Development of a multi-layer quality assurance program to evaluate the uncertainty of deformable dose accumulation in adaptive radiotherapy

被引:6
|
作者
Zhong, Hualiang [1 ,2 ]
Garcia-Alvarez, Juan A. [1 ]
Kainz, Kristofer [1 ]
Tai, An [1 ]
Ahunbay, Ergun [1 ]
Erickson, Beth [1 ]
Schultz, Christopher J. [1 ]
Li, X. Allen [1 ]
机构
[1] Med Coll Wisconsin, Dept Radiat Oncol, Milwaukee, WI USA
[2] Med Coll Wisconsin, Dept Radiat Oncol, Milwaukee, WI 53226 USA
关键词
adaptive radiotherapy; deformable image registration; dose accumulation; quality assurance; IMAGE REGISTRATION; INVERSE-CONSISTENCY; ALGORITHMS;
D O I
10.1002/mp.16137
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
PurposeDeformable 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. MethodsA 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. ResultsDIRs 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. ConclusionsA 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.
引用
收藏
页码:1766 / 1778
页数:13
相关论文
共 50 条
  • [1] Development of a Multi-Layer Quality Assurance System for Adaptive Radiotherapy
    Zhong, H.
    Kainz, K.
    Li, X.
    MEDICAL PHYSICS, 2021, 48 (06)
  • [2] Deformable dose accumulation is required for adaptive radiotherapy practice
    Zhong, Hualiang
    Pursley, Jennifer M.
    Rong, Yi
    JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS, 2024, 25 (08):
  • [3] Development of a Quality Assurance Process for Dose Accumulation in a CT-Guided Online Adaptive Radiotherapy System
    Maraghechi, B.
    Lam, D.
    Mazur, T.
    Hugo, G.
    Cai, B.
    MEDICAL PHYSICS, 2021, 48 (06)
  • [4] Development of a deformable dosimetric phantom to verify dose accumulation algorithms for adaptive radiotherapy
    Zhong, Hualiang
    Adams, Jeffrey
    Glide-Hurst, Carri
    Zhang, Hualin
    Li, Haisen
    Chetty, Indrin J.
    JOURNAL OF MEDICAL PHYSICS, 2016, 41 (02) : 106 - 114
  • [5] A Multi-Layer Auto-Segmentation Quality Assurance and Correction Pipeline for MR-Guided Adaptive Radiotherapy
    Zhang, Y.
    Amjad, A.
    Ding, J.
    Dang, N. P.
    Sarosiek, C.
    Li, A.
    INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, 2022, 114 (03): : S162 - S162
  • [6] Robust quality assurance criteria for deformable image registration for adaptive radiotherapy
    Bosma, L.
    Zachiu, C.
    de Senneville, B. Denis
    Raaymakers, B.
    Ries, M.
    RADIOTHERAPY AND ONCOLOGY, 2021, 161 : S323 - S324
  • [7] An uncertainty metric to evaluate deformation vector fields for dose accumulation in radiotherapy
    Takemura, Akihiro
    Nagano, Akira
    Kojima, Hironori
    Ikeda, Tomohiro
    Yokoyama, Noriomi
    Tsukamoto, Kosuke
    Noto, Kimiya
    Isomura, Naoki
    Ueda, Shinichi
    Kawashima, Hiroki
    PHYSICS & IMAGING IN RADIATION ONCOLOGY, 2018, 6 : 77 - 82
  • [8] Deep learning based uncertainty prediction of deformable image registration for contour propagation and dose accumulation in online adaptive radiotherapy
    Smolders, A.
    Lomax, A.
    Weber, D. C.
    Albertini, F.
    PHYSICS IN MEDICINE AND BIOLOGY, 2023, 68 (24):
  • [9] On the Utilization of a Pseudo-Inverse Consistency Metric to Evaluate Deformable Dose Accumulation Error for MRI-Guide Adaptive Radiotherapy
    Zhong, H.
    Garcia-Alvarez, J.
    Kainz, K.
    Li, X.
    MEDICAL PHYSICS, 2022, 49 (06) : E281 - E281
  • [10] Two Quality Assurance Metrics for Deformable Image Registration-Based Dose Accumulation
    Kainz, K.
    Zhong, H.
    Tai, A.
    Ahunbay, E. E.
    Li, A.
    INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, 2020, 108 (03): : E275 - E276