Optimization Of Acquisition And Analysis Methods For Clinical Dynamic Susceptibility Contrast Mri Using A Population-Based Digital Reference Object
BACKGROUND AND PURPOSE: The accuracy of DSC-MR imaging CBV maps in glioblastoma depends on acquisition and analysis protocols. Multisite protocol heterogeneity has challenged standardization initiatives due to the difficulties of in vivo validation. This study sought to compare the accuracy of routinely used protocols using a digital reference object. MATERIALSANDMETHODS: The digital reference object consisted of approximately 10,000 simulated voxels recapitulating typical signal heterogeneity encountered in vivo. The influence of acquisition and postprocessing methods on CBV reliability was evaluated across 6912 parameter combinations, including contrast agent dosing schemes, pulse sequence parameters, field strengths, and postprocessing methods. Accuracy and precision were assessed using the concordance correlation coefficient and coefficient of variation. RESULTS: Across all parameter space, the optimal protocol included full-dose contrast agent preload and bolus, intermediate (60Â°) flip angle, 30-ms TE, and postprocessing with a leakage-correction algorithm (concordance correlation coefficient = 0.97, coefficient of variation= 6.6%). Protocols with no preload or fractional dose preload and bolus using these acquisition parameters were generally less robust. However, a protocol with no preload, full-dose bolus, and low (30Â°) flip angle performed very well (concordance correlation coefficient= 0.93, coefficient of variation=8.7% at 1.5T and concordance correlation coefficient=0.92, coefficient of variation=8.2% at 3T). CONCLUSIONS: Schemes with full-dose preload and bolus maximize CBV accuracy and reduce variability, which could enable smaller sample sizes and more reliable detection of CBV changes in clinical trials. When a lower total contrast agent dose is desired, use of a low flip angle, no preload, and full-dose bolus protocol may provide an attractive alternative.
American Journal of Neuroradiology
Digital Object Identifier (DOI)
Semmineh, N. B.; Bell, L. C.; Stokes, A. M.; Hu, L. S.; Boxerman, J. L.; and Quarles, C. C., "Optimization Of Acquisition And Analysis Methods For Clinical Dynamic Susceptibility Contrast Mri Using A Population-Based Digital Reference Object" (2018). Translational Neuroscience. 354.