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  • Meningioma Consistency Prediction Utilizing Tumor to Cerebellar Peduncle Intensity on T2-weighted Magnetic Resonance Imaging Sequences: TCTI Ratio

    Final Number:

    Kyle Anthony Smith MD; John Leever MD; Phillip D Hylton MD; Paul J. Camarata MD, FACS; Roukoz B. Chamoun MD

    Study Design:

    Subject Category:

    Meeting: Congress of Neurological Surgeons 2016 Annual Meeting

    Introduction: Meningioma consistency, firmness or softness as it relates to resectability, affects the difficulty of surgery and, to some degree, the extent of resection. Preoperative knowledge of tumor consistency would affect preoperative planning and instrumentation. Several methods of prediction have been proposed, but the majority lack objectivity and reproducibility or generalizability to other surgeons. In a previous pilot study of 20 patients the authors proposed a new method of prediction based on tumor/cerebellar peduncle T2-weighted imaging intensity (TCTI) ratios in comparison with objective intraoperative findings. In the present study they sought validation of this method.

    Methods: Magnetic resonance images from 100 consecutive patients undergoing craniotomy for meningioma resection were evaluated preoperatively. During surgery a consistency grade was prospectively applied to lesions by the operating surgeon, as determined by suction and/or cavitron ultrasonic surgical aspirator (CUSA) intensity. Consistency grades were A, soft; B, intermediate; and C, fibrous. Using T2-weighted MRI sequences, TCTI ratios were calculated. Analysis of the TCTI ratios and intraoperative tumor consistency was completed with ANOVA and receiver operator characteristic curves.

    Results: Of the 100 tumors evaluated, 50 were classified as soft, 29 as intermediate, and 21 as firm. The median TCTI ratio for firm tumors was 0.88; for intermediate tumors, 1.5; and for soft tumors, 1.84. One-way ANOVA comparing TCTI ratios for these groups was statistically significant (p < 0.0001). A single cutoff TCTI value of 1.41 for soft versus firm tumors was found to be 81.9% sensitive and 84.8% specific.

    Conclusions: The authors propose this T2-based method of tumor consistency prediction with correlation to objective intraoperative consistency. This method is quantifiable and reproducible, which expands its usability. Additionally, it places tumor consistency on a graded continuum in a clinically meaningful way that could affect preoperative surgical planning.

    Patient Care: This research will potentially improve pre-operative planning for meningioma resection.

    Learning Objectives: By conclusion of this session, participants should be able to: 1) Understand value of T2-weighted MRI for tumor consistency; 2) Understand value of utilizing an internal imaging reference for consistency prediction.

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