Resection planning for robotic acoustic neuroma surgery

作     者：McBrayer, Kepra L. Wanna, George B. Dawant, Benoit M. Balachandran, Ramya Labadie, Robert F. Noble, Jack H. 

作者机构：Vanderbilt Univ Dept Elect Engn & Comp Sci 221 Kirkland Hall Nashville TN 37235 USA Vanderbilt Univ Med Ctr Dept Otolaryngol Head & Neck Surg Nashville TN USA Vanderbilt Univ Med Ctr Dept Neurol Surg Nashville TN USA 

出 版 物：《JOURNAL OF MEDICAL IMAGING》 (J. Med. Imaging)

年 卷 期：2017年第4卷第2期

页      面：025002-025002页

核心收录：

学科分类：0831[工学-生物医学工程（可授工学、理学、医学学位）] 100207[医学-影像医学与核医学] 1006[医学-中西医结合] 1002[医学-临床医学] 1001[医学-基础医学(可授医学、理学学位)] 08[工学] 1010[医学-医学技术（可授医学、理学学位）] 100106[医学-放射医学] 1009[医学-特种医学] 10[医学] 100602[医学-中西医结合临床] 

基　　金：National Institute on Deafness and Other Communication DisordersUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute on Deafness & Other Communication Disorders (NIDCD) [R01DC012593] NATIONAL INSTITUTE ON DEAFNESS AND OTHER COMMUNICATION DISORDERSUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute on Deafness & Other Communication Disorders (NIDCD) [R01DC012593] Funding Source: NIH RePORTER 

主　　题：acoustic neuroma atlas-based segmentation internal auditory canal cochlea facial nerve 

摘      要：Acoustic neuroma surgery is a procedure in which a benign mass is removed from the internal auditory canal (IAC). Currently, this surgical procedure requires manual drilling of the temporal bone followed by exposure and removal of the acoustic neuroma. This procedure is physically and mentally taxing to the surgeon. Our group is working on the development of an acoustic neuroma surgery robot (ANSR) to perform the initial drilling procedure. Planning the ANSR s drilling region using preoperative CT requires expertise and takes about 35 min. We propose an approach for automatically producing a resection plan for the ANSR that would avoid damage to sensitive ear structures and require minimal editing by the surgeon. We first compute an atlas-based segmentation of the mastoid section of the temporal bone, refine it based on the position of anatomical landmarks, and apply a safety margin to the result to produce the automatic resection plan. In experiments with CTs from nine subjects, our automated process resulted in a resection plan that was verified to be safe in every case. Approximately 2 min were required in each case for the surgeon to verify and edit the plan to permit functional access to the IAC. We measured a mean Dice coefficient of 0.99 and surface error of 0.08 mm between the final and automatically proposed plans. These preliminary results indicate that our approach is a viable method for resection planning for the ANSR and drastically reduces the surgeon s planning effort. (C) 2017 Society of Photo-Optical Instrumentation Engineers (SPIE)