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Delivered Dose Calculation Using PCA Motion Modeling and ESAPI

N K. Mahadeo1,3,4*, W Cai2 , M Lafreniere1,3,4 , J Rottmann1,3,4 , C Williams1,3,4, (1) Brigham and Women's Hospital, (2) Memorial Sloan Kettering Cancer Center, West Harrison, New York, (3) Dana Farber Cancer Institute, (4) Harvard Medical School

Presentations

(Sunday, 7/29/2018) 2:05 PM - 3:00 PM

Room: Karl Dean Ballroom C

Purpose: To develop a framework for calculating delivered dose in patients with respiratory motion by combining principal component analysis (PCA) based motion modeling and automated fast dose calculation with the Eclipse Scripting API (ESAPI).

Methods: A PCA-based motion model was built based on deformable image registration of a patient’s 4DCT, and was used to reconstruct 3D images during treatment from 2D x-ray projections. The delivered dose was calculated by using ESAPI to compute dose on reconstructed 3D images at each time interval, and deforming and accumulating the dose on a reference CT image. The performance of the pipeline was assessed using digital XCAT phantoms and clinically acquired patient data. For the XCAT phantoms, the accumulated dose on the reconstructed volumes was compared with the accumulated dose on ground truth volumes to assess the validity of the dose calculation algorithm. The speed and accuracy of the proposed method was compared with a previous Monte-Carlo (MC) based pipeline.

Results: Examination of the γ index showed that 3D dose distributions computed using AAA and MC was 98.3% for 3% DD and 3mm DTA. The 95% volume dose for the tumor (D95) was 54.6Gy for the ground truth, 53.1Gy for the reconstructed volume and 56.0Gy for the 4DCT. The average time for computing dose on each 3D volume of dimension 256X256X140 using Eclipse V.13 (Varian Medical Systems) was 33.84s per plan while the time to compute dose using MC was approximately 30 minutes per field on comparable computers.

Conclusion: The proposed approach presents a fast, fully-automated pipeline for delivered dose computation using motion model-based reconstruction. This pipeline has comparable accuracy to doses calculated with Monte Carlo methods on ground-truth phantoms, and demonstrates a potentially clinically viable solution for motion model-based delivered dose assessment.

Funding Support, Disclosures, and Conflict of Interest: Research funded by Varian Medical Systems.

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