GBM-DSC-MRI-DRO

Summary

The standardization of dynamic susceptibility contrast (DSC)-magnetic resonance imaging (MRI) have been confounded by a lack of consensus on DSC-MRI methodology for preventing potential relative cerebral blood volume (CBV) inaccuracies, including the choice of acquisition protocols and postprocessing algorithms. Therefore, a digital reference object (DRO) was developed using physiological and kinetic parameters derived from a patient database, unique voxel-wise 3-dimensional tissue structures, and a validated MRI signal computational approach. The primary, intended use of the DRO is to validate image acquisition and analysis methods for accurately measuring relative cerebral blood volume in glioblastomas [1,2]. The DRO datasets have also been used as part of the QIN-challenge titled “DSC-DRO Challenge” to evaluate multisite rCBV consistency [3], and for systematic assessment of multi-echo DSC-MRI [4].

DRO development

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 across combinations of pulse sequence parameters and contrast agent dosing schemes unlike those in the training data set was validated by comparison with in vivo dual-echo DSC-MRI data acquired in a separate cohort of patients with glioblastomas. To achieve an excellent agreement between the DRO and in vivo data the training and validation process required a DRO consisting of 10 000 unique voxels.

Application

Users can use the DRO to investigate the influence of DSC-MRI acquisition and post-processing methods on CBV accuracy and as a benchmark for perfusion analysis algorithms.

References

[1]      Semmineh NB, Stokes AM, Bell LC, Boxerman JL, Quarles CC. A Population-Based Digital Reference Object (DRO) for Optimizing Dynamic Susceptibility Contrast (DSC)-MRI Methods for Clinical Trials. Tomography 2017;3:41–9. doi:10.18383/j.tom.2016.00286.

[2]      Semmineh NB, Bell LC, Stokes AM, Hu LS, Boxerman JL, Quarles CC. Optimization of acquisition and analysis methods for clinical dynamic susceptibility contrast MRI using a population-based digital reference object. Am J Neuroradiol 2018. doi:10.3174/ajnr.A5827.

[3]      Bell LC, Semmineh N, An H, Eldeniz C, Wahl R, Schmainda KM, et al. Evaluating Multisite rCBV Consistency from DSC-MRI Imaging Protocols and Postprocessing Software Across the NCI Quantitative Imaging Network Sites Using a Digital Reference Object (DRO). Tomogr (Ann Arbor, Mich) 2019. doi:10.18383/j.tom.2018.00041.

[4]      Stokes AM, Semmineh NB, Nespodzany A, Bell LC, Quarles CC. Systematic assessment of multi-echo dynamic susceptibility contrast MRI using a digital reference object. Magn Reson Med 2020. doi:10.1002/mrm.27914.