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Zeng Y, Li H, Chang Y, Han Y, Liu H, Pang B, Han J, Hu B, Cheng J, Zhang S, Yang K, Quan H, Yang Z. In vivo EPID-based daily treatment error identification for volumetric-modulated arc therapy in head and neck cancers with a hierarchical convolutional neural network: a feasibility study. Phys Eng Sci Med 2024:10.1007/s13246-024-01414-z. [PMID: 38647634 DOI: 10.1007/s13246-024-01414-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2023] [Accepted: 03/06/2024] [Indexed: 04/25/2024]
Abstract
We proposed a deep learning approach to classify various error types in daily VMAT treatment of head and neck cancer patients based on EPID dosimetry, which could provide additional information to support clinical decisions for adaptive planning. 146 arcs from 42 head and neck patients were analyzed. Anatomical changes and setup errors were simulated in 17,820 EPID images of 99 arcs obtained from 30 patients using in-house software for model training, validation, and testing. Subsequently, 141 clinical EPID images from 47 arcs belonging to the remaining 12 patients were utilized for clinical testing. The hierarchical convolutional neural network (HCNN) model was trained to classify error types and magnitudes using EPID dose difference maps. Gamma analysis with 3%/2 mm (dose difference/distance to agreement) criteria was also performed. The F1 score, a combination of precision and recall, was utilized to evaluate the performance of the HCNN model and gamma analysis. The adaptive fractioned doses were calculated to verify the HCNN classification results. For error type identification, the overall F1 score of the HCNN model was 0.99 and 0.91 for primary type and subtype identification, respectively. For error magnitude identification, the overall F1 score in the simulation dataset was 0.96 and 0.70 for the HCNN model and gamma analysis, respectively; while the overall F1 score in the clinical dataset was 0.79 and 0.20 for the HCNN model and gamma analysis, respectively. The HCNN model-based EPID dosimetry can identify changes in patient transmission doses and distinguish the treatment error category, which could potentially provide information for head and neck cancer treatment adaption.
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Affiliation(s)
- Yiling Zeng
- Department of Medical Physics, School of Physics and Technology, Wuhan University, Wuhan, 430072, China
- Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Heng Li
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, MD, USA
| | - Yu Chang
- Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Yang Han
- College of Electrical Engineering, Sichuan University, Chengdu, 610065, China
| | - Hongyuan Liu
- Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Bo Pang
- Department of Medical Physics, School of Physics and Technology, Wuhan University, Wuhan, 430072, China
| | - Jun Han
- Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Bin Hu
- Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Junping Cheng
- Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Sheng Zhang
- Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Kunyu Yang
- Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Hong Quan
- Department of Medical Physics, School of Physics and Technology, Wuhan University, Wuhan, 430072, China.
| | - Zhiyong Yang
- Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
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Zhang J, Chen Z, Lei Y, Wen J. A Novel Approach for Position Verification and Dose Calculation through Local MVCT Reconstruction. Diagnostics (Basel) 2024; 14:482. [PMID: 38472954 DOI: 10.3390/diagnostics14050482] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 02/19/2024] [Accepted: 02/20/2024] [Indexed: 03/14/2024] Open
Abstract
Traditional positioning verification using cone-beam computed tomography (CBCT) may incur errors due to potential misalignments between the isocenter of CBCT and the treatment beams in radiotherapy. This study introduces an innovative method for verifying patient positioning in radiotherapy. Initially, the transmission images from an electronic portal imaging device (EPID) are acquired from 10 distinct angles. Utilizing the ART-TV algorithm, a sparse reconstruction of local megavoltage computed tomography (MVCT) is performed. Subsequently, this MVCT is aligned with the planning CT via a three-dimensional mutual information registration technique, pinpointing any patient-positioning discrepancies and facilitating corrective adjustments to the treatment setup. Notably, this approach employs the same radiation source as used in treatment to obtain three-dimensional images, thereby circumventing errors stemming from misalignment between the isocenter of CBCT and the accelerator. The registration process requires only 10 EPID images, and the dose absorbed during this process is included in the total dose calculation. The results show that our method's reconstructed MVCT images fulfill the requirements for registration, and the registration algorithm accurately detects positioning errors, thus allowing for adjustments in the patient's treatment position and precise calculation of the absorbed dose.
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Affiliation(s)
- Jun Zhang
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, China
- School of Life Science, Beijing Institute of Technology, Beijing 100081, China
| | - Zerui Chen
- School of Life Science, Beijing Institute of Technology, Beijing 100081, China
| | - Yuxin Lei
- School of Life Science, Beijing Institute of Technology, Beijing 100081, China
| | - Junhai Wen
- School of Life Science, Beijing Institute of Technology, Beijing 100081, China
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Zhang Y, Huang Y, Lin J, Ding S, Gong X, Liu Q, Gong C. Multi-isocenter VMAT craniospinal irradiation using feasibility dose-volume histogram-guided auto-planning technique. JOURNAL OF RADIATION RESEARCH 2023:7150737. [PMID: 37141634 DOI: 10.1093/jrr/rrad026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Revised: 12/07/2022] [Indexed: 05/06/2023]
Abstract
This study aims to propose a novel treatment planning methodology for multi-isocenter volumetric modulated arc therapy (VMAT) craniospinal irradiation (CSI) using the special feasibility dose-volume histogram (FDVH)-guided auto-planning (AP) technique. Three different multi-isocenter VMAT -CSI plans were created, including manually based plans (MUPs), conventional AP plans (CAPs) and FDVH-guided AP plans (FAPs). The CAPs and FAPs were specially designed by combining multi-isocenter VMAT and AP techniques in the Pinnacle treatment planning system. Specially, the personalized optimization parameters for FAPs were generated using the FDVH function implemented in PlanIQ software, which provides the ideal organs at risk (OARs) sparing for the specific anatomical geometry based on the valuable assumption of the dose fall-off. Compared to MUPs, CAPs and FAPs significantly reduced the dose for most of the OARs. FAPs achieved the best homogeneity index (0.092 ± 0.013) and conformity index (0.980 ± 0.011), while CAPs were slightly inferior to the FAPs but superior to the MUPs. As opposed to MUPs, FAPs delivered a lower dose to OARs, whereas the difference between FAPs and CAPs was not statistically significant except for the optic chiasm and inner ear_L. The two AP approaches had similar MUs, which were significantly lower than the MUPs. The planning time of FAPs (145.00 ± 10.25 min) was slightly lower than that of CAPs (149.83 ± 14.37 min) and was substantially lower than that of MUPs (157.92 ± 16.11 min) with P < 0.0167. Overall, introducing the multi-isocenter AP technique into VMAT-CSI yielded positive outcomes and may play an important role in clinical CSI planning in the future.
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Affiliation(s)
- Yun Zhang
- Department of Radiation Oncology, Jiangxi Cancer Hospital, 519 East Beijing Road, Qingshanhu District, Nanchang 330029, China
| | - Yuling Huang
- Department of Radiation Oncology, Jiangxi Cancer Hospital, 519 East Beijing Road, Qingshanhu District, Nanchang 330029, China
| | - Jiafan Lin
- Department of Radiation Oncology, Jiangxi Cancer Hospital, 519 East Beijing Road, Qingshanhu District, Nanchang 330029, China
| | - Shenggou Ding
- Department of Radiation Oncology, Jiangxi Cancer Hospital, 519 East Beijing Road, Qingshanhu District, Nanchang 330029, China
| | - Xiaochang Gong
- Department of Radiation Oncology, Jiangxi Cancer Hospital, 519 East Beijing Road, Qingshanhu District, Nanchang 330029, China
| | - Qiegen Liu
- Department of Electronic Information Engineering, 999 Xuefu Dadao, Honggutan District, Nanchang 330031, China
| | - Changfei Gong
- Department of Radiation Oncology, Jiangxi Cancer Hospital, 519 East Beijing Road, Qingshanhu District, Nanchang 330029, China
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Merkis M, Urbonavicius BG, Adliene D, Laurikaitiene J, Puiso J. Pilot Study of Polymerization Dynamics in nMAG Dose Gel. Gels 2022; 8:gels8050288. [PMID: 35621587 PMCID: PMC9140482 DOI: 10.3390/gels8050288] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 05/02/2022] [Accepted: 05/03/2022] [Indexed: 02/04/2023] Open
Abstract
The essential component of modern radiation therapy is the application of steep dose gradients during patient treatment in order to maximize the radiation dose to the target volume and protect neighboring heathy tissues. However, volumetric dose distribution in an irradiated target is still a bottleneck of dose verification in modern radiotherapy. Dose gels are almost the only known dosimetry tool which allows for the evaluation of dose distribution in the irradiated volume due to gel’s polymerization upon irradiation. The accuracy of dose gel dosimetry has its own obstacle, which is related to the continuation of the gel’s polymerization after the radiation treatment procedure is finished. In this article, a method to monitor the polymerization dynamics of dose gels in real-time is proposed using a modified optical spectrometry system. Using the proposed method, the changes of the optical characteristics of irradiated nMAG dose gels in situ were assessed. The investigation revealed that the detectable polymerization in dose gel proceeds up to 6 h after irradiation. This time is significantly shorter compared with a commonly recommended 24 h waiting time allocated for polymer gel to settle. It was also found that dose rate significantly influences the temporal response of the nMAG dosimeter. By increasing the irradiation dose rate by a factor of 2, the time needed for the polymerization process to settle was increased by 22%. Identification of the gel’s post-irradiation polymerization time interval and its dependence on irradiation parameters will contribute to more accurate dose verification using dose gel dosimetry.
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