Summary
The standardization and broad-scale integration of DSC-MRI has been confounded by a lack of consensus on DSC-MRI methodology for preventing potential CBV inaccuracies, including the choice of acquisition protocols and post-processing algorithms. Users can use the DRO to investigate the influence of DSC-MRI acquisition and post-processing methods on CBV accuracy, and determination of the impact of DSC-MRI methodology choices on sample size requirements and the assessment of treatment response in clinical glioblastoma trials. The DRO datasets are also being used as part of the QIN-challenge titled “DSC-MRI DRO Challenge” . If approved for TCIA inclusion, the archive and this will be the primary access point the institutes use to download the their site-specific DROs. To facilitate this effort, a range of DSC-MRI DROs is available for download from The Cancer Imaging Archive (www.cancerimagingarchive.net) under the collection name [Barrow-DRO].
Acquisition Protocol:
A dynamic susceptibility contrast (DSC) digital reference object (DRO) was developed in order validate image acquisition and analysis methods for accurately measuring perfusion parameters in glioblastomas. A validated computational approach for modeling DSC-MRI data served as the basis of the DRO, which is expanded using physiological and kinetic parameters derived from in vivo data and unique voxel-wise 3D tissue structures. To achieve DSC-MRI signals representative of the temporal characteristics, magnitude and distribution of contrast agent-induced T1 and T2* changes observed across multiple glioblastomas, the DRO’s input parameters were trained using DSC-MRI data from 23 glioblastomas (> 40,000 voxels). The DRO’s ability to produce reliable signals for combinations of pulse sequence parameters and contrast agent dosing schemes unlike those in the training dataset was validated by comparison to in vivo dual-echo DSC-MRI data acquired in a separate cohort of patients with glioblastomas. Each DRO (e.g. ones computed for a specific set of acquisition and contrast agent dosing schemes) contains ~10,000 unique voxels.
Acknowledgements
We would like to acknowledge the individuals and institutions that have provided data for this collection:
Hospital/Institution Name city, state, country - Special thanks to First Last Names, degree PhD, MD, etc from the Department of xxxxxx, Additional Names from same location.
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