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Rossi M, Belotti G, Mainardi L, Baroni G, Cerveri P. Feasibility of proton dosimetry overriding planning CT with daily CBCT elaborated through generative artificial intelligence tools. Comput Assist Surg (Abingdon) 2024; 29:2327981. [PMID: 38468391 DOI: 10.1080/24699322.2024.2327981] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/13/2024] Open
Abstract
Radiotherapy commonly utilizes cone beam computed tomography (CBCT) for patient positioning and treatment monitoring. CBCT is deemed to be secure for patients, making it suitable for the delivery of fractional doses. However, limitations such as a narrow field of view, beam hardening, scattered radiation artifacts, and variability in pixel intensity hinder the direct use of raw CBCT for dose recalculation during treatment. To address this issue, reliable correction techniques are necessary to remove artifacts and remap pixel intensity into Hounsfield Units (HU) values. This study proposes a deep-learning framework for calibrating CBCT images acquired with narrow field of view (FOV) systems and demonstrates its potential use in proton treatment planning updates. Cycle-consistent generative adversarial networks (cGAN) processes raw CBCT to reduce scatter and remap HU. Monte Carlo simulation is used to generate CBCT scans, enabling the possibility to focus solely on the algorithm's ability to reduce artifacts and cupping effects without considering intra-patient longitudinal variability and producing a fair comparison between planning CT (pCT) and calibrated CBCT dosimetry. To showcase the viability of the approach using real-world data, experiments were also conducted using real CBCT. Tests were performed on a publicly available dataset of 40 patients who received ablative radiation therapy for pancreatic cancer. The simulated CBCT calibration led to a difference in proton dosimetry of less than 2%, compared to the planning CT. The potential toxicity effect on the organs at risk decreased from about 50% (uncalibrated) up the 2% (calibrated). The gamma pass rate at 3%/2 mm produced an improvement of about 37% in replicating the prescribed dose before and after calibration (53.78% vs 90.26%). Real data also confirmed this with slightly inferior performances for the same criteria (65.36% vs 87.20%). These results may confirm that generative artificial intelligence brings the use of narrow FOV CBCT scans incrementally closer to clinical translation in proton therapy planning updates.
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Affiliation(s)
- Matteo Rossi
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy
- Laboratory of Innovation in Sleep Medicine, Istituto Auxologico Italiano, Milan, Italy
| | - Gabriele Belotti
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy
| | - Luca Mainardi
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy
| | - Guido Baroni
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy
- Bioengineering Unit, Clinical Department, National Center for Oncological Hadrontherapy (CNAO), Pavia, Italy
| | - Pietro Cerveri
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy
- Laboratory of Innovation in Sleep Medicine, Istituto Auxologico Italiano, Milan, Italy
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Rao S, Sharan K, Chandraguthi SG, Dsouza RN, David LR, Ravichandran S, Mustapha MT, Shettigar D, Uzun B, Kadavigere R, Sukumar S, Ozsahin DU. Advanced Computational Methods for Radiation Dose Optimization in CT. Diagnostics (Basel) 2024; 14:921. [PMID: 38732335 PMCID: PMC11083136 DOI: 10.3390/diagnostics14090921] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2024] [Revised: 04/18/2024] [Accepted: 04/23/2024] [Indexed: 05/13/2024] Open
Abstract
BACKGROUND In planning radiotherapy treatments, computed tomography (CT) has become a crucial tool. CT scans involve exposure to ionizing radiation, which can increase the risk of cancer and other adverse health effects in patients. Ionizing radiation doses for medical exposure must be kept "As Low As Reasonably Achievable". Very few articles on guidelines for radiotherapy-computed tomography scans are available. This paper reviews the current literature on radiation dose optimization based on the effective dose and diagnostic reference level (DRL) for head, neck, and pelvic CT procedures used in radiation therapy planning. This paper explores the strategies used to optimize radiation doses, and high-quality images for diagnosis and treatment planning. METHODS A cross-sectional study was conducted on 300 patients with head, neck, and pelvic region cancer in our institution. The DRL, effective dose, volumetric CT dose index (CTDIvol), and dose-length product (DLP) for the present and optimized protocol were calculated. DRLs were proposed for the DLP using the 75th percentile of the distribution. The DLP is a measure of the radiation dose received by a patient during a CT scan and is calculated by multiplying the CT dose index (CTDI) by the scan length. To calculate a DRL from a DLP, a large dataset of DLP values obtained from a specific imaging procedure must be collected and can be used to determine the median or 75th-percentile DLP value for each imaging procedure. RESULTS Significant variations were found in the DLP, CTDIvol, and effective dose when we compared both the standard protocol and the optimized protocol. Also, the optimized protocol was compared with other diagnostic and radiotherapy CT scan studies conducted by other centers. As a result, we found that our institution's DRL was significantly low. The optimized dose protocol showed a reduction in the CTDIvol (70% and 63%), DLP (60% and 61%), and effective dose (67% and 62%) for both head, neck, and pelvic scans. CONCLUSIONS Optimized protocol DRLs were proposed for comparison purposes.
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Affiliation(s)
- Shreekripa Rao
- Department of Radiotherapy and Oncology, Manipal College of Health Professions, Manipal 576104, India (R.N.D.)
| | - Krishna Sharan
- Department of Radiotherapy and Oncology, Kasturba Medical College and Hospital, Manipal 576104, India; (K.S.); (S.G.C.)
| | | | - Rechal Nisha Dsouza
- Department of Radiotherapy and Oncology, Manipal College of Health Professions, Manipal 576104, India (R.N.D.)
| | - Leena R. David
- Department of Medical Imaging Technology, Manipal College of Health Professions, Manipal 576104, India; (L.R.D.); (S.R.); (D.S.)
- Department of Medical Diagnostic Imaging, College of Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates
| | - Sneha Ravichandran
- Department of Medical Imaging Technology, Manipal College of Health Professions, Manipal 576104, India; (L.R.D.); (S.R.); (D.S.)
| | - Mubarak Taiwo Mustapha
- Operational Research Centre in Healthcare, Near East University, TRNC Mersin 10, Nicosia 99138, Turkey; (M.T.M.); (B.U.)
- Department of Biomedical Engineering, Near East University, TRNC Mersin 10, Nicosia 99138, Turkey
| | - Dilip Shettigar
- Department of Medical Imaging Technology, Manipal College of Health Professions, Manipal 576104, India; (L.R.D.); (S.R.); (D.S.)
| | - Berna Uzun
- Operational Research Centre in Healthcare, Near East University, TRNC Mersin 10, Nicosia 99138, Turkey; (M.T.M.); (B.U.)
- Department of Mathematics, Near East University, TRNC Mersin 10, Nicosia 99138, Turkey
| | - Rajagopal Kadavigere
- Department of Radiodiagnosis and Imaging, Kasturba Medical College and Hospital, Manipal 576104, India;
| | - Suresh Sukumar
- Department of Medical Imaging Technology, Manipal College of Health Professions, Manipal 576104, India; (L.R.D.); (S.R.); (D.S.)
| | - Dilber Uzun Ozsahin
- Department of Medical Diagnostic Imaging, College of Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates
- Operational Research Centre in Healthcare, Near East University, TRNC Mersin 10, Nicosia 99138, Turkey; (M.T.M.); (B.U.)
- Research Institute for Medical and Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates
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Bayat F, Miller B, Park Y, Yu Z, Alexeev T, Thomas D, Stuhr K, Kavanagh B, Miften M, Altunbas C. 2D antiscatter grid and scatter sampling based CBCT method for online dose calculations during CBCT guided radiation therapy of pelvis. Med Phys 2024; 51:3053-3066. [PMID: 38043086 PMCID: PMC11008043 DOI: 10.1002/mp.16867] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2023] [Revised: 10/31/2023] [Accepted: 11/15/2023] [Indexed: 12/05/2023] Open
Abstract
BACKGROUND Online dose calculations before the delivery of radiation treatments have applications in dose delivery verification, online adaptation of treatment plans, and simulation-free treatment planning. While dose calculations by directly utilizing CBCT images are desired, dosimetric accuracy can be compromised due to relatively lower HU accuracy in CBCT images. PURPOSE In this work, we propose a novel CBCT imaging pipeline to enhance the accuracy of CBCT-based dose calculations in the pelvis region. Our approach aims to improve the HU accuracy in CBCT images, thereby improving the overall accuracy of CBCT-based dose calculations prior to radiation treatment delivery. METHODS An in-house developed quantitative CBCT pipeline was implemented to address the CBCT raw data contamination problem. The pipeline combines algorithmic data correction strategies and 2D antiscatter grid-based scatter rejection to achieve high CT number accuracy. To evaluate the effect of the quantitative CBCT pipeline on CBCT-based dose calculations, phantoms mimicking pelvis anatomy were scanned using a linac-mounted CBCT system, and a gold standard multidetector CT used for treatment planning (pCT). A total of 20 intensity-modulated treatment plans were generated for five targets, using 6 and 10 MV flattening filter-free beams, and utilizing small and large pelvis phantom images. For each treatment plan, four different dose calculations were performed using pCT images and three CBCT imaging configurations: quantitative CBCT, clinical CBCT protocol, and a high-performance 1D antiscatter grid (1D ASG). Subsequently, dosimetric accuracy was evaluated for both targets and organs at risk as a function of patient size, target location, beam energy, and CBCT imaging configuration. RESULTS When compared to the gold-standard pCT, dosimetric errors in quantitative CBCT-based dose calculations were not significant across all phantom sizes, beam energies, and treatment sites. The largest error observed was 0.6% among all dose volume histogram metrics and evaluated dose calculations. In contrast, dosimetric errors reached up to 7% and 97% in clinical CBCT and high-performance ASG CBCT-based treatment plans, respectively. The largest dosimetric errors were observed in bony targets in the large phantom treated with 6 MV beams. The trends of dosimetric errors in organs at risk were similar to those observed in the targets. CONCLUSIONS The proposed quantitative CBCT pipeline has the potential to provide comparable dose calculation accuracy to the gold-standard planning CT in photon radiation therapy for the abdomen and pelvis. These robust dose calculations could eliminate the need for density overrides in CBCT images and enable direct utilization of CBCT images for dose delivery monitoring or online treatment plan adaptations before the delivery of radiation treatments.
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Affiliation(s)
- Farhang Bayat
- Department of Radiation Oncology, University of Colorado School of Medicine, 1665 Aurora Court, Suite 1032, Mail stop F-706 Aurora, CO 80045
| | - Brian Miller
- Department of Radiation Oncology, The University of Arizona, College of Medicine, Tucson, AZ 85719
| | - Yeonok Park
- Department of Radiation Oncology, University of Colorado School of Medicine, 1665 Aurora Court, Suite 1032, Mail stop F-706 Aurora, CO 80045
| | - Zhelin Yu
- Department of Computer Science and Engineering, University of Colorado Denver, 1200 Larimer Street, Denver, CO, 80204
| | - Timur Alexeev
- Department of Radiation Oncology, University of Colorado School of Medicine, 1665 Aurora Court, Suite 1032, Mail stop F-706 Aurora, CO 80045
| | - David Thomas
- Department of Radiation Oncology, University of Colorado School of Medicine, 1665 Aurora Court, Suite 1032, Mail stop F-706 Aurora, CO 80045
| | - Kelly Stuhr
- Department of Radiation Oncology, University of Colorado School of Medicine, 1665 Aurora Court, Suite 1032, Mail stop F-706 Aurora, CO 80045
| | - Brian Kavanagh
- Department of Radiation Oncology, University of Colorado School of Medicine, 1665 Aurora Court, Suite 1032, Mail stop F-706 Aurora, CO 80045
| | - Moyed Miften
- Department of Radiation Oncology, University of Colorado School of Medicine, 1665 Aurora Court, Suite 1032, Mail stop F-706 Aurora, CO 80045
| | - Cem Altunbas
- Department of Radiation Oncology, University of Colorado School of Medicine, 1665 Aurora Court, Suite 1032, Mail stop F-706 Aurora, CO 80045
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Nakao M, Ozawa S, Miura H, Yamada K, Hayata M, Hayashi K, Kawahara D, Nakashima T, Ochi Y, Okumura T, Kunimoto H, Kawakubo A, Kusaba H, Nozaki H, Habara K, Tohyama N, Nishio T, Nakamura M, Minemura T, Okamoto H, Ishikawa M, Kurooka M, Shimizu H, Hotta K, Saito M, Nakano M, Tsuneda M, Nagata Y. CT number calibration audit in photon radiation therapy. Med Phys 2024; 51:1571-1582. [PMID: 38112216 DOI: 10.1002/mp.16887] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 06/29/2023] [Accepted: 11/26/2023] [Indexed: 12/21/2023] Open
Abstract
BACKGROUND Inadequate computed tomography (CT) number calibration curves affect dose calculation accuracy. Although CT number calibration curves registered in treatment planning systems (TPSs) should be consistent with human tissues, it is unclear whether adequate CT number calibration is performed because CT number calibration curves have not been assessed for various types of CT number calibration phantoms and TPSs. PURPOSE The purpose of this study was to investigate CT number calibration curves for mass density (ρ) and relative electron density (ρe ). METHODS A CT number calibration audit phantom was sent to 24 Japanese photon therapy institutes from the evaluating institute and scanned using their individual clinical CT scan protocols. The CT images of the audit phantom and institute-specific CT number calibration curves were submitted to the evaluating institute for analyzing the calibration curves registered in the TPSs at the participating institutes. The institute-specific CT number calibration curves were created using commercial phantom (Gammex, Gammex Inc., Middleton, WI, USA) or CIRS phantom (Computerized Imaging Reference Systems, Inc., Norfolk, VA, USA)). At the evaluating institute, theoretical CT number calibration curves were created using a stoichiometric CT number calibration method based on the CT image, and the institute-specific CT number calibration curves were compared with the theoretical calibration curve. Differences in ρ and ρe over the multiple points on the curve (Δρm and Δρe,m , respectively) were calculated for each CT number, categorized for each phantom vendor and TPS, and evaluated for three tissue types: lung, soft tissues, and bones. In particular, the CT-ρ calibration curves for Tomotherapy TPSs (ACCURAY, Sunnyvale, CA, USA) were categorized separately from the Gammex CT-ρ calibration curves because the available tissue-equivalent materials (TEMs) were limited by the manufacturer recommendations. In addition, the differences in ρ and ρe for the specific TEMs (ΔρTEM and Δρe,TEM , respectively) were calculated by subtracting the ρ or ρe of the TEMs from the theoretical CT-ρ or CT-ρe calibration curve. RESULTS The mean ± standard deviation (SD) of Δρm and Δρe,m for the Gammex phantom were -1.1 ± 1.2 g/cm3 and -0.2 ± 1.1, -0.3 ± 0.9 g/cm3 and 0.8 ± 1.3, and -0.9 ± 1.3 g/cm3 and 1.0 ± 1.5 for lung, soft tissues, and bones, respectively. The mean ± SD of Δρm and Δρe,m for the CIRS phantom were 0.3 ± 0.8 g/cm3 and 0.9 ± 0.9, 0.6 ± 0.6 g/cm3 and 1.4 ± 0.8, and 0.2 ± 0.5 g/cm3 and 1.6 ± 0.5 for lung, soft tissues, and bones, respectively. The mean ± SD of Δρm for Tomotherapy TPSs was 2.1 ± 1.4 g/cm3 for soft tissues, which is larger than those for other TPSs. The mean ± SD of Δρe,TEM for the Gammex brain phantom (BRN-SR2) was -1.8 ± 0.4, implying that the tissue equivalency of the BRN-SR2 plug was slightly inferior to that of other plugs. CONCLUSIONS Latent deviations between human tissues and TEMs were found by comparing the CT number calibration curves of the various institutes.
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Affiliation(s)
- Minoru Nakao
- Hiroshima High-Precision Radiotherapy Cancer Center, Hiroshima, Japan
- Department of Radiation Oncology, Graduate School of Biomedical & Health Sciences, Hiroshima University, Hiroshima, Japan
- Technical Support Working Group in Hiroshima High-Precision Radiotherapy Cancer Center, Hiroshima, Japan
- Medical Physics Working Group in Japan Clinical Oncology Group - Radiation Therapy Study Group, Tokyo, Japan
| | - Shuichi Ozawa
- Hiroshima High-Precision Radiotherapy Cancer Center, Hiroshima, Japan
- Department of Radiation Oncology, Graduate School of Biomedical & Health Sciences, Hiroshima University, Hiroshima, Japan
- Technical Support Working Group in Hiroshima High-Precision Radiotherapy Cancer Center, Hiroshima, Japan
- Medical Physics Working Group in Japan Clinical Oncology Group - Radiation Therapy Study Group, Tokyo, Japan
| | - Hideharu Miura
- Hiroshima High-Precision Radiotherapy Cancer Center, Hiroshima, Japan
- Department of Radiation Oncology, Graduate School of Biomedical & Health Sciences, Hiroshima University, Hiroshima, Japan
- Technical Support Working Group in Hiroshima High-Precision Radiotherapy Cancer Center, Hiroshima, Japan
| | - Kiyoshi Yamada
- Hiroshima High-Precision Radiotherapy Cancer Center, Hiroshima, Japan
- Technical Support Working Group in Hiroshima High-Precision Radiotherapy Cancer Center, Hiroshima, Japan
| | - Masahiro Hayata
- Hiroshima High-Precision Radiotherapy Cancer Center, Hiroshima, Japan
- Technical Support Working Group in Hiroshima High-Precision Radiotherapy Cancer Center, Hiroshima, Japan
| | - Kosuke Hayashi
- Hiroshima High-Precision Radiotherapy Cancer Center, Hiroshima, Japan
- Technical Support Working Group in Hiroshima High-Precision Radiotherapy Cancer Center, Hiroshima, Japan
| | - Daisuke Kawahara
- Department of Radiation Oncology, Graduate School of Biomedical & Health Sciences, Hiroshima University, Hiroshima, Japan
- Technical Support Working Group in Hiroshima High-Precision Radiotherapy Cancer Center, Hiroshima, Japan
- Medical Physics Working Group in Japan Clinical Oncology Group - Radiation Therapy Study Group, Tokyo, Japan
| | - Takeo Nakashima
- Technical Support Working Group in Hiroshima High-Precision Radiotherapy Cancer Center, Hiroshima, Japan
- Medical Physics Working Group in Japan Clinical Oncology Group - Radiation Therapy Study Group, Tokyo, Japan
- Radiation Therapy Section, Department of Clinical Support, Hiroshima University Hospital, Hiroshima, Japan
| | - Yusuke Ochi
- Technical Support Working Group in Hiroshima High-Precision Radiotherapy Cancer Center, Hiroshima, Japan
- Radiation Therapy Section, Department of Clinical Support, Hiroshima University Hospital, Hiroshima, Japan
| | - Takuro Okumura
- Technical Support Working Group in Hiroshima High-Precision Radiotherapy Cancer Center, Hiroshima, Japan
- Radiation Therapy Section, Department of Clinical Support, Hiroshima University Hospital, Hiroshima, Japan
| | - Haruhide Kunimoto
- Technical Support Working Group in Hiroshima High-Precision Radiotherapy Cancer Center, Hiroshima, Japan
- Radiation Therapy Department, Hiroshima Prefectural Hospital, Hiroshima, Japan
| | - Atsushi Kawakubo
- Technical Support Working Group in Hiroshima High-Precision Radiotherapy Cancer Center, Hiroshima, Japan
- Radiation Therapy Department, Hiroshima City Hiroshima Citizens Hospital, Hiroshima, Japan
| | - Hayate Kusaba
- Technical Support Working Group in Hiroshima High-Precision Radiotherapy Cancer Center, Hiroshima, Japan
- Radiation Therapy Department, Hiroshima City Hiroshima Citizens Hospital, Hiroshima, Japan
| | - Hiroshige Nozaki
- Technical Support Working Group in Hiroshima High-Precision Radiotherapy Cancer Center, Hiroshima, Japan
- Division of Radiology, Hiroshima Red Cross Hospital & Atomic-bomb Survivors Hospital, Hiroshima, Japan
| | - Kosaku Habara
- Technical Support Working Group in Hiroshima High-Precision Radiotherapy Cancer Center, Hiroshima, Japan
- Division of Radiology, Hiroshima Red Cross Hospital & Atomic-bomb Survivors Hospital, Hiroshima, Japan
| | - Naoki Tohyama
- Medical Physics Working Group in Japan Clinical Oncology Group - Radiation Therapy Study Group, Tokyo, Japan
- Division of Medical Physics, Tokyo Bay Makuhari Clinic for Advanced Imaging, Cancer Screening, and High-Precision Radiotherapy, Chiba, Japan
| | - Teiji Nishio
- Medical Physics Working Group in Japan Clinical Oncology Group - Radiation Therapy Study Group, Tokyo, Japan
- Medical Physics Laboratory, Division of Health Science, Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Mitsuhiro Nakamura
- Medical Physics Working Group in Japan Clinical Oncology Group - Radiation Therapy Study Group, Tokyo, Japan
- Department of Radiation Oncology and Image-Applied Therapy, Kyoto University, Kyoto, Japan
- Department of Advanced Medical Physics, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Toshiyuki Minemura
- Medical Physics Working Group in Japan Clinical Oncology Group - Radiation Therapy Study Group, Tokyo, Japan
- Division of Medical Support and Partnership, Institute for Cancer Control, National Cancer Center, Tokyo, Japan
| | - Hiroyuki Okamoto
- Medical Physics Working Group in Japan Clinical Oncology Group - Radiation Therapy Study Group, Tokyo, Japan
- Radiation Safety and Quality Assurance Division, National Cancer Center Hospital, Tokyo, Japan
| | - Masayori Ishikawa
- Medical Physics Working Group in Japan Clinical Oncology Group - Radiation Therapy Study Group, Tokyo, Japan
- Faculty of Health Sciences, Hokkaido University, Hokkaido, Japan
| | - Masahiko Kurooka
- Medical Physics Working Group in Japan Clinical Oncology Group - Radiation Therapy Study Group, Tokyo, Japan
- Department of Radiation Therapy, Tokyo Medical University Hospital, Tokyo, Japan
| | - Hidetoshi Shimizu
- Medical Physics Working Group in Japan Clinical Oncology Group - Radiation Therapy Study Group, Tokyo, Japan
- Department of Radiation Oncology, Aichi Cancer Center Hospital, Aichi, Japan
| | - Kenji Hotta
- Medical Physics Working Group in Japan Clinical Oncology Group - Radiation Therapy Study Group, Tokyo, Japan
- Radiation Safety and Quality Assurance division, National Cancer Center Hospital East, Chiba, Japan
- Particle Therapy Division, Exploratory Oncology Research and Clinical Trial Center, National Cancer Center, Chiba, Japan
| | - Masahide Saito
- Medical Physics Working Group in Japan Clinical Oncology Group - Radiation Therapy Study Group, Tokyo, Japan
- Department of Radiology, University of Yamanashi, Yamanashi, Japan
| | - Masahiro Nakano
- Medical Physics Working Group in Japan Clinical Oncology Group - Radiation Therapy Study Group, Tokyo, Japan
- Department of Radiation Oncology, Kitasato University School of Medicine, Kanagawa, Japan
| | - Masato Tsuneda
- Medical Physics Working Group in Japan Clinical Oncology Group - Radiation Therapy Study Group, Tokyo, Japan
- Graduate School of Medicine, Chiba University, Chiba, Japan
| | - Yasushi Nagata
- Hiroshima High-Precision Radiotherapy Cancer Center, Hiroshima, Japan
- Department of Radiation Oncology, Graduate School of Biomedical & Health Sciences, Hiroshima University, Hiroshima, Japan
- Technical Support Working Group in Hiroshima High-Precision Radiotherapy Cancer Center, Hiroshima, Japan
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Patrick HM, Kildea J. The use of dose surface maps as a tool to investigate spatial dose delivery accuracy for the rectum during prostate radiotherapy. J Appl Clin Med Phys 2024:e14314. [PMID: 38425148 DOI: 10.1002/acm2.14314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 01/17/2024] [Accepted: 02/07/2024] [Indexed: 03/02/2024] Open
Abstract
PURPOSE This study aims to address the lack of spatial dose comparisons of planned and delivered rectal doses during prostate radiotherapy by using dose-surface maps (DSMs) to analyze dose delivery accuracy and comparing these results to those derived using DVHs. METHODS Two independent cohorts were used in this study: twenty patients treated with 36.25 Gy in five fractions (SBRT) and 20 treated with 60 Gy in 20 fractions (IMRT). Daily delivered rectum doses for each patient were retrospectively calculated using daily CBCT images. For each cohort, planned and average-delivered DVHs were generated and compared, as were planned and accumulated DSMs. Permutation testing was used to identify DVH metrics and DSM regions where significant dose differences occurred. Changes in rectal volume and position between planning and delivery were also evaluated to determine possible correlation to dosimetric changes. RESULTS For both cohorts, DVHs and DSMs reported conflicting findings on how planned and delivered rectum doses differed from each other. DVH analysis determined average-delivered DVHs were on average 7.1% ± 7.6% (p ≤ 0.002) and 5.0 ± 7.4% (p ≤ 0.021) higher than planned for the IMRT and SBRT cohorts, respectively. Meanwhile, DSM analysis found average delivered posterior rectal wall dose was 3.8 ± 0.6 Gy (p = 0.014) lower than planned in the IMRT cohort and no significant dose differences in the SBRT cohort. Observed dose differences were moderately correlated with anterior-posterior rectal wall motion, as well as PTV superior-inferior motion in the IMRT cohort. Evidence of both these relationships were discernable in DSMs. CONCLUSION DSMs enabled spatial investigations of planned and delivered doses can uncover associations with interfraction motion that are otherwise masked in DVHs. Investigations of dose delivery accuracy in radiotherapy may benefit from using DSMs over DVHs for certain organs such as the rectum.
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Affiliation(s)
- Haley M Patrick
- Medical Physics Unit, McGill University, Montreal, Quebec, Canada
| | - John Kildea
- Medical Physics Unit, McGill University, Montreal, Quebec, Canada
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Cao N, Wang Z, Ding J, Zhang H, Zhang S, Gao L, Sun J, Xie K, Ni X. A 4D-CBCT correction network based on contrastive learning for dose calculation in lung cancer. Radiat Oncol 2024; 19:20. [PMID: 38336759 DOI: 10.1186/s13014-024-02411-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 01/23/2024] [Indexed: 02/12/2024] Open
Abstract
OBJECTIVE This study aimed to present a deep-learning network called contrastive learning-based cycle generative adversarial networks (CLCGAN) to mitigate streak artifacts and correct the CT value in four-dimensional cone beam computed tomography (4D-CBCT) for dose calculation in lung cancer patients. METHODS 4D-CBCT and 4D computed tomography (CT) of 20 patients with locally advanced non-small cell lung cancer were used to paired train the deep-learning model. The lung tumors were located in the right upper lobe, right lower lobe, left upper lobe, and left lower lobe, or in the mediastinum. Additionally, five patients to create 4D synthetic computed tomography (sCT) for test. Using the 4D-CT as the ground truth, the quality of the 4D-sCT images was evaluated by quantitative and qualitative assessment methods. The correction of CT values was evaluated holistically and locally. To further validate the accuracy of the dose calculations, we compared the dose distributions and calculations of 4D-CBCT and 4D-sCT with those of 4D-CT. RESULTS The structural similarity index measure (SSIM) and peak signal-to-noise ratio (PSNR) of the 4D-sCT increased from 87% and 22.31 dB to 98% and 29.15 dB, respectively. Compared with cycle consistent generative adversarial networks, CLCGAN enhanced SSIM and PSNR by 1.1% (p < 0.01) and 0.42% (p < 0.01). Furthermore, CLCGAN significantly decreased the absolute mean differences of CT value in lungs, bones, and soft tissues. The dose calculation results revealed a significant improvement in 4D-sCT compared to 4D-CBCT. CLCGAN was the most accurate in dose calculations for left lung (V5Gy), right lung (V5Gy), right lung (V20Gy), PTV (D98%), and spinal cord (D2%), with the relative dose difference were reduced by 6.84%, 3.84%, 1.46%, 0.86%, 3.32% compared to 4D-CBCT. CONCLUSIONS Based on the satisfactory results obtained in terms of image quality, CT value measurement, it can be concluded that CLCGAN-based corrected 4D-CBCT can be utilized for dose calculation in lung cancer.
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Affiliation(s)
- Nannan Cao
- Department of Radiotherapy, The Affiliated Changzhou NO.2 People's Hospital of Nanjing Medical University, Changzhou, 213003, China
- Jiangsu Province Engineering Research Center of Medical Physics, Changzhou, 213003, China
- Center for Medical Physics, Nanjing Medical University, Changzhou, 213003, China
- Key Laboratory of Medical Physics in Changzhou, Changzhou, 213003, China
| | - Ziyi Wang
- Department of Radiotherapy, The Affiliated Changzhou NO.2 People's Hospital of Nanjing Medical University, Changzhou, 213003, China
- Jiangsu Province Engineering Research Center of Medical Physics, Changzhou, 213003, China
- Center for Medical Physics, Nanjing Medical University, Changzhou, 213003, China
- Key Laboratory of Medical Physics in Changzhou, Changzhou, 213003, China
| | - Jiangyi Ding
- Department of Radiotherapy, The Affiliated Changzhou NO.2 People's Hospital of Nanjing Medical University, Changzhou, 213003, China
- Jiangsu Province Engineering Research Center of Medical Physics, Changzhou, 213003, China
- Center for Medical Physics, Nanjing Medical University, Changzhou, 213003, China
- Key Laboratory of Medical Physics in Changzhou, Changzhou, 213003, China
| | - Heng Zhang
- Department of Radiotherapy, The Affiliated Changzhou NO.2 People's Hospital of Nanjing Medical University, Changzhou, 213003, China
- Jiangsu Province Engineering Research Center of Medical Physics, Changzhou, 213003, China
- Center for Medical Physics, Nanjing Medical University, Changzhou, 213003, China
- Key Laboratory of Medical Physics in Changzhou, Changzhou, 213003, China
| | - Sai Zhang
- Department of Radiotherapy, The Affiliated Changzhou NO.2 People's Hospital of Nanjing Medical University, Changzhou, 213003, China
- Jiangsu Province Engineering Research Center of Medical Physics, Changzhou, 213003, China
- Center for Medical Physics, Nanjing Medical University, Changzhou, 213003, China
- Key Laboratory of Medical Physics in Changzhou, Changzhou, 213003, China
| | - Liugang Gao
- Department of Radiotherapy, The Affiliated Changzhou NO.2 People's Hospital of Nanjing Medical University, Changzhou, 213003, China
- Jiangsu Province Engineering Research Center of Medical Physics, Changzhou, 213003, China
- Center for Medical Physics, Nanjing Medical University, Changzhou, 213003, China
- Key Laboratory of Medical Physics in Changzhou, Changzhou, 213003, China
| | - Jiawei Sun
- Department of Radiotherapy, The Affiliated Changzhou NO.2 People's Hospital of Nanjing Medical University, Changzhou, 213003, China
- Jiangsu Province Engineering Research Center of Medical Physics, Changzhou, 213003, China
- Center for Medical Physics, Nanjing Medical University, Changzhou, 213003, China
- Key Laboratory of Medical Physics in Changzhou, Changzhou, 213003, China
| | - Kai Xie
- Department of Radiotherapy, The Affiliated Changzhou NO.2 People's Hospital of Nanjing Medical University, Changzhou, 213003, China
- Jiangsu Province Engineering Research Center of Medical Physics, Changzhou, 213003, China
- Center for Medical Physics, Nanjing Medical University, Changzhou, 213003, China
- Key Laboratory of Medical Physics in Changzhou, Changzhou, 213003, China
| | - Xinye Ni
- Department of Radiotherapy, The Affiliated Changzhou NO.2 People's Hospital of Nanjing Medical University, Changzhou, 213003, China.
- Jiangsu Province Engineering Research Center of Medical Physics, Changzhou, 213003, China.
- Center for Medical Physics, Nanjing Medical University, Changzhou, 213003, China.
- Key Laboratory of Medical Physics in Changzhou, Changzhou, 213003, China.
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Lundberg M, Meijers A, Souris K, Deffet S, Weber DC, Lomax A, Knopf A. Technical note: development of a simulation framework, enabling the investigation of locally tuned single energy proton radiography. Biomed Phys Eng Express 2024; 10:027002. [PMID: 38241732 DOI: 10.1088/2057-1976/ad20a8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Accepted: 01/19/2024] [Indexed: 01/21/2024]
Abstract
Range uncertainties remain a limitation for the confined dose distribution that proton therapy can offer. The uncertainty stems from the ambiguity when translating CT Hounsfield Units (HU) into proton stopping powers. Proton Radiography (PR) can be used to verify the proton range. Specifically, PR can be used as a quality-control tool for CBCT-based synthetic CTs. An essential part of the work illustrating the potential of PR has been conducted using multi-layer ionization chamber (MLIC) detectors and mono-energetic PR. Due to the dimensions of commercially available MLICs, clinical adoption is cumbersome. Here, we present a simulation framework exploring locally-tuned single energy (LTSE) proton radiography and corresponding potential compact PR detector designs. Based on a planning CT data set, the presented framework models the water equivalent thickness. Subsequently, it analyses the proton energies required to pass through the geometry within a defined ROI. In the final step, an LTSE PR is simulated using the MCsquare Monte Carlo code. In an anatomical head phantom, we illustrate that LTSE PR allows for a significantly shorter longitudinal dimension of MLICs. We compared PR simulations for two exemplary 30 × 30 mm2proton fields passing the phantom at a 90° angle at an anterior and a posterior location in an iso-centric setup. The longitudinal distance over which all spots per field range out is significantly reduced for LTSE PR compared to mono-energetic PR. In addition, we illustrate the difference in shape of integral depth dose (IDD) when using constrained PR energies. Finally, we demonstrate the accordance of simulated and experimentally acquired IDDs for an LTSE PR acquisition. As the next steps, the framework will be used to investigate the sensitivity of LTSE PR to various sources of errors. Furthermore, we will use the framework to systematically explore the dimensions of an optimized MLIC design for daily clinical use.
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Affiliation(s)
- Måns Lundberg
- Institute for Medical Engineering and Medical Informatics, School of Life Science FHNW, Muttenz, Switzerland
- Center for Proton Therapy, Paul Scherrer Institute, Villigen, Switzerland
| | - Arturs Meijers
- Center for Proton Therapy, Paul Scherrer Institute, Villigen, Switzerland
| | - Kevin Souris
- Ion Beam Applications SA, Louvain-La-Neuve, Belgium
| | | | - Damien C Weber
- Center for Proton Therapy, Paul Scherrer Institute, Villigen, Switzerland
- Department of Radiation Oncology, University Hospital of Zürich, Zürich, Switzerland
- Department of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Antony Lomax
- Center for Proton Therapy, Paul Scherrer Institute, Villigen, Switzerland
- Department of Physics, ETH Zurich, Zurich, Switzerland
| | - Antje Knopf
- Institute for Medical Engineering and Medical Informatics, School of Life Science FHNW, Muttenz, Switzerland
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8
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van Elmpt W, Trier Taasti V, Redalen KR. Current and future developments of synthetic computed tomography generation for radiotherapy. Phys Imaging Radiat Oncol 2023; 28:100521. [PMID: 38058591 PMCID: PMC10696097 DOI: 10.1016/j.phro.2023.100521] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/08/2023] Open
Affiliation(s)
- Wouter van Elmpt
- Department of Radiation Oncology (MAASTRO), GROW School for Oncology and Reproduction, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - Vicki Trier Taasti
- Department of Radiation Oncology (MAASTRO), GROW School for Oncology and Reproduction, Maastricht University Medical Center+, Maastricht, The Netherlands
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Stevens S, Moloney S, Blackmore A, Hart C, Rixham P, Bangiri A, Pooler A, Doolan P. IPEM topical report: guidance for the clinical implementation of online treatment monitoring solutions for IMRT/VMAT. Phys Med Biol 2023; 68:18TR02. [PMID: 37531959 DOI: 10.1088/1361-6560/acecd0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 08/02/2023] [Indexed: 08/04/2023]
Abstract
This report provides guidance for the implementation of online treatment monitoring (OTM) solutions in radiotherapy (RT), with a focus on modulated treatments. Support is provided covering the implementation process, from identification of an OTM solution to local implementation strategy. Guidance has been developed by a RT special interest group (RTSIG) working party (WP) on behalf of the Institute of Physics and Engineering in Medicine (IPEM). Recommendations within the report are derived from the experience of the WP members (in consultation with manufacturers, vendors and user groups), existing guidance or legislation and a UK survey conducted in 2020 (Stevenset al2021). OTM is an inclusive term representing any system capable of providing a direct or inferred measurement of the delivered dose to a RT patient. Information on each type of OTM is provided but, commensurate with UK demand, guidance is largely influenced byin vivodosimetry methods utilising the electronic portal imager device (EPID). Sections are included on the choice of OTM solutions, acceptance and commissioning methods with recommendations on routine quality control, analytical methods and tolerance setting, clinical introduction and staffing/resource requirements. The guidance aims to give a practical solution to sensitivity and specificity testing. Functionality is provided for the user to introduce known errors into treatment plans for local testing. Receiver operating characteristic analysis is discussed as a tool to performance assess OTM systems. OTM solutions can help verify the correct delivery of radiotherapy treatment. Furthermore, modern systems are increasingly capable of providing clinical decision-making information which can impact the course of a patient's treatment. However, technical limitations persist. It is not within the scope of this guidance to critique each available solution, but the user is encouraged to carefully consider workflow and engage with manufacturers in resolving compatibility issues.
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Affiliation(s)
| | - Stephen Moloney
- University Hospitals Dorset NHS Foundation Trust, Poole, United Kingdom
| | | | - Clare Hart
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - Philip Rixham
- Leeds Cancer Centre, Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom
| | - Anna Bangiri
- Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom
| | - Alistair Pooler
- Christie Medical Physics and Engineering, The Christie NHS Foundation Trust, Manchester, United Kingdom
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10
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Gan Y, Langendijk JA, van der Schaaf A, van den Bosch L, Oldehinkel E, Lin Z, Both S, Brouwer CL. An efficient strategy to select head and neck cancer patients for adaptive radiotherapy. Radiother Oncol 2023; 186:109763. [PMID: 37353058 DOI: 10.1016/j.radonc.2023.109763] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 06/14/2023] [Accepted: 06/16/2023] [Indexed: 06/25/2023]
Abstract
BACKGROUND AND PURPOSE Adaptive radiotherapy (ART) is workload intensive but only benefits a subgroup of patients. We aimed to develop an efficient strategy to select candidates for ART in the first two weeks of head and neck cancer (HNC) radiotherapy. MATERIALS AND METHODS This study retrospectively enrolled 110 HNC patients who underwent modern photon radiotherapy with at least 5 weekly in-treatment re-scan CTs. A semi auto-segmentation method was applied to obtain the weekly mean dose (Dmean) to OARs. A comprehensive NTCP-profile was applied to obtain NTCP's. The difference between planning and actual values of Dmean (ΔDmean) and dichotomized difference of clinical relevance (BIOΔNTCP) were used for modelling to determine the cut-off maximum ΔDmean of OARs in week 1 and 2 (maxΔDmean_1 and maxΔDmean_2). Four strategies to select candidates for ART, using cut-off maxΔDmean were compared. RESULTS The Spearman's rank correlation test showed significant positive correlation between maxΔDmean and BIOΔNTCP (p-value <0.001). For major BIOΔNTCP (>5%) of acute and late toxicity, 10.9% and 4.5% of the patients were true candidates for ART. Strategy C using both cut-off maxΔDmean_1 (3.01 and 5.14 Gy) and cut-off maxΔDmean_2 (3.41 and 5.30 Gy) showed the best sensitivity, specificity, positive and negative predictive values (0.92, 0.82, 0.38, 0.99 for acute toxicity and 1.00, 0.92, 0.38, 1.00 for late toxicity, respectively). CONCLUSIONS We propose an efficient selection strategy for ART that is able to classify the subgroup of patients with >5% BIOΔNTCP for late toxicity using imaging in the first two treatment weeks.
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Affiliation(s)
- Yong Gan
- University of Groningen, University Medical Center Groningen, Department of Radiation Oncology, Groningen, The Netherlands; Shantou University, Cancer Hospital of Shantou University Medical College, Department of Radiotherapy, China.
| | - Johannes A Langendijk
- University of Groningen, University Medical Center Groningen, Department of Radiation Oncology, Groningen, The Netherlands
| | - Arjen van der Schaaf
- University of Groningen, University Medical Center Groningen, Department of Radiation Oncology, Groningen, The Netherlands
| | - Lisa van den Bosch
- University of Groningen, University Medical Center Groningen, Department of Radiation Oncology, Groningen, The Netherlands
| | - Edwin Oldehinkel
- University of Groningen, University Medical Center Groningen, Department of Radiation Oncology, Groningen, The Netherlands
| | - Zhixiong Lin
- Shantou University, Cancer Hospital of Shantou University Medical College, Department of Radiotherapy, China
| | - Stefan Both
- University of Groningen, University Medical Center Groningen, Department of Radiation Oncology, Groningen, The Netherlands
| | - Charlotte L Brouwer
- University of Groningen, University Medical Center Groningen, Department of Radiation Oncology, Groningen, The Netherlands
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11
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Hemon C, Rigaud B, Barateau A, Tilquin F, Noblet V, Sarrut D, Meyer P, Bert J, De Crevoisier R, Simon A. Contour-guided deep learning based deformable image registration for dose monitoring during CBCT-guided radiotherapy of prostate cancer. J Appl Clin Med Phys 2023; 24:e13991. [PMID: 37232048 PMCID: PMC10445205 DOI: 10.1002/acm2.13991] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 02/16/2023] [Accepted: 03/17/2023] [Indexed: 05/27/2023] Open
Abstract
PURPOSE To evaluate deep learning (DL)-based deformable image registration (DIR) for dose accumulation during radiotherapy of prostate cancer patients. METHODS AND MATERIALS Data including 341 CBCTs (209 daily, 132 weekly) and 23 planning CTs from 23 patients was retrospectively analyzed. Anatomical deformation during treatment was estimated using free-form deformation (FFD) method from Elastix and DL-based VoxelMorph approaches. The VoxelMorph method was investigated using anatomical scans (VMorph_Sc) or label images (VMorph_Msk), or the combination of both (VMorph_Sc_Msk). Accumulated doses were compared with the planning dose. RESULTS The DSC ranges, averaged for prostate, rectum and bladder, were 0.60-0.71, 0.67-0.79, 0.93-0.98, and 0.89-0.96 for the FFD, VMorph_Sc, VMorph_Msk, and VMorph_Sc_Msk methods, respectively. When including both anatomical and label images, VoxelMorph estimated more complex deformations resulting in heterogeneous determinant of Jacobian and higher percentage of deformation vector field (DVF) folding (up to a mean value of 1.90% in the prostate). Large differences were observed between DL-based methods regarding estimation of the accumulated dose, showing systematic overdosage and underdosage of the bladder and rectum, respectively. The difference between planned mean dose and accumulated mean dose with VMorph_Sc_Msk reached a median value of +6.3 Gy for the bladder and -5.1 Gy for the rectum. CONCLUSION The estimation of the deformations using DL-based approach is feasible for male pelvic anatomy but requires the inclusion of anatomical contours to improve organ correspondence. High variability in the estimation of the accumulated dose depending on the deformable strategy suggests further investigation of DL-based techniques before clinical deployment.
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Affiliation(s)
- Cédric Hemon
- Univ Rennes, CLCC Eugène Marquis, INSERM, LTSI – UMR 1099RennesFrance
| | - Bastien Rigaud
- Univ Rennes, CLCC Eugène Marquis, INSERM, LTSI – UMR 1099RennesFrance
| | - Anais Barateau
- Univ Rennes, CLCC Eugène Marquis, INSERM, LTSI – UMR 1099RennesFrance
| | - Florian Tilquin
- Univ Rennes, CLCC Eugène Marquis, INSERM, LTSI – UMR 1099RennesFrance
| | - Vincent Noblet
- Laboratoire des sciences de l'ingénieurde l'informatique et de l'imagerieICube UMR 7357Illkirch‐GraffenstadenFrance
| | - David Sarrut
- Université de LyonCREATIS, CNRS UMR5220Inserm U1294INSA‐LyonUniversité Lyon 1LyonFrance
| | - Philippe Meyer
- Department of Medical PhysicsPaul Strauss CenterStrasbourgFrance
| | - Julien Bert
- Faculty of MedicineLaTIM, INSERM UMR 1101, IBRBS, Univ BrestBrestFrance
| | | | - Antoine Simon
- Univ Rennes, CLCC Eugène Marquis, INSERM, LTSI – UMR 1099RennesFrance
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12
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Lavrova E, Garrett MD, Wang YF, Chin C, Elliston C, Savacool M, Price M, Kachnic LA, Horowitz DP. Adaptive Radiation Therapy: A Review of CT-based Techniques. Radiol Imaging Cancer 2023; 5:e230011. [PMID: 37449917 PMCID: PMC10413297 DOI: 10.1148/rycan.230011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 04/18/2023] [Accepted: 05/10/2023] [Indexed: 07/18/2023]
Abstract
Adaptive radiation therapy is a feedback process by which imaging information acquired over the course of treatment, such as changes in patient anatomy, can be used to reoptimize the treatment plan, with the end goal of improving target coverage and reducing treatment toxicity. This review describes different types of adaptive radiation therapy and their clinical implementation with a focus on CT-guided online adaptive radiation therapy. Depending on local anatomic changes and clinical context, different anatomic sites and/or disease stages and presentations benefit from different adaptation strategies. Online adaptive radiation therapy, where images acquired in-room before each fraction are used to adjust the treatment plan while the patient remains on the treatment table, has emerged to address unpredictable anatomic changes between treatment fractions. Online treatment adaptation places unique pressures on the radiation therapy workflow, requiring high-quality daily imaging and rapid recontouring, replanning, plan review, and quality assurance. Generating a new plan with every fraction is resource intensive and time sensitive, emphasizing the need for workflow efficiency and clinical resource allocation. Cone-beam CT is widely used for image-guided radiation therapy, so implementing cone-beam CT-guided online adaptive radiation therapy can be easily integrated into the radiation therapy workflow and potentially allow for rapid imaging and replanning. The major challenge of this approach is the reduced image quality due to poor resolution, scatter, and artifacts. Keywords: Adaptive Radiation Therapy, Cone-Beam CT, Organs at Risk, Oncology © RSNA, 2023.
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Affiliation(s)
- Elizaveta Lavrova
- From the Department of Radiation Oncology, Columbia University Irving
Medical Center, 622 W 168th St, New York, NY 10032 (E.L., M.D.G., Y.F.W., C.C.,
C.E., M.S., M.P., L.A.K., D.P.H.); and Herbert Irving Comprehensive Cancer
Center, New York, NY (C.C., L.A.K., D.P.H.)
| | - Matthew D. Garrett
- From the Department of Radiation Oncology, Columbia University Irving
Medical Center, 622 W 168th St, New York, NY 10032 (E.L., M.D.G., Y.F.W., C.C.,
C.E., M.S., M.P., L.A.K., D.P.H.); and Herbert Irving Comprehensive Cancer
Center, New York, NY (C.C., L.A.K., D.P.H.)
| | - Yi-Fang Wang
- From the Department of Radiation Oncology, Columbia University Irving
Medical Center, 622 W 168th St, New York, NY 10032 (E.L., M.D.G., Y.F.W., C.C.,
C.E., M.S., M.P., L.A.K., D.P.H.); and Herbert Irving Comprehensive Cancer
Center, New York, NY (C.C., L.A.K., D.P.H.)
| | - Christine Chin
- From the Department of Radiation Oncology, Columbia University Irving
Medical Center, 622 W 168th St, New York, NY 10032 (E.L., M.D.G., Y.F.W., C.C.,
C.E., M.S., M.P., L.A.K., D.P.H.); and Herbert Irving Comprehensive Cancer
Center, New York, NY (C.C., L.A.K., D.P.H.)
| | - Carl Elliston
- From the Department of Radiation Oncology, Columbia University Irving
Medical Center, 622 W 168th St, New York, NY 10032 (E.L., M.D.G., Y.F.W., C.C.,
C.E., M.S., M.P., L.A.K., D.P.H.); and Herbert Irving Comprehensive Cancer
Center, New York, NY (C.C., L.A.K., D.P.H.)
| | - Michelle Savacool
- From the Department of Radiation Oncology, Columbia University Irving
Medical Center, 622 W 168th St, New York, NY 10032 (E.L., M.D.G., Y.F.W., C.C.,
C.E., M.S., M.P., L.A.K., D.P.H.); and Herbert Irving Comprehensive Cancer
Center, New York, NY (C.C., L.A.K., D.P.H.)
| | - Michael Price
- From the Department of Radiation Oncology, Columbia University Irving
Medical Center, 622 W 168th St, New York, NY 10032 (E.L., M.D.G., Y.F.W., C.C.,
C.E., M.S., M.P., L.A.K., D.P.H.); and Herbert Irving Comprehensive Cancer
Center, New York, NY (C.C., L.A.K., D.P.H.)
| | - Lisa A. Kachnic
- From the Department of Radiation Oncology, Columbia University Irving
Medical Center, 622 W 168th St, New York, NY 10032 (E.L., M.D.G., Y.F.W., C.C.,
C.E., M.S., M.P., L.A.K., D.P.H.); and Herbert Irving Comprehensive Cancer
Center, New York, NY (C.C., L.A.K., D.P.H.)
| | - David P. Horowitz
- From the Department of Radiation Oncology, Columbia University Irving
Medical Center, 622 W 168th St, New York, NY 10032 (E.L., M.D.G., Y.F.W., C.C.,
C.E., M.S., M.P., L.A.K., D.P.H.); and Herbert Irving Comprehensive Cancer
Center, New York, NY (C.C., L.A.K., D.P.H.)
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Taasti VT, Hattu D, Peeters S, van der Salm A, van Loon J, de Ruysscher D, Nilsson R, Andersson S, Engwall E, Unipan M, Canters R. Clinical evaluation of synthetic computed tomography methods in adaptive proton therapy of lung cancer patients. Phys Imaging Radiat Oncol 2023; 27:100459. [PMID: 37397874 PMCID: PMC10314284 DOI: 10.1016/j.phro.2023.100459] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 06/13/2023] [Accepted: 06/13/2023] [Indexed: 07/04/2023] Open
Abstract
Background and purpose Efficient workflows for adaptive proton therapy are of high importance. This study evaluated the possibility to replace repeat-CTs (reCTs) with synthetic CTs (sCTs), created based on cone-beam CTs (CBCTs), for flagging the need of plan adaptations in intensity-modulated proton therapy (IMPT) treatment of lung cancer patients. Materials and methods Forty-two IMPT patients were retrospectively included. For each patient, one CBCT and a same-day reCT were included. Two commercial sCT methods were applied; one based on CBCT number correction (Cor-sCT), and one based on deformable image registration (DIR-sCT). The clinical reCT workflow (deformable contour propagation and robust dose re-computation) was performed on the reCT as well as the two sCTs. The deformed target contours on the reCT/sCTs were checked by radiation oncologists and edited if needed. A dose-volume-histogram triggered plan adaptation method was compared between the reCT and the sCTs; patients needing a plan adaptation on the reCT but not on the sCT were denoted false negatives. As secondary evaluation, dose-volume-histogram comparison and gamma analysis (2%/2mm) were performed between the reCT and sCTs. Results There were five false negatives, two for Cor-sCT and three for DIR-sCT. However, three of these were only minor, and one was caused by tumour position differences between the reCT and CBCT and not by sCT quality issues. An average gamma pass rate of 93% was obtained for both sCT methods. Conclusion Both sCT methods were judged to be of clinical quality and valuable for reducing the amount of reCT acquisitions.
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Affiliation(s)
- Vicki Trier Taasti
- Department of Radiation Oncology (Maastro), GROW School for Oncology and Reproduction, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Djoya Hattu
- Department of Radiation Oncology (Maastro), GROW School for Oncology and Reproduction, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Stephanie Peeters
- Department of Radiation Oncology (Maastro), GROW School for Oncology and Reproduction, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Anke van der Salm
- Department of Radiation Oncology (Maastro), GROW School for Oncology and Reproduction, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Judith van Loon
- Department of Radiation Oncology (Maastro), GROW School for Oncology and Reproduction, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Dirk de Ruysscher
- Department of Radiation Oncology (Maastro), GROW School for Oncology and Reproduction, Maastricht University Medical Centre, Maastricht, The Netherlands
| | | | | | | | - Mirko Unipan
- Department of Radiation Oncology (Maastro), GROW School for Oncology and Reproduction, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Richard Canters
- Department of Radiation Oncology (Maastro), GROW School for Oncology and Reproduction, Maastricht University Medical Centre, Maastricht, The Netherlands
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14
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Allen C, Yeo AU, Hardcastle N, Franich RD. Evaluating synthetic computed tomography images for adaptive radiotherapy decision making in head and neck cancer. Phys Imaging Radiat Oncol 2023; 27:100478. [PMID: 37655123 PMCID: PMC10465931 DOI: 10.1016/j.phro.2023.100478] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 07/19/2023] [Accepted: 07/22/2023] [Indexed: 09/02/2023] Open
Abstract
Background and purpose Adaptive radiotherapy (ART) decision-making benefits from dosimetric information to supplement image inspection when assessing the significance of anatomical changes. This study evaluated a dosimetry-based clinical decision workflow for ART utilizing deformable registration of the original planning computed tomography (CT) image to the daily Cone Beam CT (CBCT) to replace the need for a replan CT for dose estimation. Materials and methods We used 12 retrospective Head & Neck patient cases having a ground truth - a replan CT (rCT) in response to anatomical changes apparent in the daily CBCT - to evaluate the accuracy of dosimetric assessment conducted on synthetic CTs (sCT) generated by deforming the original planning CT Hounsfield Units to the daily CBCT anatomy.The original plan was applied to the sCT and dosimetric accuracy of the sCT was assessed by analyzing plan objectives for targets and organs-at-risk compared to calculations on the ground-truth rCT. Three commercial DIR algorithms were compared. Results For the best-performing algorithms, the majority of dose metrics calculated on the sCTs differed by less than 4 Gy (5.7% of 70 Gy prescription dose). An uncertainty of ±2.5 Gy (3.6% of 70 Gy prescription) is recommended as a conservative tolerance when evaluating dose metrics on sCTs for head and neck. Conclusions Synthetic CTs present a valuable addition to the adaptive radiotherapy workflow, and synthetic CT dose estimates can be effectively used in addition to the current practice of visually inspecting the overlay of the planning CT and CBCT to assess the significance of anatomical change.
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Affiliation(s)
- Caitlin Allen
- Physical Sciences, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- School of Science, RMIT University, Melbourne, Victoria, Australia
| | - Adam U. Yeo
- Physical Sciences, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- School of Science, RMIT University, Melbourne, Victoria, Australia
| | - Nicholas Hardcastle
- Physical Sciences, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Centre for Medical Radiation Physics, University of Wollongong, NSW, Australia
| | - Rick D. Franich
- Physical Sciences, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- School of Science, RMIT University, Melbourne, Victoria, Australia
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15
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Schmitz H, Thummerer A, Kawula M, Lombardo E, Parodi K, Belka C, Kamp F, Kurz C, Landry G. ScatterNet for projection-based 4D cone-beam computed tomography intensity correction of lung cancer patients. Phys Imaging Radiat Oncol 2023; 27:100482. [PMID: 37680905 PMCID: PMC10480315 DOI: 10.1016/j.phro.2023.100482] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 08/04/2023] [Accepted: 08/11/2023] [Indexed: 09/09/2023] Open
Abstract
Background and purpose: In radiotherapy, dose calculations based on 4D cone beam CTs (4DCBCTs) require image intensity corrections. This retrospective study compared the dose calculation accuracy of a deep learning, projection-based scatter correction workflow (ScatterNet), to slower workflows: conventional 4D projection-based scatter correction (CBCTcor) and a deformable image registration (DIR)-based method (4DvCT). Materials and methods: For 26 lung cancer patients, planning CTs (pCTs), 4DCTs and CBCT projections were available. ScatterNet was trained with pairs of raw and corrected CBCT projections. Corrected projections from ScatterNet and the conventional workflow were reconstructed using MA-ROOSTER, yielding 4DCBCTSN and 4DCBCTcor. The 4DvCT was generated by 4DCT to 4DCBCT DIR, as part of the 4DCBCTcor workflow. Robust intensity modulated proton therapy treatment plans were created on free-breathing pCTs. 4DCBCTSN was compared to 4DCBCTcor and the 4DvCT in terms of image quality and dose calculation accuracy (dose-volume-histogram parameters and 3 % /3 mm gamma analysis). Results: 4DCBCTSN resulted in an average mean absolute error of 87 HU and 102 HU when compared to 4DCBCTcor and 4DvCT respectively. High agreement was observed in targets with median dose differences of 0.4 Gy (4DCBCTSN-4DCBCTcor) and 0.3 Gy (4DCBCTSN-4DvCT). The gamma analysis showed high average 3 % /3 mm pass rates of 96 % for both 4DCBCTSN vs. 4DCBCTcor and 4DCBCTSN vs. 4DvCT. Conclusions: Accurate 4D dose calculations are feasible for lung cancer patients using ScatterNet for 4DCBCT correction. Average scatter correction times could be reduced from 10 min (4DCBCTcor) to 3.9 s , showing the clinical suitability of the proposed deep learning-based method.
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Affiliation(s)
- Henning Schmitz
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Adrian Thummerer
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Maria Kawula
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Elia Lombardo
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Katia Parodi
- Department of Medical Physics, Ludwig-Maximilians-Universität München (LMU Munich), Garching (Munich), Germany
| | - Claus Belka
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
- Bavarian Cancer Research Center (BZKF), Munich, Germany
| | - Florian Kamp
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
- Department of Radiation Oncology, University Hospital Cologne, Cologne, Germany
| | - Christopher Kurz
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Guillaume Landry
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
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16
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Jassim H, Nedaei HA, Geraily G, Banaee N, Kazemian A. The geometric and dosimetric accuracy of kilovoltage cone beam computed tomography images for adaptive treatment: a systematic review. BJR Open 2023; 5:20220062. [PMID: 37389008 PMCID: PMC10301728 DOI: 10.1259/bjro.20220062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Accepted: 01/24/2023] [Indexed: 07/01/2023] Open
Abstract
Objectives To provide an overview and meta-analysis of different techniques adopted to accomplish kVCBCT for dose calculation and automated segmentation. Methods A systematic review and meta-analysis were performed on eligible studies demonstrating kVCBCT-based dose calculation and automated contouring of different tumor features. Meta-analysis of the performance was accomplished on the reported γ analysis and dice similarity coefficient (DSC) score of both collected results as three subgroups (head and neck, chest, and abdomen). Results After the literature scrutinization (n = 1008), 52 papers were recognized for the systematic review. Nine studies of dosimtric studies and eleven studies of geometric analysis were suitable for inclusion in meta-analysis. Using kVCBCT for treatment replanning depends on a method used. Deformable Image Registration (DIR) methods yielded small dosimetric error (≤2%), γ pass rate (≥90%) and DSC (≥0.8). Hounsfield Unit (HU) override and calibration curve-based methods also achieved satisfactory yielded small dosimetric error (≤2%) and γ pass rate ((≥90%), but they are prone to error due to their sensitivity to a vendor-specific variation in kVCBCT image quality. Conclusions Large cohorts of patients ought to be undertaken to validate methods achieving low levels of dosimetric and geometric errors. Quality guidelines should be established when reporting on kVCBCT, which include agreed metrics for reporting on the quality of corrected kVCBCT and defines protocols of new site-specific standardized imaging used when obtaining kVCBCT images for adaptive radiotherapy. Advances in knowledge This review gives useful knowledge about methods making kVCBCT feasible for kVCBCT-based adaptive radiotherapy, simplifying patient pathway and reducing concomitant imaging dose to the patient.
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Affiliation(s)
| | | | | | - Nooshin Banaee
- Medical Radiation Research Center, Islamic Azad University, Tehran, Iran
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17
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Szmul A, Taylor S, Lim P, Cantwell J, Moreira I, Zhang Y, D’Souza D, Moinuddin S, Gaze MN, Gains J, Veiga C. Deep learning based synthetic CT from cone beam CT generation for abdominal paediatric radiotherapy. Phys Med Biol 2023; 68:105006. [PMID: 36996837 PMCID: PMC10160738 DOI: 10.1088/1361-6560/acc921] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Revised: 03/13/2023] [Accepted: 03/30/2023] [Indexed: 04/01/2023]
Abstract
Objective. Adaptive radiotherapy workflows require images with the quality of computed tomography (CT) for re-calculation and re-optimisation of radiation doses. In this work we aim to improve the quality of on-board cone beam CT (CBCT) images for dose calculation using deep learning.Approach. We propose a novel framework for CBCT-to-CT synthesis using cycle-consistent Generative Adversarial Networks (cycleGANs). The framework was tailored for paediatric abdominal patients, a challenging application due to the inter-fractional variability in bowel filling and small patient numbers. We introduced to the networks the concept of global residuals only learning and modified the cycleGAN loss function to explicitly promote structural consistency between source and synthetic images. Finally, to compensate for the anatomical variability and address the difficulties in collecting large datasets in the paediatric population, we applied a smart 2D slice selection based on the common field-of-view (abdomen) to our imaging dataset. This acted as a weakly paired data approach that allowed us to take advantage of scans from patients treated for a variety of malignancies (thoracic-abdominal-pelvic) for training purposes. We first optimised the proposed framework and benchmarked its performance on a development dataset. Later, a comprehensive quantitative evaluation was performed on an unseen dataset, which included calculating global image similarity metrics, segmentation-based measures and proton therapy-specific metrics.Main results. We found improved performance for our proposed method, compared to a baseline cycleGAN implementation, on image-similarity metrics such as Mean Absolute Error calculated for a matched virtual CT (55.0 ± 16.6 HU proposed versus 58.9 ± 16.8 HU baseline). There was also a higher level of structural agreement for gastrointestinal gas between source and synthetic images measured using the dice similarity coefficient (0.872 ± 0.053 proposed versus 0.846 ± 0.052 baseline). Differences found in water-equivalent thickness metrics were also smaller for our method (3.3 ± 2.4% proposed versus 3.7 ± 2.8% baseline).Significance. Our findings indicate that our innovations to the cycleGAN framework improved the quality and structure consistency of the synthetic CTs generated.
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Affiliation(s)
- Adam Szmul
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London, United Kingdom
| | - Sabrina Taylor
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Pei Lim
- Department of Oncology, University College London Hospitals NHS Foundation Trust, London, United Kingdom
| | - Jessica Cantwell
- Radiotherapy, University College London Hospitals NHS Foundation Trust, London, United Kingdom
| | - Isabel Moreira
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Ying Zhang
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Derek D’Souza
- Radiotherapy Physics Services, University College London Hospitals NHS Foundation Trust, London, United Kingdom
| | - Syed Moinuddin
- Radiotherapy, University College London Hospitals NHS Foundation Trust, London, United Kingdom
| | - Mark N. Gaze
- Department of Oncology, University College London Hospitals NHS Foundation Trust, London, United Kingdom
| | - Jennifer Gains
- Department of Oncology, University College London Hospitals NHS Foundation Trust, London, United Kingdom
| | - Catarina Veiga
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
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18
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Trnkova P, Zhang Y, Toshito T, Heijmen B, Richter C, Aznar MC, Albertini F, Bolsi A, Daartz J, Knopf AC, Bertholet J. A survey of practice patterns for adaptive particle therapy for interfractional changes. Phys Imaging Radiat Oncol 2023; 26:100442. [PMID: 37197154 PMCID: PMC10183663 DOI: 10.1016/j.phro.2023.100442] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Revised: 04/22/2023] [Accepted: 04/24/2023] [Indexed: 05/19/2023] Open
Abstract
Background and purpose Anatomical changes may compromise the planned target coverage and organs-at-risk dose in particle therapy. This study reports on the practice patterns for adaptive particle therapy (APT) to evaluate current clinical practice and wishes and barriers to further implementation. Materials and methods An institutional questionnaire was distributed to PT centres worldwide (7/2020-6/2021) asking which type of APT was used, details of the workflow, and what the wishes and barriers to implementation were. Seventy centres from 17 countries participated. A three-round Delphi consensus analysis (10/2022) among the authors followed to define recommendations on required actions and future vision. Results Out of the 68 clinically operational centres, 84% were users of APT for at least one treatment site with head and neck being most common. APT was mostly performed offline with only two online APT users (plan-library). No centre used online daily re-planning. Daily 3D imaging was used for APT by 19% of users. Sixty-eight percent of users had plans to increase their use or change their technique for APT. The main barrier was "lack of integrated and efficient workflows". Automation and speed, reliable dose deformation for dose accumulation and higher quality of in-room volumetric imaging were identified as the most urgent task for clinical implementation of online daily APT. Conclusion Offline APT was implemented by the majority of PT centres. Joint efforts between industry research and clinics are needed to translate innovations into efficient and clinically feasible workflows for broad-scale implementation of online APT.
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Affiliation(s)
- Petra Trnkova
- Department of Radiation Oncology, Medical University of Vienna, Vienna, Austria
- Corresponding author.
| | - Ye Zhang
- Center for Proton Therapy, Paul Scherrer Institute, Villigen, Switzerland
| | - Toshiyuki Toshito
- Nagoya Proton Therapy Center, Nagoya City University West Medical Center, Nagoya, Japan
| | - Ben Heijmen
- Department of Radiotherapy, Erasmus University Medical Center (Erasmus MC), Rotterdam, the Netherlands
| | - Christian Richter
- OncoRay – National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden – Rossendorf, Dresden, Germany
| | - Marianne C. Aznar
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
| | | | - Alessandra Bolsi
- Center for Proton Therapy, Paul Scherrer Institute, Villigen, Switzerland
| | - Juliane Daartz
- Department of Radiation Oncology, Massachusetts General Hospital & Harvard Medical School, Boston, MA 02114, United States of America
| | - Antje C. Knopf
- Center for Proton Therapy, Paul Scherrer Institute, Villigen, Switzerland
- Institute for Medical Engineering and Medical Informatics, School of Life Science FHNW, Muttenz, Switzerland
| | - Jenny Bertholet
- Division of Medical Radiation Physics and Department of Radiation Oncology, Inselspital, Bern University Hospital, Bern, Switzerland
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19
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Hoppen L, Sarria GR, Kwok CS, Boda-Heggemann J, Buergy D, Ehmann M, Giordano FA, Fleckenstein J. Dosimetric benefits of adaptive radiation therapy for patients with stage III non-small cell lung cancer. Radiat Oncol 2023; 18:34. [PMID: 36814271 PMCID: PMC9945670 DOI: 10.1186/s13014-023-02222-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Accepted: 02/06/2023] [Indexed: 02/24/2023] Open
Abstract
BACKGROUND Daily adaptive radiation therapy (ART) of patients with non-small cell lung cancer (NSCLC) lowers organs at risk exposure while maintaining the planning target volume (PTV) coverage. Thus, ART allows an isotoxic approach with increased doses to the PTV that could improve local tumor control. Herein we evaluate daily online ART strategies regarding their impact on relevant dose-volume metrics. METHODS Daily cone-beam CTs (1 × n = 28, 1 × n = 29, 11 × n = 30) of 13 stage III NSCLC patients were converted into synthetic CTs (sCTs). Treatment plans (TPs) were created retrospectively on the first-fraction sCTs (sCT1) and subsequently transferred unaltered to the sCTs of the remaining fractions of each patient (sCT2-n) (IGRT scenario). Two additional TPs were generated on sCT2-n: one minimizing the lung-dose while preserving the D95%(PTV) (isoeffective scenario), the other escalating the D95%(PTV) with a constant V20Gy(lungipsilateral) (isotoxic scenario). RESULTS Compared to the original TPs predicted dose, the median D95%(PTV) in the IGRT scenario decreased by 1.6 Gy ± 4.2 Gy while the V20Gy(lungipsilateral) increased in median by 1.1% ± 4.4%. The isoeffective scenario preserved the PTV coverage and reduced the median V20Gy(lungipsilateral) by 3.1% ± 3.6%. Furthermore, the median V5%(heart) decreased by 2.9% ± 6.4%. With an isotoxic prescription, a median dose-escalation to the gross target volume of 10.0 Gy ± 8.1 Gy without increasing the V20Gy(lungipsilateral) and V5%(heart) was feasible. CONCLUSIONS We demonstrated that even without reducing safety margins, ART can reduce lung-doses, while still reaching adequate target coverage or escalate target doses without increasing ipsilateral lung exposure. Clinical benefits by means of toxicity and local control of both strategies should be evaluated in prospective clinical trials.
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Affiliation(s)
- Lea Hoppen
- Department of Radiation Oncology, University Medical Center Mannheim, University of Heidelberg, Theodor-Kutzer-Ufer 1-3, 68167, Mannheim, Germany.
| | - Gustavo R. Sarria
- grid.10388.320000 0001 2240 3300Department of Radiation Oncology, University Hospital Bonn, University of Bonn, Bonn, Germany
| | - Chung S. Kwok
- grid.7700.00000 0001 2190 4373Department of Radiation Oncology, University Medical Center Mannheim, University of Heidelberg, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
| | - Judit Boda-Heggemann
- grid.7700.00000 0001 2190 4373Department of Radiation Oncology, University Medical Center Mannheim, University of Heidelberg, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
| | - Daniel Buergy
- grid.7700.00000 0001 2190 4373Department of Radiation Oncology, University Medical Center Mannheim, University of Heidelberg, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
| | - Michael Ehmann
- grid.7700.00000 0001 2190 4373Department of Radiation Oncology, University Medical Center Mannheim, University of Heidelberg, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
| | - Frank A. Giordano
- grid.7700.00000 0001 2190 4373Department of Radiation Oncology, University Medical Center Mannheim, University of Heidelberg, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
| | - Jens Fleckenstein
- grid.7700.00000 0001 2190 4373Department of Radiation Oncology, University Medical Center Mannheim, University of Heidelberg, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
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20
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Gong H, Liu B, Zhang G, Dai X, Qu B, Cai B, Xie C, Xu S. Evaluation of Dose Calculation Based on Cone-Beam CT Using Different Measuring Correction Methods for Head and Neck Cancer Patients. Technol Cancer Res Treat 2023; 22:15330338221148317. [PMID: 36638542 PMCID: PMC9841465 DOI: 10.1177/15330338221148317] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023] Open
Abstract
Purpose: To investigate and compare 2 cone-beam computed tomography (CBCT) correction methods for CBCT-based dose calculation. Materials and Methods: Routine CBCT image sets of 12 head and neck cancer patients who received volumetric modulated arc therapy (VMAT) treatment were retrospectively analyzed. The CBCT images obtained using an on-board imager (OBI) at the first treatment fraction were firstly deformable registered and padded with the kVCT images to provide enough anatomical information about the tissues for dose calculation. Then, 2 CBCT correction methods were developed and applied to correct CBCT Hounsfield unit (HU) values. One method (HD method) is based on protocol-specific CBCT HU to physical density (HD) curve, and the other method (HM method) is based on histogram matching (HM) of HU value. The corrected CBCT images (CBCTHD and CBCTHM for HD and HM methods) were imported into the original planning system for dose calculation based on the HD curve of kVCT (the planning CT). The dose computation result was analyzed and discussed to compare these 2 CBCT-correction methods. Results: Dosimetric parameters, such as the Dmean, Dmax and D5% of the target volume in CBCT plan doses, were higher than those in the kVCT plan doses; however, the deviations were less than 2%. The D2%, in parallel organs such as the parotid glands, the deviations from the CBCTHM plan dose were less than those of the CBCTHD plan dose. The differences were statistically significant (P < .05). Meanwhile, the V30 value based on the HM method was better than that based on the HD method in the oral cavity region (P = .016). In addition, we also compared the γ passing rates of kVCT plan doses with the 2 CBCT plan doses, and negligible differences were found. Conclusion: The HM method was more suitable for head and neck cancer patients than the HD one. Furthermore, with the CBCTHM-based method, the dose calculation result better matches the kVCT-based dose calculation.
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Affiliation(s)
- Hanshun Gong
- Department of Radiation Oncology, The First Medical Center of PLA General
Hospital, Beijing, China
| | - Bo Liu
- School of Astronautics, Beihang
University, Beijing, China
| | - Gaolong Zhang
- School of Physics, Beihang
University, Beijing, China
| | - Xiangkun Dai
- Department of Radiation Oncology, The First Medical Center of PLA General
Hospital, Beijing, China
| | - Baolin Qu
- Department of Radiation Oncology, The First Medical Center of PLA General
Hospital, Beijing, China
| | - Boning Cai
- Department of Radiation Oncology, The First Medical Center of PLA General
Hospital, Beijing, China
| | - Chuanbin Xie
- Department of Radiation Oncology, The First Medical Center of PLA General
Hospital, Beijing, China
| | - Shouping Xu
- Department of Radiation Oncology, National Cancer Center/Cancer
Hospital, Chinese
Academy of Medical Sciences and Peking Union Medical
College, Beijing, China,National Cancer Center/National Clinical Research Center for
Cancer/Hebei Cancer Hospital, Chinese Academy of Medical
Sciences, Langfang, China,Shouping Xu, Department of Radiation
Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical
Sciences and Peking Union Medical College, Beijing, China.
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21
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Sakulsingharoj S, Kadoya N, Tanaka S, Sato K, Nakamura M, Jingu K. Dosimetric impact of deformable image registration using radiophotoluminescent glass dosimeters with a physical geometric phantom. J Appl Clin Med Phys 2023; 24:e13890. [PMID: 36609786 PMCID: PMC10113686 DOI: 10.1002/acm2.13890] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 11/04/2022] [Accepted: 12/15/2022] [Indexed: 01/09/2023] Open
Abstract
PURPOSE To study the dosimetry impact of deformable image registration (DIR) using radiophotoluminescent glass dosimeter (RPLD) and custom developed phantom with various inserts. METHODS The phantom was developed to facilitate simultaneous evaluation of geometric and dosimetric accuracy of DIR. Four computed tomography (CT) images of the phantom were acquired with four different configurations. Four volumetric modulated arc therapy (VMAT) plans were computed for different phantom. Two different patterns were applied to combination of four phantom configurations. RPLD dose measurement was combined between corresponding two phantom configurations. DIR-based dose accumulation was calculated between corresponding two CT images with two commercial DIR software and various DIR parameter settings, and an open source software. Accumulated dose calculated using DIR was then compared with measured dose using RPLD. RESULTS The mean ± standard deviation (SD) of dose difference was 2.71 ± 0.23% (range, 2.22%-3.01%) for tumor-proxy and 3.74 ± 0.79% (range, 1.56%-4.83%) for rectum-proxy. The mean ± SD of target registration error (TRE) was 1.66 ± 1.36 mm (range, 0.03-4.43 mm) for tumor-proxy and 6.87 ± 5.49 mm (range, 0.54-17.47 mm) for rectum-proxy. These results suggested that DIR accuracy had wide range among DIR parameter setting. CONCLUSIONS The dose difference observed in our study was 3% for tumor-proxy and within 5% for rectum-proxy. The custom developed physical phantom with inserts showed potential for accurate evaluation of DIR-based dose accumulation. The prospect of simultaneous evaluation of geometric and dosimetric DIR accuracy in a single phantom may be useful for validation of DIR for clinical use.
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Affiliation(s)
- Siwaporn Sakulsingharoj
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan.,Division of Radiation Oncology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Noriyuki Kadoya
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Shohei Tanaka
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Kiyokazu Sato
- Department of Radiation Technology, Tohoku University Hospital, Sendai, Japan
| | - Mitsuhiro Nakamura
- Department of Radiation Oncology and Image-Applied Therapy, Kyoto University, Kyoto, Japan.,Department of Information Technology and Medical Engineering, Human Health Sciences, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Keiichi Jingu
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan
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22
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Huesa-Berral C, Juan-Cruz C, van Kranen S, Rossi M, Belderbos J, Diego Azcona J, Burguete J, Sonke JJ. Detailed dosimetric evaluation of inter-fraction and respiratory motion in lung stereotactic body radiation therapy based on daily 4D cone beam CT images. Phys Med Biol 2022; 68. [PMID: 36538287 DOI: 10.1088/1361-6560/aca94d] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 12/06/2022] [Indexed: 12/12/2022]
Abstract
Objective. Periodic respiratory motion and inter-fraction variations are sources of geometric uncertainty in stereotactic body radiation therapy (SBRT) of pulmonary lesions. This study extensively evaluates and validates the separate and combined dosimetric effect of both factors using 4D-CT and daily 4D-cone beam CT (CBCT) dose accumulation scenarios.Approach. A first cohort of twenty early stage or metastatic disease lung cancer patients were retrospectively selected to evaluate each scenario. The planned-dose (3DRef) was optimized on a 3D mid-position CT. To estimate the dosimetric impact of respiratory motion (4DRef), inter-fractional variations (3DAcc) and the combined effect of both factors (4DAcc), three dose accumulation scenarios based on 4D-CT, daily mid-cone beam CT (CBCT) position and 4D-CBCT were implemented via CT-CT/CT-CBCT deformable image registration (DIR) techniques. Each scenario was compared to 3DRef.A separate cohort of ten lung SBRT patients was selected to validate DIR techniques. The distance discordance metric (DDM) was implemented per voxel and per patient for tumor and organs at risk (OARs), and the dosimetric impact for CT-CBCT DIR geometric errors was calculated.Main results.Median and interquartile range (IQR) of the dose difference per voxel were 0.05/2.69 Gy and -0.12/2.68 Gy for3DAcc-3DRefand4DAcc-3DRef.For4DRef-3DRefthe IQR was considerably smaller -0.15/0.78 Gy. These findings were confirmed by dose volume histogram parameters calculated in tumor and OARs. For CT-CT/CT-CBCT DIR validation, DDM (95th percentile) was highest for heart (6.26 mm)/spinal cord (8.00 mm), and below 3 mm for tumor and the rest of OARs. The dosimetric impact of CT-CBCT DIR errors was below 2 Gy for tumor and OARs.Significance. The dosimetric impact of inter-fraction variations were shown to dominate those of periodic respiration in SBRT for pulmonary lesions. Therefore, treatment evaluation and dose-effect studies would benefit more from dose accumulation focusing on day-to-day changes then those that focus on respiratory motion.
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Affiliation(s)
- Carlos Huesa-Berral
- Department of Radiation Oncology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands.,Physics and Applied Mathematics, School of Science, University of Navarra, E-31008 Pamplona, Navarra, Spain.,Service of Radiation Physics and Radiation Protection, University of Navarra Clinic, E-31008 Pamplona, Navarra, Spain
| | - Celia Juan-Cruz
- Department of Radiation Oncology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Simon van Kranen
- Department of Radiation Oncology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Maddalena Rossi
- Department of Radiation Oncology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - José Belderbos
- Department of Radiation Oncology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Juan Diego Azcona
- Service of Radiation Physics and Radiation Protection, University of Navarra Clinic, E-31008 Pamplona, Navarra, Spain
| | - Javier Burguete
- Physics and Applied Mathematics, School of Science, University of Navarra, E-31008 Pamplona, Navarra, Spain
| | - Jan-Jakob Sonke
- Department of Radiation Oncology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
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23
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Hamming VC, Andersson S, Maduro JH, Langendijk JA, Both S, Sijtsema NM. Daily dose evaluation based on corrected CBCTs for breast cancer patients: accuracy of dose and complication risk assessment. Radiat Oncol 2022; 17:205. [PMID: 36510254 PMCID: PMC9746176 DOI: 10.1186/s13014-022-02174-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Accepted: 11/30/2022] [Indexed: 12/14/2022] Open
Abstract
OBJECTIVES The goal of this study is to validate different CBCT correction methods to select the superior method that can be used for dose evaluation in breast cancer patients with large anatomical changes treated with photon irradiation. MATERIALS AND METHOD Seventy-six breast cancer patients treated with a partial VMAT photon technique (70% conformal, 30% VMAT) were included in this study. All patients showed at least a 5 mm variation (swelling or shrinkage) of the breast on the CBCT compared to the planning-CT (pCT) and had a repeat-CT (rCT) for dose evaluation acquired within 3 days of this CBCT. The original CBCT was corrected using four methods: (1) HU-override correction (CBCTHU), (2) analytical correction and conversion (CBCTCC), (3) deep learning (DL) correction (CTDL) and (4) virtual correction (CTV). Image quality evaluation consisted of calculating the mean absolute error (MAE) and mean error (ME) within the whole breast clinical target volume (CTV) and the field of view of the CBCT minus 2 cm (CBCT-ROI) with respect to the rCT. The dose was calculated on all image sets using the clinical treatment plan for dose and gamma passing rate analysis. RESULTS The MAE of the CBCT-ROI was below 66 HU for all corrected CBCTs, except for the CBCTHU with a MAE of 142 HU. No significant dose differences were observed in the CTV regions in the CBCTCC, CTDL and CTv. Only the CBCTHU deviated significantly (p < 0.01) resulting in 1.7% (± 1.1%) average dose deviation. Gamma passing rates were > 95% for 2%/2 mm for all corrected CBCTs. CONCLUSION The analytical correction and conversion, deep learning correction and virtual correction methods can be applied for an accurate CBCT correction that can be used for dose evaluation during the course of photon radiotherapy of breast cancer patients.
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Affiliation(s)
- Vincent C. Hamming
- grid.4830.f0000 0004 0407 1981Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, The Netherlands
| | | | - John H. Maduro
- grid.4830.f0000 0004 0407 1981Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, The Netherlands
| | - Johannes A. Langendijk
- grid.4830.f0000 0004 0407 1981Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, The Netherlands
| | - Stefan Both
- grid.4830.f0000 0004 0407 1981Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, The Netherlands
| | - Nanna M. Sijtsema
- grid.4830.f0000 0004 0407 1981Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, The Netherlands
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24
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Lim R, Penoncello GP, Hobbis D, Harrington DP, Rong Y. Technical note: Characterization of novel iterative reconstructed cone beam CT images for dose tracking and adaptive radiotherapy on L-shape linacs. Med Phys 2022; 49:7715-7732. [PMID: 36031929 DOI: 10.1002/mp.15943] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 08/05/2022] [Accepted: 08/10/2022] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND Cone-beam computed tomography (CBCT) allows for patient setup and positioning, and potentially dose verification or adaptive replanning prior to each treatment delivery. Poor CBCT image quality due to scatter artifacts and patient motion has been a major limiting factor. A new image reconstruction algorithm was recently clinically implemented for improving image quality through iterative reconstruction (iCBCT). PURPOSE This study aims to characterize iCBCT image quality, establish image value (HU)-to-relative electron density (RED) calibration curves for dose calculation, and assess the dosimetric accuracy for different anatomical sites. MATERIAL AND METHODS Both conventional CBCT and iCBCT scans were acquired from a Varian TrueBeam On-Board Imager system. A Catphan 604 phantom was scanned to compare image quality between the traditional Feldkamp-Davis-Kress (FDK) and novel iterative reconstruction techniques. Computerized Imaging Reference Systems (CIRS) electron density phantom was used to construct site-specific HU-RED curves corresponding to various scan settings. The CIRS Dynamic Thorax phantom, Rando pelvis phantom, and BrainLab head phantom were used for assessing dosimetric accuracy calculated on iCBCT images, compared to that on traditional FDK-based CBCT images. All phantoms were scanned on a computed tomography (CT) to obtain baseline HU values for comparison. RESULTS Test results obtained from Catphan showed statistically significant improvement with iCBCT, compared to FDK CBCT. Average HU differences from the baseline CT values were improved to within ±30 HU for iCBCT, compared to FDK CBCT for phantom studies. Dose calculated on iCBCT for both phantoms and patient cases directly using baseline HU-RED calibration from CT showed 0.5%-2.0% accuracy from the baseline dose calculated on CT, which is comparable to doses calculated using site-specific HU-RED calibration curves. CONCLUSION iCBCT provides improved image quality, improved HU accuracy compared to CT baseline, and has potential to provide online dose verification as part of the adaptive radiotherapy workflow directly using the baseline HU-RED calibration curve from CT.
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Affiliation(s)
- Rebecca Lim
- Department of Radiation Oncology, Mayo Clinic, Phoenix, Arizona, USA.,Department of Physics, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Gregory P Penoncello
- Department of Radiation Oncology, Mayo Clinic, Phoenix, Arizona, USA.,Department of Radiation Oncology, University of Colorado, Aurora, Colorado, USA
| | - Dean Hobbis
- Department of Radiation Oncology, Mayo Clinic, Phoenix, Arizona, USA
| | | | - Yi Rong
- Department of Radiation Oncology, Mayo Clinic, Phoenix, Arizona, USA
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25
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Chen L, Zhang Z, Yu L, Peng J, Feng B, Zhao J, Liu Y, Xia F, Zhang Z, Hu W, Wang J. A clinically relevant online patient QA solution with daily CT scans and EPID-based in vivo dosimetry: a feasibility study on rectal cancer. Phys Med Biol 2022; 67. [DOI: 10.1088/1361-6560/ac9950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 10/11/2022] [Indexed: 11/06/2022]
Abstract
Abstract
Objective. Adaptive radiation therapy (ART) could protect organs at risk (OARs) while maintain high dose coverage to targets. However, there is still a lack of efficient online patient quality assurance (QA) methods, which is an obstacle to large-scale adoption of ART. We aim to develop a clinically relevant online patient QA solution for ART using daily CT scans and EPID-based in vivo dosimetry. Approach. Ten patients with rectal cancer at our center were included. Patients’ daily CT scans and portal images were collected to generate reconstructed 3D dose distributions. Contours of targets and OARs were recontoured on these daily CT scans by a clinician or an auto-segmentation algorithm, then dose-volume indices were calculated, and the percent deviation of these indices to their original plans were determined. This deviation was regarded as the metric for clinically relevant patient QA. The tolerance level was obtained using a 95% confidence interval of the QA metric distribution. These deviations could be further divided into anatomically relevant or delivery relevant indicators for error source analysis. Finally, our QA solution was validated on an additional six clinical patients. Main results. In rectal cancer, the 95% confidence intervals of the QA metric for PTV ΔD
95 (%) were [−3.11%, 2.35%], and for PTV ΔD
2 (%) were [−0.78%, 3.23%]. In validation, 68% for PTV ΔD
95 (%), and 79% for PTV ΔD
2 (%) of the 28 fractions are within tolerances of the QA metrics. one patient’s dosimetric impact of anatomical variations during treatment were observed through the source of error analysis. Significance. The online patient QA solution using daily CT scans and EPID-based in vivo dosimetry is clinically feasible. Source of error analysis has the potential for distinguishing sources of error and guiding ART for future treatments.
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An online adaptive plan library approach for intensity modulated proton therapy for head and neck cancer. Radiother Oncol 2022; 176:68-75. [PMID: 36150418 DOI: 10.1016/j.radonc.2022.09.011] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 08/25/2022] [Accepted: 09/13/2022] [Indexed: 12/14/2022]
Abstract
BACKGROUND AND PURPOSE In intensity modulated proton therapy (IMPT), the impact of setup errors and anatomical changes is commonly mitigated by robust optimization with population-based setup robustness (SR) settings and offline replanning. In this study we propose and evaluate an alternative approach based on daily plan selection from patient-specific pre-treatment established plan libraries (PLs). Clinical implementation of the PL strategy would be rather straightforward compared to daily online re-planning. MATERIALS AND METHODS For 15 head-and-neck cancer patients, the planning CT was used to generate a PL with 5 plans, robustly optimized for increasing SR: 0, 1, 2, 3, 5 mm, and 3% range robustness. Repeat CTs (rCTs) and realistic setup and range uncertainty distributions were used for simulation of treatment courses for the PL approach, treatments with fixed SR (fSR3) and a trigger-based offline adaptive schedule for 3 mm SR (fSR3OfA). Daily plan selection in the PL approach was based only on recomputed dose to the CTV on the rCT. RESULTS Compared to using fSR3 and fSR3OfA, the risk of xerostomia grade ≥ II & III and dysphagia ≥ grade III were significantly reduced with the PL. For 6/15 patients the risk of xerostomia and/or dysphagia ≥ grade II could be reduced by > 2% by using PL. For the other patients, adherence to target coverage constraints was often improved. fSR3OfA resulted in significantly improved coverage compared to PL for selected patients. CONCLUSION The proposed PL approach resulted in overall reduced NTCPs compared to fSR3 and fSR3OfA at limited cost in target coverage.
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27
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Evaluation of CBCT based dose calculation in the thorax and pelvis using two generic algorithms. Phys Med 2022; 103:157-165. [DOI: 10.1016/j.ejmp.2022.10.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 09/26/2022] [Accepted: 10/22/2022] [Indexed: 11/24/2022] Open
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28
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Thummerer A, Seller Oria C, Zaffino P, Visser S, Meijers A, Guterres Marmitt G, Wijsman R, Seco J, Langendijk JA, Knopf AC, Spadea MF, Both S. Deep learning-based 4D-synthetic CTs from sparse-view CBCTs for dose calculations in adaptive proton therapy. Med Phys 2022; 49:6824-6839. [PMID: 35982630 PMCID: PMC10087352 DOI: 10.1002/mp.15930] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Revised: 07/20/2022] [Accepted: 08/08/2022] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Time-resolved 4D cone beam-computed tomography (4D-CBCT) allows a daily assessment of patient anatomy and respiratory motion. However, 4D-CBCTs suffer from imaging artifacts that affect the CT number accuracy and prevent accurate proton dose calculations. Deep learning can be used to correct CT numbers and generate synthetic CTs (sCTs) that can enable CBCT-based proton dose calculations. PURPOSE In this work, sparse view 4D-CBCTs were converted into 4D-sCT utilizing a deep convolutional neural network (DCNN). 4D-sCTs were evaluated in terms of image quality and dosimetric accuracy to determine if accurate proton dose calculations for adaptive proton therapy workflows of lung cancer patients are feasible. METHODS A dataset of 45 thoracic cancer patients was utilized to train and evaluate a DCNN to generate 4D-sCTs, based on sparse view 4D-CBCTs reconstructed from projections acquired with a 3D acquisition protocol. Mean absolute error (MAE) and mean error were used as metrics to evaluate the image quality of single phases and average 4D-sCTs against 4D-CTs acquired on the same day. The dosimetric accuracy was checked globally (gamma analysis) and locally for target volumes and organs-at-risk (OARs) (lung, heart, and esophagus). Furthermore, 4D-sCTs were also compared to 3D-sCTs. To evaluate CT number accuracy, proton radiography simulations in 4D-sCT and 4D-CTs were compared in terms of range errors. The clinical suitability of 4D-sCTs was demonstrated by performing a 4D dose reconstruction using patient specific treatment delivery log files and breathing signals. RESULTS 4D-sCTs resulted in average MAEs of 48.1 ± 6.5 HU (single phase) and 37.7 ± 6.2 HU (average). The global dosimetric evaluation showed gamma pass ratios of 92.3% ± 3.2% (single phase) and 94.4% ± 2.1% (average). The clinical target volume showed high agreement in D98 between 4D-CT and 4D-sCT, with differences below 2.4% for all patients. Larger dose differences were observed in mean doses of OARs (up to 8.4%). The comparison with 3D-sCTs showed no substantial image quality and dosimetric differences for the 4D-sCT average. Individual 4D-sCT phases showed slightly lower dosimetric accuracy. The range error evaluation revealed that lung tissues cause range errors about three times higher than the other tissues. CONCLUSION In this study, we have investigated the accuracy of deep learning-based 4D-sCTs for daily dose calculations in adaptive proton therapy. Despite image quality differences between 4D-sCTs and 3D-sCTs, comparable dosimetric accuracy was observed globally and locally. Further improvement of 3D and 4D lung sCTs could be achieved by increasing CT number accuracy in lung tissues.
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Affiliation(s)
- Adrian Thummerer
- Department, of Radiation Oncology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Carmen Seller Oria
- Department, of Radiation Oncology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Paolo Zaffino
- Department of Experimental and Clinical Medicine, Magna Graecia University, Catanzaro, Italy
| | - Sabine Visser
- Department, of Radiation Oncology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Arturs Meijers
- Department, of Radiation Oncology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.,Center for Proton Therapy, Paul Scherrer Institute, Villigen, Switzerland
| | - Gabriel Guterres Marmitt
- Department, of Radiation Oncology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Robin Wijsman
- Department, of Radiation Oncology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Joao Seco
- Department of Biomedical Physics in Radiation Oncology, Deutsches Krebsforschungszentrum (DKFZ), Heidelberg, Germany.,Department of Physics and Astronomy, Heidelberg University, Heidelberg, Germany
| | - Johannes Albertus Langendijk
- Department, of Radiation Oncology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Antje Christin Knopf
- Department, of Radiation Oncology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.,Department I of Internal Medicine, Center for Integrated Oncology Cologne, University Hospital of Cologne, Cologne, Germany
| | - Maria Francesca Spadea
- Department of Experimental and Clinical Medicine, Magna Graecia University, Catanzaro, Italy
| | - Stefan Both
- Department, of Radiation Oncology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
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O'Hara CJ, Bird D, Al-Qaisieh B, Speight R. Assessment of CBCT-based synthetic CT generation accuracy for adaptive radiotherapy planning. J Appl Clin Med Phys 2022; 23:e13737. [PMID: 36200179 DOI: 10.1002/acm2.13737] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 05/26/2022] [Accepted: 07/04/2022] [Indexed: 11/09/2022] Open
Abstract
PURPOSE Cone-beam CT (CBCT)-based synthetic CT (sCT) dose calculation has the potential to make the adaptive radiotherapy (ART) pathway more efficient while removing subjectivity. This study assessed four sCT generation methods using 15 head-and-neck rescanned ART patients. Each patient's planning CT (pCT), rescan CT (rCT), and CBCT post-rCT was acquired with the CBCT deformably registered to the rCT (dCBCT). METHODS The four methods investigated were as follows: method 1-deformably registering the pCT to the dCBCT. Method 2-assigning six mass density values to the dCBCT. Method 3-iteratively removing artifacts and correcting the dCBCT Hounsfield units (HU). Method 4-using a cycle general adversarial network machine learning model (trained with 45 paired pCT and CBCT). Treatment plans were created on the rCT and recalculated on each sCT. Planning target volume (PTV) and organ-at-risk (OAR) structures were contoured by clinicians on the rCT (high-dose PTV, low-dose PTV, spinal canal, larynx, brainstem, and parotids) to allow the assessment of dose-volume histogram statistics at clinically relevant points. RESULTS The HU mean absolute error (MAE) and minimum dose gamma index pass rate (2%/2 mm) were calculated, and the generation time was measured for 15 patients using the rCT as the comparator. For methods 1-4 the MAE, gamma index analysis, and generation time were as follows: 59.7 HU, 100.0%, and 143 s; 164.2 HU, 95.2%, and 232 s; 75.7 HU, 99.9%, and 153 s; and 79.4 HU, 99.8%, and 112 s, respectively. Dose differences for PTVs and OARs were all <0.3 Gy except for method 2 (<0.5 Gy). CONCLUSION All methods were considered clinically viable. The machine learning method was found to be most suitable for clinical implementation due to its high dosimetric accuracy and short generation time. Further investigation is required for larger anatomical changes between the CBCT and pCT and for other anatomical sites.
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Affiliation(s)
| | - David Bird
- Leeds Cancer Centre, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | | | - Richard Speight
- Leeds Cancer Centre, Leeds Teaching Hospitals NHS Trust, Leeds, UK
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30
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Argota-Perez R, Sharma MB, Elstrøm UV, Møller DS, Grau C, Jensen K, Holm AIS, Korreman SS. Dose and robustness comparison of nominal, daily and accumulated doses for photon and proton treatment of sinonasal cancer. Radiother Oncol 2022; 173:102-108. [PMID: 35667574 DOI: 10.1016/j.radonc.2022.05.038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Revised: 05/30/2022] [Accepted: 05/31/2022] [Indexed: 11/16/2022]
Abstract
INTRODUCTION The aim was to evaluate and compare the dosimetric effect and robustness towards day-to-day anatomical and setup variations in the delivered dose for photon and proton treatments of sinonasal cancer (SNC) patients. MATERIALS AND METHODS Photon (VMAT) and proton (IMPT) plans were optimized retrospectively for 24 SNC patients. Synthetic CTs (synCT) were obtained by deforming the planning CT (pCT) to the anatomy of every daily cone-beam CT. Both VMAT and IMPT plans were recalculated on the synCTs. The recalculated daily dose was accumulated over the whole treatment on the pCT. Target coverage and dose to organs and risk (OARs) were evaluated for all patients for the nominal, daily and accumulated dose distribution. RESULTS In general, dose to OARs farther away from the target, including brain, chiasm and contralateral optic nerve, was lower for proton plans than photon plans. Whereas, OARs in proximity of the target received a lower dose for photon plans. For proton plans, the target coverage (volume of CTV receiving 95% of prescribed dose), V95%, fell below 99% for 9/24 patients in one or more fractions. For photon plans, 4/24 patients had one or more fractions where V95% fell below 99%. For accumulated doses, V95% was below 99% only in two cases, but above 98% for all patients. CONCLUSION Photon and proton treatment have different strengths regarding OAR sparing. The robustness was high for both treatment modalities. Patient selection for either proton or photon radiation therapy of SNC patients should be based on a case-by-case comparison.
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Affiliation(s)
- R Argota-Perez
- Department of Oncology, Aarhus University Hospital, Denmark
| | - M B Sharma
- Department of Oncology, Aarhus University Hospital, Denmark
| | - U V Elstrøm
- Danish Center for Particle Therapy, Aarhus University Hospital, Denmark
| | - D S Møller
- Department of Oncology, Aarhus University Hospital, Denmark
| | - C Grau
- Department of Oncology, Aarhus University Hospital, Denmark; Danish Center for Particle Therapy, Aarhus University Hospital, Denmark; Department of Clinical Medicine, Aarhus University, Denmark
| | - K Jensen
- Danish Center for Particle Therapy, Aarhus University Hospital, Denmark
| | - A I S Holm
- Department of Oncology, Aarhus University Hospital, Denmark.
| | - S S Korreman
- Department of Oncology, Aarhus University Hospital, Denmark; Danish Center for Particle Therapy, Aarhus University Hospital, Denmark; Department of Clinical Medicine, Aarhus University, Denmark
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31
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Li H, Hrinivich WT, Chen H, Sheikh K, Ho MW, Ger R, Liu D, Hales RK, Voong KR, Halthore A, Deville C. Evaluating Proton Dose and Associated Range Uncertainty Using Daily Cone-Beam CT. Front Oncol 2022; 12:830981. [PMID: 35449577 PMCID: PMC9016186 DOI: 10.3389/fonc.2022.830981] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 03/02/2022] [Indexed: 11/13/2022] Open
Abstract
Purpose This study aimed to quantitatively evaluate the range uncertainties that arise from daily cone-beam CT (CBCT) images for proton dose calculation compared to CT using a measurement-based technique. Methods For head and thorax phantoms, wedge-shaped intensity-modulated proton therapy (IMPT) treatment plans were created such that the gradient of the wedge intersected and was measured with a 2D ion chamber array. The measured 2D dose distributions were compared with 2D dose planes extracted from the dose distributions using the IMPT plan calculated on CT and CBCT. Treatment plans of a thymoma cancer patient treated with breath-hold (BH) IMPT were recalculated on 28 CBCTs and 9 CTs, and the resulting dose distributions were compared. Results The range uncertainties for the head phantom were determined to be 1.2% with CBCT, compared to 0.5% for CT, whereas the range uncertainties for the thorax phantom were 2.1% with CBCT, compared to 0.8% for CT. The doses calculated on CBCT and CT were similar with similar anatomy changes. For the thymoma patient, the primary source of anatomy change was the BH uncertainty, which could be up to 8 mm in the superior-inferior (SI) direction. Conclusion We developed a measurement-based range uncertainty evaluation method with high sensitivity and used it to validate the accuracy of CBCT-based range and dose calculation. Our study demonstrated that the CBCT-based dose calculation could be used for daily dose validation in selected proton patients.
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Affiliation(s)
- Heng Li
- Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - William T Hrinivich
- Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Hao Chen
- Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Khadija Sheikh
- Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Meng Wei Ho
- Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Rachel Ger
- Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Dezhi Liu
- Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Russell Kenneth Hales
- Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Khinh Ranh Voong
- Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Aditya Halthore
- Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Curtiland Deville
- Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
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Usui K, Ogawa K, Goto M, Sakano Y, Kyougoku S, Daida H. A cycle generative adversarial network for improving the quality of four-dimensional cone-beam computed tomography images. Radiat Oncol 2022; 17:69. [PMID: 35392947 PMCID: PMC8991563 DOI: 10.1186/s13014-022-02042-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 03/23/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Four-dimensional cone-beam computed tomography (4D-CBCT) can visualize moving tumors, thus adaptive radiation therapy (ART) could be improved if 4D-CBCT were used. However, 4D-CBCT images suffer from severe imaging artifacts. The aim of this study is to investigate the use of synthetic 4D-CBCT (sCT) images created by a cycle generative adversarial network (CycleGAN) for ART for lung cancer. METHODS Unpaired thoracic 4D-CBCT images and four-dimensional multislice computed tomography (4D-MSCT) images of 20 lung-cancer patients were used for training. High-quality sCT lung images generated by the CycleGAN model were tested on another 10 cases. The mean and mean absolute errors were calculated to assess changes in the computed tomography number. The structural similarity index measure (SSIM) and peak signal-to-noise ratio (PSNR) were used to compare the sCT and original 4D-CBCT images. Moreover, a volumetric modulation arc therapy plan with a dose of 48 Gy in four fractions was recalculated using the sCT images and compared with ideal dose distributions observed in 4D-MSCT images. RESULTS The generated sCT images had fewer artifacts, and lung tumor regions were clearly observed in the sCT images. The mean and mean absolute errors were near 0 Hounsfield units in all organ regions. The SSIM and PSNR results were significantly improved in the sCT images by approximately 51% and 18%, respectively. Moreover, the results of gamma analysis were significantly improved; the pass rate reached over 90% in the doses recalculated using the sCT images. Moreover, each organ dose index of the sCT images agreed well with those of the 4D-MSCT images and were within approximately 5%. CONCLUSIONS The proposed CycleGAN enhances the quality of 4D-CBCT images, making them comparable to 4D-MSCT images. Thus, clinical implementation of sCT-based ART for lung cancer is feasible.
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Affiliation(s)
- Keisuke Usui
- Department of Radiological Technology, Faculty of Health Science, Juntendo University, 2-1-1, Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan.
| | - Koichi Ogawa
- Department of Applied Informatics, Faculty of Science and Engineering, Hosei University, 3-7-3, Kajino, Koganei, Tokyo, 184-8584, Japan
| | - Masami Goto
- Department of Radiological Technology, Faculty of Health Science, Juntendo University, 2-1-1, Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
| | - Yasuaki Sakano
- Department of Radiological Technology, Faculty of Health Science, Juntendo University, 2-1-1, Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
| | - Shinsuke Kyougoku
- Department of Radiological Technology, Faculty of Health Science, Juntendo University, 2-1-1, Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
| | - Hiroyuki Daida
- Department of Radiological Technology, Faculty of Health Science, Juntendo University, 2-1-1, Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
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Ma T, Liu CW, Ahmed S, Yu N, Qi P, Stephans KL, Videtic GM, Xia P. Is adaptive planning necessary for patients with large tumor position displacements observed on daily image guidance during lung SBRT? Med Dosim 2022; 47:207-215. [DOI: 10.1016/j.meddos.2022.02.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 02/18/2022] [Accepted: 02/23/2022] [Indexed: 11/26/2022]
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Božanić A, Šegota D, Debeljuh DD, Kolacio MŠ, Radojčić ĐS, Ružić K, Budanec M, Kasabašić M, Hrepić D, Valković Zujić P, Brambilla M, Kalra MK, Jurković S. National reference levels of CT procedures dedicated for treatment planning in radiation oncology. Phys Med 2022; 96:123-129. [PMID: 35278930 DOI: 10.1016/j.ejmp.2022.03.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2021] [Revised: 02/16/2022] [Accepted: 03/02/2022] [Indexed: 11/17/2022] Open
Abstract
OBJECTIVE To present results of the first national survey on reference levels of CT imaging performed for the treatment planning purposes in radiation oncology in Croatia. METHODS Data for CT protocols of five anatomical regions including head, head and neck, pelvis, breast, and thorax were collected at eight radiation oncology departments in Croatia. Data included volume CT dose index (CTDIvol), dose-length product (DLP), scan length and set of acquisition and reconstruction parameters. Data on a total of 600 patients were collected. Median values of scan length, DLP and CTDIvol were calculated for each acquisition protocol. Third quartiles of the median CTDIvol and DLP values were proposed as the national radiotherapy planning reference levels (RPRL). RESULTS The largest CoV were assessed for RT Breast (63.8% for CTDIvol), RT Thorax (79.7% for DLP) and RT H&N (21.2% for scan length). RT Head had the lowest CoV for CTDIvol (1,9%) and DLP (17,2%), while RT Breast had the lowest coefficient of variation for scan length (12.8%). Proposed national RPRLs are: for RT Head CTDIvol16cm = 62 mGy and DLP16cm = 1738 mGy.cm; for RT H&N CTDIvol16cm = 35 mGy and DLP16cm = 1444 mGy.cm; for RT Breast CTDIvol32cm = 16 mGy and DLP32cm = 731 mGy.cm; for RT Thorax CTDIvol32cm = 17 mGy and DLP32cm = 865 mGy.cm; for RT Pelvis CTDIvol32cm = 20 mGy and DLP32cm = 1133 mGy.cm. CONCLUSIONS Results of this study show variations in CT imaging for treatment planning practice at the national level which call for optimization of procedures.
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Affiliation(s)
- Ana Božanić
- Medical Physics and Radiation Protection Department, Clinical Hospital Centre Rijeka, Krešimirova 42, Rijeka, Croatia; Medical Physics and Biophysics Department, Medical Faculty, University of Rijeka, Braće Branchetta 20, Rijeka, Croatia.
| | - Doris Šegota
- Medical Physics and Radiation Protection Department, Clinical Hospital Centre Rijeka, Krešimirova 42, Rijeka, Croatia
| | - Dea Dundara Debeljuh
- Medical Physics and Radiation Protection Department, Clinical Hospital Centre Rijeka, Krešimirova 42, Rijeka, Croatia; Medical Physics and Biophysics Department, Medical Faculty, University of Rijeka, Braće Branchetta 20, Rijeka, Croatia; Radiology Department, General Hospital Pula, Santiorova 24a, Pula, Croatia
| | - Manda Švabić Kolacio
- Medical Physics and Radiation Protection Department, Clinical Hospital Centre Rijeka, Krešimirova 42, Rijeka, Croatia
| | - Đeni Smilović Radojčić
- Medical Physics and Radiation Protection Department, Clinical Hospital Centre Rijeka, Krešimirova 42, Rijeka, Croatia; Medical Physics and Biophysics Department, Medical Faculty, University of Rijeka, Braće Branchetta 20, Rijeka, Croatia
| | - Katarina Ružić
- Department of Medical Physics, The University Hospital Centre Zagreb, Kišpatićeva 12, Zagreb, Croatia
| | - Mirjana Budanec
- University Clinical Hospital Center Sestre Milosrdnice, Department of Medical Physics, Vinogradska 29, Zagreb, Croatia
| | - Mladen Kasabašić
- Osijek University Hospital, Department of Medical Physics, Osijek, Josipa Huttlera 4, Croatia
| | - Darijo Hrepić
- Department of Medical Physics, University Hospital of Split, Spinčićeva 1, Split, Croatia
| | - Petra Valković Zujić
- Radiology Department, University Hospital Rijeka, Krešimirova 42, Rijeka, Croatia; Radiology Department, Medical Faculty, University of Rijeka, Braće Branchetta 20, Rijeka, Croatia
| | - Marco Brambilla
- Department of Medical Physics, Azienda Ospedaliero Universitaria Maggiore della Carità, Novara, Italy
| | - Mannudeep K Kalra
- Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Slaven Jurković
- Medical Physics and Radiation Protection Department, Clinical Hospital Centre Rijeka, Krešimirova 42, Rijeka, Croatia; Medical Physics and Biophysics Department, Medical Faculty, University of Rijeka, Braće Branchetta 20, Rijeka, Croatia
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Dosimetric Comparison of Ultra-Hypofractionated and Conventionally Fractionated Radiation Therapy Boosts for Patients with High-Risk Prostate Cancer. Life (Basel) 2022; 12:life12030394. [PMID: 35330145 PMCID: PMC8951141 DOI: 10.3390/life12030394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Revised: 03/04/2022] [Accepted: 03/07/2022] [Indexed: 11/23/2022] Open
Abstract
Recent comparison of an ultra-hypofractionated radiotherapy (UF-RT) boost to a conventionally fractionated (CF-RT) option showed similar toxicity and disease control outcomes. An analysis of the treatment plans for these patients is needed for evaluating calculated doses for different organs, treatment beam-on time, and requirements for human and financial resources. Eighty-six plans for UF-RT and 93 plans for CF-RT schemes were evaluated. The biologically equivalent dose, EQD2, summed for the first phase and the boost, was calculated for dose-volume parameters for organs at risk (OARs), as well as for the PTV1. ArcCHECK measurements for the boost plans were used for a comparison of planned and delivered doses. Monitor units and beam-on times were recorded by the Eclipse treatment planning system. Statistical analysis was performed with a significance level of 0.05. Dosimetric parameter values for OARs were well within tolerance for both groups. EQD2 for the PTV1 was on average 84 Gy for UF-RT patients and 76 Gy for CF-RT patients. Gamma passing rate for planned/delivered doses comparison was above 98% for both groups with 3 mm/3% distance to agreement/dose difference criteria. Total monitor units per fraction were 647 ± 94 and 2034 ± 570 for CF-RT and UF-RT, respectively. The total delivery time for boost radiation for the patients in the UF-RT arm was, on average, four times less than the total time for a conventional regimen with statistically equal clinical outcomes for the two arms in this study.
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Czajkowski P, Piotrowski T. Evaluation of the accuracy of dose delivery in stereotactic radiotherapy using the Velocity commercial software. Phys Med 2022; 95:133-139. [DOI: 10.1016/j.ejmp.2022.02.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Revised: 01/31/2022] [Accepted: 02/04/2022] [Indexed: 12/18/2022] Open
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Shinde P, Jadhav A, Shankar V, Gupta KK, Dhoble NS, Dhoble SJ. Evaluation of kV-CBCT based 3D dose calculation accuracy and its validation using delivery fluence derived dose metrics in Head and Neck Cancer. Phys Med 2022; 96:32-45. [PMID: 35217498 DOI: 10.1016/j.ejmp.2022.02.014] [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: 06/19/2021] [Revised: 02/11/2022] [Accepted: 02/12/2022] [Indexed: 10/19/2022] Open
Abstract
PURPOSE The purpose of this study is to evaluate the dosimetric impact of Hounsfield unit (HU) variations in kilovoltage cone-beam computed tomography (kV-CBCT) based 3D dose calculation accuracy in the treatment planning system and its validation using measured treatment delivery dose (MTDD) derived dose metrics for Volumetric Modulated Arc Therapy (VMAT) and Intensity Modulated Radiotherapy (IMRT) plans in Head and Neck (HN) Cancer. METHODS CBCT dose calculation accuracy was evaluated for 8 VMAT plans on inhomogeneous phantom and 40 VMAT and IMRT plans of HN Cancer patients and validated using ArcCHECK diode array MTDD derived 3D dose metric on CT and CBCT. RESULTS The mean percentage dose difference between CBCT and CT in TPS (ΔD(CBCT-CT)TPS) and 3DVH (ΔD(CBCT-CT)3DVH) were compared for the corresponding evaluation dose metrics (D98%, D95%, D50%, D2%, Dmax, D1cc, D0.03cc, Dmean) of all PTVs and OARs in phantom and patients. ΔD(CBCT-CT)TPS and ΔD(CBCT-CT)3DVH for all evaluation dose points of all PTVs and OARs were less than 2.55% in phantom and 2.4% in HN patients. The Pearson correlation coefficient (r) between ΔD(CBCT-CT)TPS and ΔD(CBCT-CT)3DVH for all dose points in all PTVs and OARs showed a strong to moderate correlation in phantom and patients with p < 0.001. CONCLUSIONS This study evaluated and validated the potential feasibility of kV-CBCT for treatment plan 3D dose reconstruction in clinical decision making for Adaptive radiotherapy on CT in Head and Neck cancer.
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Affiliation(s)
- Prashantkumar Shinde
- Department of Physics, Rashtrasant Tukadoji Maharaj Nagpur University, Nagpur 440033, India
| | - Anand Jadhav
- Department of Radiation Oncology, Sir H N Reliance Foundation Hospital and Research Centre, Mumbai 400004, India
| | - V Shankar
- Department of Radiation Oncology, Apollo Cancer Center, Chennai 600035, India
| | - Karan Kumar Gupta
- Department of Chemical Engineering, National Taiwan University, Taipei, Taiwan, ROC.
| | - Nirupama S Dhoble
- Department of Chemistry, Sevadal Mahila Mahavidhyalay, Nagpur 440015, India
| | - Sanjay J Dhoble
- Department of Physics, Rashtrasant Tukadoji Maharaj Nagpur University, Nagpur 440033, India.
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Xue X, Ding Y, Shi J, Hao X, Li X, Li D, Wu Y, An H, Jiang M, Wei W, Wang X. Cone Beam CT (CBCT) Based Synthetic CT Generation Using Deep Learning Methods for Dose Calculation of Nasopharyngeal Carcinoma Radiotherapy. Technol Cancer Res Treat 2021; 20:15330338211062415. [PMID: 34851204 PMCID: PMC8649448 DOI: 10.1177/15330338211062415] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Objective: To generate synthetic CT (sCT) images with high quality
from CBCT and planning CT (pCT) for dose calculation by using deep learning
methods. Methods: 169 NPC patients with a total of 20926 slices of
CBCT and pCT images were included. In this study the CycleGAN, Pix2pix and U-Net
models were used to generate the sCT images. The Mean Absolute Error (MAE), Root
Mean Squared Error (RMSE), Peak Signal to Noise Ratio (PSNR), and Structural
Similarity Index (SSIM) were used to quantify the accuracy of the proposed
models in a testing cohort of 34 patients. Radiation dose were calculated on pCT
and sCT following the same protocol. Dose distributions were evaluated for 4
patients by comparing the dose-volume-histogram (DVH) and 2D gamma index
analysis. Results: The average MAE and RMSE values between sCT by
three models and pCT reduced by 15.4 HU and 26.8 HU at least, while the mean
PSNR and SSIM metrics between sCT by different models and pCT added by 10.6 and
0.05 at most, respectively. There were only slight differences for DVH of
selected contours between different plans. The passing rates of 2D gamma index
analysis under 3 mm/3% 3 mm/2%, 2 mm/3%and 2 mm/2% criteria were all higher than
95%. Conclusions: All the sCT had achieved better evaluation
metrics than those of original CBCT, while the performance of CycleGAN model was
proved to be best among three methods. The dosimetric agreement confirmed the HU
accuracy and consistent anatomical structures of sCT by deep learning
methods.
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Affiliation(s)
- Xudong Xue
- 117922Hubei Cancer Hospital, Tongji Medical College, Huzhong University of Science and Technology, Wuhan, Hubei, China
| | - Yi Ding
- 117922Hubei Cancer Hospital, Tongji Medical College, Huzhong University of Science and Technology, Wuhan, Hubei, China
| | - Jun Shi
- 546497School of Computer Science and Technology, 12652University of Science and Technology of China, Hefei, 117556Anhui, China
| | - Xiaoyu Hao
- 546497School of Computer Science and Technology, 12652University of Science and Technology of China, Hefei, 117556Anhui, China
| | - Xiangbin Li
- 117922Hubei Cancer Hospital, Tongji Medical College, Huzhong University of Science and Technology, Wuhan, Hubei, China
| | - Dan Li
- 117922Hubei Cancer Hospital, Tongji Medical College, Huzhong University of Science and Technology, Wuhan, Hubei, China
| | - Yuan Wu
- 117922Hubei Cancer Hospital, Tongji Medical College, Huzhong University of Science and Technology, Wuhan, Hubei, China
| | - Hong An
- 546497School of Computer Science and Technology, 12652University of Science and Technology of China, Hefei, 117556Anhui, China
| | - Man Jiang
- School of Energy and Power Engineering, 12443Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Wei Wei
- 117922Hubei Cancer Hospital, Tongji Medical College, Huzhong University of Science and Technology, Wuhan, Hubei, China
| | - Xiao Wang
- Rutgers-Cancer Institute of New Jersey, Rutgers-Robert Wood Johnson Medical School, New Brunswick, NJ, USA
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Inui S, Nishio T, Ueda Y, Ohira S, Ueda H, Washio H, Ono S, Miyazaki M, Koizumi M, Konishi K. Machine log file-based dose verification using novel iterative CBCT reconstruction algorithm in commercial software during volumetric modulated arc therapy for prostate cancer patients. Phys Med 2021; 92:24-31. [PMID: 34837857 DOI: 10.1016/j.ejmp.2021.11.004] [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: 06/26/2021] [Revised: 11/06/2021] [Accepted: 11/16/2021] [Indexed: 10/19/2022] Open
Abstract
PURPOSE To evaluate the utility of the use of iterative cone-beam computed tomography (CBCT) for machine log file-based dose verification during volumetric modulated arc therapy (VMAT) for prostate cancer patients. METHODS All CBCT acquisition data were used to reconstruct images with the Feldkamp-Davis-Kress algorithm (FDK-CBCT) and the novel iterative algorithm (iCBCT). The Hounsfield unit (HU)-electron density curves for CBCT images were created using the Advanced Electron Density Phantom. The I'mRT and anthropomorphic phantoms were irradiated with VMAT after CBCT registration. Subsequently, fourteen prostate cancer patients received VMAT after CBCT registration. Machine log files and both CBCT images were exported to the PerFRACTION software, and a 3D patient dose was reconstructed. Mean dose for planning target volume (PTV), the bladder, and rectum and the 3D gamma analysis were evaluated. RESULTS For the phantom studies, the variation of HU values was observed at the central position surrounding the bones in FDK-CBCT. There were almost no changes in the difference of doses at the isocenter between measurement and reconstructed dose for planning CT (pCT), FDK-CBCT, and iCBCT. Mean dose differences of PTV, rectum, and bladder between iCBCT and pCT were approximately 2% lower than those between FDK-CBCT and pCT. For the clinical study, average gamma analysis for 2%/2 mm was 98.22% ± 1.07 and 98.81% ± 1.25% in FDK-CBCT and iCBCT, respectively. CONCLUSIONS A similar machine log file-based dose verification accuracy is obtained for FDK-CBCT and iCBCT during VMAT for prostate cancer patients.
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Affiliation(s)
- Shoki Inui
- Department of Radiation Oncology, Osaka International Cancer Institute, Osaka, Japan; Department of Medical Physics and Engineering, Osaka University Graduate School of Medicine, Suita, Japan.
| | - Teiji Nishio
- Department of Medical Physics and Engineering, Osaka University Graduate School of Medicine, Suita, Japan
| | - Yoshihiro Ueda
- Department of Radiation Oncology, Osaka International Cancer Institute, Osaka, Japan
| | - Shingo Ohira
- Department of Radiation Oncology, Osaka International Cancer Institute, Osaka, Japan
| | - Hikari Ueda
- Department of Radiation Oncology, Osaka International Cancer Institute, Osaka, Japan
| | - Hayate Washio
- Department of Radiation Oncology, Osaka International Cancer Institute, Osaka, Japan; Graduate School of Health Sciences, Kumamoto University, Kumamoto, Japan
| | - Shunsuke Ono
- Department of Radiation Oncology, Osaka International Cancer Institute, Osaka, Japan
| | - Masayoshi Miyazaki
- Department of Radiation Oncology, Osaka International Cancer Institute, Osaka, Japan
| | - Masahiko Koizumi
- Department of Medical Physics and Engineering, Osaka University Graduate School of Medicine, Suita, Japan
| | - Koji Konishi
- Department of Radiation Oncology, Osaka International Cancer Institute, Osaka, Japan
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Paganetti H, Botas P, Sharp GC, Winey B. Adaptive proton therapy. Phys Med Biol 2021; 66:10.1088/1361-6560/ac344f. [PMID: 34710858 PMCID: PMC8628198 DOI: 10.1088/1361-6560/ac344f] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Accepted: 10/28/2021] [Indexed: 12/25/2022]
Abstract
Radiation therapy treatments are typically planned based on a single image set, assuming that the patient's anatomy and its position relative to the delivery system remains constant during the course of treatment. Similarly, the prescription dose assumes constant biological dose-response over the treatment course. However, variations can and do occur on multiple time scales. For treatment sites with significant intra-fractional motion, geometric changes happen over seconds or minutes, while biological considerations change over days or weeks. At an intermediate timescale, geometric changes occur between daily treatment fractions. Adaptive radiation therapy is applied to consider changes in patient anatomy during the course of fractionated treatment delivery. While traditionally adaptation has been done off-line with replanning based on new CT images, online treatment adaptation based on on-board imaging has gained momentum in recent years due to advanced imaging techniques combined with treatment delivery systems. Adaptation is particularly important in proton therapy where small changes in patient anatomy can lead to significant dose perturbations due to the dose conformality and finite range of proton beams. This review summarizes the current state-of-the-art of on-line adaptive proton therapy and identifies areas requiring further research.
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Affiliation(s)
- Harald Paganetti
- Department of Radiation Oncology, Physics Division, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
| | - Pablo Botas
- Department of Radiation Oncology, Physics Division, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
- Foundation 29 of February, Pozuelo de Alarcón, Madrid, Spain
| | - Gregory C Sharp
- Department of Radiation Oncology, Physics Division, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
| | - Brian Winey
- Department of Radiation Oncology, Physics Division, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
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Russo S, Ricotti R, Molinelli S, Patti F, Barcellini A, Mastella E, Pella A, Paganelli C, Marvaso G, Pepa M, Comi S, Zaffaroni M, Avuzzi B, Giandini T, Pignoli E, Valdagni R, Baroni G, Cattani F, Ciocca M, Jereczek-Fossa BA, Orlandi E, Orecchia R, Vischioni B. Dosimetric Impact of Inter-Fraction Anatomical Changes in Carbon Ion Boost Treatment for High-Risk Prostate Cancer (AIRC IG 14300). Front Oncol 2021; 11:740661. [PMID: 34650922 PMCID: PMC8506150 DOI: 10.3389/fonc.2021.740661] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Accepted: 09/06/2021] [Indexed: 02/04/2023] Open
Abstract
Rectum and bladder volumes play an important role in the dose distribution reproducibility in prostate cancer adenocarcinoma (PCa) radiotherapy, especially for particle therapy, where density variation can strongly affect the dose distribution. We investigated the reliability and reproducibility of our image-guided radiotherapy (IGRT) and treatment planning protocol for carbon ion radiotherapy (CIRT) within the phase II mixed beam study (AIRC IG 14300) for the treatment of high-risk PCa. In order to calculate the daily dose distribution, a set of synthetic computed tomography (sCT) images was generated from the cone beam computed tomography (CBCT) images acquired in each treatment session. Planning target volume (PTV) together with rectum and bladder volume variation was evaluated with sCT dose-volume histogram (DVH) metric deviations from the planning values. The correlations between the bladder and rectum volumes, and the corresponding DVH metrics, were also assessed. No significant difference in the bladder, rectum, and PTV median volumes between the planning computed tomography (pCT) and the sCT was found. In addition, no significant difference was assessed when comparing the average DVHs and median DVH metrics between pCT and sCT. Dose deviations determined by bladder and rectum filling variations demonstrated that dose distributions were reproducible in terms of both target coverage and organs at risk (OARs) sparing.
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Affiliation(s)
- Stefania Russo
- Medical Physics Unit, Clinical Department, National Center for Oncological Hadrontherapy (CNAO), Pavia, Italy
| | - Rosalinda Ricotti
- Bioengineering Unit, Clinical Department, National Center for Oncological Hadrontherapy (CNAO), Pavia, Italy
| | - Silvia Molinelli
- Medical Physics Unit, Clinical Department, National Center for Oncological Hadrontherapy (CNAO), Pavia, Italy
| | - Filippo Patti
- Radiotherapy Unit, Clinical Department, National Center for Oncological Hadrontherapy (CNAO), Pavia, Italy.,Division of Radiotherapy, IEO, European Institute of Oncology Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Milan, Italy
| | - Amelia Barcellini
- Radiotherapy Unit, Clinical Department, National Center for Oncological Hadrontherapy (CNAO), Pavia, Italy
| | - Edoardo Mastella
- Medical Physics Unit, Clinical Department, National Center for Oncological Hadrontherapy (CNAO), Pavia, Italy
| | - Andrea Pella
- Bioengineering Unit, Clinical Department, National Center for Oncological Hadrontherapy (CNAO), Pavia, Italy
| | - Chiara Paganelli
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy
| | - Giulia Marvaso
- Division of Radiotherapy, IEO, European Institute of Oncology Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Milan, Italy.,Department of Oncology and Hemato-oncology, University of Milan, Milan, Italy
| | - Matteo Pepa
- Division of Radiotherapy, IEO, European Institute of Oncology Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Milan, Italy
| | - Stefania Comi
- Medical Physics Unit, IEO, European Institute of Oncology Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Milan, Italy
| | - Mattia Zaffaroni
- Division of Radiotherapy, IEO, European Institute of Oncology Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Milan, Italy
| | - Barbara Avuzzi
- Department of Radiation Oncology, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Istituto Nazionale dei Tumori, Milan, Italy
| | - Tommaso Giandini
- Medical Physics Unit, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Istituto Nazionale dei Tumori, Milan, Italy
| | - Emanuele Pignoli
- Medical Physics Unit, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Istituto Nazionale dei Tumori, Milan, Italy
| | - Riccardo Valdagni
- Department of Oncology and Hemato-oncology, University of Milan, Milan, Italy.,Medical Physics Unit, IEO, European Institute of Oncology Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Milan, Italy
| | - Guido Baroni
- Bioengineering Unit, Clinical Department, National Center for Oncological Hadrontherapy (CNAO), Pavia, Italy.,Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy
| | - Federica Cattani
- Medical Physics Unit, IEO, European Institute of Oncology Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Milan, Italy
| | - Mario Ciocca
- Medical Physics Unit, Clinical Department, National Center for Oncological Hadrontherapy (CNAO), Pavia, Italy
| | - Barbara Alicja Jereczek-Fossa
- Division of Radiotherapy, IEO, European Institute of Oncology Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Milan, Italy.,Department of Oncology and Hemato-oncology, University of Milan, Milan, Italy
| | - Ester Orlandi
- Radiotherapy Unit, Clinical Department, National Center for Oncological Hadrontherapy (CNAO), Pavia, Italy
| | - Roberto Orecchia
- Scientific Directorate, IEO, European Institute of Oncology Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Milan, Italy
| | - Barbara Vischioni
- Radiotherapy Unit, Clinical Department, National Center for Oncological Hadrontherapy (CNAO), Pavia, Italy
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Holm AIS, Nyeng TB, S. Møller D, Assenholt MS, Hansen R, Nyvang L, Ravkilde T, Thomsen MS, Hoffmann L. Density calibrated cone beam CT as a tool for adaptive radiotherapy. Acta Oncol 2021; 60:1275-1282. [PMID: 34224288 DOI: 10.1080/0284186x.2021.1945678] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
BACKGROUND Visual inspections of anatomical changes observed on daily cone-beam CT (CBCT) images are often used as triggers for radiotherapy plan adaptation to avoid unacceptable dose levels to the target or OARs. Direct CBCT dose calculations would improve the ability to adapt only those plans where dosimetric changes are observed. This study investigates the accuracy of dose calculations on CBCTs. MATERIALS AND METHODS Calibration curves were obtained for CBCT imagers at nine identical accelerators. CBCT scans of a phantom with different density inserts were recorded for two scan modes (Head-Neck and Pelvis) and mean calibration curves were calculated. Subsequently, CBCT scans of the phantom with six different density inserts were recorded, the dose distributions on the CBCTs were calculated and compared to dose on the planning CT (pCT). The uncertainty was quantified by the dosimetric difference between the pCT and the CBCT. The two mean calibration curves were used to calculate the daily delivered CBCT dose for ten Head-Neck-, eleven Lung-, and ten pelvic patients. Additional patient calculations were performed using low-HU empirically corrected calibration curves. Patient doses were compared on target coverage and mean dose, and D1cc for OARs. RESULTS The dose differences between pCT and CBCT for phantom data were small for all DVH parameters, with mean deviations below ±0.6% for both CBCT modes. For patient data, it was found that low-HU corrected calibration curves performed the best. The mean deviations for the mean dose and coverage of the target were 0.2%±0.7% and 0.1%±0.6%, across all patient groups. CONCLUSION Dose calculation on CBCT images results in target coverage and mean dose with an accuracy of the order of 1%, which makes this acceptable for clinical use. The CBCT mode specific calibration curves can be used at all identical imaging devices and for all patient groups.
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Affiliation(s)
- Anne I. S. Holm
- Department of Oncology, Section for Medical Physics, Aarhus University Hospital, Aarhus, Denmark
| | - Tine B. Nyeng
- Department of Oncology, Section for Medical Physics, Aarhus University Hospital, Aarhus, Denmark
| | - Ditte S. Møller
- Department of Oncology, Section for Medical Physics, Aarhus University Hospital, Aarhus, Denmark
| | - Marianne S. Assenholt
- Department of Oncology, Section for Medical Physics, Aarhus University Hospital, Aarhus, Denmark
| | - Rune Hansen
- Department of Oncology, Section for Medical Physics, Aarhus University Hospital, Aarhus, Denmark
| | - Lars Nyvang
- Department of Oncology, Section for Medical Physics, Aarhus University Hospital, Aarhus, Denmark
| | - Thomas Ravkilde
- Department of Oncology, Section for Medical Physics, Aarhus University Hospital, Aarhus, Denmark
| | - Mette S. Thomsen
- Department of Oncology, Section for Medical Physics, Aarhus University Hospital, Aarhus, Denmark
| | - Lone Hoffmann
- Department of Oncology, Section for Medical Physics, Aarhus University Hospital, Aarhus, Denmark
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Souleyman S, Maria KD, Cheikh T, Karima KK. Impact of Acquisition Protocols on Accuracy of Dose Calculation Based on XVI Cone Beam Computed Tomography. J Med Phys 2021; 46:94-104. [PMID: 34566289 PMCID: PMC8415252 DOI: 10.4103/jmp.jmp_128_20] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Revised: 04/19/2021] [Accepted: 04/23/2021] [Indexed: 11/26/2022] Open
Abstract
Purpose: The objective of this work is to study the impact of acquisition protocols on the accuracy of cone beam computed tomography (CBCT)-based dose calculation and to determinate its limits from image characteristics such as image quality, Hounsfield numbers consistency, and restrictive sizes of volume acquisition, compared to the CT imaging for the different anatomy localizations: head and neck (H&N), thorax, and pelvis. Materials and Methods: In this work, we used a routine on-board imaging CBCT of the XVI system (Elekta, Stockholm, Sweden). Dosimetric calculations performed on CT images require the knowledge of the Hounsfield unit-relative electron density (HU-ReD) calibration curve, which is determined for each imaging technology and must be adapted to the imaging acquisition parameters (filter/field of view). The accuracy of the dose calculation from CBCT images strongly depends on the quality of these images and also on the appropriate correspondence to the electronic densities, which will be used by the treatment planning system to simulate the dose distribution. In this study, we evaluated the accuracy of the dose calculation for each protocol, as already pointed in many studies. Results: As a result, the protocols that give better results in terms of dose calculation are F0S20 for the H&N region and F1M20 for the thoracic and pelvic regions, with an error <2% compared to results obtained with CT images. In addition, the dose distributions obtained with CT and CBCT imaging modalities were compared by two different methods. The first comparison was done by gamma index in three planes (sagittal, coronal, and transverse) with 2%; 2 mm criteria. The results showed good correspondence, with more than 95% of points passed the criteria. We also compared the target volume, the organs at risk (OARs), and the maximum and minimum doses for the three localizations (H&N, thorax, and pelvis) in CT and CBCT imaging modalities using a Rando phantom. Conclusions: The choice of the adequate CBCT acquisition protocol and the appropriate phantom to determine the HU-ReD calibration curve provides a better precision in the calculation of dose on CBCT images. This allows improving the results obtained when using the HU-ReD calibration method for dose calculation in adaptive radiotherapy.
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Affiliation(s)
- Slimani Souleyman
- Department of Radiotherapy, HCA Hospital, Kouba, Algeria.,SNIRM Laboratory, Faculty of Physics, University of Sciences and Technology Houari Boumediene, Algiers, ALGERIA
| | - Khalal Dorea Maria
- Dosage, Analyse and Characterisation in High Resolution Laboratory, Department of Physics, Ferhat Abbas Setif 1 University, Setif, Algeria
| | - Tyeb Cheikh
- Department of Radiotherapy, HCA Hospital, Kouba, Algeria
| | - Khalal-Kouache Karima
- SNIRM Laboratory, Faculty of Physics, University of Sciences and Technology Houari Boumediene, Algiers, ALGERIA
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Rossi M, Cerveri P. Comparison of Supervised and Unsupervised Approaches for the Generation of Synthetic CT from Cone-Beam CT. Diagnostics (Basel) 2021; 11:diagnostics11081435. [PMID: 34441369 PMCID: PMC8395013 DOI: 10.3390/diagnostics11081435] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 07/30/2021] [Accepted: 08/07/2021] [Indexed: 12/04/2022] Open
Abstract
Due to major artifacts and uncalibrated Hounsfield units (HU), cone-beam computed tomography (CBCT) cannot be used readily for diagnostics and therapy planning purposes. This study addresses image-to-image translation by convolutional neural networks (CNNs) to convert CBCT to CT-like scans, comparing supervised to unsupervised training techniques, exploiting a pelvic CT/CBCT publicly available dataset. Interestingly, quantitative results were in favor of supervised against unsupervised approach showing improvements in the HU accuracy (62% vs. 50%), structural similarity index (2.5% vs. 1.1%) and peak signal-to-noise ratio (15% vs. 8%). Qualitative results conversely showcased higher anatomical artifacts in the synthetic CBCT generated by the supervised techniques. This was motivated by the higher sensitivity of the supervised training technique to the pixel-wise correspondence contained in the loss function. The unsupervised technique does not require correspondence and mitigates this drawback as it combines adversarial, cycle consistency, and identity loss functions. Overall, two main impacts qualify the paper: (a) the feasibility of CNN to generate accurate synthetic CT from CBCT images, which is fast and easy to use compared to traditional techniques applied in clinics; (b) the proposal of guidelines to drive the selection of the better training technique, which can be shifted to more general image-to-image translation.
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Washio H, Ohira S, Funama Y, Ueda Y, Isono M, Inui S, Miyazaki M, Teshima T. Accuracy of dose calculation on iterative CBCT for head and neck radiotherapy. Phys Med 2021; 86:106-112. [PMID: 34102546 DOI: 10.1016/j.ejmp.2021.05.027] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 05/15/2021] [Accepted: 05/19/2021] [Indexed: 10/21/2022] Open
Abstract
PURPOSE To evaluate the feasibility of the use of iterative cone-beam computed tomography (CBCT) for dose calculation in the head and neck region. METHODS This study includes phantom and clinical studies. All acquired CBCT images were reconstructed with Feldkamp-Davis-Kress algorithm-based CBCT (FDK-CBCT) and iterative CBCT (iCBCT) algorithm. The Hounsfield unit (HU) consistency between the head and body phantoms was determined in both reconstruction techniques. Volumetric modulated arc therapy (VMAT) plans were generated for 16 head and neck patients on a planning CT scan, and the doses were recalculated on FDK-CBCT and iCBCT with Anisotropic Analytical Algorithm (AAA) and Acuros XB (AXB). As a comparison of the accuracy of dose calculations, the absolute dosimetric difference and 1%/1 mm gamma passing rate analysis were analyzed. RESULTS The difference in the mean HU values between the head and body phantoms was larger for FDK-CBCT (max value: 449.1 HU) than iCBCT (260.0 HU). The median dosimetric difference from the planning CT were <1.0% for both FDK-CBCT and iCBCT but smaller differences were found with iCBCT (planning target volume D50%: 0.38% (0.15-0.59%) for FDK-CBCT, 0.28% (0.13-0.49%) for iCBCT, AAA; 0.14% (0.04-0.19%) for FDK-CBCT, 0.07% (0.02-0.20%) for iCBCT). The mean gamma passing rate was significantly better in iCBCT than FDK-CBCT (AAA: 98.7% for FDK-CBCT, 99.4% for iCBCT; AXB: 96.8% for FDK_CBCT, 97.5% for iCBCT). CONCLUSION The iCBCT-based dose calculation in VMAT for head and neck cancer was accurate compared to FDK-CBCT.
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Affiliation(s)
- Hayate Washio
- Department of Radiation Oncology, Osaka International Cancer Institute, Osaka, Japan; Graduate School of Health Sciences, Kumamoto University, Kumamoto, Japan
| | - Shingo Ohira
- Department of Radiation Oncology, Osaka International Cancer Institute, Osaka, Japan.
| | - Yoshinori Funama
- Department of Medical Radiation Sciences, Faculty of Life Science, Kumamoto University, Kumamoto, Japan
| | - Yoshihiro Ueda
- Department of Radiation Oncology, Osaka International Cancer Institute, Osaka, Japan
| | - Masaru Isono
- Department of Radiation Oncology, Osaka International Cancer Institute, Osaka, Japan
| | - Shoki Inui
- Department of Radiation Oncology, Osaka International Cancer Institute, Osaka, Japan; Department of Medical Physics and Engineering, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Masayoshi Miyazaki
- Department of Radiation Oncology, Osaka International Cancer Institute, Osaka, Japan
| | - Teruki Teshima
- Department of Radiation Oncology, Osaka International Cancer Institute, Osaka, Japan
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Cone-beam CT image quality improvement using Cycle-Deblur consistent adversarial networks (Cycle-Deblur GAN) for chest CT imaging in breast cancer patients. Sci Rep 2021; 11:1133. [PMID: 33441936 PMCID: PMC7807016 DOI: 10.1038/s41598-020-80803-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Accepted: 12/23/2020] [Indexed: 01/26/2023] Open
Abstract
Cone-beam computed tomography (CBCT) integrated with a linear accelerator is widely used to increase the accuracy of radiotherapy and plays an important role in image-guided radiotherapy (IGRT). For comparison with fan-beam computed tomography (FBCT), the image quality of CBCT is indistinct due to X-ray scattering, noise, and artefacts. We proposed a deep learning model, “Cycle-Deblur GAN”, combined with CycleGAN and Deblur-GAN models to improve the image quality of chest CBCT images. The 8706 CBCT and FBCT image pairs were used for training, and 1150 image pairs were used for testing in deep learning. The generated CBCT images from the Cycle-Deblur GAN model demonstrated closer CT values to FBCT in the lung, breast, mediastinum, and sternum compared to the CycleGAN and RED-CNN models. The quantitative evaluations of MAE, PSNR, and SSIM for CBCT generated from the Cycle-Deblur GAN model demonstrated better results than the CycleGAN and RED-CNN models. The Cycle-Deblur GAN model improved image quality and CT-value accuracy and preserved structural details for chest CBCT images.
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Eckl M, Hoppen L, Sarria GR, Boda-Heggemann J, Simeonova-Chergou A, Steil V, Giordano FA, Fleckenstein J. Evaluation of a cycle-generative adversarial network-based cone-beam CT to synthetic CT conversion algorithm for adaptive radiation therapy. Phys Med 2020; 80:308-316. [PMID: 33246190 DOI: 10.1016/j.ejmp.2020.11.007] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Revised: 10/29/2020] [Accepted: 11/05/2020] [Indexed: 12/17/2022] Open
Abstract
PURPOSE Image-guided radiation therapy could benefit from implementing adaptive radiation therapy (ART) techniques. A cycle-generative adversarial network (cycle-GAN)-based cone-beam computed tomography (CBCT)-to-synthetic CT (sCT) conversion algorithm was evaluated regarding image quality, image segmentation and dosimetric accuracy for head and neck (H&N), thoracic and pelvic body regions. METHODS Using a cycle-GAN, three body site-specific models were priorly trained with independent paired CT and CBCT datasets of a kV imaging system (XVI, Elekta). sCT were generated based on first-fraction CBCT for 15 patients of each body region. Mean errors (ME) and mean absolute errors (MAE) were analyzed for the sCT. On the sCT, manually delineated structures were compared to deformed structures from the planning CT (pCT) and evaluated with standard segmentation metrics. Treatment plans were recalculated on sCT. A comparison of clinically relevant dose-volume parameters (D98, D50 and D2 of the target volume) and 3D-gamma (3%/3mm) analysis were performed. RESULTS The mean ME and MAE were 1.4, 29.6, 5.4 Hounsfield units (HU) and 77.2, 94.2, 41.8 HU for H&N, thoracic and pelvic region, respectively. Dice similarity coefficients varied between 66.7 ± 8.3% (seminal vesicles) and 94.9 ± 2.0% (lungs). Maximum mean surface distances were 6.3 mm (heart), followed by 3.5 mm (brainstem). The mean dosimetric differences of the target volumes did not exceed 1.7%. Mean 3D gamma pass rates greater than 97.8% were achieved in all cases. CONCLUSIONS The presented method generates sCT images with a quality close to pCT and yielded clinically acceptable dosimetric deviations. Thus, an important prerequisite towards clinical implementation of CBCT-based ART is fulfilled.
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Affiliation(s)
- Miriam Eckl
- Department of Radiation Oncology, University Medical Center Mannheim, University of Heidelberg, Germany
| | - Lea Hoppen
- Department of Radiation Oncology, University Medical Center Mannheim, University of Heidelberg, Germany.
| | - Gustavo R Sarria
- Department of Radiology and Radiation Oncology, University Hospital Bonn, Germany
| | - Judit Boda-Heggemann
- Department of Radiation Oncology, University Medical Center Mannheim, University of Heidelberg, Germany
| | - Anna Simeonova-Chergou
- Department of Radiation Oncology, University Medical Center Mannheim, University of Heidelberg, Germany
| | - Volker Steil
- Department of Radiation Oncology, University Medical Center Mannheim, University of Heidelberg, Germany
| | - Frank A Giordano
- Department of Radiology and Radiation Oncology, University Hospital Bonn, Germany
| | - Jens Fleckenstein
- Department of Radiation Oncology, University Medical Center Mannheim, University of Heidelberg, Germany
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