Development of a multi-layer quality assurance program to evaluate the uncertainty of deformable dose accumulation in adaptive radiotherapy. Med Phys 2023 Mar;50(3):1766-1778
Date
11/27/2022Pubmed ID
36434751Pubmed Central ID
PMC10033340DOI
10.1002/mp.16137Scopus ID
2-s2.0-85144053188 (requires institutional sign-in at Scopus site) 6 CitationsAbstract
PURPOSE: Deformable dose accumulation (DDA) has uncertainties which impede the implementation of DDA-based adaptive radiotherapy (ART) in clinic. The purpose of this study is to develop a multi-layer quality assurance (MLQA) program to evaluate uncertainties in DDA.
METHODS: A computer program is developed to generate a pseudo-inverse displacement vector field (DVF) for each deformable image registration (DIR) performed in Accuray's PreciseART. The pseudo-inverse DVF is first used to calculate a pseudo-inverse consistency error (PICE) and then implemented in an energy and mass congruent mapping (EMCM) method to reconstruct a deformed dose. The PICE is taken as a metric to estimate DIR uncertainties. A pseudo-inverse dose agreement rate (PIDAR) is used to evaluate the consequence of the DIR uncertainties in DDA and the principle of energy conservation is used to validate the integrity of dose mappings. The developed MLQA program was tested using the data collected from five representative cancer patients treated with tomotherapy.
RESULTS: DIRs were performed in PreciseART to generate primary DVFs for the five patients. The fidelity index and PICE of these DVFs on average are equal to 0.028 mm and 0.169 mm, respectively. With the criteria of 3 mm/3% and 5 mm/5%, the PIDARs of the PreciseART-reconstructed doses are 73.9 ± 4.4% and 87.2 ± 3.3%, respectively. The PreciseART and EMCM-based dose reconstructions have their deposited energy changed by 5.6 ± 3.9% and 2.6 ± 1.5% in five GTVs, and by 9.2 ± 7.8% and 4.7 ± 3.6% in 30 OARs, respectively.
CONCLUSIONS: A pseudo-inverse map-based EMCM program has been developed to evaluate DIR and dose mapping uncertainties. This program could also be used as a sanity check tool for DDA-based ART.
Author List
Zhong H, Garcia-Alvarez JA, Kainz K, Tai A, Ahunbay E, Erickson B, Schultz CJ, Li XAAuthors
Ergun Ahunbay PhD Professor in the Radiation Oncology department at Medical College of WisconsinBeth A. Erickson MD Professor in the Radiation Oncology department at Medical College of Wisconsin
Juan A. Garcia Alvarez PhD Medical Physicist Assistant in the Radiation Oncology department at Medical College of Wisconsin
Kristofer Kainz PhD Associate Professor in the Radiation Oncology department at Medical College of Wisconsin
Christopher J. Schultz MD Professor in the Radiation Oncology department at Medical College of Wisconsin
An Tai PhD Associate Professor in the Radiation Oncology department at Medical College of Wisconsin
Hualiang Zhong PhD Associate Professor in the Radiation Oncology department at Medical College of Wisconsin
MESH terms used to index this publication - Major topics in bold
AlgorithmsHumans
Image Processing, Computer-Assisted
Neoplasms
Radiotherapy Dosage
Radiotherapy Planning, Computer-Assisted
Radiotherapy, Intensity-Modulated
Software
Uncertainty