Literature DB >> 28331887

Android application for determining surgical variables in brain-tumor resection procedures.

Rohan C Vijayan1, Reid C Thompson2, Lola B Chambless2, Peter J Morone2, Le He2, Logan W Clements1, Rebekah H Griesenauer1, Hakmook Kang3, Michael I Miga4.   

Abstract

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.

Entities:  

Keywords:  Android application; brain shift; finite element; image guidance; image-guided surgery; neurosurgery; preoperative planning; resection; soft tissue; tumor; workflow

Year:  2017        PMID: 28331887      PMCID: PMC5333766          DOI: 10.1117/1.JMI.4.1.015003

Source DB:  PubMed          Journal:  J Med Imaging (Bellingham)        ISSN: 2329-4302


  27 in total

1.  Cortical surface registration for image-guided neurosurgery using laser-range scanning.

Authors:  Michael I Miga; Tuhin K Sinha; David M Cash; Robert L Galloway; Robert J Weil
Journal:  IEEE Trans Med Imaging       Date:  2003-08       Impact factor: 10.048

2.  Neurosurgical craniotomy localization using a virtual reality planning system versus intraoperative image-guided navigation.

Authors:  Axel T Stadie; Ralf A Kockro; Luis Serra; Gerrit Fischer; Eike Schwandt; Peter Grunert; Robert Reisch
Journal:  Int J Comput Assist Radiol Surg       Date:  2010-09-01       Impact factor: 2.924

3.  Patient-specific analysis of the volume of tissue activated during deep brain stimulation.

Authors:  Christopher R Butson; Scott E Cooper; Jaimie M Henderson; Cameron C McIntyre
Journal:  Neuroimage       Date:  2006-11-17       Impact factor: 6.556

4.  Laser range scanning for image-guided neurosurgery: investigation of image-to-physical space registrations.

Authors:  Aize Cao; R C Thompson; P Dumpuri; B M Dawant; R L Galloway; S Ding; M I Miga
Journal:  Med Phys       Date:  2008-04       Impact factor: 4.071

5.  Clinical evaluation of a model-updated image-guidance approach to brain shift compensation: experience in 16 cases.

Authors:  Michael I Miga; Kay Sun; Ishita Chen; Logan W Clements; Thomas S Pheiffer; Amber L Simpson; Reid C Thompson
Journal:  Int J Comput Assist Radiol Surg       Date:  2015-10-17       Impact factor: 2.924

6.  Automatic deformable MR-ultrasound registration for image-guided neurosurgery.

Authors:  Hassan Rivaz; Sean Jy-Shyang Chen; D Louis Collins
Journal:  IEEE Trans Med Imaging       Date:  2014-09-17       Impact factor: 10.048

7.  Data assimilation using a gradient descent method for estimation of intraoperative brain deformation.

Authors:  Songbai Ji; Alex Hartov; David Roberts; Keith Paulsen
Journal:  Med Image Anal       Date:  2009-07-09       Impact factor: 8.545

8.  A noncontacting 3-D digitizer for use in image-guided neurosurgery.

Authors:  Hai Sun; Hany Farid; David W Roberts; Kyle Rick; Alex Hartov; Keith D Paulsen
Journal:  Stereotact Funct Neurosurg       Date:  2003       Impact factor: 1.875

9.  Intraoperative image guidance in neurosurgery: development, current indications, and future trends.

Authors:  Chris Schulz; Stephan Waldeck; Uwe Max Mauer
Journal:  Radiol Res Pract       Date:  2012-05-08

10.  Integrating Retraction Modeling Into an Atlas-Based Framework for Brain Shift Prediction.

Authors:  Ishita Chen; Rowena E Ong; Amber L Simpson; Kay Sun; Reid C Thompson; Michael I Miga
Journal:  IEEE Trans Biomed Eng       Date:  2013-07-10       Impact factor: 4.538

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