Multisite Concordance Of Dsc-Mri Analysis For Brain Tumors: Results Of A National Cancer Institute Quantitative Imaging Network Collaborative Project
BACKGROUND AND PURPOSE: Standard assessment criteria for brain tumors that only include anatomic imaging continue to be insufficient. While numerous studies have demonstrated the value of DSC-MR imaging perfusion metrics for this purpose, they have not been incorporated due to a lack of confidence in the consistency of DSC-MR imaging metrics across sites and platforms. This study addresses this limitation with a comparison of multisite/multiplatform analyses of shared DSC-MR imaging datasets of patients with brain tumors. MATERIALS AND METHODS: DSC-MR imaging data were collected after a preload and during a bolus injection of gadolinium contrast agent using a gradient recalled-echoâ€“EPI sequence (TE/TR 30/1200 ms; flip angle 72Â°). Forty-nine low-grade (n 13) and high-grade (n 36) glioma datasets were uploaded to The Cancer Imaging Archive. Datasets included a predetermined arterial input function, enhancing tumor ROIs, and ROIs necessary to create normalized relative CBV and CBF maps. Seven sites computed 20 different perfusion metrics. Pair-wise agreement among sites was assessed with the Lin concordance correlation coefficient. Distinction of low- from high-grade tumors was evaluated with the Wilcoxon rank sum test followed by receiver operating characteristic analysis to identify the optimal thresholds based on sensitivity and specificity. RESULTS: For normalized relative CBV and normalized CBF, 93% and 94% of entries showed good or excellent cross-site agreement (0.8 Lin concordance correlation coefficient 1.0). All metrics could distinguish low- from high-grade tumors. Optimum thresholds were determined for pooled data (normalized relative CBV 1.4, sensitivity/specificity 90%:77%; normalized CBF 1.58, sensitivity/specificity 86%:77%). CONCLUSIONS: By means of DSC-MR imaging data obtained after a preload of contrast agent, substantial consistency resulted across sites for brain tumor perfusion metrics with a common threshold discoverable for distinguishing low- from high-grade tumors.
American Journal of Neuroradiology
Digital Object Identifier (DOI)
Schmainda, K. M.; Prah, M. A.; Rand, S. D.; Liu, Y.; Logan, B.; Muzi, M.; Rane, S. D.; Da, X.; Yen, Y. F.; Kalpathy-Cramer, J.; Chenevert, T. L.; Hoff, B.; Ross, B.; Cao, Y.; Aryal, M. P.; Erickson, B.; Korfiatis, P.; Dondlinger, T.; Bell, L.; Hu, L.; Kinahan, P. E.; and Quarles, C. C., "Multisite Concordance Of Dsc-Mri Analysis For Brain Tumors: Results Of A National Cancer Institute Quantitative Imaging Network Collaborative Project" (2018). Neurobiology. 353.