Most brain-shift compensation methods address the problem of updating preoperative images to reflect brain deformations following the craniotomy and dura opening. However, fewer enable to take into account the resection-induced deformations occuring all along the tumor removal procedure. This paper evaluates the use of two existing methods to tackle that problem. Both techniques rely on blood vessels segmented then skeletonized from preoperative MR Angiography and navigated Doppler Ultrasound images acquired during resection. While the first one proposes to register the vascular trees using a rigid modified ICP algorithm, the second method relies on a non-rigid constrained-based biomechanical approach. Quantitative results are provided, based on distances between paired landmarks set on blood vessels then anatomical structures delineated on medical images. A qualitative evaluation of the compensation is also presented using initial and updated images. An analysis on three cases of surface tumor shows both methods, especially the biomechanical one, can compensate up to 63% of the brain-shift, with an error in the range of 2 mm. However, these results are not reproduced on a more complex case of deep tumor. While more patients must be included, these preliminary results show that vesselbased methods are well suited to compensate for resection-induced brain-shift, but better outcomes in complex cases still require to improve the methods to take the resection into account.
Fanny Morin, Hadrien Courtecuisse, Ingerid Reinertsen, Florian Le Lann, Olivier Palombi, Yohan Payan, and Matthieu Chabanas, "Resection-induced brain-shift compensation using vessel-based methods," Proc. SPIE 10576, Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling, 105760Q (Presented at SPIE Medical Imaging: February 14, 2018; Published: 12 March 2018); https://doi.org/10.1117/12.2293640.
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