pMR images and registered using a two-step registration method. Extracted nonrigid cortical displacements were assimilated by a finite element model to estimate whole-brain deformation. Updated MR (uMR) images were generated by deforming pMR by the resulting displacement field. A tracked stylus sampled the exposed cortical surface to provide independent measurements for error assessments. The uMR images were evaluated in terms of the misfit between model estimates and measured displacements, target registration error (TRE), and point-to-surface distance (PSD) relative to their pMR counterparts.

Results: Fifteen patients (age range 45-85 years) who underwent open cranial procedures were included in the study. The overall accuracy of reconstructed iSV surfaces relative to stylus positions was 0.8 ± 0.7 mm. The overall mean misfit, TRE, and PSD of uMR images were 2.1 ± 1.2 mm, 1.9 ± 1.0 mm, and 1.6 ± 1.0 mm, respectively, compared with 6.5 ± 1.3 mm, 6.2 ± 1.2 mm, and 4.5 ± 1.2 mm for pMR images. Image updating was completed automatically without any user intervention in an overall mean of 3.9 ± 0.6 minutes.

Conclusions: Automatic image updating compensated for brain shift due to dural opening and achieved clinically acceptable accuracy and efficiency. The system required no user intervention or expertise and caused minimal interruptions to surgical flow, suggesting it has potential for future integration into open cranial procedures.

硬脑膜打开后脑移补偿的全自动图像更新。
目的:在颅脑开颅手术中,术中脑移位会降低手术导航的准确性,一旦暴露皮质表面,术前MR (pMR)图像就会降低导航的准确性。本研究的目的是开发一种全自动图像更新系统,以解决开颅手术开始时的脑转移问题,并评估其准确性和效率。方法:本研究包括在单一中心接受开颅手术的患者。术中立体视觉(iSV)图像作为外科手术表面变形的高分辨率图像数据的易于集成的非破坏性来源,并与计算模型相结合,通过更新共配准的术前图像来补偿硬脑膜打开后的体积脑偏移。一种快速分割任意模型算法在iSV图像上自动分割暴露的皮质表面。从iSV和pMR图像中自动分割血管和沟槽特征,并使用两步配准方法进行配准。提取的非刚性皮质位移被一个有限元模型同化以估计全脑变形。通过产生的位移场对pMR进行变形,生成更新的MR (uMR)图像。追踪式触笔对暴露的皮质表面进行采样,为误差评估提供独立的测量。根据模型估计与测量位移之间的不拟合、目标配准误差(TRE)和相对于其pMR对应的点到表面距离(PSD)对uMR图像进行评估。结果:15例接受开颅手术的患者(年龄45-85岁)被纳入研究。重建的iSV表面相对于触针位置的总体精度为0.8±0.7 mm。uMR图像的总体平均失配、TRE和PSD分别为2.1±1.2 mm、1.9±1.0 mm和1.6±1.0 mm,而pMR图像的总体平均失配、TRE和PSD分别为6.5±1.3 mm、6.2±1.2 mm和4.5±1.2 mm。图像更新自动完成,无需用户干预,平均时间为3.9±0.6分钟。结论:自动图像更新弥补了硬脑膜打开引起的脑偏移,达到了临床可接受的准确性和效率。该系统不需要用户干预或专业知识,对手术流程的干扰最小,这表明它有可能在未来整合到开颅手术中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of neurosurgery
Journal of neurosurgery 医学-临床神经学
CiteScore
7.20
自引率
7.30%
发文量
1003
审稿时长
1 months
期刊介绍: The Journal of Neurosurgery, Journal of Neurosurgery: Spine, Journal of Neurosurgery: Pediatrics, and Neurosurgical Focus are devoted to the publication of original works relating primarily to neurosurgery, including studies in clinical neurophysiology, organic neurology, ophthalmology, radiology, pathology, and molecular biology. The Editors and Editorial Boards encourage submission of clinical and laboratory studies. Other manuscripts accepted for review include technical notes on instruments or equipment that are innovative or useful to clinicians and researchers in the field of neuroscience; papers describing unusual cases; manuscripts on historical persons or events related to neurosurgery; and in Neurosurgical Focus, occasional reviews. Letters to the Editor commenting on articles recently published in the Journal of Neurosurgery, Journal of Neurosurgery: Spine, and Journal of Neurosurgery: Pediatrics are welcome.
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