SU‐D‐207A‐07: The Effects of Inter‐Cycle Respiratory Motion Variation On Dose Accumulation in Single Fraction MR‐Guided SBRT Treatment of Renal Cell Carcinoma

Abstract

Purpose:To assess the dose deposition in simulated single‐fraction MR‐Linac treatments of renal cell carcinoma, when inter‐cycle respiratory motion variation is taken into account using online MRI.Methods:Three motion characterization methods, with increasing complexity, were compared to evaluate the effect of inter‐cycle motion variation and drifts on the accumulated dose for an SBRT kidney MR‐Linac treatment: 1) STATIC, in which static anatomy was assumed, 2) AVG‐RESP, in which 4D‐MRI phase‐volumes were time‐weighted, based on the respiratory phase and 3) PCA, in which 3D volumes were generated using a PCA‐model, enabling the detection of inter‐cycle variations and drifts. An experimental ITV‐based kidney treatment was simulated in a 1.5T magnetic field on three volunteer datasets. For each volunteer a retrospectively sorted 4D‐MRI (ten respiratory phases) and fast 2D cine‐MR images (temporal resolution = 476ms) were acquired to simulate MR‐imaging during radiation. For each method, the high spatio‐temporal resolution 3D volumes were non‐rigidly registered to obtain deformation vector fields (DVFs). Using the DVFs, pseudo‐CTs (generated from the 4D‐MRI) were deformed and the dose was accumulated for the entire treatment. The accuracies of all methods were independently determined using an additional, orthogonal 2D‐MRI slice.Results:Motion was most accurately estimated using the PCA method, which correctly estimated drifts and inter‐cycle variations (RMSE=3.2, 2.2, 1.1mm on average for STATIC, AVG‐RESP and PCA, compared to the 2DMRI slice). Dose‐volume parameters on the ITV showed moderate changes (D99=35.2, 32.5, 33.8Gy for STATIC, AVG‐RESP and PCA). AVG‐RESP showed distinct hot/cold spots outside the ITV margin, which were more distributed for the PCA scenario, since inter‐cycle variations were not modeled by the AVG‐RESP method.Conclusion:Dose differences were observed when inter‐cycle variations were taken into account. The increased inter‐cycle randomness in motion as captured by the PCA model mitigates the local (erroneous) hotspots estimated by the AVG‐RESP method.