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Slip interface imaging based on MR-elastography preoperatively predicts meningioma-brain adhesion. | LitMetric

Purpose: To investigate the ability of slip interface imaging (SII), a recently developed magnetic resonance elastography (MRE)-based technique, to predict the degree of meningioma-brain adhesion, using findings at surgery as the reference standard.

Materials And Methods: With Institutional Review Board approval and written informed consent, 25 patients with meningiomas >2.5 cm in maximal diameter underwent preoperative SII assessment. Intracranial shear motions were introduced using a soft, pillow-like head driver and the resulting displacement field was acquired with an MRE pulse sequence on 3T MR scanners. The displacement data were analyzed to determine tumor-brain adhesion by assessing intensities on shear line images and raw as well as normalized octahedral shear strain (OSS) values along the interface. The SII findings of shear line images, OSS, and normalized OSS were independently and blindly correlated with surgical findings of tumor adhesion by using the Cohen's κ coefficient and chi-squared test.

Results: Neurosurgeons categorized the surgical plane as extrapial (no adhesion) in 15 patients, mixed in four, and subpial (adhesion) in six. Both shear line images and OSS agreed with the surgical findings in 18 (72%) cases (fair agreement, κ = 0.37, 95% confidence interval [CI]: 0.05-0.69), while normalized OSS was concordant with the surgical findings in 23 (92%) cases (good agreement, κ = 0.86, 95% CI: 0.67-1). The correlation between SII predictions (shear line images, OSS, and normalized OSS) and the surgical findings were statistically significant (chi-squared test, P = 0.02, P = 0.02, and P < 0.0001, respectively).

Conclusion: SII preoperatively evaluates the degree of meningioma-brain adhesion noninvasively, allowing for improved prediction of surgical risk and tumor resectability.

Level Of Evidence: 1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1007-1016.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5600107PMC
http://dx.doi.org/10.1002/jmri.25623DOI Listing

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