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Abstract #0411

Quantification of meningioma-brain adhesion using MR-elastography based slip interface imaging

Ziying Yin1, Xin Lu1, Salomon Cohen Cohen2, Yi Sui1, Armando Manduca3, Jamie J Van Gompel2, Richard L. Ehman1, and John III Huston1
1Radiology, Mayo Clinic, Rochester, MN, United States, 2Neurosurgery, Mayo Clinic, Rochester, MN, United States, 3Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, United States

Brain tumor adherence has been long recognized to impact surgical resection difficulty. Recently-developed slip interface imaging (SII) can preoperatively predict tumor-brain adhesion. In previous studies, subjectively-determined SII assessment of tumor adhesion has been shown to agree well with intraoperative findings. The purpose of this work was to develop an objective quantitative method for analyzing SII data for adherence, thereby minimizing inter- and intraobserver variability. We developed a radiomics-based metric (termed “adhesion degree”) based on SII to quantify the degree of tumor adhesion. In 46 meningiomas, the adhesion degree showed excellent accuracy in predicting completely adherent tumors (AUROC=0.96) from non-adherent tumors.

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