2 March 2017 Android application for determining surgical variables in brain-tumor resection procedures
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The fidelity of image-guided neurosurgical procedures is often compromised due to the mechanical deformations that occur during surgery. In recent work, a framework was developed to predict the extent of this brain shift in brain-tumor resection procedures. The approach uses preoperatively determined surgical variables to predict brain shift and then subsequently corrects the patient’s preoperative image volume to more closely match the intraoperative state of the patient’s brain. However, a clinical workflow difficulty with the execution of this framework is the preoperative acquisition of surgical variables. To simplify and expedite this process, an Android, Java-based application was developed for tablets to provide neurosurgeons with the ability to manipulate three-dimensional models of the patient’s neuroanatomy and determine an expected head orientation, craniotomy size and location, and trajectory to be taken into the tumor. These variables can then be exported for use as inputs to the biomechanical model associated with the correction framework. A multisurgeon, multicase mock trial was conducted to compare the accuracy of the virtual plan to that of a mock physical surgery. It was concluded that the Android application was an accurate, efficient, and timely method for planning surgical variables.
© 2017 Society of Photo-Optical Instrumentation Engineers (SPIE)
Rohan C. Vijayan, Rohan C. Vijayan, Reid C. Thompson, Reid C. Thompson, Lola B. Chambless, Lola B. Chambless, Peter J. Morone, Peter J. Morone, Le He, Le He, Logan W. Clements, Logan W. Clements, Rebekah H. Griesenauer, Rebekah H. Griesenauer, Hakmook Kang, Hakmook Kang, Michael I. Miga, Michael I. Miga, } "Android application for determining surgical variables in brain-tumor resection procedures," Journal of Medical Imaging 4(1), 015003 (2 March 2017). https://doi.org/10.1117/1.JMI.4.1.015003 . Submission: Received: 16 December 2016; Accepted: 13 February 2017
Received: 16 December 2016; Accepted: 13 February 2017; Published: 2 March 2017

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