Multimodal Registration of the Brain's Cortical Surface

描述(由申请人提供)： 在注重成本的医疗保健系统的背景下，提供丰富的术前影像信息和实际患者之间的量化关系的必要性是显而易见的。这在神经外科环境中尤其重要，因为神经外科环境中明显缺乏解剖标志。开发一种经济高效的方法来提高神经外科医生在手术中对大脑皮质结构的识别能力，并在术中动态跟踪这些区域，将是图像引导手术的重要贡献。激光距离扫描(LRS)是一种候选技术，它具有以最小的空间提供丰富的术中数据的优势。本文提出的工作涉及LRS技术在临床上的可翻译使用，该技术可能对患有脑肿瘤的患者的手术治疗产生直接影响。在目前的技术下，神经外科医生通常通过研究患者的MR断层图像作为分段重建的灰度编码体绘制来制定手术治疗计划。通过在MR灰阶提供解剖标志的情况下可视化分割的大脑的三维状态，外科医生可以识别可能在提供治疗中重要的敏感区域。例如，与初级、运动、躯体感觉、听觉和视觉功能相关的脑回通常可以在这些图像上或在皮质刺激和/或功能磁共振(MR)成像的帮助下被识别。不幸的是，由于缺乏外科医生视野(FOV)内的标志性识别，即术中皮质表面的表现，这些区域往往很难在术中识别。围绕这项拟议研究的一个基本假设是，纹理(纹理来自FOV的数字图像)激光距离扫描(TLRS)数据可以用于使用多模式配准方法将术前图像数据与外科医生的视野相关联。具体地说，这项建议的目标是：(1)通过将纹理点云记录到MR断层图像来加强手术指导，(2)为外科医生提供新的解剖学线索，以及(3)在手术过程中测量皮质脑移位。虽然这些增强对于将皮质表面与其对应的MR相关联是至关重要的，但表征表层下组织运动的需要也同样重要。因此，这项建议概述了一种策略，直接使用TLRS数据作为一种手段来预测正在接受神经外科干预的患者的表面下移位。综上所述，如果影像引导程序要推进外科治疗，这些系统的下一步发展将需要考虑软组织变形的方法。本文提出的TLRS研究代表了一种临床上可翻译的记录脑移位的策略，这可能是开发能够补偿软组织变形的负担得起的图像引导平台的关键。

DESCRIPTION (provided by applicant): Within the backdrop of a cost-conscious healthcare system, the need for providing quantitative relationships between the abundance of preoperative imaging information and the physical patient is clear. This is particularly important within the neurosurgical context where there is a distinct lack of anatomical landmarks. Developing a cost-effective method to improve a neurosurgeon's recognition of cortical brain structures during surgery as well as dynamically tracking these regions intraoperatively would be an important contribution to image-guided procedures. Laser range scanning (LRS) is a candidate technology that has the advantage of providing a wealth of intraoperative data with minimal space requirements. The work proposed herein involves a clinically translatable use of LRS technology that could have direct impact on surgical therapy for patients afflicted with brain tumors. With current technology, neurosurgeons often develop a surgical treatment plan by studying the patient's MR tomogram as a segmented reconstructed gray-scale encoded volume rendering. By visualizing the segmented brain in its three-dimensional state with the MR gray-scale providing anatomical landmarks, the surgeon can identify sensitive regions which may be important in the delivery of therapy. For example, gyri that are associated with primary, motor, somesthetic, auditory and visual functions can be identified usually on these renderings or with the assistance of cortical stimulation and/or functional magnetic resonance (MR) imaging. Unfortunately, these regions can often be difficult to recognize intraoperatively due to the lack of landmark recognition within the surgeon's field of view (FOV), i.e. the intraoperative presentation of the cortical surface. One fundamental hypothesis encompassing this proposed research is that textured (texture is from a digital image of the FOV) laser-range scan (tLRS) data can be used to correlate preoperative image data to the surgeon's field of view using a multi-modal registration approach. Specifically, the aims within this proposal are focused at: (1) enhancing surgical guidance by registering textured point clouds to the MR tomogram, (2) providing new anatomical cues to the surgeon, and (3) measuring cortical brain shift during surgical procedures. Although these enhancements are critical for correlating the cortical surface to its MR counterpart, the need to characterize subsurface tissue motion is equally important. As a result, this proposal outlines a strategy to directly address the use of tLRS data as a means to predict subsurface shift within patients undergoing a neurosurgical intervention. In summary, if image-guided procedures are to advance surgical therapy, the next evolution of these systems will require methods to account for soft tissue deformation. The tLRS studies proposed herein represent a clinically translatable strategy for documenting brain shift which could be pivotal in developing affordable image-guided platforms capable of compensating for soft tissue deformation.