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Updated: Apr 5, 2026
A Unified Methodological Framework for Vestibular Schwannoma Research
Published on: June 20, 2017
Slip Interface Imaging Predicts Tumor-Brain Adhesion in Vestibular Schwannomas
Ziying Yin1, Kevin J Glaser1, Armando Manduca1
1From the Departments of Radiology (Z.Y., K.J.G., R.L.E., J.H.), Physiology and Biomedical Engineering (A.M.), and Neurosurgery (J.J.V.G., M.J.L., J.D.H.), Mayo Clinic College of Medicine, 200 First St SW, Rochester, MN 55905; and Naval Research Laboratory, Washington, DC (A.R.).
Purpose:
To test the clinical feasibility and usefulness of slip interface imaging (SII) to identify and quantify the degree of tumor-brain adhesion in patients with vestibular schwannomas.
Materials And Method:
S With institutional review board approval and after obtaining written informed consent, SII examinations were performed in nine patients with vestibular schwannomas. During the SII acquisition, a low-amplitude mechanical vibration is applied to the head with a pillow-like device placed in the head coil and the resulting shear waves are imaged by using a phase-contrast pulse sequence with motion-encoding gradients synchronized with the applied vibration. Imaging was performed with a 3-T magnetic resonance (MR) system in less than 7 minutes. The acquired shear motion data were processed with two different algorithms (shear line analysis and calculation of octahedral shear strain [OSS]) to identify the degree of tumor-brain adhesion. Blinded to the SII results, neurosurgeons qualitatively assessed tumor adhesion at the time of tumor resection. Standard T2-weighted, fast imaging employing steady-state acquisition (FIESTA), and T2-weighted fluid-attenuated inversion recovery (FLAIR) imaging were reviewed to identify the presence of cerebral spinal fluid (CSF) clefts around the tumors. The performance of the use of the CSF cleft and SII to predict the degree of tumor adhesion was evaluated by using the κ coefficient and McNemar test.
Results:
Among the nine patients, SII agreed with the intraoperative assessment of the degree of tumor adhesion in eight patients (88.9%; 95% confidence interval [CI]: 57%, 98%), with four of four, three of three, and one of two cases correctly predicted as no adhesion, partial adhesion, and complete adhesion, respectively. However, the T2-weighted, FIESTA, and T2-weighted FLAIR images that used the CSF cleft sign to predict adhesion agreed with surgical findings in only four cases (44.4% [four of nine]; 95% CI: 19%, 73%). The κ coefficients indicate good agreement (0.82 [95% CI: 0.5, 1]) for the SII prediction versus surgical findings, but only fair agreement (0.21 [95% CI: -0.21, 0.63]) between the CSF cleft prediction and surgical findings. However, the difference between the SII prediction and the CSF cleft prediction was not significant (P = .103; McNemar test), likely because of the small sample size in this study.
Conclusion:
SII can be used to predict the degree of tumor-brain adhesion of vestibular schwannomas and may provide a method to improve preoperative planning and determination of surgical risk in these patients.
