Predicting meningioma consistency and brain-meningioma interface with intraoperative strain ultrasound elastography: a novel application to guide surgical strategy.

OBJECTIVE

Providing new tools to improve surgical planning is considered a main goal in meningioma treatment. In this context, two factors are crucial in determining operating strategy: meningioma-brain interface and meningioma consistency. The use of intraoperative ultrasound (ioUS) elastosonography, a real-time imaging technique, has been introduced in general surgery to evaluate similar features in other pathological settings such as thyroid and prostate cancer. The aim of the present study was to evaluate ioUS elastosonography in the intraoperative prediction of key intracranial meningioma features and to evaluate its application in guiding surgical strategy.

METHODS

An institutional series of 36 meningiomas studied with ioUS elastosonography is reported. Elastographic data, intraoperative surgical findings, and corresponding preoperative MRI features were classified, applying a score from 0 to 2 to both meningioma consistency and meningioma-brain interface. Statistical analysis was performed to determine the degree of agreement between meningioma elastosonographic features and surgical findings, and whether intraoperative elastosonography was a better predictor than preoperative MRI in assessing meningioma consistency and slip-brain interface, using intraoperative findings as the gold standard.

RESULTS

A significantly high degree of reliability and agreement between ioUS elastographic scores and surgical finding scores was reported (intraclass correlation coefficient = 0.848, F = 12.147, p < 0.001). When analyzing both consistency and brain-tumor interface, ioUS elastography proved to have a rather elevated sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and positive (LR+) and negative likelihood ratio (LR-). This consideration was true especially for meningiomas with a hard consistency (sensitivity = 0.92, specificity = 0.96, PPV = 0.92, NPV = 0.96, LR+ = 22.00, LR- = 0.09) and for those presenting with an adherent slip-brain interface (sensitivity = 0.76, specificity = 0.95, PPV = 0.93, NPV = 0.82, LR+ = 14.3, LR- = 0.25). Furthermore, predictions derived from ioUS elastography were found to be more accurate than MRI-derived predictions, as demonstrated by McNemar's test results in both consistency (p < 0.001) and interface (p < 0.001).

CONCLUSIONS

While external validation of the data is needed to transform ioUS elastography into a fully deployable clinical tool, this experience confirmed that it may be integrated into meningioma surgical planning, especially because of its rapidity and cost-effectiveness.