Intraoperative image updating for brain shift following dural opening

Abstract

OBJECTIVE Preoperative magnetic resonance images (pMR) are typically coregistered to provide intraoperative navigation, the accuracy of which can be significantly compromised by brain deformation. In this study, the authors generated updated MR images (uMR) in the operating room (OR) to compensate for brain shift due to dural opening, and evaluated the accuracy and computational efficiency of the process. METHODS In 20 open cranial neurosurgical cases, a pair of intraoperative stereovision (iSV) images was acquired after dural opening to reconstruct a 3D profile of the exposed cortical surface. The iSV surface was registered with pMR to detect cortical displacements that were assimilated by a biomechanical model to estimate whole-brain nonrigid deformation and produce uMR in the OR. The uMR views were displayed on a commercial navigation system and compared side by side with the corresponding coregistered pMR. A tracked stylus was used to acquire coordinate locations of features on the cortical surface that served as independent positions for calculating target registration errors (TREs) for the coregistered uMR and pMR image volumes. RESULTS The uMR views were visually more accurate and well aligned with the iSV surface in terms of both geometry and texture compared with pMR where misalignment was evident. The average misfit between model estimates and measured displacements was 1.80 ± 0.35 mm, compared with the average initial misfit of 7.10 ± 2.78 mm between iSV and pMR, and the average TRE was 1.60 ± 0.43 mm across the 20 patients in the uMR image volume, compared with 7.31 ± 2.82 mm on average in the pMR cases. The iSV also proved to be accurate with an average error of 1.20 ± 0.37 mm. The overall computational time required to generate the uMR views was 7–8 minutes. CONCLUSIONS This study compensated for brain deformation caused by intraoperative dural opening using computational model–based assimilation of iSV cortical surface displacements. The uMR proved to be more accurate in terms of model-data misfit and TRE in the 20 patient cases evaluated relative to pMR. The computational time was acceptable (7–8 minutes) and the process caused minimal interruption of surgical workflow.

Image Updating for Brain Shift Compensation During Resection

“…First, uMR was produced to compensate for brain deformation due to dural opening. 14 Specifically, the brain was segmented from pMR using an adaptive preterm segmentation algorithm. 19 After dural opening, an iSV image pair was acquired and a 3-dimensional (3-D) profile of the exposed cortical surface was reconstructed (iSV 1 ).…”

“…The computational time of first image update was 7 to 8 min on average as reported previously. 14 Here, we present the time involved in generating the second update. Reconstruction of the iSV surface was completed in ∼6 to 7 s with graphics processing unit acceleration.…”

“…In a previous work, 14 we produced uMRs in the OR to compensate for brain deformation but only after dural opening. Sun et al 15 used laser range scanning to account for postresection brain shift, but tumor volume was not removed to represent extent of resection.…”

Computational Biomechanics of the Brain in the Operating Theatre

“…To our knowledge, almost all existing studies, including our own, are retrospective only. A notable exception is [22], in which simulations were carried out in the operating room, using the method proposed in [19], before updated MRI was displayed in the neuronavigation system. This study could then be considered as one of the first computational models of the brain actually used in the operating theater.…”

Infrared thermography mapping plus neuronavigation target location in an eloquent area cavernoma resection

“…In many surgical scenarios, NN can misguide to false locations mainly due to the brain shift phenomenon and deformation. [2,6,8,12,15] To perform safer and more efficient surgeries, particularly in surgery in eloquent areas, it is necessary to add in vivo information to increase the accuracy in locating surgical targets (computed tomography [CT], brain mapping, magnetic resonance [MR], ultrasound, and trans-operatory fluorescence angiography, among others). thermometers, and qualitative thermosensitive materials can measure brain metabolism by its caloric radiation.…”