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术中超声在图像引导神经外科手术中的引导及组织移位校正作用

Intraoperative ultrasound for guidance and tissue shift correction in image-guided neurosurgery.

作者信息

Comeau R M, Sadikot A F, Fenster A, Peters T M

机构信息

McConnell Brain Imaging Center, Montreal Neurological Institute and Department of Biomedical Engineering, McGill University, Quebec, Canada.

出版信息

Med Phys. 2000 Apr;27(4):787-800. doi: 10.1118/1.598942.

Abstract

We present a surgical guidance system that incorporates pre-operative image information (e.g., MRI) with intraoperative ultrasound (US) imaging to detect and correct for brain tissue deformation during image-guided neurosurgery (IGNS). Many interactive IGNS implementations employ pre-operative images as a guide to the surgeons throughout the procedure. However, when a craniotomy is involved, tissue movement during a procedure can be a significant source of error in these systems. By incorporating intraoperative US imaging, the target volume can be scanned at any time, and two-dimensional US images may be compared directly to the corresponding slice from the pre-operative image. Homologous points may be mapped from the intraoperative to the pre-operative image space with an accuracy of better than 2 mm, enabling the surgeon to use this information to assess the accuracy of the guidance system along with the progress of the procedure (e.g., extent of lesion removal) at any time during the operation. Anatomical features may be identified on both the pre-operative and intraoperative images and used to generate a deformation map, which can be used to warp the pre-operative image to match the intraoperative US image. System validation is achieved using a deformable multi-modality imaging phantom, and preliminary clinical results are presented.

摘要

我们提出了一种手术引导系统,该系统将术前图像信息(如MRI)与术中超声(US)成像相结合,以在图像引导神经外科手术(IGNS)期间检测并校正脑组织变形。许多交互式IGNS实施方案在整个手术过程中都将术前图像用作外科医生的指导。然而,当涉及开颅手术时,手术过程中的组织移动可能是这些系统中一个重大的误差来源。通过纳入术中US成像,可以随时扫描目标体积,并且二维US图像可以直接与术前图像的相应切片进行比较。同源点可以从术中图像映射到术前图像空间,精度优于2毫米,这使得外科医生能够在手术过程中的任何时候利用这些信息来评估引导系统的准确性以及手术进展情况(如病变切除范围)。可以在术前和术中图像上识别解剖特征,并用于生成变形图,该变形图可用于使术前图像变形以匹配术中US图像。使用可变形多模态成像体模实现了系统验证,并展示了初步的临床结果。

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