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He Y, Cazoulat G, Wu C, Svensson S, Almodovar-Abreu L, Rigaud B, McCollum E, Peterson C, Wooten Z, Rhee DJ, Balter P, Pollard-Larkin J, Cardenas C, Court L, Liao Z, Mohan R, Brock K. Quantifying the Effect of 4-Dimensional Computed Tomography-Based Deformable Dose Accumulation on Representing Radiation Damage for Patients with Locally Advanced Non-Small Cell Lung Cancer Treated with Standard-Fractionated Intensity-Modulated Radiation Therapy. Int J Radiat Oncol Biol Phys 2024; 118:231-241. [PMID: 37552151 DOI: 10.1016/j.ijrobp.2023.07.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 06/04/2023] [Accepted: 07/14/2023] [Indexed: 08/09/2023]
Abstract
PURPOSE The aim of this study was to investigate the dosimetric and clinical effects of 4-dimensional computed tomography (4DCT)-based longitudinal dose accumulation in patients with locally advanced non-small cell lung cancer treated with standard-fractionated intensity-modulated radiation therapy (IMRT). METHODS AND MATERIALS Sixty-seven patients were retrospectively selected from a randomized clinical trial. Their original IMRT plan, planning and verification 4DCTs, and ∼4-month posttreatment follow-up CTs were imported into a commercial treatment planning system. Two deformable image registration algorithms were implemented for dose accumulation, and their accuracies were assessed. The planned and accumulated doses computed using average-intensity images or phase images were compared. At the organ level, mean lung dose and normal-tissue complication probability (NTCP) for grade ≥2 radiation pneumonitis were compared. At the region level, mean dose in lung subsections and the volumetric overlap between isodose intervals were compared. At the voxel level, the accuracy in estimating the delivered dose was compared by evaluating the fit of a dose versus radiographic image density change (IDC) model. The dose-IDC model fit was also compared for subcohorts based on the magnitude of NTCP difference (|ΔNTCP|) between planned and accumulated doses. RESULTS Deformable image registration accuracy was quantified, and the uncertainty was considered for the voxel-level analysis. Compared with planned doses, accumulated doses on average resulted in <1-Gy lung dose increase and <2% NTCP increase (up to 8.2 Gy and 18.8% for a patient, respectively). Volumetric overlap of isodose intervals between the planned and accumulated dose distributions ranged from 0.01 to 0.93. Voxel-level dose-IDC models demonstrated a fit improvement from planned dose to accumulated dose (pseudo-R2 increased 0.0023) and a further improvement for patients with ≥2% |ΔNTCP| versus for patients with <2% |ΔNTCP|. CONCLUSIONS With a relatively large cohort, robust image registrations, multilevel metric comparisons, and radiographic image-based evidence, we demonstrated that dose accumulation more accurately represents the delivered dose and can be especially beneficial for patients with greater longitudinal response.
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Affiliation(s)
- Yulun He
- Graduate School of Biomedical Sciences, University of Texas MD Anderson Cancer Center UTHealth Houston, Houston, Texas; Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, Texas.
| | - Guillaume Cazoulat
- Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Carol Wu
- Department of Diagnostic Radiology, University of Texas MD Anderson Cancer Center, Houston, Texas
| | | | | | - Bastien Rigaud
- Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Emma McCollum
- Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Christine Peterson
- Department of Biostatistics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Zachary Wooten
- Department of Statistics, Rice University, Houston, Texas
| | - Dong Joo Rhee
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Peter Balter
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Julianne Pollard-Larkin
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Carlos Cardenas
- Department of Radiation Oncology, University of Alabama at Birmingham, Birmingham, Alabama
| | - Laurence Court
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Zhongxing Liao
- Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Radhe Mohan
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Kristy Brock
- Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
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Kim WC, Won YK, Lee SM, Heo NH, Yeo SG, Chang AR, Bae SH, Kim JS, Yoo ID, Hong SP, Min CK, Jo IY, Kim ES. Evaluating the Necessity of Adaptive RT and the Role of Deformable Image Registration in Lung Cancer with Different Pathologic Classifications. Diagnostics (Basel) 2023; 13:2956. [PMID: 37761323 PMCID: PMC10527903 DOI: 10.3390/diagnostics13182956] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 09/07/2023] [Accepted: 09/09/2023] [Indexed: 09/29/2023] Open
Abstract
BACKGROUND This study aimed to analyze differential radiotherapy (RT) responses according to the pathological type of lung cancer to see the possibility of applying adaptive radiotherapy (ART). METHODS ART planning with resampled-computed tomography was conducted for a total of 30 patients (20 non-small-cell lung cancer patients and 10 small-cell lung cancer patients) using a deformable image registration technique to reveal gross tumor volume (GTV) changes according to the duration of RT. RESULTS The small-cell lung cancer group demonstrated an average GTV reduction of 20.95% after the first week of initial treatment (p = 0.001), whereas the adenocarcinoma and squamous cell carcinoma groups showed an average volume reduction of 20.47% (p = 0.015) and 12.68% in the second week. The application of ART according to the timing of GTV reduction has been shown to affect changes in radiation dose irradiated to normal tissues. This suggests that ART applications may have to be different depending on pathological differences in lung cancer. CONCLUSION Through these results, the present study proposes the possibility of personalized treatment options for individual patients by individualizing ART based on specific radiation responses by pathologic types of lung cancer.
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Affiliation(s)
- Woo Chul Kim
- Department of Radiation Oncology, Division of Medical Physics, Soonchunhyang University Cheonan Hospital, 31, Suncheonhyang 6-gil, Dongnam-gu, Cheonan 31151, Republic of Korea; (W.C.K.); (C.K.M.)
- Department of Radiation Oncology, Soonchunhyang University Cheonan Hospital, 31, Suncheonhyang 6-gil, Dongnam-gu, Cheonan 31151, Republic of Korea;
| | - Yong Kyun Won
- Department of Radiation Oncology, Soonchunhyang University Cheonan Hospital, 31, Suncheonhyang 6-gil, Dongnam-gu, Cheonan 31151, Republic of Korea;
| | - Sang Mi Lee
- Department of Nuclear Medicine, Soonchunhyang University Cheonan Hospital, 31, Suncheonhyang 6-gil, Dongnam-gu, Cheonan 31151, Republic of Korea; (S.M.L.); (I.D.Y.); (S.-p.H.)
| | - Nam Hun Heo
- Clinical Trial Center, Soonchunhyang University Cheonan Hospital, 31, Suncheonhyang 6-gil, Dongnam-gu, Cheonan 31151, Republic of Korea;
| | - Seung-Gu Yeo
- Department of Radiation Oncology, Soonchunhyang University Bucheon Hospital, 170, Jomaru-ro, Bucheon 14584, Republic of Korea; (S.-G.Y.); (S.H.B.)
| | - Ah Ram Chang
- Department of Radiation Oncology, Soonchunhyang University Seoul Hospital, 59, Daesagwan-ro, Yongsan-gu, Seoul 04401, Republic of Korea; (A.R.C.); (J.S.K.)
| | - Sun Hyun Bae
- Department of Radiation Oncology, Soonchunhyang University Bucheon Hospital, 170, Jomaru-ro, Bucheon 14584, Republic of Korea; (S.-G.Y.); (S.H.B.)
| | - Jae Sik Kim
- Department of Radiation Oncology, Soonchunhyang University Seoul Hospital, 59, Daesagwan-ro, Yongsan-gu, Seoul 04401, Republic of Korea; (A.R.C.); (J.S.K.)
| | - Ik Dong Yoo
- Department of Nuclear Medicine, Soonchunhyang University Cheonan Hospital, 31, Suncheonhyang 6-gil, Dongnam-gu, Cheonan 31151, Republic of Korea; (S.M.L.); (I.D.Y.); (S.-p.H.)
| | - Sun-pyo Hong
- Department of Nuclear Medicine, Soonchunhyang University Cheonan Hospital, 31, Suncheonhyang 6-gil, Dongnam-gu, Cheonan 31151, Republic of Korea; (S.M.L.); (I.D.Y.); (S.-p.H.)
| | - Chul Kee Min
- Department of Radiation Oncology, Division of Medical Physics, Soonchunhyang University Cheonan Hospital, 31, Suncheonhyang 6-gil, Dongnam-gu, Cheonan 31151, Republic of Korea; (W.C.K.); (C.K.M.)
- Department of Radiation Oncology, Soonchunhyang University Cheonan Hospital, 31, Suncheonhyang 6-gil, Dongnam-gu, Cheonan 31151, Republic of Korea;
| | - In Young Jo
- Department of Radiation Oncology, Soonchunhyang University Cheonan Hospital, 31, Suncheonhyang 6-gil, Dongnam-gu, Cheonan 31151, Republic of Korea;
| | - Eun Seog Kim
- Department of Radiation Oncology, Soonchunhyang University Cheonan Hospital, 31, Suncheonhyang 6-gil, Dongnam-gu, Cheonan 31151, Republic of Korea;
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He Y, Anderson BM, Cazoulat G, Rigaud B, Almodovar-Abreu L, Pollard-Larkin J, Balter P, Liao Z, Mohan R, Odisio B, Svensson S, Brock KK. Optimization of mesh generation for geometric accuracy, robustness, and efficiency of biomechanical-model-based deformable image registration. Med Phys 2023; 50:323-329. [PMID: 35978544 DOI: 10.1002/mp.15939] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 08/11/2022] [Accepted: 08/11/2022] [Indexed: 01/25/2023] Open
Abstract
BACKGROUND Successful generation of biomechanical-model-based deformable image registration (BM-DIR) relies on user-defined parameters that dictate surface mesh quality. The trial-and-error process to determine the optimal parameters can be labor-intensive and hinder DIR efficiency and clinical workflow. PURPOSE To identify optimal parameters in surface mesh generation as boundary conditions for a BM-DIR in longitudinal liver and lung CT images to facilitate streamlined image registration processes. METHODS Contrast-enhanced CT images of 29 colorectal liver cancer patients and end-exhale four-dimensional CT images of 26 locally advanced non-small cell lung cancer patients were collected. Different combinations of parameters that determine the triangle mesh quality (voxel side length and triangle edge length) were investigated. The quality of DIRs generated using these parameters was evaluated with metrics for geometric accuracy, robustness, and efficiency. Metrics for geometric accuracy included target registration error (TRE) of internal vessel bifurcations, dice similar coefficient (DSC), mean distance to agreement (MDA), Hausdorff distance (HD) for organ contours, and number of vertices in the triangle mesh. American Association of Physicists in Medicine Task Group 132 was used to ensure parameters met TRE, DSC, MDA recommendations before the comparison among the parameters. Robustness was evaluated as the success rate of DIR generation, and efficiency was evaluated as the total time to generate boundary conditions and compute finite element analysis. RESULTS Voxel side length of 0.2 cm and triangle edge length of 3 were found to be the optimal parameters for both liver and lung, with success rate of 1.00 and 0.98 and average DIR computation time of 100 and 143 s, respectively. For this combination, the average TRE, DSC, MDA, and HD were 0.38-0.40, 0.96-0.97, 0.09-0.12, and 0.87-1.17 mm, respectively. CONCLUSION The optimal parameters were found for the analyzed patients. The decision-making process described in this study serves as a recommendation for BM-DIR algorithms to be used for liver and lung. These parameters can facilitate consistence in the evaluation of published studies and more widespread utilization of BM-DIR in clinical practice.
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Affiliation(s)
- Yulun He
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Brian M Anderson
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Guillaume Cazoulat
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Bastien Rigaud
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | | | - Julianne Pollard-Larkin
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Peter Balter
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Zhongxing Liao
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Radhe Mohan
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Bruno Odisio
- Department of Interventional Radiology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | | | - Kristy K Brock
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.,Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
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Dossun C, Niederst C, Noel G, Meyer P. Evaluation of DIR algorithm performance in real patients for radiotherapy treatments: A systematic review of operator-dependent strategies. Phys Med 2022; 101:137-157. [PMID: 36007403 DOI: 10.1016/j.ejmp.2022.08.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Revised: 07/21/2022] [Accepted: 08/16/2022] [Indexed: 11/15/2022] Open
Abstract
PURPOSE The performance of deformable medical image registration (DIR) algorithms has become a major concern. METHODS We aimed to obtain updated information on DIR algorithm performance quantification through a literature review of articles published between 2010 and 2022. We focused only on studies using operator-based methods to treat real patients. The PubMed, Google Scholar and Embase databases were searched following PRISMA guidelines. RESULTS One hundred and seven articles were identified. The mean number of patients and registrations per publication was 20 and 63, respectively. We found 23 different geometric metrics appearing at least twice, and the dosimetric impact of DIR was quantified in 32 articles. Forty-eight different at-risk organs were described, and target volumes were studied in 43 publications. Prostate, head-and-neck and thoracic locations represented more than ¾ of the studied locations. We summarized the type of DIR and the images used, and other key elements. Intra/interobserver variability, threshold values and the correlation between metrics were also discussed. CONCLUSIONS This literature review covers the past decade and should facilitate the implementation of DIR algorithms in clinical practice by providing practical and pertinent information to quantify their performance on real patients.
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Affiliation(s)
- C Dossun
- Department of Radiotherapy, Institut de Cancerologie Strasbourg Europe (ICANS), Strasbourg, France
| | - C Niederst
- Department of Radiotherapy, Institut de Cancerologie Strasbourg Europe (ICANS), Strasbourg, France
| | - G Noel
- Department of Radiotherapy, Institut de Cancerologie Strasbourg Europe (ICANS), Strasbourg, France
| | - P Meyer
- Department of Radiotherapy, Institut de Cancerologie Strasbourg Europe (ICANS), Strasbourg, France; ICUBE, CNRS UMR 7357, Team IMAGES, Strasbourg, France.
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Rammohan N, Randall JW, Yadav P. History of Technological Advancements towards MR-Linac: The Future of Image-Guided Radiotherapy. J Clin Med 2022; 11:jcm11164730. [PMID: 36012969 PMCID: PMC9409689 DOI: 10.3390/jcm11164730] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 07/27/2022] [Accepted: 08/05/2022] [Indexed: 11/16/2022] Open
Abstract
Image-guided radiotherapy (IGRT) enables optimal tumor targeting and sparing of organs-at-risk, which ultimately results in improved outcomes for patients. Magnetic resonance imaging (MRI) revolutionized diagnostic imaging with its superior soft tissue contrast, high spatiotemporal resolution, and freedom from ionizing radiation exposure. Over the past few years there has been burgeoning interest in MR-guided radiotherapy (MRgRT) to overcome current challenges in X-ray-based IGRT, including but not limited to, suboptimal soft tissue contrast, lack of efficient daily adaptation, and incremental exposure to ionizing radiation. In this review, we present an overview of the technologic advancements in IGRT that led to MRI-linear accelerator (MRL) integration. Our report is organized in three parts: (1) a historical timeline tracing the origins of radiotherapy and evolution of IGRT, (2) currently available MRL technology, and (3) future directions and aspirations for MRL applications.
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Park JW, Yea JW, Park J, Oh SA. Setup uncertainties and appropriate setup margins in the head-tilted supine position of whole-brain radiotherapy (WBRT). PLoS One 2022; 17:e0271077. [PMID: 35925916 PMCID: PMC9352041 DOI: 10.1371/journal.pone.0271077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Accepted: 06/22/2022] [Indexed: 11/18/2022] Open
Abstract
Various applications of head-tilting techniques in whole-brain radiotherapy (WBRT) have been introduced. However, a study on the setup uncertainties and margins in head-tilting techniques has not been reported. This study evaluated the setup uncertainties and determined the appropriate planning target volume (PTV) margins for patients treated in the head-tilted supine (ht-SP) and conventional supine position (c-SP) in WBRT. Thirty patients who received WBRT at our institution between October 2020 and May 2021 in the c-SP and ht-SP were investigated. The DUON head mask (60124, Orfit Industries, Wijnegem, Belgium) was used in the c-SP, and a thermoplastic U-Frame Mask (R420U, Klarity Medical & Equipment Co. Ltd., Lan Yu, China) was used in the ht-SP. Daily setup verification using planning computed tomography (CT) and cone-beam CT was corrected for translational (lateral, longitudinal, and vertical) and rotational (yaw) errors. In the c-SP, the means of systematic errors were -0.80, 0.79, and 0.37 mm and random errors were 0.27, 0.54, and 0.39 mm in the lateral, longitudinal, and vertical translational dimensions, respectively. Whereas, for the ht-SP, the means of systematic errors were -0.07, 0.73, and -0.63 mm, and random errors were 0.75, 1.39, 1.02 mm in the lateral, longitudinal, and vertical translational dimensions, respectively. The PTV margins were calculated using Stroom et al.’s [2Σ+0.7σ] and van Herk et al.’s recipe [2.5Σ+0.7σ]. Appropriate PTV margins with van Herk et al.’s recipe in WBRT were <2 mm and 1.5° in the c-SP and <3 mm and 2° in the ht-SP in the translational and rotational directions, respectively. Although the head tilt in the supine position requires more margin, it can be applied as a sufficiently stable and effective position in radiotherapy.
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Affiliation(s)
- Jae Won Park
- Department of Radiation Oncology, Yeungnam University Medical Center, Daegu, Korea
- Department of Radiation Oncology, Yeungnam University College of Medicine, Daegu, Korea
| | - Ji Woon Yea
- Department of Radiation Oncology, Yeungnam University Medical Center, Daegu, Korea
- Department of Radiation Oncology, Yeungnam University College of Medicine, Daegu, Korea
| | - Jaehyeon Park
- Department of Radiation Oncology, Yeungnam University Medical Center, Daegu, Korea
- Department of Radiation Oncology, Yeungnam University College of Medicine, Daegu, Korea
| | - Se An Oh
- Department of Radiation Oncology, Yeungnam University Medical Center, Daegu, Korea
- Department of Radiation Oncology, Yeungnam University College of Medicine, Daegu, Korea
- * E-mail:
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He Y, Cazoulat G, Wu C, Peterson C, McCulloch M, Anderson B, Pollard‐Larkin J, Balter P, Liao Z, Mohan R, Brock K. Geometric and dosimetric accuracy of deformable image registration between average-intensity images for 4DCT-based adaptive radiotherapy for non-small cell lung cancer. J Appl Clin Med Phys 2021; 22:156-167. [PMID: 34310827 PMCID: PMC8364273 DOI: 10.1002/acm2.13341] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Revised: 04/26/2021] [Accepted: 06/09/2021] [Indexed: 01/11/2023] Open
Abstract
PURPOSE Re-planning for four-dimensional computed tomography (4DCT)-based lung adaptive radiotherapy commonly requires deformable dose mapping between the planning average-intensity image (AVG) and the newly acquired AVG. However, such AVG-AVG deformable image registration (DIR) lacks accuracy assessment. The current work quantified and compared geometric accuracies of AVG-AVG DIR and corresponding phase-phase DIRs, and subsequently investigated the clinical impact of such AVG-AVG DIR on deformable dose mapping. METHODS AND MATERIALS Hybrid intensity-based AVG-AVG and phase-phase DIRs were performed between the planning and mid-treatment 4DCTs of 28 non-small cell lung cancer patients. An automated landmark identification algorithm detected vessel bifurcation pairs in both lungs. Target registration error (TRE) of these landmark pairs was calculated for both DIR types. The correlation between TRE and respiratory-induced landmark motion in the planning 4DCT was analyzed. Global and local dose metrics were used to assess the clinical implications of AVG-AVG deformable dose mapping with both DIR types. RESULTS TRE of AVG-AVG and phase-phase DIRs averaged 3.2 ± 1.0 and 2.6 ± 0.8 mm respectively (p < 0.001). Using AVG-AVG DIR, TREs for landmarks with <10 mm motion averaged 2.9 ± 2.0 mm, compared to 3.1 ± 1.9 mm for the remaining landmarks (p < 0.01). Comparatively, no significant difference was demonstrated for phase-phase DIRs. Dosimetrically, no significant difference in global dose metrics was observed between doses mapped with AVG-AVG DIR and the phase-phase DIR, but a positive linear relationship existed (p = 0.04) between the TRE of AVG-AVG DIR and local dose difference. CONCLUSIONS When the region of interest experiences <10 mm respiratory-induced motion, AVG-AVG DIR may provide sufficient geometric accuracy; conversely, extra attention is warranted, and phase-phase DIR is recommended. Dosimetrically, the differences in geometric accuracy between AVG-AVG and phase-phase DIRs did not impact global lung-based metrics. However, as more localized dose metrics are needed for toxicity assessment, phase-phase DIR may be required as its lower mean TRE improved voxel-based dosimetry.
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Affiliation(s)
- Yulun He
- Department of Imaging PhysicsThe University of Texas MD Anderson Cancer CenterHoustonTXUSA
| | - Guillaume Cazoulat
- Department of Imaging PhysicsThe University of Texas MD Anderson Cancer CenterHoustonTXUSA
| | - Carol Wu
- Department of Diagnostic RadiologyThe University of Texas MD Anderson Cancer CenterHoustonTXUSA
| | - Christine Peterson
- Department of BiostatisticsThe University of Texas MD Anderson Cancer CenterHoustonTXUSA
| | - Molly McCulloch
- Department of Imaging PhysicsThe University of Texas MD Anderson Cancer CenterHoustonTXUSA
| | - Brian Anderson
- Department of Imaging PhysicsThe University of Texas MD Anderson Cancer CenterHoustonTXUSA
| | - Julianne Pollard‐Larkin
- Department of Radiation PhysicsThe University of Texas MD Anderson Cancer CenterHoustonTXUSA
| | - Peter Balter
- Department of Radiation PhysicsThe University of Texas MD Anderson Cancer CenterHoustonTXUSA
| | - Zhongxing Liao
- Department of Radiation OncologyThe University of Texas MD Anderson Cancer CenterHoustonTXUSA
| | - Radhe Mohan
- Department of Radiation PhysicsThe University of Texas MD Anderson Cancer CenterHoustonTXUSA
| | - Kristy Brock
- Department of Imaging PhysicsThe University of Texas MD Anderson Cancer CenterHoustonTXUSA
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