Fifty-seventh annual meeting of the American association of physicists in medicine
SU-F-303-12: Implementation of MR-Only Simulation for Brain Cancer: A Virtual Clinical Trial
To perform a retrospective virtual clinical trial using an MR-only workflow for a variety of brain cancer cases by incorporating novel imaging sequences, tissue segmentation using phase images, and an innovative synthetic CT (synCT) solution.
Ten patients (16 lesions) were evaluated using a 1.0T MR-SIM including UTE-DIXON imaging (TE = 0.144/3.4/6.9ms). Bone-enhanced images were generated from DIXON-water/fat and inverted UTE. Automated air segmentation was performed using unwrapped UTE phase maps. Segmentation accuracy was assessed by calculating intersection and Dice similarity coefficients (DSC) using CT-SIM as ground truth. SynCTs were generated using voxel-based weighted summation incorporating T2, FLAIR, UTE1, and bone-enhanced images. Mean absolute error (MAE) characterized HU differences between synCT and CT-SIM. Dose was recalculated on synCTs; differences were quantified using planar gamma analysis (2%/2 mm dose difference/distance to agreement) at isocenter. Digitally reconstructed radiographs (DRRs) were compared.
On average, air maps intersected 80.8 ±5.5% (range: 71.8–88.8%) between MR-SIM and CT-SIM yielding DSCs of 0.78 ± 0.04 (range: 0.70–0.83). Whole-brain MAE between synCT and CT-SIM was 160.7±8.8 HU, with the largest uncertainty arising from bone (MAE = 423.3±33.2 HU). Gamma analysis revealed pass rates of 99.4 ± 0.04% between synCT and CT-SIM for the cohort. Dose volume histogram analysis revealed that synCT tended to yield slightly higher doses. Organs at risk such as the chiasm and optic nerves were most sensitive due to their proximities to air/bone interfaces. DRRs generated via synCT and CT-SIM were within clinical tolerances.
Our approach for MR-only simulation for brain cancer treatment planning yielded clinically acceptable results relative to the CT-based benchmark. While slight dose differences were observed, reoptimization of treatment plans and improved image registration can address this limitation. Future work will incorporate automated registration between setup images (cone-beam CT and kilovoltage images) for synCT and CT-SIM.
Submitting institution holds research agreements with Philips HealthCare, Best, Netherlands and Varian Medical Systems, Palo Alto, CA. Research partially sponsored via an Internal Mentored Research Grant.