Detection of Volume-Changing Metastatic Brain Tumors on Longitudinal MRI Using a Semiautomated Algorithm Based on the Jacobian Operator Field.

BACKGROUND AND PURPOSE: Accurate follow-up of metastatic brain tumors has important implications for patient prognosis and management. The aim of this study was to develop and evaluate the accuracy of a semiautomated algorithm in detecting growing or shrinking metastatic brain tumors on longitudinal brain MRIs. MATERIALS AND METHODS: We used 50 pairs of successive MR imaging datasets, 30 on 1.5T and 20 on 3T, containing contrast-enhanced 3D T1-weighted sequences. These yielded 150 growing or shrinking metastatic brain tumors. To detect them, we completed 2 major steps: 1) spatial normalization and calculation of the Jacobian operator field to quantify changes between scans, and 2) metastatic brain tumor candidate segmentation and detection of volume-changing metastatic brain tumors with the Jacobian operator field. Receiver operating characteristic analysis was used to assess the detection accuracy of the algorithm, and it was verified with jackknife resampling. The reference standard was based on detections by a neuroradiologist. RESULTS: The areas under the receiver operating characteristic curves were 0.925 for 1.5T and 0.965 for 3T. Furthermore, at its optimal performance, the algorithm achieved a sensitivity of 85.1% and 92.1% and specificity of 86.7% and 91.3% for 1.5T and 3T, respectively. Vessels were responsible for most false-positives. Newly developed or resolved metastatic brain tumors were a major source of false-negatives. CONCLUSIONS: The proposed algorithm could detect volume-changing metastatic brain tumors on longitudinal brain MRIs with statistically high accuracy, demonstrating its potential as a computer-aided change-detection tool for complementing the performance of radiologists, decreasing inter- and intraobserver variability, and improving efficacy.

Diagnostic Performance of Routine Brain MRI Sequences for Dural Venous Sinus Thrombosis.

BACKGROUND AND PURPOSE: Signs suggestive of unexpected dural venous sinus thrombosis are detectable on routine MR imaging studies without MRV. We assessed performance characteristics and interrater reliability of routine MR imaging for the diagnosis of dural venous sinus thrombosis, focusing on the superior sagittal, transverse, and sigmoid sinuses. MATERIALS AND METHODS: This case series included 350 patients with MRIs performed with contrast-enhanced MRV and 79 patients with routine MRIs performed within 48 hours of a CTV from 2008 to 2014 (total, n = 429). Routine MR images were separated from the contrast-enhanced MRVs and CTVs. Three neuroradiologists, blinded to clinical data, independently reviewed the MRIs for signs of dural venous sinus thrombosis, including high signal on sagittal T1, loss of flow void on axial T2, high signal on FLAIR, high signal on DWI, increased susceptibility effects on T2*-weighted gradient recalled-echo imaging, and filling defects on axial contrast-enhanced spin-echo T1WI and/or volumetric gradient-echo T1WI. Two neuroradiologists independently reviewed contrast-enhanced MRVs and CTVs to determine the consensus gold standard. Interrater reliability was calculated by using the κ coefficient. RESULTS: Contrast-enhanced MRV and CTV confirmed that dural venous sinus thrombosis was present in 72 of 429 cases (16.8%). The combination of routine MR sequences had an overall sensitivity of 79.2%, specificity of 89.9%, and moderate interrater reliability (κ = 0.50). The 3 readers did not have similar performance characteristics. 69.4% of positive cases had clinical suspicion of dural venous sinus thrombosis indicated on imaging requisition. CONCLUSIONS: Routine MR images can suggest dural venous sinus thrombosis with high specificity in high-risk patients, even in cases without clinical suspicion.