Ms. Kepra L. McBrayer Profile

Kepra L. McBrayer

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SPIE Journal Paper | 5 June 2017

Resection planning for robotic acoustic neuroma surgery

Kepra McBrayer, George Wanna, Benoit Dawant, Ramya Balachandran, Robert Labadie, Jack Noble

JMI, Vol. 4, Issue 02, 025002, (June 2017) https://doi.org/10.1117/12.10.1117/1.JMI.4.2.025002

KEYWORDS: Surgery, Acoustics, Robotics, Bone, Ear, Image segmentation, Safety

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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.

Proceedings Article | 18 March 2016 Paper

Resection planning for robotic acoustic neuroma surgery

Kepra McBrayer, George Wanna, Benoit Dawant, Ramya Balachandran, Robert Labadie, Jack Noble

Proceedings Volume 9786, 978608 (2016) https://doi.org/10.1117/12.2216867

KEYWORDS: Surgery, Robotics, Bone, Nerve, Ear, Image segmentation, Image registration, Skull

Read Abstract +

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 to develop an Acoustic Neuroma Surgery Robot (ANSR) to perform the initial drilling procedure. Planning the ANSR's drilling region using pre-operative CT requires expertise and around 35 minutes' time. 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 9 subjects, our automated process resulted in a resection plan that was verified to be safe in every case. Approximately 2 minutes 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.

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