In this analysis, the authors sought to identify variables triggering an additional resection (AR) and determining residual intraoperative tumor volume in 1.5-T intraoperative MRI (iMRI)-guided glioma resections.
A consecutive case series of 224 supratentorial glioma resections (WHO Grades I–IV) from a prospective iMRI registry (inclusion dates January 2011–April 2013) was examined with univariate and multiple regression models including volumetric data, tumor-related, and surgeon-related factors. The surgeon's expectation of an AR, in response to a questionnaire completed prior to iMRI, was evaluated using contingency analysis. A machine-learning prediction model was applied to consider if anticipation of intraoperative findings permits preoperative identification of ideal iMRI cases.
An AR was performed in 70% of cases after iMRI, but did not translate into an accumulated risk for neurological morbidity after surgery (p = 0.77 for deficits in cases with AR vs no AR). New severe persistent deficits occurred in 6.7% of patients. Initial tumor volume determined frequency of ARs and was independently correlated with larger tumor remnants delineated on iMRI (p < 0.0001). Larger iMRI volume was further associated with eloquent location (p = 0.010) and recurrent tumors (p < 0.0001), and with WHO grade (p = 0.0113). Greater surgical experience had no significant influence on the course of surgery. The surgeon's capability of ruling out an AR prior to iMRI turned out to incorporate guesswork (negative predictive value 43.6%). In a prediction model, AR could only be anticipated with 65% accuracy after integration of confounding variables.
Routine use of iMRI in glioma surgery is a safe and reliable method for resection guidance and is characterized by frequent ARs after scanning. Tumor-related factors were identified that influenced the course of surgery and intraoperative decision-making, and iMRI had a common value for surgeons of all experience levels. Commonly, the subjective intraoperative impression of the extent of resection had to be revised after iMRI review, which underscores the manifold potential of iMRI guidance. In combination with the failure to identify ideal iMRI cases preoperatively, this study supports a generous, tumor-oriented rather than surgeon-oriented indication for iMRI in glioma surgery.