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Choosing Statistically Safe, Variable-Thickness Margins in Robot-Assisted Partial Nephrectomy

Michael Siebold, James M. Ferguson, E. Pitt, Nicholas Kavoussi, Naren Nimmagadda, Duke Herrell, Robert J. Webster

发表年份
2020
引用次数
3

摘要

In robot-assisted partial nephrectomy, kidney tumors are removed surgically, along with a margin of healthy tissue around the tumor. This margin is taken to prevent positive margins (i.e. tumor tissue accidentally left behind). Yet it is desirable to minimize the thickness of the margin, since the effectiveness of post-surgery kidney function is related to the volume of kidney tissue preserved. In this paper we use statistical information on robot-mediated surface-based registration to select variable-thickness margins that optimally account for registration uncertainty. These margins can then be displayed in the surgeon console to provide enhanced information to the surgeon during robotic partial nephrectomy.

关键词

NephrectomyMargin (machine learning)RobotSurgical marginSurgical robotComputer scienceMedicineVariable (mathematics)Artificial intelligenceSurgery

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