Room: Karl Dean Ballroom C
Purpose: Quantitative assessment of treatment response is critical for risk-adaptive therapies. The Quantitative Imaging Biomarkers Alliance (QIBA) has established diffusion weighted imaging (DWI) profiles that ensure accurate, reproducible, quantitative apparent diffusion coefficient (ADC) estimates. However, MR simulation is performed with alternative RF coil, pulse sequences, and patient setups compared to those used to establish the QIBA profile. We demonstrate here differences in ADC estimates obtained with optimized MR simulation protocols compared with the QIBA profile.
Methods: The QIBA DWI phantom (High Precision Devices, Inc) was prepared and maintained at 0 Â°C during imaging on a Siemens 3T. DW images were acquired using diagnostic and flexible phased-array RF coils. For each coil setup, DW images were acquired using the QIBA profile (single-shot DW-EPI sequence) and a RESOLVE sequence. ADC estimates were averaged and compared against known phantom values, with a percentage error being used to measure ADC accuracy. Distortion in ADC, presumably due to gradient nonlinearities, was quantified by averaging the percentage difference between pairs or triplets of vials with the same ADC values, arranged in spatial varying locations in the phantom.
Results: ADC estimates differed dramatically below 600 mm/s2. The absolute mean percentage error in the diagnostic setup was found to be 2.68% and 3.99%, and 3.10% and 12.50% in the MR simulation setup for the QIBA profile and RESOLVE sequence, respectively. In the diagnostic setup, the percentage variation at similar ADC values were 3.08%, and 3.00%, while in MR simulation, values were 4.23% and 6.20% for the QIBA profile and RESOVLE sequence, respectively.
Conclusion: These results suggest that compromises made to set up patients in treatment position and control geometric distortions during MR simulation can challege ADC accuracy, particularly at lower diffusion coefficients. Care should be taken when MR simulation ADC estimates are used as baselines for response assessment.
Funding Support, Disclosures, and Conflict of Interest: This work was partially supported by Siemens Healthineers.