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In successful brain tumor surgery, the neurosurgeon's objectives are threefold: (1) reach the target, (2) remove
it and (3) preserve eloquent tissue surrounding it. Surgical Planning (SP) consists in identifying optimal access
route(s) to the target based on anatomical references and constrained by functional areas. Preoperative
images are essential input in Multi-modal Image Guided NeuroSurgery systems (MIGNS) and update of these
images, with precision and accuracy, is crucial to approach the anatomical reality in the Operating Room (OR).
Intraoperative brain deformation has been previously identified by many research groups and related update
of preoperative images has also been studied. We present a study of three surgical cases with tumors accompanied
with edema and where corticosteroids were administered and monitored during a preoperative stage
[t0, t1 = t0 + 10 days]. In each case we observed a significant change in the Region Of Interest (ROI) and in
anatomical references around it. This preoperative brain shift could induce error for localization during intervention
(time tS) if the SP is based on the t0 preoperative images. We computed volume variation, distance maps based on closest point (CP) for different components of the ROI, and displacement of center of mass (CM) of
the ROI. The matching between sets of homologous landmarks from t0 to t1 was performed by an expert. The
estimation of the landmarks displacement showed significant deformations around the ROI (landmarks shifted
with mean of 3.90 ± 0.92 mm and maximum of 5.45 mm for one case resection). The CM of the ROI moved
about 6.92 mm for one biopsy. Accordingly, there was a sizable difference between SP based at t0 vs SP based
at t1, up to 7.95 mm for localization of reference access in one resection case. When compared to the typical
MIGNS system accuracy (2 mm), it is recommended that preoperative images be updated within the interval time [t1,tS] in order to minimize the error correspondence between the anatomical reality and the preoperative data. This should help maximize the accuracy of registration between the preoperative images and the patient in the OR.
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