BACKGROUND: Neurosurgeons regularly plan their surgery using magnetic resonance imaging (MRI) images, which may show a clear distinction between the area to be resected and the surrounding healthy brain tissue depending on the nature of the pathology. However, this distinction is often unclear with the naked eye during the surgical intervention, and it may be difficult to infer depth and an accurate volumetric interpretation from a series of MRI image slices. OBJECTIVES: In this work, MRI data are used to create affordable patient-specific 3-dimensional (3D) scale models of the brain which clearly indicate the location and extent of a tumour relative to brain surface features and important adjacent structures. METHODS: This is achieved using custom software and rapid prototyping. In addition, functionally eloquent areas identified using functional MRI are integrated into the 3D models. RESULTS: Preliminary in vivo results are presented for 2 patients. The accuracy of the technique was estimated both theoretically and by printing a geometrical phantom, with mean dimensional errors of less than 0.5 mm observed. CONCLUSIONS: This may provide a practical and cost-effective tool which can be used for training, and during neurosurgical planning and intervention.
BACKGROUND: Neurosurgeons regularly plan their surgery using magnetic resonance imaging (MRI) images, which may show a clear distinction between the area to be resected and the surrounding healthy brain tissue depending on the nature of the pathology. However, this distinction is often unclear with the naked eye during the surgical intervention, and it may be difficult to infer depth and an accurate volumetric interpretation from a series of MRI image slices. OBJECTIVES: In this work, MRI data are used to create affordable patient-specific 3-dimensional (3D) scale models of the brain which clearly indicate the location and extent of a tumour relative to brain surface features and important adjacent structures. METHODS: This is achieved using custom software and rapid prototyping. In addition, functionally eloquent areas identified using functional MRI are integrated into the 3D models. RESULTS: Preliminary in vivo results are presented for 2 patients. The accuracy of the technique was estimated both theoretically and by printing a geometrical phantom, with mean dimensional errors of less than 0.5 mm observed. CONCLUSIONS: This may provide a practical and cost-effective tool which can be used for training, and during neurosurgical planning and intervention.
Authors: Vivian H M Mouser; Riccardo Levato; Lawrence J Bonassar; Darryl D D'Lima; Daniel A Grande; Travis J Klein; Daniel B F Saris; Marcy Zenobi-Wong; Debby Gawlitta; Jos Malda Journal: Cartilage Date: 2016-09-01 Impact factor: 4.634
Authors: Michael P Chae; Warren M Rozen; Paul G McMenamin; Michael W Findlay; Robert T Spychal; David J Hunter-Smith Journal: Front Surg Date: 2015-06-16