PERFORM Centre, Concordia University, Rm 2.211, 7200 Sherbrooke St. W., Montreal, QC, H4B 1R6, Canada.
Department of Electrical and Computer Engineering, Concordia University, Montreal, Canada.
Int J Comput Assist Radiol Surg. 2018 Mar;13(3):457-467. doi: 10.1007/s11548-017-1699-x. Epub 2018 Jan 3.
In brain tumor surgeries, maximum removal of cancerous tissue without compromising normal brain functions can improve the patient's survival rate and therapeutic benefits. To achieve this, diffusion MRI and intra-operative ultrasound (iUS) can be highly instrumental. While diffusion MRI allows the visualization of white matter tracts and helps define the resection plan to best preserve the eloquent areas, iUS can effectively track the brain shift after craniotomy that often renders the pre-surgical plan invalid, ensuring the accuracy and safety of the intervention. Unfortunately, brain shift correction using iUS and automatic registration has never been shown for brain tractography so far despite its rising significance in brain tumor resection.
We employed a correlation-ratio-based nonlinear registration algorithm to account for brain shift through MRI-iUS registration and used the recovered deformations to warp both the brain anatomy and tractography seen in pre-surgical plans. The overall technique was demonstrated retrospectively on four patients who underwent iUS-guided low-grade brain gliomas resection.
Through qualitative and quantitative evaluations, the preoperative MRI and iUS scans were well realigned after nonlinear registration, and the deformed brain tumor volumes and white matter tracts showed large displacements away from the pre-surgical plans.
We are the first to demonstrate the technique to track nonlinear deformation of brain tractography using real clinical MRI and iUS data, and the results confirm the need for updating white matter tracts due to tissue shift during surgery.
在脑肿瘤手术中,最大限度地切除癌组织而不影响正常脑功能,可以提高患者的生存率和治疗效果。为了实现这一目标,扩散 MRI 和术中超声(iUS)可以发挥重要作用。虽然扩散 MRI 可以显示白质束并帮助制定切除计划,以最好地保留功能区,但 iUS 可以有效地跟踪开颅术后的脑移位,这通常会使术前计划失效,从而确保干预的准确性和安全性。不幸的是,尽管术中超声引导下自动配准在脑肿瘤切除中越来越重要,但到目前为止,还没有将其用于脑束追踪中的脑移位校正。
我们采用基于相关比的非线性配准算法,通过 MRI-iUS 配准来考虑脑移位,并使用恢复的变形来扭曲术前计划中看到的大脑解剖结构和束追踪。该技术整体在四名接受 iUS 引导的低级别脑胶质瘤切除的患者中进行了回顾性演示。
通过定性和定量评估,非线性配准后可以很好地重新对齐术前 MRI 和 iUS 扫描,变形后的脑肿瘤体积和白质束明显偏离术前计划。
我们首次展示了使用真实临床 MRI 和 iUS 数据跟踪脑束追踪非线性变形的技术,结果证实了由于手术过程中的组织移位,需要更新白质束。