Biomedical Signal and Image Computing Laboratory, University of British Columbia, Vancouver, BC, Canada.
Medical Image Analysis Laboratory, Simon Fraser University, Burnaby, BC, Canada.
Med Image Anal. 2015 Oct;25(1):103-10. doi: 10.1016/j.media.2015.04.010. Epub 2015 Apr 23.
Hilar dissection is an important and delicate stage in partial nephrectomy, during which surgeons remove connective tissue surrounding renal vasculature. Serious complications arise when the occluded blood vessels, concealed by fat, are missed in the endoscopic view and as a result are not appropriately clamped. Such complications may include catastrophic blood loss from internal bleeding and associated occlusion of the surgical view during the excision of the cancerous mass (due to heavy bleeding), both of which may compromise the visibility of surgical margins or even result in a conversion from a minimally invasive to an open intervention. To aid in vessel discovery, we propose a novel automatic method to segment occluded vasculature from labeling minute pulsatile motion that is otherwise imperceptible with the naked eye. Our segmentation technique extracts subtle tissue motions using a technique adapted from phase-based video magnification, in which we measure motion from periodic changes in local phase information albeit for labeling rather than magnification. Based on measuring local phase through spatial decomposition of each frame of the endoscopic video using complex wavelet pairs, our approach assigns segmentation labels by detecting regions exhibiting temporal local phase changes matching the heart rate. We demonstrate how our technique is a practical solution for time-critical surgical applications by presenting quantitative and qualitative performance evaluations of our vessel detection algorithms with a retrospective study of fifteen clinical robot-assisted partial nephrectomies.
肾门解剖是部分肾切除术的一个重要而精细的阶段，在此期间，外科医生切除围绕肾血管的结缔组织。当内窥镜下被脂肪隐藏的闭塞血管被遗漏而未被适当夹闭时，会出现严重的并发症。这些并发症可能包括因内部出血导致的灾难性失血，以及在切除癌组织时由于大量出血导致手术视野阻塞（这可能会影响手术边缘的可见度，甚至导致从微创手术转为开放性干预）。为了帮助发现血管，我们提出了一种新的自动方法，从标记微小的脉动运动中分割闭塞的血管，而这些运动用肉眼是无法察觉的。我们的分割技术使用基于相位的视频放大技术的改编版本来提取细微的组织运动，在该技术中，我们测量局部相位信息的周期性变化来测量运动，尽管这是用于标记而不是放大。基于使用复小波对每个内窥镜视频帧进行空间分解来测量局部相位，我们的方法通过检测与心率匹配的表现出时间局部相位变化的区域来分配分割标签。我们通过对十五例机器人辅助部分肾切除术的回顾性研究，展示了我们的血管检测算法的定量和定性性能评估，证明了我们的技术如何成为时间关键型手术应用的实用解决方案。
