Purpose: To develop automated vestibular schwannoma measurements on contrast-enhanced T1- and T2-weighted MRI scans.Materials and Methods: MRI data from 214 patients in 37 different centers were... Show morePurpose: To develop automated vestibular schwannoma measurements on contrast-enhanced T1- and T2-weighted MRI scans.Materials and Methods: MRI data from 214 patients in 37 different centers were retrospectively analyzed between 2020 and 2021. Patients with hearing loss (134 positive for vestibular schwannoma [mean age 6 SD, 54 years 6 12; 64 men] and 80 negative for vestibular schwannoma) were randomly assigned to a training and validation set and to an independent test set. A convolutional neural network (CNN) was trained using fivefold cross-validation for two models (T1 and T2). Quantitative analysis, including Dice index, Hausdorff distance, surface-to-surface distance (S2S), and relative volume error, was used to compare the computer and the human delineations. An observer study was performed in which two experienced physicians evaluated both delineations.Results: The T1-weighted model showed state-of-the-art performance, with a mean S2S distance of less than 0.6 mm for the whole tumor and the intrameatal and extrameatal tumor parts. The whole tumor Dice index and Hausdorff distance were 0.92 and 2.1 mm in the independent test set, respectively. T2-weighted images had a mean S2S distance less than 0.6 mm for the whole tumor and the intrameatal and extrameatal tumor parts. The whole tumor Dice index and Hausdorff distance were 0.87 and 1.5 mm in the independent test set. The observer study indicated that the tool was similar to human delineations in 85%-92% of cases.Conclusion: The CNN model detected and delineated vestibular schwannomas accurately on contrast-enhanced T1- and T2-weighted MRI scans and distinguished the clinically relevant difference between intrameatal and extrameatal tumor parts. (C) RSNA, 2022 Show less
Pont, L.M.H. de; Steekelenburg, J.M. van; Verbist, B.M.; Buchem, M.A. van; Blom, H.M.; Hammer, S. 2020
Purpose of ReviewMeniere's disease (MD) is a burdensome and not well understood inner ear disorder that has received increasing attention of scientists over the past decade. Until 2007, a certain... Show morePurpose of ReviewMeniere's disease (MD) is a burdensome and not well understood inner ear disorder that has received increasing attention of scientists over the past decade. Until 2007, a certain diagnosis of endolymphatic hydrops (EH) required post-mortem histology. Today, dedicated high-resolution magnetic resonance imaging (MRI) protocols enable detection of disease-related changes in the membranous labyrinth in vivo. In this review, we summarize the current status of MR imaging for MD.Recent FindingsThe mainstays of hydrops imaging are inversion recovery sequences using delayed acquisition after intravenous or intratympanic contrast administration. Based on these techniques, several methods have been developed to detect and classify EH. In addition, novel imaging features of MD, such as blood-labyrinth barrier impairment, have recently been observed.SummaryDelayed contrast enhanced MRI has emerged as a reliable technique to demonstrate EH in vivo, with promising application in the diagnosis and follow-up of MD patients. Therefore, familiarity with current techniques and diagnostic imaging criteria is increasingly important. Show less
