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Validation of Model-Based Brain Shift Correction in Neurosurgery via Intraoperative Magnetic Resonance Imaging: Preliminary Results

机译:通过术中磁共振成像在神经外科中基于模型的脑移位校正的验证:初步结果

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The quality of brain tumor resection surgery is dependent on the spatial agreement between preoperative image and intraoperative anatomy. However, brain shift compromises the aforementioned alignment. Currently, the clinical standard to monitor brain shift is intraoperative magnetic resonance (iMR). While iMR provides better understanding of brain shift, its cost and encumbrance is a consideration for medical centers. Hence, we are developing a model-based method that can be a complementary technology to address brain shift in standard resections, with resource-intensive cases as referrals for iMR facilities. Our strategy constructs a deformation 'atlas' containing potential deformation solutions derived from a biomechanical model that account for variables such as cerebrospinal fluid drainage and mannitol effects. Volumetric deformation is estimated with an inverse approach that determines the optimal combinatory 'atlas' solution fit to best match measured surface deformation. Accordingly, preoperative image is updated based on the computed deformation field. This study is the latest development to validate our methodology with iMR. Briefly, preoperative and intraoperative MR images of 2 patients were acquired. Homologous surface points were selected on preoperative and intraoperative scans as measurement of surface deformation and used to drive the inverse problem. To assess the model accuracy, subsurface shift of targets between preoperative and intraoperative states was measured and compared to model prediction. Considering subsurface shift above 3 mm, the proposed strategy provides an average shift correction of 59% across 2 cases. While further improvements in both the model and ability to validate with iMR are desired, the results reported are encouraging.
机译:脑肿瘤切除手术的质量取决于术前图像与术中解剖结构之间的空间一致性。然而,脑转移损害了前述的对准。当前,监测脑移位的临床标准是术中磁共振(iMR)。尽管iMR可以更好地了解脑转移,但其成本和负担是医疗中心的考虑因素。因此,我们正在开发一种基于模型的方法,该方法可以作为一种补充技术来解决标准切除术中的脑部转移,并提供资源密集型案例作为iMR设施的推荐。我们的策略构建了一个变形“图集”,其中包含源自生物力学模型的潜在变形解,该变形解考虑了诸如脑脊髓液引流和甘露醇效应等变量。体积变形是通过逆方法估算的,该方法确定最佳的组合“图集”解决方案,以最匹配所测表面变形。因此,基于计算出的变形场来更新术前图像。这项研究是利用iMR验证我们的方法的最新进展。简要地说,获取了2例患者的术前和术中MR图像。在术前和术中扫描中选择均质的表面点作为表面变形的量度,并用于驱动逆问题。为了评估模型的准确性,测量了术前和术中状态之间目标的地下移位,并将其与模型预测进行比较。考虑到3mm以上的地下位移,提出的策略在2种情况下均提供了59%的平均位移校正。尽管希望在模型和iMR验证能力方面进一步改进,但报告的结果令人鼓舞。

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