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Xu D, Descovich M, Liu H, Sheng K. Robust localization of poorly visible tumor in fiducial free stereotactic body radiation therapy. Radiother Oncol 2024; 200:110514. [PMID: 39214256 DOI: 10.1016/j.radonc.2024.110514] [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: 05/24/2024] [Revised: 07/27/2024] [Accepted: 08/23/2024] [Indexed: 09/04/2024]
Abstract
BACKGROUND AND PURPOSE Effective respiratory motion management reduces healthy tissue toxicity and ensures sufficient dose delivery to lung cancer cells in pulmonary stereotactic body radiation therapy (SBRT) with high fractional doses. An articulated robotic arm paired with an X-ray imaging system is designed for real-time motion-tracking (RTMT) dose delivery. However, small tumors (<15 mm) or tumors at challenging locations may not be visible in the X-ray images, disqualifying patients with such tumors from RTMT dose delivery unless fiducials are implanted via an invasive procedure. To track these practically invisible lung tumors in SBRT, we hereby develop a deep learning-enabled template-free tracking framework, SAFE Track. METHODS SAFE Track is a fully supervised framework that trains a generalizable prior for template-free target localization. Two sub-stages are incorporated in SAFE Track, including the initial pretraining on two large-scale medical image datasets (DeepLesion and Node21) followed by fine-tuning on our in-house dataset. A two-stage detector, Faster R-CNN, with a backbone of ResNet50, was selected as our detection network. 94 patients (415 fractions; 40,348 total frames) with low tumor visibility who thus had implanted fiducials were included. The cohort is categorized by the longest dimension of the tumor (<10 mm, 10-15 mm and > 15 mm). The patients were split into training (n = 66) and testing (n = 28) sets. We simulated fiducial-free tumors by removing the fiducials from the X-ray images. We classified the patients into two groups - fiducial implanted inside tumors and implanted outside tumors. To ensure the rigor of our experiment design, we only conducted fiducial removal simulation in training patients and utilized patients with fiducial implanted outside of the tumors for testing. Commercial Xsight Lung Tracking (XLT) and a Deep Match were included for comparison. RESULTS SAFE Track achieves promising outcomes to as accurate as 1.23±1.32 mm 3D distance in testing patients with tumor size > 15 mm where Deep Match is at 4.75±1.67 mm and XLT is at 12.23±4.58 mm 3D distance. Even for the most challenging tumor size (<10 mm), SAFE Track maintains its robustness at 1.82 plus or minus 1.67 mm 3D distance, where Deep Match is at 5.32 plus or minus 2.32 mm, and XLT is at 24.83±12.95 mm 3D distance. Moreover, SAFE Track can detect some considerably challenging cases where the tumor is almost invisible or overlapped with dense anatomies. CONCLUSION SAFE Track is a robust, clinically compatible, fiducial-free, and template-free tracking framework that is applicable to patients with small tumors or tumors obscured by overlapped anatomies in SBRT.
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Affiliation(s)
- Di Xu
- Radiation Oncology, University of California, San Francisco, USA
| | | | - Hengjie Liu
- Radiation Oncology, University of California, Los Angeles, USA
| | - Ke Sheng
- Radiation Oncology, University of California, San Francisco, USA.
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Gunnarsson K, Mövik L, Pettersson N, Bäck A, Nyman J, Hallqvist A. Assessment of radiation pneumonitis and predictive factors in patients with locally advanced non-small cell lung cancer treated with chemoradiotherapy. Acta Oncol 2024; 63:791-797. [PMID: 39415565 PMCID: PMC11495145 DOI: 10.2340/1651-226x.2024.40576] [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: 04/25/2024] [Accepted: 09/20/2024] [Indexed: 10/18/2024]
Abstract
PURPOSE Radiation pneumonitis (RP) is a dose-limiting toxicity associated with increased mortality for patients with non-small cell lung cancer (NSCLC) treated with chemoradiotherapy (CRT). This study aims to assess the incidence of symptomatic RP (grade 2-5), rate of recovery and associated predictive factors. MATERIAL AND METHODS We performed a retrospective population-based study including 602 patients with NSCLC who were treated with CRT between 2002 and 2016. RP and rate of recovery were analysed using Common Terminology Criteria for Adverse Events version 4.0. Stepwise logistic regression was performed to analyse potential predictive factors for the two endpoints RP grade ≥ 2 and RP grade ≥ 3. RESULTS A total of 136 (23%) patients developed symptomatic RP and 37 (6%) developed RP grade ≥ 3. A total of 67 (71%) recovered, whereas the remaining 27 (29%), with the major proportion of patients belonging to the RP grade ≥ 3 group, suffered from prevailing sequelae. On multivariable analysis, the selected model for predicting RP grade ≥ 2 included the factors V20, smoking status, average fractions per week and chemotherapy agent. V20 and age were selected factors for RP grade ≥ 3. INTERPRETATION The results suggest that regardless of all proposed factors predictive for RP, the most important influenceable significant factor still is dose to the lung. The main aim should be to avoid RP grade ≥ 3, where a substantial proportion of patients suffer from prevailing sequalae. Consequently, the technical improvement and precision of radiotherapy delivery should continue to focus on lung sparing techniques also in the ongoing immunotherapy-containing schedules where the risk of pneumonitis may be increased. e factor still is dose to the lung. Consequently, the technical improvement and precision of radiotherapy delivery should continue to focus on lung sparing techniques also in the ongoing immunotherapy-containing schedules where the risk of pneumonitis may be increased.
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Affiliation(s)
- Kerstin Gunnarsson
- Department of Oncology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Sahlgrenska University Hospital, Gothenburg, Sweden.
| | - Louise Mövik
- Department of Medical Radiation Sciences, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Niclas Pettersson
- Department of Medical Radiation Sciences, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Anna Bäck
- Department of Medical Radiation Sciences, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Jan Nyman
- Department of Oncology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Andreas Hallqvist
- Department of Oncology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Sahlgrenska University Hospital, Gothenburg, Sweden
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Wang K, Yang F, Feng C, Xu F, Li L, Duan J, Yuan S. Dose-Volume Constraints Parameters for Lung Tissue in Thoracic Radiotherapy Following Immune Checkpoint Inhibitor Treatment. J Inflamm Res 2024; 17:7141-7154. [PMID: 39398227 PMCID: PMC11471064 DOI: 10.2147/jir.s484489] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2024] [Accepted: 10/04/2024] [Indexed: 10/15/2024] Open
Abstract
Purpose This study aims to identify risk factors associated with symptomatic radiation pneumonitis (RP, Grade ≥ 2) following immunotherapy preceding thoracic radiotherapy (ICI-TRT) and establish safe dose constraints. Patients and Methods This retrospective study enrolled patients diagnosed with non-small-cell lung cancer (NSCLC) who underwent thoracic radiotherapy (TRT) following immune checkpoint inhibitors (ICIs) treatment. The primary endpoint was the occurrence of symptomatic RP (Grade ≥ 2), as defined by the Common Terminology Criteria for Adverse Events version 5.0. Clinical and lung dosimetric parameters were analyzed to determine their associations with symptomatic RP. Dosimetric parameters included mean lung dose (MLD) and the percentage of lung volume receiving ≥10 Gy (V10), ≥20 Gy (V20), ≥30 Gy (V30), and ≥40 Gy (V40). Receiver operating characteristic curves were used to predict the risk of developing symptomatic RP to establish optimal threshold values for each dosimetric predictor. Results Among the 118 patients included, the incidence of symptomatic RP was 25.4%. Tumor locations, intervals between immunotherapy and radiotherapy, and MLD, V10, V20, V30, and V40 were identified as independent risk factors for symptomatic RP. The area under the curve (AUC) values for MLD, V10, V20, V30, and V40 were 0.788 (95% confidence interval [CI] 0.704-0.873), 0.789 (95% CI 0.705-0.874), 0.791 (95% CI 0.706-0.876), 0.784 (95% CI 0.697-0.871), and 0.749 (95% CI 0.656-0.842), respectively. The optimal threshold values for MLD, V10, V20, V30, and V40 were 9.7 Gy, 26.3%, 15.9%, 13.3%, and 8.6%, respectively. These thresholds are lower than current guideline recommendations, and maintaining dosimetric parameters below these values resulted in a cumulative symptomatic RP incidence of <12%. Conclusion The recommended dose thresholds for MLD, V10, V20, V30, and V40 are lower than the current guidelines, underscoring the importance of radiotherapy planning to minimize symptomatic RP occurrence in patients receiving ICI-TRT.
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Affiliation(s)
- Kang Wang
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, People’s Republic of China
| | - Fengchang Yang
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, People’s Republic of China
| | - Changxing Feng
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, People’s Republic of China
| | - Fuhao Xu
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, People’s Republic of China
| | - Li Li
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, People’s Republic of China
| | - Jinghao Duan
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, People’s Republic of China
| | - Shuanghu Yuan
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, People’s Republic of China
- Department of Radiation Oncology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, People’s Republic of China
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Chang S, Lv J, Wang X, Su J, Bian C, Zheng Z, Yu H, Bao J, Xin Y, Jiang X. Pathogenic mechanisms and latest therapeutic approaches for radiation-induced lung injury: A narrative review. Crit Rev Oncol Hematol 2024; 202:104461. [PMID: 39103129 DOI: 10.1016/j.critrevonc.2024.104461] [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: 10/13/2023] [Revised: 07/26/2024] [Accepted: 07/28/2024] [Indexed: 08/07/2024] Open
Abstract
The treatment of thoracic tumors with ionizing radiation can cause radiation-induced lung injury (RILI), which includes radiation pneumonitis and radiation-induced pulmonary fibrosis. Preventing RILI is crucial for controlling tumor growth and improving quality of life. However, the serious adverse effects of traditional RILI treatment methods remain a major obstacle, necessitating the development of novel treatment options that are both safe and effective. This review summarizes the molecular mechanisms of RILI and explores novel treatment options, including natural compounds, gene therapy, nanomaterials, and mesenchymal stem cells. These recent experimental approaches show potential as effective prevention and treatment options for RILI in clinical practice.
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Affiliation(s)
- Sitong Chang
- Jilin Provincial Key Laboratory of Radiation Oncology & Therapy, The First Hospital of Jilin University and College of Basic Medical Science, Jilin University, Changchun, China; Department of Radiation Oncology, the First Hospital of Jilin University, Changchun 130021, China; NHC Key Laboratory of Radiobiology, School of Public Health of Jilin University, Changchun 130021, China.
| | - Jincai Lv
- Jilin Provincial Key Laboratory of Radiation Oncology & Therapy, The First Hospital of Jilin University and College of Basic Medical Science, Jilin University, Changchun, China; Key Laboratory of Pathobiology, Ministry of Education, Jilin University, Changchun 130021, China.
| | - Xuanzhong Wang
- Jilin Provincial Key Laboratory of Radiation Oncology & Therapy, The First Hospital of Jilin University and College of Basic Medical Science, Jilin University, Changchun, China; Department of Radiation Oncology, the First Hospital of Jilin University, Changchun 130021, China; NHC Key Laboratory of Radiobiology, School of Public Health of Jilin University, Changchun 130021, China.
| | - Jing Su
- Jilin Provincial Key Laboratory of Radiation Oncology & Therapy, The First Hospital of Jilin University and College of Basic Medical Science, Jilin University, Changchun, China; Department of Radiation Oncology, the First Hospital of Jilin University, Changchun 130021, China; NHC Key Laboratory of Radiobiology, School of Public Health of Jilin University, Changchun 130021, China.
| | - Chenbin Bian
- Jilin Provincial Key Laboratory of Radiation Oncology & Therapy, The First Hospital of Jilin University and College of Basic Medical Science, Jilin University, Changchun, China; Department of Radiation Oncology, the First Hospital of Jilin University, Changchun 130021, China; NHC Key Laboratory of Radiobiology, School of Public Health of Jilin University, Changchun 130021, China.
| | - Zhuangzhuang Zheng
- Jilin Provincial Key Laboratory of Radiation Oncology & Therapy, The First Hospital of Jilin University and College of Basic Medical Science, Jilin University, Changchun, China; Department of Radiation Oncology, the First Hospital of Jilin University, Changchun 130021, China; NHC Key Laboratory of Radiobiology, School of Public Health of Jilin University, Changchun 130021, China.
| | - Huiyuan Yu
- Jilin Provincial Key Laboratory of Radiation Oncology & Therapy, The First Hospital of Jilin University and College of Basic Medical Science, Jilin University, Changchun, China; Department of Radiation Oncology, the First Hospital of Jilin University, Changchun 130021, China; NHC Key Laboratory of Radiobiology, School of Public Health of Jilin University, Changchun 130021, China.
| | - Jindian Bao
- Jilin Provincial Key Laboratory of Radiation Oncology & Therapy, The First Hospital of Jilin University and College of Basic Medical Science, Jilin University, Changchun, China; Department of Radiation Oncology, the First Hospital of Jilin University, Changchun 130021, China; NHC Key Laboratory of Radiobiology, School of Public Health of Jilin University, Changchun 130021, China.
| | - Ying Xin
- Jilin Provincial Key Laboratory of Radiation Oncology & Therapy, The First Hospital of Jilin University and College of Basic Medical Science, Jilin University, Changchun, China; Key Laboratory of Pathobiology, Ministry of Education, Jilin University, Changchun 130021, China.
| | - Xin Jiang
- Jilin Provincial Key Laboratory of Radiation Oncology & Therapy, The First Hospital of Jilin University and College of Basic Medical Science, Jilin University, Changchun, China; Department of Radiation Oncology, the First Hospital of Jilin University, Changchun 130021, China; NHC Key Laboratory of Radiobiology, School of Public Health of Jilin University, Changchun 130021, China.
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Liang B, Lu X, Liu L, Dai J, Wang L, Bi N. Synergizing the interaction of single nucleotide polymorphisms with dosiomics features to build a dual-omics model for the prediction of radiation pneumonitis. Radiother Oncol 2024; 196:110261. [PMID: 38548115 DOI: 10.1016/j.radonc.2024.110261] [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: 11/12/2023] [Revised: 03/11/2024] [Accepted: 03/21/2024] [Indexed: 05/06/2024]
Abstract
OBJECTIVE Radiation pneumonitis (RP) is the major dose-limiting toxicity of thoracic radiotherapy. This study aimed to developed a dual-omics (single nucleotide polymorphisms, SNP and dosiomics) prediction model for symptomatic RP. MATERIALS AND METHODS The potential SNPs, which are of significant difference between the RP grade ≥ 3 group and the RP grade ≤ 1 group, were selected from the whole exome sequencing SNPs using the Fisher's exact test. Patients with lung cancer who received thoracic radiotherapy at our institution from 2009 to 2016 were enrolled for SNP selection and model construction. The factorization machine (FM) method was used to model the SNP epistasis effect, and to construct the RP prediction model (SNP-FM). The dosiomics features were extracted, and further selected using the minimum redundancy maximum relevance (mRMR) method. The selected dosiomics features were added to the SNP-FM model to construct the dual-omics model. RESULTS For SNP screening, peripheral blood samples of 28 patients with RP grade ≥ 3 and the matched 28 patients with RP grade ≤ 1 were sequenced. 81 SNPs were of significant difference (P < 0.015) and considered as potential SNPs. In addition, 21 radiation toxicity related SNPs were also included. For model construction, 400 eligible patients (including 108 RP grade ≥ 2) were enrolled. Single SNP showed no strong correlation with RP. On the other hand, the SNP-SNP interaction (epistasis effect) of 19 SNPs were modeled by the FM method, and achieved an area under the curve (AUC) of 0.76 in the testing group. In addition, 4 dosiomics features were selected and added to the model, and increased the AUC to 0.81. CONCLUSIONS A novel dual-omics model by synergizing the SNP epistasis effect with dosiomics features was developed. The enhanced the RP prediction suggested its promising clinical utility in identifying the patients with severe RP during thoracic radiotherapy.
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Affiliation(s)
- Bin Liang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Xiaotong Lu
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China; Department of Radiation Oncology, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou, China
| | - Lipin Liu
- Department of Radiation Oncology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing 100000, China
| | - Jianrong Dai
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
| | - Luhua Wang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China; Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital and Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China.
| | - Nan Bi
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
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Zhang L, Cheng H, Du F, Shao K, Zheng S, Yang Y, Shan G. Single isocenter versus dual isocenter treatment using flattening filter-free and jaw-tracking volumetrically modulated arc therapy for boot-shaped lung cancer: Evaluation of dosimetric and feasibility. J Appl Clin Med Phys 2024; 25:e14292. [PMID: 38286001 PMCID: PMC11163486 DOI: 10.1002/acm2.14292] [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: 10/22/2023] [Revised: 12/23/2023] [Accepted: 01/16/2024] [Indexed: 01/31/2024] Open
Abstract
BACKGROUND To determine whether a dual-isocenter volumetrically modulated arc therapy (VMAT) technique results in lower normal pulmonary dosage compared to a traditional single isocenter technique for boot-shaped lung cancer. METHODS A cohort of 15 patients with advanced peripheral or central lung cancer who had metastases in the mediastinum and supraclavicular lymph nodes was randomly selected for this retrospective study. VMAT plans were generated for each patient using two different beam alignment techniques with the 6-MV flattening filter-free (FFF) photon beam: single-isocenter jaw-tracking VMAT based on the Varian TrueBeam linear accelerator (S-TV), and dual-isocenter VMAT based on both TrueBeam (D-TV) and Halcyon linear accelerator (D-HV). For all 45 treatment plans, planning target volume (PTV) dose coverage, conformity/homogeneity index (CI/HI), mean heart dose (MHD), mean lung dose (MLD) and the total lung tissue receiving 5, 20, 30 Gy (V5, V20, V30) were evaluated. The monitor units (MUs), delivery time, and plan quality assurance (QA) results were recorded. RESULTS The quality of the objectives of the three plans was comparable to each other. In comparison with S-TV, D-TV and D-HV improved the CI and HI of the PTV (p < 0.05). The MLD was 13.84 ± 1.44 Gy (mean ± SD) for D-TV, 14.22 ± 1.30 Gy and 14.16 ± 1.42 Gy for S-TV and D-HV, respectively. Lungs-V5Gy was 50.78 ± 6.24%, 52.00 ± 7.32% and 53.36 ± 8.48%, Lungs-V20Gy was 23.72 ± 2.27%, 26.18 ± 2.86% and 24.96 ± 3.09%, Lungs-V30Gy was 15.69 ± 1.76%, 17.20 ± 1.72% and 16.52 ± 2.07%. Compared to S-TV, D-TV provided statistically significant better protection for the total lung, with the exception of the lungs-V5. All plans passed QA according the gamma criteria of 3%/3 mm. CONCLUSIONS Taking into account the dosimetric results and published clinical data on radiation-induced pulmonary injury, dual-isocenter jaw-tracking VMAT may be the optimal choice for treating boot-shaped lung cancer.
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Affiliation(s)
- Lei Zhang
- Department of Radiation PhysicsZhejiang Cancer HospitalHangzhouZhejiangChina
- Hangzhou Institute of Medicine(HIM)Chinese Academy of SciencesHangzhouZhejiangChina
- Radiotherapy Technology DepartmentYuyao People's Hospital of Zhejiang ProvinceNingBoZhejiangChina
| | - Hang Cheng
- Radiotherapy Technology DepartmentYuyao People's Hospital of Zhejiang ProvinceNingBoZhejiangChina
| | - Fenglei Du
- Department of Radiation PhysicsZhejiang Cancer HospitalHangzhouZhejiangChina
- Hangzhou Institute of Medicine(HIM)Chinese Academy of SciencesHangzhouZhejiangChina
| | - Kainan Shao
- Department of Radiation PhysicsZhejiang Cancer HospitalHangzhouZhejiangChina
- Hangzhou Institute of Medicine(HIM)Chinese Academy of SciencesHangzhouZhejiangChina
| | - Shiming Zheng
- Department of Radiation PhysicsZhejiang Cancer HospitalHangzhouZhejiangChina
- Hangzhou Institute of Medicine(HIM)Chinese Academy of SciencesHangzhouZhejiangChina
| | - Yiwei Yang
- Department of Radiation PhysicsZhejiang Cancer HospitalHangzhouZhejiangChina
- Hangzhou Institute of Medicine(HIM)Chinese Academy of SciencesHangzhouZhejiangChina
| | - Guoping Shan
- Department of Radiation PhysicsZhejiang Cancer HospitalHangzhouZhejiangChina
- Hangzhou Institute of Medicine(HIM)Chinese Academy of SciencesHangzhouZhejiangChina
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Kong Y, Su M, Zhu Y, Li X, Zhang J, Gu W, Yang F, Zhou J, Ni J, Yang X, Zhu Z, Huang J. Enhancing the prediction of symptomatic radiation pneumonitis for locally advanced non-small-cell lung cancer by combining 3D deep learning-derived imaging features with dose-volume metrics: a two-center study. Strahlenther Onkol 2024:10.1007/s00066-024-02221-x. [PMID: 38498173 DOI: 10.1007/s00066-024-02221-x] [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: 12/11/2023] [Accepted: 02/25/2024] [Indexed: 03/20/2024]
Abstract
OBJECTIVE This study aims to examine the ability of deep learning (DL)-derived imaging features for the prediction of radiation pneumonitis (RP) in locally advanced non-small-cell lung cancer (LA-NSCLC) patients. MATERIALS AND METHODS The study cohort consisted of 90 patients from the Fudan University Shanghai Cancer Center and 59 patients from the Affiliated Hospital of Jiangnan University. Occurrences of RP were used as the endpoint event. A total of 512 3D DL-derived features were extracted from two regions of interest (lung-PTV and PTV-GTV) delineated on the pre-radiotherapy planning CT. Feature selection was done using LASSO regression, and the classification models were built using the multilayered perceptron method. Performances of the developed models were evaluated by receiver operating characteristic curve analysis. In addition, the developed models were supplemented with clinical variables and dose-volume metrics of relevance to search for increased predictive value. RESULTS The predictive model using DL features derived from lung-PTV outperformed the one based on features extracted from PTV-GTV, with AUCs of 0.921 and 0.892, respectively, in the internal test dataset. Furthermore, incorporating the dose-volume metric V30Gy into the predictive model using features from lung-PTV resulted in an improvement of AUCs from 0.835 to 0.881 for the training data and from 0.690 to 0.746 for the validation data, respectively (DeLong p < 0.05). CONCLUSION Imaging features extracted from pre-radiotherapy planning CT using 3D DL networks could predict radiation pneumonitis and may be of clinical value for risk stratification and toxicity management in LA-NSCLC patients. CLINICAL RELEVANCE STATEMENT Integrating DL-derived features with dose-volume metrics provides a promising noninvasive method to predict radiation pneumonitis in LA-NSCLC lung cancer radiotherapy, thus improving individualized treatment and patient outcomes.
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Affiliation(s)
- Yan Kong
- Department of Radiation Oncology, Affiliated Hospital of Jiangnan University, 1000 Hefeng Road, 214122, Wuxi, Jiangsu, China
| | - Mingming Su
- Department of Radiation Oncology, Affiliated Hospital of Jiangnan University, 1000 Hefeng Road, 214122, Wuxi, Jiangsu, China
- Department of Medical Oncology, Affiliated Huishan Hospital of Xinglin College, Nantong University, Wuxi Huishan District People's Hospital, 214187, Wuxi, Jiangsu, China
| | - Yan Zhu
- Department of Radiation Oncology, Affiliated Hospital of Jiangnan University, 1000 Hefeng Road, 214122, Wuxi, Jiangsu, China
| | - Xuan Li
- Department of Radiation Oncology, Affiliated Hospital of Jiangnan University, 1000 Hefeng Road, 214122, Wuxi, Jiangsu, China
- Department of Medical Oncology, Affiliated Huishan Hospital of Xinglin College, Nantong University, Wuxi Huishan District People's Hospital, 214187, Wuxi, Jiangsu, China
| | - Jinmeng Zhang
- Department of Radiation Oncology, Affiliated Hospital of Jiangnan University, 1000 Hefeng Road, 214122, Wuxi, Jiangsu, China
- Department of Radiation Oncology, Fudan University Shanghai Cancer Center, 270 Dongan Road, Xuhui, 200032, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, 200032, Shanghai, China
| | - Wenchao Gu
- Department of Diagnostic and Interventional Radiology, University of Tsukuba, 305-8577, Ibaraki, Japan
| | - Fei Yang
- Department of Radiation Oncology, University of Miami, 33136, Miami, FL, USA
| | - Jialiang Zhou
- Department of Radiation Oncology, Affiliated Hospital of Jiangnan University, 1000 Hefeng Road, 214122, Wuxi, Jiangsu, China
| | - Jianjiao Ni
- Department of Radiation Oncology, Fudan University Shanghai Cancer Center, 270 Dongan Road, Xuhui, 200032, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, 200032, Shanghai, China
| | - Xi Yang
- Department of Radiation Oncology, Fudan University Shanghai Cancer Center, 270 Dongan Road, Xuhui, 200032, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, 200032, Shanghai, China
| | - Zhengfei Zhu
- Department of Radiation Oncology, Fudan University Shanghai Cancer Center, 270 Dongan Road, Xuhui, 200032, Shanghai, China.
- Department of Oncology, Shanghai Medical College, Fudan University, 200032, Shanghai, China.
| | - Jianfeng Huang
- Department of Radiation Oncology, Affiliated Hospital of Jiangnan University, 1000 Hefeng Road, 214122, Wuxi, Jiangsu, China.
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Zha Y, Zhang J, Yan X, Yang C, Wen L, Li M. A dynamic nomogram predicting symptomatic pneumonia in patients with lung cancer receiving thoracic radiation. BMC Pulm Med 2024; 24:99. [PMID: 38409084 PMCID: PMC10895758 DOI: 10.1186/s12890-024-02899-w] [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: 07/04/2023] [Accepted: 02/07/2024] [Indexed: 02/28/2024] Open
Abstract
PURPOSE The most common and potentially fatal side effect of thoracic radiation therapy is radiation pneumonitis (RP). Due to the lack of effective treatments, predicting radiation pneumonitis is crucial. This study aimed to develop a dynamic nomogram to accurately predict symptomatic pneumonitis (RP ≥ 2) following thoracic radiotherapy for lung cancer patients. METHODS Data from patients with pathologically diagnosed lung cancer at the Zhongshan People's Hospital Department of Radiotherapy for Thoracic Cancer between January 2017 and June 2022 were retrospectively analyzed. Risk factors for radiation pneumonitis were identified through multivariate logistic regression analysis and utilized to construct a dynamic nomogram. The predictive performance of the nomogram was validated using a bootstrapped concordance index and calibration plots. RESULTS Age, smoking index, chemotherapy, and whole lung V5/MLD were identified as significant factors contributing to the accurate prediction of symptomatic pneumonitis. A dynamic nomogram for symptomatic pneumonitis was developed using these risk factors. The area under the curve was 0.89(95% confidence interval 0.83-0.95). The nomogram demonstrated a concordance index of 0.89(95% confidence interval 0.82-0.95) and was well calibrated. Furthermore, the threshold values for high- risk and low- risk were determined to be 154 using the receiver operating curve. CONCLUSIONS The developed dynamic nomogram offers an accurate and convenient tool for clinical application in predicting the risk of symptomatic pneumonitis in patients with lung cancer undergoing thoracic radiation.
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Affiliation(s)
- Yawen Zha
- Departments of Thoracic Cancer Radiotherapy, Zhongshan People's Hospital, Zhanshan, China
| | - Jingjing Zhang
- Departments of Thoracic Cancer Radiotherapy, Zhongshan People's Hospital, Zhanshan, China
| | - Xinyu Yan
- Xinxiang Medical University, Xinxiang, China
| | - Chen Yang
- Xinxiang Medical University, Xinxiang, China
| | - Lei Wen
- Departments of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Minying Li
- Departments of Thoracic Cancer Radiotherapy, Zhongshan People's Hospital, Zhanshan, China.
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9
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Cogno N, Bauer R, Durante M. Mechanistic model of radiotherapy-induced lung fibrosis using coupled 3D agent-based and Monte Carlo simulations. COMMUNICATIONS MEDICINE 2024; 4:16. [PMID: 38336802 PMCID: PMC10858213 DOI: 10.1038/s43856-024-00442-w] [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: 07/14/2023] [Accepted: 01/22/2024] [Indexed: 02/12/2024] Open
Abstract
BACKGROUND Mechanistic modelling of normal tissue toxicities is unfolding as an alternative to the phenomenological normal tissue complication probability models. The latter, currently used in the clinics, rely exclusively on limited patient data and neglect spatial dose distribution information. Among the various approaches, agent-based models are appealing as they provide the means to include patient-specific parameters and simulate long-term effects in complex systems. However, Monte Carlo tools remain the state-of-the-art for modelling radiation transport and provide measurements of the delivered dose with unmatched precision. METHODS In this work, we develop and characterize a coupled 3D agent-based - Monte Carlo model that mechanistically simulates the onset of the radiation-induced lung fibrosis in an alveolar segment. To the best of our knowledge, this is the first such model. RESULTS Our model replicates extracellular matrix patterns, radiation-induced lung fibrosis severity indexes and functional subunits survivals that show qualitative agreement with experimental studies and are consistent with our past results. Moreover, in accordance with experimental results, higher functional subunits survival and lower radiation-induced lung fibrosis severity indexes are achieved when a 5-fractions treatment is simulated. Finally, the model shows increased sensitivity to more uniform protons dose distributions with respect to more heterogeneous ones from photon irradiation. CONCLUSIONS This study lays thus the groundwork for further investigating the effects of different radiotherapeutic treatments on the onset of radiation-induced lung fibrosis via mechanistic modelling.
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Affiliation(s)
- Nicolò Cogno
- Biophysics Department, GSI Helmholtzzentrum für Schwerionenforschung GmbH, 64291, Darmstadt, Germany
- Institute for Condensed Matter Physics, Technische Universität Darmstadt, 64289, Darmstadt, Germany
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Roman Bauer
- Department of Computer Science, University of Surrey, Guildford, GU2 7XH, UK
| | - Marco Durante
- Biophysics Department, GSI Helmholtzzentrum für Schwerionenforschung GmbH, 64291, Darmstadt, Germany.
- Institute for Condensed Matter Physics, Technische Universität Darmstadt, 64289, Darmstadt, Germany.
- Department of Physics "Ettore Pancini", University Federico II, Naples, Italy.
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10
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Burmeister JW, Bossenberger T, Nalichowski A, Hammoud A, Baran G, Dominello MM. Total body irradiation delivered using a dedicated Co-60 TBI unit: Evaluation of dosimetric uniformity and dose verification. J Appl Clin Med Phys 2024; 25:e14188. [PMID: 37910646 PMCID: PMC10860458 DOI: 10.1002/acm2.14188] [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: 07/12/2023] [Revised: 10/03/2023] [Accepted: 10/11/2023] [Indexed: 11/03/2023] Open
Abstract
This work presents the dosimetric characteristics of Total Body Irradiation (TBI) delivered using a dedicated Co-60 TBI unit. We demonstrate the ability to deliver a uniform dose to the entire patient without the need for a beam spoiler or patient-specific compensation. Full dose distributions are calculated using an in-house Monte Carlo treatment planning system, and cumulative dose distributions are created by deforming the dose distributions within two different patient orientations. Sample dose distributions and profiles are provided to illustrate the plan characteristics, and dose and DVH statistics are provided for a heterogeneous cohort of patients. The patient cohort includes adult and pediatric patients with a range of 132-198 cm in length and 16.5-37.5 cm in anterior-posterior thickness. With the exception of the lungs, a uniform dose of 12 Gy is delivered to the patient with nearly the entire volume receiving a dose within 10% of the prescription dose. Mean lung doses (MLDs) are maintained below the estimated threshold for radiation pneumonitis, with MLDs ranging from 7.3 to 9.3 Gy (estimated equivalent dose in 2 Gy fractions (EQD2 ) of 6.2-8.5 Gy). Dose uniformity is demonstrated across five anatomical locations within the patient for which mean doses are all within 3.1% of the prescription dose. In-vivo dosimetry demonstrates excellent agreement between measured and calculated doses, with 78% of measurements within ±5% of the calculated dose and 99% within ±10%. These results demonstrate a state-of-the-art TBI planning and delivery system using a dedicated TBI unit and hybrid in-house and commercial planning techniques which provide comprehensive dosimetric data for TBI treatment plans that are accurately verified using in-vivo dosimetry.
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Affiliation(s)
- Jay W. Burmeister
- Department of OncologyWayne State University School of MedicineDetroitMichiganUSA
- Gershenson Radiation Oncology CenterBarbara Ann Karmanos Cancer InstituteDetroitMichiganUSA
| | - Todd Bossenberger
- Gershenson Radiation Oncology CenterBarbara Ann Karmanos Cancer InstituteDetroitMichiganUSA
| | - Adrian Nalichowski
- Department of OncologyWayne State University School of MedicineDetroitMichiganUSA
- Gershenson Radiation Oncology CenterBarbara Ann Karmanos Cancer InstituteDetroitMichiganUSA
| | - Ahmad Hammoud
- Gershenson Radiation Oncology CenterBarbara Ann Karmanos Cancer InstituteDetroitMichiganUSA
| | - Geoff Baran
- Gershenson Radiation Oncology CenterBarbara Ann Karmanos Cancer InstituteDetroitMichiganUSA
| | - Michael M. Dominello
- Department of OncologyWayne State University School of MedicineDetroitMichiganUSA
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11
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Orfanakos K, Alifieris CE, Verigos EK, Deligiorgi MV, Verigos KE, Panayiotidis MI, Nikolaou M, Trafalis DT. The Predictive Value of 8-Hydroxy-Deoxyguanosine (8-OHdG) Serum Concentrations in Irradiated Non-Small Cell Lung Carcinoma (NSCLC) Patients. Biomedicines 2024; 12:134. [PMID: 38255239 PMCID: PMC10813052 DOI: 10.3390/biomedicines12010134] [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: 11/26/2023] [Revised: 12/11/2023] [Accepted: 12/18/2023] [Indexed: 01/24/2024] Open
Abstract
Ionizing radiation is strongly linked to direct or indirect DNA damage, as with the production of reactive oxygen species (ROS), which in turn produce DNA damage products, such as 8-hydroxy-2-deoxyguanosine (8-OHdG). In this study, we aimed to investigate the formation of 8-OHdG after irradiation in patients with non-small cell cancer (NSCLC) and its use as a biomarker. Sixteen patients with squamous and thirty-six patients with non-squamous pathology were included. An enzyme-linked-immunosorbent assay (ELISA) was performed before and after radiation. A dose-dependent relationship was confirmed: 8-OHdG plasma concentrations, increased in the total of NSCLC patients and specifically with a linear correlation in non-squamous pathology; in squamous histology, after an initial increase, a significant decrease followed after 20 Gy dose of irradiation. The pretreatment total irradiated tumor volume (cm3) was positively correlated with 8-OHdG levels in patients with squamous histology. When plotting the 8-OHdG plasma concentration at a 10 Gy irradiation dose to the baseline, the AUC was 0.873 (95% CI 0.614-0.984), p < 0.0001, with an associated criterion value of >1378 as a cutoff (sensitivity 72.7%, specificity 100%). When normalizing this ratio to BSA, the associated criterion cutoff value was >708 (sensitivity of 100%, specificity 80%). Lastly, 8-OHdG levels were closely related with the development of radiation-induced toxicities.
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Affiliation(s)
- Kyriakos Orfanakos
- Laboratory of Pharmacology, Faculty of Medicine, National and Kapodistrian University of Athens, 11527 Athens, Greece; (K.O.); (M.V.D.); (K.E.V.); (D.T.T.)
- Department of Radiation Therapy, 401 General Military Hospital, 11525 Athens, Greece
| | - Constantinos E. Alifieris
- Laboratory of Pharmacology, Faculty of Medicine, National and Kapodistrian University of Athens, 11527 Athens, Greece; (K.O.); (M.V.D.); (K.E.V.); (D.T.T.)
- Department of Hepatobiliary and Transplant Surgery, St. Vincent’s University Hospital, D04 T6F4 Dublin, Ireland
| | - Emmanouil K. Verigos
- Department of Radiation Oncology, General Anticancer Oncology Hospital of Athens “O Agios Savvas”, 11522 Athens, Greece
| | - Maria V. Deligiorgi
- Laboratory of Pharmacology, Faculty of Medicine, National and Kapodistrian University of Athens, 11527 Athens, Greece; (K.O.); (M.V.D.); (K.E.V.); (D.T.T.)
| | - Kosmas E. Verigos
- Laboratory of Pharmacology, Faculty of Medicine, National and Kapodistrian University of Athens, 11527 Athens, Greece; (K.O.); (M.V.D.); (K.E.V.); (D.T.T.)
- Department of Radiation Therapy, 401 General Military Hospital, 11525 Athens, Greece
| | - Mihalis I. Panayiotidis
- Department of Cancer Genetics, Therapeutics & Ultrastructural Pathology, The Cyprus Institute of Neurology & Genetics, Nicosia 2371, Cyprus
| | - Michail Nikolaou
- Laboratory of Pharmacology, Faculty of Medicine, National and Kapodistrian University of Athens, 11527 Athens, Greece; (K.O.); (M.V.D.); (K.E.V.); (D.T.T.)
| | - Dimitrios T. Trafalis
- Laboratory of Pharmacology, Faculty of Medicine, National and Kapodistrian University of Athens, 11527 Athens, Greece; (K.O.); (M.V.D.); (K.E.V.); (D.T.T.)
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Aoyama T, Shimizu H, Koide Y, Kamezawa H, Fukunaga JI, Kitagawa T, Tachibana H, Suzuki K, Kodaira T. Deep Learning-based Lung dose Prediction Using Chest X-ray Images in Non-small Cell Lung Cancer Radiotherapy. J Med Phys 2024; 49:33-40. [PMID: 38828071 PMCID: PMC11141742 DOI: 10.4103/jmp.jmp_122_23] [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: 09/15/2023] [Revised: 01/29/2024] [Accepted: 01/29/2024] [Indexed: 06/05/2024] Open
Abstract
Purpose This study aimed to develop a deep learning model for the prediction of V20 (the volume of the lung parenchyma that received ≥20 Gy) during intensity-modulated radiation therapy using chest X-ray images. Methods The study utilized 91 chest X-ray images of patients with lung cancer acquired routinely during the admission workup. The prescription dose for the planning target volume was 60 Gy in 30 fractions. A convolutional neural network-based regression model was developed to predict V20. To evaluate model performance, the coefficient of determination (R2), root mean square error (RMSE), and mean absolute error (MAE) were calculated with conducting a four-fold cross-validation method. The patient characteristics of the eligible data were treatment period (2018-2022) and V20 (19.3%; 4.9%-30.7%). Results The predictive results of the developed model for V20 were 0.16, 5.4%, and 4.5% for the R2, RMSE, and MAE, respectively. The median error was -1.8% (range, -13.0% to 9.2%). The Pearson correlation coefficient between the calculated and predicted V20 values was 0.40. As a binary classifier with V20 <20%, the model showed a sensitivity of 75.0%, specificity of 82.6%, diagnostic accuracy of 80.6%, and area under the receiver operator characteristic curve of 0.79. Conclusions The proposed deep learning chest X-ray model can predict V20 and play an important role in the early determination of patient treatment strategies.
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Affiliation(s)
- Takahiro Aoyama
- Department of Radiation Oncology, Aichi Cancer Center, Nagoya, Japan
| | - Hidetoshi Shimizu
- Department of Radiation Oncology, Aichi Cancer Center, Nagoya, Japan
| | - Yutaro Koide
- Department of Radiation Oncology, Aichi Cancer Center, Nagoya, Japan
| | - Hidemi Kamezawa
- Division of Radiological Sciences, Graduate School of Health Sciences, Teikyo University, Fukuoka, Japan
| | - Jun-Ichi Fukunaga
- Division of Radiology, Department of Medical Technology, Kyushu University Hospital, Fukuoka, Japan
| | - Tomoki Kitagawa
- Department of Radiation Oncology, Aichi Cancer Center, Nagoya, Japan
| | | | - Kojiro Suzuki
- Department of Radiology, Aichi Medical University, Nagakute, Aichi, Japan
| | - Takeshi Kodaira
- Department of Radiation Oncology, Aichi Cancer Center, Nagoya, Japan
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13
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Hirama N, Yamamoto M, Nagaoka S, Segawa W, Sugimoto C, Nagayama H, Hiro S, Kajita Y, Maeda C, Kubo S, Seki K, Nagahara Y, Teranishi S, Tashiro K, Hara Y, Kobayashi N, Watanabe S, Kudo M, Kaneko T. Predictors of lung injury during durvalumab maintenance therapy following concurrent chemoradiotherapy in unresectable locally advanced non-small cell lung carcinoma. Thorac Cancer 2023; 14:2601-2607. [PMID: 37533115 PMCID: PMC10481134 DOI: 10.1111/1759-7714.15042] [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: 06/29/2023] [Accepted: 07/06/2023] [Indexed: 08/04/2023] Open
Abstract
BACKGROUND Based on the results of the PACIFIC trial, maintenance with durvalumab has emerged as the standard treatment following concurrent chemoradiotherapy in patients with unresectable locally advanced non-small cell lung carcinoma (NSCLC). However, adverse events attributed to durvalumab, especially lung injuries, including immune-related adverse events, and radiation pneumonitis, are concerning. This study retrospectively investigated the factors related to lung injury in patients receiving the PACIFIC regimen. METHODS Patients with unresectable locally advanced NSCLC who received durvalumab maintenance therapy following concurrent chemoradiotherapy at Yokohama City University Medical Centre between July 2018 and March 2022 were included. Clinical data, volume of normal lung receiving 20 or 5 Gy or more (V20 or V5), planning target volume (PTV), and relative lung parenchyma volume in emphysematous lung receiving 20 or 5 Gy or more (RLPV20 or 5; V20 or V5/100-percentage of low-attenuation volume) were evaluated. RESULTS Performance status (PS), V20, V5, PTV, RLPV20, and RLPV5 were significantly higher in the lung injury group in the univariate analysis. Furthermore, RLPV20 was the most significant factor in the lung injury group in the multivariate analysis comprising PS, PTV, V20, and RLPV20. CONCLUSION RLPV20 and RLPV5 are useful in estimating lung inflammation. RLPV20 could be considered the most reliable risk factor for maintenance therapy with durvalumab following concurrent chemoradiotherapy in patients with unresectable locally advanced NSCLC.
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Affiliation(s)
- Nobuyuki Hirama
- Respiratory Disease CenterYokohama City University Medical CenterYokohamaJapan
| | - Masaki Yamamoto
- Respiratory Disease CenterYokohama City University Medical CenterYokohamaJapan
| | - Satoshi Nagaoka
- Respiratory Disease CenterYokohama City University Medical CenterYokohamaJapan
| | - Wataru Segawa
- Respiratory Disease CenterYokohama City University Medical CenterYokohamaJapan
| | - Chihiro Sugimoto
- Respiratory Disease CenterYokohama City University Medical CenterYokohamaJapan
| | - Hirokazu Nagayama
- Respiratory Disease CenterYokohama City University Medical CenterYokohamaJapan
| | - Shuntaro Hiro
- Respiratory Disease CenterYokohama City University Medical CenterYokohamaJapan
| | - Yukihito Kajita
- Respiratory Disease CenterYokohama City University Medical CenterYokohamaJapan
| | - Chihiro Maeda
- Respiratory Disease CenterYokohama City University Medical CenterYokohamaJapan
| | - Sousuke Kubo
- Respiratory Disease CenterYokohama City University Medical CenterYokohamaJapan
| | - Kenichi Seki
- Respiratory Disease CenterYokohama City University Medical CenterYokohamaJapan
| | - Yoshinori Nagahara
- Respiratory Disease CenterYokohama City University Medical CenterYokohamaJapan
| | - Shuhei Teranishi
- Respiratory Disease CenterYokohama City University Medical CenterYokohamaJapan
| | - Ken Tashiro
- Respiratory Disease CenterYokohama City University Medical CenterYokohamaJapan
| | - Yu Hara
- Department of PulmonologyYokohama City University Graduate School of MedicineYokohamaJapan
| | - Nobuaki Kobayashi
- Department of PulmonologyYokohama City University Graduate School of MedicineYokohamaJapan
| | | | - Makoto Kudo
- Respiratory Disease CenterYokohama City University Medical CenterYokohamaJapan
| | - Takeshi Kaneko
- Department of PulmonologyYokohama City University Graduate School of MedicineYokohamaJapan
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14
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Sosa-Marrero C, Acosta O, Pasquier D, Thariat J, Delpon G, Fiorino C, Rancatti T, Malard O, Foray N, de Crevoisier R. Voxel-wise analysis: A powerful tool to predict radio-induced toxicity and potentially perform personalised planning in radiotherapy. Cancer Radiother 2023; 27:638-642. [PMID: 37517974 DOI: 10.1016/j.canrad.2023.06.024] [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: 06/22/2023] [Accepted: 06/27/2023] [Indexed: 08/01/2023]
Abstract
Dose - volume histograms have been historically used to study the relationship between the planned radiation dose and healthy tissue damage. However, this approach considers neither spatial information nor heterogenous radiosensitivity within organs at risk, depending on the tissue. Recently, voxel-wise analyses have emerged in the literature as powerful tools to fully exploit three-dimensional information from the planned dose distribution. They allow to identify anatomical subregions of one or several organs in which the irradiation dose is associated with a given toxicity. These methods rely on an accurate anatomical alignment, usually obtained by means of a non-rigid registration. Once the different anatomies are spatially normalised, correlations between the three-dimensional dose and a given toxicity can be explored voxel-wise. Parametric or non-parametric statistical tests can be performed on every voxel to identify the voxels in which the dose is significantly different between patients presenting or not toxicity. Several anatomical subregions associated with genitourinary, gastrointestinal, cardiac, pulmonary or haematological toxicity have already been identified in the literature for prostate, head and neck or thorax irradiation. Voxel-wise analysis appears therefore first particularly interesting to increase toxicity prediction capability by identifying specific subregions in the organs at risk whose irradiation is highly predictive of specific toxicity. The second interest is potentially to decrease the radio-induced toxicity by limiting the dose in the predictive subregions, while not decreasing the dose in the target volume. Limitations of the approach have been pointed out.
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Affiliation(s)
- C Sosa-Marrero
- Université de Rennes, CLCC Eugène-Marquis, Inserm, LTSI - UMR 1099, 35000 Rennes, France
| | - O Acosta
- Université de Rennes, CLCC Eugène-Marquis, Inserm, LTSI - UMR 1099, 35000 Rennes, France
| | - D Pasquier
- Radiotherapy Department, centre Oscar-Lambret, 59000 Lille, France; Université de Lille, CNRS, école centrale de Lille, Cristal UMR 9189, Lille, France
| | - J Thariat
- Department of Radiation Oncology, centre François-Baclesse, 14000 Caen, France
| | - G Delpon
- Medical physics department, institut de cancérologie de l'Ouest, IMT Atlantique, Nantes université, CNRS/IN2P3, Subatech, Nantes, France
| | - C Fiorino
- Medical Physics, San Raffaele Scientific Institute, Via Olgettina 690, 20132 Milan, Italy
| | - T Rancatti
- Data Science Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - O Malard
- Service de chirurgie oto-rhinolaryngologique (ORL) et chirurgie cervicofaciale, Hôtel-Dieu, CHU de Nantes, Nantes, France
| | - N Foray
- Centre Léon-Bérard, Inserm U1296 "Radiation: Defense/Health/Environment", 69008 Lyon, France
| | - R de Crevoisier
- Université de Rennes, CLCC Eugène-Marquis, Inserm, LTSI - UMR 1099, 35000 Rennes, France; Département de radiothérapie, centre Eugène-Marquis, 35000 Rennes, France.
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15
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Zhao J, Ma C, Gan G, Xu X, Zhou J. Analysis of clinical and physical dosimetric factors that determine the outcome of severe acute radiation pneumonitis in lung cancer patients. Radiat Oncol 2023; 18:143. [PMID: 37644602 PMCID: PMC10463737 DOI: 10.1186/s13014-023-02304-6] [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: 01/02/2023] [Accepted: 06/20/2023] [Indexed: 08/31/2023] Open
Abstract
OBJECTIVE We conducted a retrospective statistical analysis of clinical and physical dosimetric factors of lung cancer patients who had previously undergone lung and/or mediastinal radiotherapy and died of or survived severe acute radiation pneumonitis (SARP). Our study was the first to reveal the heterogeneity in clinical factors, physical dosimetric factors, and SARP onset time that determined the clinical outcomes of lung cancer patients who developed SARP. MATERIALS AND METHODS The clinical characteristics, physical dosimetry factors, and SARP onset time of deceased and surviving patients were retrospectively analyzed. SPSS 20.0 was used for data analysis. Student's t-test was used for intergroup comparison, and a Mann-Whitney U test was used for data with skewed distribution. Qualitative data were represented using frequencies (%), and Fisher's exact test or χ2 test was used for intergroup comparison of nonparametric data. Binary logistic analysis was used for univariate and multivariate analyses. Differences with a P < 0.05 were considered statistically significant. RESULTS Univariate analysis revealed that the potential predictors of SARP death were as follows: ipsilateral lung V5 and V30, contralateral lung V5, V10, and V30, total lung V5, V10, and V30, mean lung dose, mean heart dose, and maximum spinal cord dose. Multivariate analysis showed that ipsilateral lung V5 and total lung V5 were predictors that determined the final outcome of SARP patients. In addition, we analyzed the time from the completion of radiotherapy to SARP onset, and found significant difference between the two groups. CONCLUSIONS There was no decisive correlation between clinical characteristics and SARP outcome (i.e., death or survival) in lung radiotherapy patients. Ipsilateral lung V5 and total lung V5 were independent predictors of death in SARP patients.
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Affiliation(s)
- Jing Zhao
- Department of Radiation Oncology, First Affiliated Hospital of Soochow University, Suzhou, 215000, China
| | - Chenying Ma
- Department of Radiation Oncology, First Affiliated Hospital of Soochow University, Suzhou, 215000, China
| | - Guanghui Gan
- Department of Radiation Oncology, First Affiliated Hospital of Soochow University, Suzhou, 215000, China
| | - Xiaoting Xu
- Department of Radiation Oncology, First Affiliated Hospital of Soochow University, Suzhou, 215000, China.
| | - Juying Zhou
- Department of Radiation Oncology, First Affiliated Hospital of Soochow University, Suzhou, 215000, China.
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16
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Kirakli EK, Erdem S, Susam S, Erim E. Ipsilateral lung dose as a correlative measure for radiation pneumonitis in patients treated with definitive concurrent radiochemotherapy. J Cancer Res Ther 2023; 19:1153-1159. [PMID: 37787278 DOI: 10.4103/jcrt.jcrt_618_21] [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: 10/04/2023]
Abstract
Objective Mean lung dose (MLD) and percent of total lung (TL) volume that receive a dose greater than 20 Gy (V20) have been the most validated parameters in the prediction of radiation pneumonitis (RP). However, these parameters present mean values of TL parenchyma and predict the right and the left lung as a unique functional organ unit, not take into account the difference in function and dose density between the lungs. Furthermore, there have been very limited data evaluating ipsilateral lung dosimetric constraints in addition to TL parameters to predict RP in non-small cell lung cancer (NSCLC) patients treated with radiochemotherapy (RCT). Methods Between 2010 and 2017, clinical-radiological findings of NSCLC patients treated with RCT were evaluated in terms of RP, retrospectively. MLD, V20, and V30 values of ipsilateral lung were assessed from dose-volume histogram and registered. The primary endpoint was to assess the relation between ipsilateral lung dose constraints and RP risk. Results There were 75 patients. There was ≥Grade 2 RP in 33 cases (%44). In univariate analysis, ipsilateral MLD, ipsilateral V20, ipsilateral V30, and TL V30 were found to be significant. Ipsilateral MLD and PTV were found to be the independent risk factors for RP. Cutoff values for RP risk were determined as 18Gy, 35%, and 28% for ipsilateral MLD, ipsilateral V20, and ipsilateral V30, respectively. Predictive values for ipsilateral MLD and ipsilateral V20 were higher than TL. Conclusions In NSCLC patients treated with RCT, MLD, V20, and V30 values of ipsilateral lung parameters might increase the predictability of RP risk in addition to TL parameters. Advances in Knowledge Cutoff values for RP risk were determined as 18Gy, 35%, and 28% for ipsilateral MLD, ipsilateral V20, and ipsilateral V30, respectively. Predictive values for ipsilateral MLD and ipsilateral V20 were higher than TL.
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Affiliation(s)
- Esra Korkmaz Kirakli
- Department of Radiation, Dr. Suat Seren Chest Diseases and Surgery Research and Training Hospital, Konak, Izmir, Turkey
| | - Sevilay Erdem
- Department of Radiation, Dr. Suat Seren Chest Diseases and Surgery Research and Training Hospital, Konak, Izmir, Turkey
| | - Seher Susam
- Department of Radiology, Dr. Suat Seren Chest Diseases and Surgery Research and Training Hospital, Konak, Izmir, Turkey
| | - Eser Erim
- Department of Radiation, Dr. Suat Seren Chest Diseases and Surgery Research and Training Hospital, Konak, Izmir, Turkey
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Chen F, Niu J, Wang M, Zhu H, Guo Z. Re-evaluating the risk factors for radiation pneumonitis in the era of immunotherapy. J Transl Med 2023; 21:368. [PMID: 37287014 DOI: 10.1186/s12967-023-04212-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Accepted: 05/19/2023] [Indexed: 06/09/2023] Open
Abstract
As one of the common complications of radiotherapy, radiation pneumonia (RP) limits the prognosis of patients. Therefore, better identifying the high-risk factors that lead to RP is essential to effectively prevent its occurrence. However, as lung cancer treatment modalities are being replaced and the era of immunotherapy has arrived, literature that reviews the parameters and mode of radiotherapy, chemotherapy drugs, targeted drugs and current hot immune checkpoint inhibitors related to RP is lacking. This paper summarizes the risk factors for radiation pneumonia by retrieving and analysing previously published literature and the results of large clinical trials. The literature primarily included retrospective analyses, including clinical trials in different periods and a part of the literature review. A systematic literature search of Embase, PubMed, Web of Science, and Clinicaltrials.gov was performed for relevant publications up to 6 Dec. 2022. Search keywords include, but are not limited to, "radiation pneumonia", "pneumonia", "risk factors", "immunotherapy", etc. The factors related to RP in this paper include physical parameters of radiotherapy, including V5, V20, and MLD; chemoradiotherapy mode and chemotherapy drugs, including paclitaxel and gemcitabine; EGFR-TKI; ALK inhibitors; antiangiogenic drugs; immune drugs and the underlying disease of the patient. We also introduce the possible mechanism of RP. In the future, we hope that this article not only sounds the alarm for clinicians but also helps to identify a method that can effectively intervene and reduce the occurrence of RP, significantly improve the quality of life and prognosis of patients, and more effectively improve the therapeutic effect of radiation therapy.
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Affiliation(s)
- Feihu Chen
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, 440 Jiyan Road, Jinan, 250117, Shandong, China
| | - Jiling Niu
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, 440 Jiyan Road, Jinan, 250117, Shandong, China
| | - Min Wang
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, 440 Jiyan Road, Jinan, 250117, Shandong, China
| | - Hui Zhu
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, 440 Jiyan Road, Jinan, 250117, Shandong, China.
| | - Zhijun Guo
- Department of Intensive Care Unit, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, 440 Jiyan Road, Jinan, 250117, Shandong, China.
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18
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Sakagami M, Inokuchi H, Mukumoto N, Itoyama H, Hamaura N, Yamagishi M, Mukumoto N, Matsuda S, Kabata D, Shibuya K. Clinical features and risk factors for interstitial lung disease spreading in low-dose irradiated areas after definitive radiotherapy with or without durvalumab consolidation therapy for patients with non-small cell lung cancer. Radiat Oncol 2023; 18:87. [PMID: 37217919 DOI: 10.1186/s13014-023-02276-7] [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: 08/18/2022] [Accepted: 05/04/2023] [Indexed: 05/24/2023] Open
Abstract
BACKGROUND The current standard of care for patients with unresectable locally advanced non-small cell lung cancer (NSCLC) is chemoradiotherapy (CRT) combined with durvalumab consolidation therapy. However, radiotherapy (RT) always carries the risk of radiation pneumonitis (RP), which can preclude durvalumab continuation. In particular, the spread of interstitial lung disease (ILD) in low-dose areas or extending beyond the RT field often makes it difficult to determine the safety of continuation or rechallenging of durvalumab. Thus, we retrospectively analyzed ILD/RP after definitive RT with and without durvalumab, with assessment of radiologic features and dose distribution in RT. METHODS We retrospectively evaluated the clinical records, CT imaging, and radiotherapy planning data of 74 patients with NSCLC who underwent definitive RT at our institution between July 2016 and July 2020. We assessed the risk factors for recurrence within one year and occurrence of ILD/RP. RESULTS Kaplan-Meier method showed that ≥ 7 cycles of durvalumab significantly improved 1-year progression free survival (PFS) (p < 0.001). Nineteen patients (26%) were diagnosed with ≥ Grade 2 and 7 (9.5%) with ≥ Grade 3 ILD/RP after completing RT. There was no significant correlation between durvalumab administration and ≥ Grade 2 ILD/RP. Twelve patients (16%) developed ILD/RP that spread outside the high-dose (> 40 Gy) area, of whom 8 (67%) had ≥ Grade 2 and 3 (25%) had Grade 3 symptoms. In unadjusted and multivariate Cox proportional-hazards models adjusted for V20 (proportion of the lung volume receiving ≥ 20 Gy), high HbA1c level was significantly correlated with ILD/RP pattern spreading outside the high-dose area (hazard ratio, 1.842; 95% confidence interval, 1.35-2.51). CONCLUSIONS Durvalumab improved 1-year PFS without increasing the risk of ILD/RP. Diabetic factors were associated with ILD/RP distribution pattern spreading in the lower dose area or outside RT fields, with a high rate of symptoms. Further study of the clinical background of patients including diabetes is needed to safely increase the number of durvalumab doses after CRT.
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Affiliation(s)
- Mai Sakagami
- Department of Radiation Oncology, Graduate School of Medicine, Osaka City University, Osaka, Japan.
| | - Haruo Inokuchi
- Department of Radiation Oncology, Graduate School of Medicine, Osaka Metropolitan University, Osaka, Japan
| | - Nobutaka Mukumoto
- Department of Radiation Oncology, Graduate School of Medicine, Osaka Metropolitan University, Osaka, Japan
| | - Hiroshige Itoyama
- Department of Radiation Oncology, Graduate School of Medicine, Osaka Metropolitan University, Osaka, Japan
| | - Nobunari Hamaura
- Department of Radiation Oncology, Graduate School of Medicine, Osaka Metropolitan University, Osaka, Japan
| | - Mutsumi Yamagishi
- Department of Radiation Oncology, Graduate School of Medicine, Osaka Metropolitan University, Osaka, Japan
| | - Naoki Mukumoto
- Department of Radiation Oncology, Graduate School of Medicine, Osaka Metropolitan University, Osaka, Japan
| | - Shogo Matsuda
- Department of Radiation Oncology, Graduate School of Medicine, Osaka Metropolitan University, Osaka, Japan
| | - Daijiro Kabata
- Department of Medical Statistics, Graduate School of Medicine, Osaka Metropolitan University, Osaka, Japan
| | - Keiko Shibuya
- Department of Radiation Oncology, Graduate School of Medicine, Osaka Metropolitan University, Osaka, Japan
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19
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Laughlin BS, Stoker J, Vern-Gross T. Proton Beam Therapy for Unresectable Mediastinal and Pericardial Spindle Cell Sarcoma: A Case Report. Int J Part Ther 2023; 10:43-50. [PMID: 37823013 PMCID: PMC10563663 DOI: 10.14338/ijpt-23-00001.1] [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: 01/15/2023] [Accepted: 03/29/2023] [Indexed: 10/13/2023] Open
Abstract
Unresectable mediastinal soft tissue sarcomas are often aggressive and associated with a poor prognosis. A 17-year-old male presented with progressive fatigue, shortness of breath, and heart palpitations secondary to an extensive mass involving the mediastinum and pericardium. He was treated with chemotherapy per protocol Children's Oncology Group Protocol ARST0332 and proton beam therapy to the involved mediastinum, pericardium, and heart. At the 5-year follow-up evaluation, he remained disease-free on surveillance imaging. An echocardiogram revealed a 55% to 60% left ventricular ejection fraction. Given the patient's extended survival, we present the oncologic rationale for treatment and considerations of late toxicity.
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Affiliation(s)
| | - Joshua Stoker
- Department of Radiation Oncology, Mayo Clinic, Phoenix, AZ, USA
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20
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Katsuta Y, Kadoya N, Kajikawa T, Mouri S, Kimura T, Takeda K, Yamamoto T, Imano N, Tanaka S, Ito K, Kanai T, Nakajima Y, Jingu K. Radiation pneumonitis prediction model with integrating multiple dose-function features on 4DCT ventilation images. Phys Med 2023; 105:102505. [PMID: 36535238 DOI: 10.1016/j.ejmp.2022.11.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 11/18/2022] [Accepted: 11/25/2022] [Indexed: 12/23/2022] Open
Abstract
PURPOSE Radiation pneumonitis (RP) is dose-limiting toxicity for non-small-cell cancer (NSCLC). This study developed an RP prediction model by integrating dose-function features from computed four-dimensional computed tomography (4DCT) ventilation using the least absolute shrinkage and selection operator (LASSO). METHODS Between 2013 and 2020, 126 NSCLC patients were included in this study who underwent a 4DCT scan to calculate ventilation images. We computed two sets of candidate dose-function features from (1) the percentage volume receiving > 20 Gy or the mean dose on the functioning zones determined with the lower cutoff percentile ventilation value, (2) the functioning zones determined with lower and upper cutoff percentile ventilation value using 4DCT ventilation images. An RP prediction model was developed by LASSO while simultaneously determining the regression coefficient and feature selection through fivefold cross-validation. RESULTS We found 39.3 % of our patients had a ≥ grade 2 RP. The mean area under the curve (AUC) values for the developed models using clinical, dose-volume, and dose-function features with a lower cutoff were 0.791, and the mean AUC values with lower and upper cutoffs were 0.814. The relative regression coefficient (RRC) on dose-function features with upper and lower cutoffs revealed a relative impact of dose to each functioning zone to RP. RRCs were 0.52 for the mean dose on the functioning zone, with top 20 % of all functioning zone was two times greater than that of 0.19 for these with 60 %-80 % and 0.17 with 40 %-60 % (P < 0.01). CONCLUSIONS The introduction of dose-function features computed from functioning zones with lower and upper cutoffs in a machine learning framework can improve RP prediction. The RRC given by LASSO using dose-function features allows for the quantification of the RP impact of dose on each functioning zones and having the potential to support treatment planning on functional image-guided radiotherapy.
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Affiliation(s)
- Yoshiyuki Katsuta
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan.
| | - Noriyuki Kadoya
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Tomohiro Kajikawa
- Department of Radiology, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Shina Mouri
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Tomoki Kimura
- Department of Radiation Oncology, Kochi Medical School, Kochi University, Nangoku, Japan
| | - Kazuya Takeda
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Takaya Yamamoto
- Department of Radiation Oncology, Graduate School of Biomedical Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Nobuki Imano
- 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
| | - Kengo Ito
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Takayuki Kanai
- Department of Radiation Oncology, Yamagata University, Yamagata, Japan
| | - Yujiro Nakajima
- Department of Radiological Sciences, Komazawa University, Tokyo, Japan
| | - Keiichi Jingu
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan
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21
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Diamond BH, Belani N, Masel R, DeCarli K, DiPetrillo T, Hepel JT, Azzoli CG, Khurshid H, Abbas A, Koffer PP. Predictors of Pneumonitis in Patients With Locally Advanced Non-Small Cell Lung Cancer Treated With Definitive Chemoradiation Followed by Consolidative Durvalumab. Adv Radiat Oncol 2022; 8:101130. [PMID: 36845618 PMCID: PMC9943772 DOI: 10.1016/j.adro.2022.101130] [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: 09/02/2022] [Accepted: 11/21/2022] [Indexed: 11/29/2022] Open
Abstract
Purpose In patients with locally advanced, unresectable non-small cell lung cancer (NSCLC), the standard of care is concurrent chemoradiation (CRT) followed by consolidative immunotherapy with durvalumab. Pneumonitis is a known adverse event of both radiation therapy and immune checkpoint inhibitors such as durvalumab. We sought to characterize pneumonitis rates and dosimetric predictors of pneumonitis in a real-world population of patients with NSCLC treated with definitive CRT followed by consolidative durvalumab. Methods and Materials Patients with NSCLC from a single institution who were treated with definitive CRT followed by consolidative durvalumab were identified. Outcomes of interest included pneumonitis incidence, type of pneumonitis, progression-free survival, and overall survival. Results Sixty-two patients were included in our data set treated from 2018 to 2021 with a median follow-up of 17 months. The rate of grade 2+ pneumonitis in our cohort was 32.3%, and the rate of grade 3+ pneumonitis was 9.7%. Lung dosimetry parameters including V20 ≥30% and mean lung dose (MLD) >18 Gy were found to be correlated with increased rates of grade 2+ and grade 3+ pneumonitis. Patients with a lung V20 ≥30% had a grade 2+ pneumonitis rate at 1 year of 49.8% compared with 17.8% in patients with a lung V20 <30% (P = .015). Similarly, patients with an MLD >18 Gy had a grade 2+ pneumonitis rate at 1 year of 52.4% compared with 25.8% in patients with an MLD ≤18 Gy (P = .01). Moreover, heart dosimetry parameters including mean heart dose ≥10 Gy were found to be correlated with increased rates of grade 2+ pneumonitis. The estimated 1-year overall survival and progression-free survival of our cohort were 86.8% and 64.1%, respectively. Conclusions The modern management of locally advanced, unresectable NSCLC involves definitive chemoradiation followed by consolidative durvalumab. Pneumonitis rates were higher than expected in this cohort, particularly for patients with a lung V20 ≥30%, MLD >18 Gy, and mean heart dose ≥10 Gy, suggesting that more stringent radiation planning dose constraints may be needed.
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Affiliation(s)
- Brett H. Diamond
- Department of Radiation Oncology, Rhode Island Hospital, Providence, Rhode Island,Department of Radiation Oncology, Tufts Medical Center, Boston, Massachusetts
| | - Neel Belani
- Department of Medical Oncology, Fox Chase Cancer Center, Philadelphia, Pennsylvania
| | - Rebecca Masel
- Department of Medicine, Rhode Island Hospital, Providence, Rhode Island
| | - Kathryn DeCarli
- Warren Alpert School of Medicine, Providence, Rhode Island,Department of Medical Oncology, Rhode Island Hospital, Providence, Rhode Island
| | - Thomas DiPetrillo
- Department of Radiation Oncology, Rhode Island Hospital, Providence, Rhode Island,Department of Radiation Oncology, Tufts Medical Center, Boston, Massachusetts,Warren Alpert School of Medicine, Providence, Rhode Island
| | - Jaroslaw T. Hepel
- Department of Radiation Oncology, Rhode Island Hospital, Providence, Rhode Island,Warren Alpert School of Medicine, Providence, Rhode Island
| | - Christopher G. Azzoli
- Warren Alpert School of Medicine, Providence, Rhode Island,Department of Medical Oncology, Rhode Island Hospital, Providence, Rhode Island
| | - Humera Khurshid
- Warren Alpert School of Medicine, Providence, Rhode Island,Department of Medical Oncology, Rhode Island Hospital, Providence, Rhode Island
| | - Abbas Abbas
- Warren Alpert School of Medicine, Providence, Rhode Island,Department of Thoracic Surgery, Rhode Island Hospital, Providence, Rhode Island
| | - Paul P. Koffer
- Department of Radiation Oncology, Rhode Island Hospital, Providence, Rhode Island,Warren Alpert School of Medicine, Providence, Rhode Island,Corresponding author: Paul P. Koffer, MD
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22
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Doshita K, Tabuchi Y, Kenmotsu H, Omori S, Kawabata T, Kodama H, Nishioka N, Miyawaki E, Iida Y, Mamesaya N, Kobayashi H, Ko R, Wakuda K, Ono A, Naito T, Murakami H, Mori K, Harada H, Kaneko T, Takahashi T. Incidence and Treatment Outcome of Radiation Pneumonitis in Patients With Limited-stage Small Cell Lung Cancer Treated With Concurrent Accelerated Hyperfractionated Radiation Therapy and Chemotherapy. Adv Radiat Oncol 2022; 8:101129. [PMID: 36845617 PMCID: PMC9943774 DOI: 10.1016/j.adro.2022.101129] [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: 03/15/2022] [Accepted: 11/15/2022] [Indexed: 11/25/2022] Open
Abstract
Purpose This study aimed to clarify the characteristics of and evaluate the risk factors for radiation pneumonitis (RP) induced by chemoradiation therapy (CRT) using accelerated hyperfractionated (AHF) radiation therapy (RT) in patients with limited-stage small cell lung cancer (LS-SCLC). Methods and Materials Between September 2002 and February 2018, 125 patients with LS-SCLC were treated with early concurrent CRT using AHF-RT. Chemotherapy was comprised of carboplatin/cisplatin with etoposide. RT was administered twice daily (45 Gy/30 fractions). We collected data regarding onset and treatment outcomes for RP, and analyzed the relationship between RP and total lung dose-volume histogram findings. Uni- and multivariate analyses were performed to assess patient- and treatment-related factors for grade ≥2 RP. Results The median age of patients was 65 years, and 73.6% of participants were men. In addition, 20% and 80.0% of participants presented with disease stage II and III, respectively. The median follow-up time was 73.1 months. Grades 1, 2, and 3 RP were observed in 69, 17, and 12 patients, respectively. Grades 4 to 5 RP were not observed. RP was treated with corticosteroids in patients with grade ≥2 RP, without recurrence. The median time from initiation of RT to onset of RP was 147 days. Three patients developed RP within 59 days, 6 within 60 to 89 days, 16 within 90 to 119 days, 29 within 120 to 149 days, 24 within 150 to 179 days, and 20 within ≥180 days. Among the dose-volume histogram parameters, the percentage of lung volume receiving >30 Gy (V30) was most strongly related to the incidence of grade ≥2 RP, and the optimal threshold to predict RP incidence was V30 ≥20%. On multivariate analysis, V30 ≥20% was an independent risk factor for grade ≥2 RP. Conclusions The incidence of grade ≥2 RP correlated strongly with a V30 of ≥20%. Contrarily, the onset of RP induced by concurrent CRT using AHF-RT may occur later. RP is manageable in patients with LS-SCLC.
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Affiliation(s)
- Kosei Doshita
- Division of Thoracic Oncology, Shizuoka Cancer Center, Nagaizumi-cho Sunto-gun, Shizuoka, Japan,Department of Pulmonology, Yokohama City University Graduate School of Medicine, Yokohama, Kanagawa, Japan
| | - Yuya Tabuchi
- Radiation and Proton Therapy Center, Shizuoka Cancer Center, Nagaizumi-cho Suntou-gun, Shizuoka, Japan
| | - Hirotsugu Kenmotsu
- Division of Thoracic Oncology, Shizuoka Cancer Center, Nagaizumi-cho Sunto-gun, Shizuoka, Japan,Corresponding author: Hirotsugu Kenmotsu, PhD
| | - Shota Omori
- Division of Thoracic Oncology, Shizuoka Cancer Center, Nagaizumi-cho Sunto-gun, Shizuoka, Japan
| | - Takanori Kawabata
- Clinical Research Center, Shizuoka Cancer Center, Nagaizumi-cho Sunto-gun, Shizuoka, Japan
| | - Hiroaki Kodama
- Division of Thoracic Oncology, Shizuoka Cancer Center, Nagaizumi-cho Sunto-gun, Shizuoka, Japan
| | - Naoya Nishioka
- Division of Thoracic Oncology, Shizuoka Cancer Center, Nagaizumi-cho Sunto-gun, Shizuoka, Japan
| | - Eriko Miyawaki
- Division of Thoracic Oncology, Shizuoka Cancer Center, Nagaizumi-cho Sunto-gun, Shizuoka, Japan
| | - Yuko Iida
- Division of Thoracic Oncology, Shizuoka Cancer Center, Nagaizumi-cho Sunto-gun, Shizuoka, Japan
| | - Nobuaki Mamesaya
- Division of Thoracic Oncology, Shizuoka Cancer Center, Nagaizumi-cho Sunto-gun, Shizuoka, Japan
| | - Haruki Kobayashi
- Division of Thoracic Oncology, Shizuoka Cancer Center, Nagaizumi-cho Sunto-gun, Shizuoka, Japan
| | - Ryo Ko
- Division of Thoracic Oncology, Shizuoka Cancer Center, Nagaizumi-cho Sunto-gun, Shizuoka, Japan
| | - Kazushige Wakuda
- Division of Thoracic Oncology, Shizuoka Cancer Center, Nagaizumi-cho Sunto-gun, Shizuoka, Japan
| | - Akira Ono
- Division of Thoracic Oncology, Shizuoka Cancer Center, Nagaizumi-cho Sunto-gun, Shizuoka, Japan
| | - Tateaki Naito
- Division of Thoracic Oncology, Shizuoka Cancer Center, Nagaizumi-cho Sunto-gun, Shizuoka, Japan
| | - Haruyasu Murakami
- Division of Thoracic Oncology, Shizuoka Cancer Center, Nagaizumi-cho Sunto-gun, Shizuoka, Japan
| | - Keita Mori
- Clinical Research Center, Shizuoka Cancer Center, Nagaizumi-cho Sunto-gun, Shizuoka, Japan
| | - Hideyuki Harada
- Radiation and Proton Therapy Center, Shizuoka Cancer Center, Nagaizumi-cho Suntou-gun, Shizuoka, Japan
| | - Takeshi Kaneko
- Department of Pulmonology, Yokohama City University Graduate School of Medicine, Yokohama, Kanagawa, Japan
| | - Toshiaki Takahashi
- Division of Thoracic Oncology, Shizuoka Cancer Center, Nagaizumi-cho Sunto-gun, Shizuoka, Japan
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23
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Varlotto JM, Sun Z, Ky B, Upshaw J, Fitzgerald TJ, Diehn M, Lovly C, Belani C, Oettel K, Masters G, Harkenrider M, Ross H, Ramalingam S, Pennell NA. A Review of Concurrent Chemo/Radiation, Immunotherapy, Radiation Planning, and Biomarkers for Locally Advanced Non-small Cell Lung Cancer and Their Role in the Development of ECOG-ACRIN EA5181. Clin Lung Cancer 2022; 23:547-560. [PMID: 35882620 DOI: 10.1016/j.cllc.2022.06.005] [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: 10/31/2021] [Revised: 06/20/2022] [Accepted: 06/20/2022] [Indexed: 01/27/2023]
Abstract
ECOG-ACRIN EA5181 is a current prospective, randomized trial that is investigating whether the addition of concomitant durvalumab to standard chemo/radiation followed by 1 year of consolidative durvalumab results in an overall survival benefit over standard chemo/radiation alone followed by 1 year of consolidative durvalumab in patients with locally advanced, unresectable non-small cell lung cancer (NSCLC). Because multiple phase I/II trials have shown the relative safety of adding immunotherapy to chemo/radiation and due to the known synergism between chemotherapy and immunotherapy, it is hoped that concomitant durvalumab can reduce the relatively high incidence of local failure (38%-46%) as seen in recent prospective, randomized trials of standard chemo/radiation in this patient population. We will review the history of radiation for LA-NSCLC and discuss the role of induction, concurrent and consolidative chemotherapy as well as the concerns for late cardiac and pulmonary toxicities associated with treatment. Furthermore, we will review the potential role of next generation sequencing, PD-L1, ctDNA and tumor mutation burden and their possible impact on this trial.
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Affiliation(s)
- John Michael Varlotto
- Department of Oncology, Edwards Comprehensive Cancer Center/Marshall University, Huntington, WV.
| | - Zhuoxin Sun
- Dana Farber Cancer Institute - ECOG-ACRIN Biostatistics Center, Boston, MA
| | - Bonnie Ky
- Division of Cardiovascular Medicine, University of Pennsylvania, Philadelphia, PA
| | - Jenica Upshaw
- Department of Medicine, Tufts University, Boston, MA
| | | | - Max Diehn
- Department of Radiation Oncology, Stanford University, Stanford, CA
| | - Christine Lovly
- Division of Hematology Oncology, Vanderbilt University, Nashville, TN
| | - Chandra Belani
- Department of Medical Oncology, Penn State Cancer Institute, Hershey, PA
| | - Kurt Oettel
- Department of Medical Oncology, Gundersen Lutheran Medical Center, La Crosse, WI
| | | | - Matthew Harkenrider
- Department of Radiation Oncology, Stritch School of Medicine Loyola University Chicago, Maywood, IL
| | - Helen Ross
- Department of Medical Oncology, Banner MD Anderson Cancer Center, Gilbert, AZ
| | | | - Nathan A Pennell
- Department of Hematology Oncology, Cleveland Clinic, Cleveland, OH
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24
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van der Weijst L, Azria D, Berkovic P, Boisselier P, Briers E, Bultijnck R, Chang-Claude J, Choudhury A, Defraene G, Demontois S, Elliott RM, Ennis D, Faivre-Finn C, Franceschini M, Giandini T, Giraldo A, Gutiérrez-Enríquez S, Herskind C, Higginson DS, Kerns SL, Johnson K, Lambrecht M, Lang P, Ramos M, Rancati T, Rimner A, Rosenstein BS, De Ruysscher D, Salem A, Sangalli C, Seibold P, Sosa Fajardo P, Sperk E, Stobart H, Summersgill H, Surmont V, Symonds P, Taboada-Valladares B, Talbot CJ, Vega A, Veldeman L, Veldwijk MR, Ward T, Webb A, West CML, Lievens Y. The correlation between pre-treatment symptoms, acute and late toxicity and patient-reported health-related quality of life in non-small cell lung cancer patients: Results of the REQUITE study. Radiother Oncol 2022; 176:127-137. [PMID: 36195214 PMCID: PMC10404651 DOI: 10.1016/j.radonc.2022.09.020] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 09/16/2022] [Accepted: 09/25/2022] [Indexed: 12/14/2022]
Abstract
BACKGROUND AND PURPOSE To investigate the association between clinician-scored toxicities and patient-reported health-related quality of life (HRQoL), in early-stage (ES-) and locally-advanced (LA-) non-small cell lung cancer (NSCLC) patients receiving loco-regional radiotherapy, included in the international real-world REQUITE study. MATERIALS AND METHODS Clinicians scored eleven radiotherapy-related toxicities (and baseline symptoms) with the Common Terminology Criteria for Adverse Events version 4. HRQoL was assessed with the European Organization for Research and Treatment of Cancer core HRQoL questionnaire (EORTC-QLQ-C30). Statistical analyses used the mixed-model method; statistical significance was set at p = 0.01. Analyses were performed for baseline and subsequent time points up to 2 years after radiotherapy and per treatment modality, radiotherapy technique and disease stage. RESULTS Data of 435 patients were analysed. Pre-treatment, overall symptoms, dyspnea, chest wall pain, dysphagia and cough impacted overall HRQoL and specific domains. At subsequent time points, cough and dysphagia were overtaken by pericarditis in affecting HRQoL. Toxicities during concurrent chemo-radiotherapy and 3-dimensional radiotherapy had the most impact on HRQoL. Conversely, toxicities in sequential chemo-radiotherapy and SBRT had limited impact on patients' HRQoL. Stage impacts the correlations: LA-NSCLC patients are more adversely affected by toxicity than ES-NSCLC patients, mimicking the results of radiotherapy technique and treatment modality. CONCLUSION Pre-treatment symptoms and acute/late toxicities variously impact HRQoL of ES- and LA-NSCLC patients undergoing different treatment approaches and radiotherapy techniques. Throughout the disease, dyspnea seems crucial in this association, highlighting the additional effect of co-existing comorbidities. Our data call for optimized radiotherapy limiting toxicities that may affect patients' HRQoL.
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Affiliation(s)
- Lotte van der Weijst
- Department of Radiation Oncology, Ghent University Hospital and Ghent University, Ghent, Belgium.
| | - David Azria
- Federation Universitaire d'oncologie radiothérapie d'Occitanie Méditerranée, Univ Montpellier, IRCM Inserm U1194, ICM, Montpellier, France
| | - Patrick Berkovic
- Department of Radiotherapy-oncology, Leuvens Kanker Instituut, UZ Leuven, Leuven, Belgium
| | - Pierre Boisselier
- Federation Universitaire d'oncologie radiothérapie d'Occitanie Méditerranée, Univ Montpellier, IRCM Inserm U1194, ICM, Montpellier, France
| | | | - Renée Bultijnck
- Department of Radiation Oncology, Ghent University Hospital and Ghent University, Ghent, Belgium; Research Foundation - Flanders (FWO), Brussels, Belgium
| | - Jenny Chang-Claude
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany; University Cancer Center Hamburg, University Medical Center Hamburg-Eppendorf, Germany
| | - Ananya Choudhury
- Translational Radiobiology Group, Division of Cancer Sciences, University of Manchester, Manchester Academic Health Science Centre, Christie Hospital, United Kingdom
| | - Gilles Defraene
- Laboratory of Experimental Radiotherapy, Department of Oncology, KULEUVEN, Leuven, Belgium
| | - Sylvian Demontois
- Federation Universitaire d'oncologie radiothérapie d'Occitanie Méditerranée, Univ Montpellier, IRCM Inserm U1194, ICM, Montpellier, France
| | - Rebecca M Elliott
- Translational Radiobiology Group, Division of Cancer Sciences, University of Manchester, Manchester Academic Health Science Centre, Christie Hospital, United Kingdom
| | - Dawn Ennis
- Royal Derby Hospital, Derby DE22 3NE, United Kingdom
| | - Corinne Faivre-Finn
- University of Manchester, UK, The Christie NHS Foundation Trust, United Kingdom
| | - Marzia Franceschini
- Unit of Radiation Oncology 2, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Tommaso Giandini
- Unit of Medical Physics, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Alexandra Giraldo
- Radiation Oncology Department, Vall d'Hebron Hospital Universitari, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain
| | - Sara Gutiérrez-Enríquez
- Hereditary Cancer Genetics Group, Vall d'Hebron Institute of Oncology (VHIO), Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain
| | - Carsten Herskind
- Department of Radiation Oncology, Universitätsmedizin Mannheim, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Daniel S Higginson
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, United States
| | - Sarah L Kerns
- Departments of Radiation Oncology and Surgery, University of Rochester Medical Center, Rochester, New York, NY, United States
| | - Kerstie Johnson
- Leicester Cancer Research Centre, University of Leicester, Leicester LE1 7RH, United Kingdom
| | - Maarten Lambrecht
- Department of Radiotherapy-oncology, Leuvens Kanker Instituut, UZ Leuven, Leuven, Belgium
| | - Philippe Lang
- Federation Universitaire d'oncologie radiothérapie d'Occitanie, ICG CHU Caremeau, Nîmes, France
| | - Mónica Ramos
- Radiation Oncology Department, Vall d'Hebron Hospital Universitari, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain
| | - Tiziana Rancati
- Prostate Cancer Program, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Andreas Rimner
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, United States
| | - Barry S Rosenstein
- Department of Radiation Oncology, Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, United States
| | - Dirk De Ruysscher
- Department of Radiation Oncology (Maastro), Maastricht University Medical Center, GROW School for Oncology and Developmental Biology, Maastricht, The Netherlands
| | - Ahmed Salem
- University of Manchester, UK, The Christie NHS Foundation Trust, United Kingdom; Department of Basic Medical Sciences, School of Medicine, Hashemite University, Zarqa, Jordan
| | - Claudia Sangalli
- Unit of Radiation Oncology 1, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Petra Seibold
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Paloma Sosa Fajardo
- Department of Radiation Oncology, Hospital Clínico Universitario de Santiago, SERGAS.Instituto de Investigación Sanitaria de Santiago de Compostela, Spain
| | - Elena Sperk
- Department of Radiation Oncology, Universitätsmedizin Mannheim, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | | | - Holly Summersgill
- Translational Radiobiology Group, Division of Cancer Sciences, University of Manchester, Manchester Academic Health Science Centre, Christie Hospital, United Kingdom
| | - Veerle Surmont
- Department of Respiratory Medicine, Ghent University Hospital and Ghent University, Ghent, Belgium
| | - Paul Symonds
- Leicester Cancer Research Centre, University of Leicester, Leicester LE1 7RH, United Kingdom
| | - Begoña Taboada-Valladares
- Department of Radiation Oncology, Hospital Clínico Universitario de Santiago, SERGAS.Instituto de Investigación Sanitaria de Santiago de Compostela, Spain
| | - Christopher J Talbot
- Leicester Cancer Research Centre, University of Leicester, Leicester LE1 7RH, United Kingdom
| | - Ana Vega
- Fundación Pública Galega de Medicina Xenómica, Grupo de Medicina Xenómica (USC), Santiago de Compostela, Spain; Instituto de Investigación Sanitaria de Santiago de Compostela, Spain; Biomedical Network on Rare Diseases (CIBERER), Spain
| | - Liv Veldeman
- Department of Radiation Oncology, Ghent University Hospital and Ghent University, Ghent, Belgium
| | - Marlon R Veldwijk
- Department of Radiation Oncology, Universitätsklinikum Mannheim, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Tim Ward
- Trustee Pelvic Radiation Disease Association, NCRI CTRad Consumer, United Kingdom
| | - Adam Webb
- Department of Genetics and Genome Biology, University of Leicester, United Kingdom
| | - Catharine M L West
- Translational Radiobiology Group, Division of Cancer Sciences, University of Manchester, Manchester Academic Health Science Centre, Christie Hospital, United Kingdom
| | - Yolande Lievens
- Department of Radiation Oncology, Ghent University Hospital and Ghent University, Ghent, Belgium
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Katsuta Y, Kadoya N, Sugai Y, Katagiri Y, Yamamoto T, Takeda K, Tanaka S, Jingu K. Feasibility of Differential Dose-Volume Histogram Features in Multivariate Prediction Model for Radiation Pneumonitis Occurrence. Diagnostics (Basel) 2022; 12:diagnostics12061354. [PMID: 35741164 PMCID: PMC9221601 DOI: 10.3390/diagnostics12061354] [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: 04/01/2022] [Revised: 05/16/2022] [Accepted: 05/20/2022] [Indexed: 11/18/2022] Open
Abstract
The purpose of this study is to introduce differential dose−volume histogram (dDVH) features into machine learning for radiation pneumonitis (RP) prediction and to demonstrate the predictive performance of the developed model based on integrated cumulative dose−volume histogram (cDVH) and dDVH features. Materials and methods: cDVH and dDVH features were calculated for 153 patients treated for non-small-cell lung cancer with 60−66 Gy and dose bins ranging from 2 to 8 Gy in 2 Gy increments. RP prediction models were developed with the least absolute shrinkage and selection operator (LASSO) through fivefold cross-validation. Results: Among the 152 patients in the patient cohort, 41 presented ≥grade 2 RP. The interdependencies between cDVH features evaluated by Spearman’s correlation were significantly resolved by the inclusion of dDVH features. The average area under curve for the RP prediction model using cDVH and dDVH model was 0.73, which was higher than the average area under curve using cDVH model for 0.62 with statistically significance (p < 0.01). An analysis using the entire set of regression coefficients determined by LASSO demonstrated that dDVH features represented four of the top five frequently selected features in the model fitting, regardless of dose bin. Conclusions: We successfully developed an RP prediction model that integrated cDVH and dDVH features. The best RP prediction model was achieved using dDVH (dose bin = 4 Gy) features in the machine learning process.
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Affiliation(s)
- Yoshiyuki Katsuta
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, 1-1 Seiryo-machi, Aoba-ku, Sendai 980-8574, Japan; (N.K.); (Y.S.); (T.Y.); (K.T.); (S.T.); (K.J.)
- Correspondence: ; Tel.: +81-22-717-7312; Fax: +81-22-717-7316
| | - Noriyuki Kadoya
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, 1-1 Seiryo-machi, Aoba-ku, Sendai 980-8574, Japan; (N.K.); (Y.S.); (T.Y.); (K.T.); (S.T.); (K.J.)
| | - Yuto Sugai
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, 1-1 Seiryo-machi, Aoba-ku, Sendai 980-8574, Japan; (N.K.); (Y.S.); (T.Y.); (K.T.); (S.T.); (K.J.)
| | - Yu Katagiri
- Department of Radiation Oncology, Japan Red Cross Ishinomaki Hospital, Ishinomaki 986-8522, Japan;
| | - Takaya Yamamoto
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, 1-1 Seiryo-machi, Aoba-ku, Sendai 980-8574, Japan; (N.K.); (Y.S.); (T.Y.); (K.T.); (S.T.); (K.J.)
| | - Kazuya Takeda
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, 1-1 Seiryo-machi, Aoba-ku, Sendai 980-8574, Japan; (N.K.); (Y.S.); (T.Y.); (K.T.); (S.T.); (K.J.)
| | - Shohei Tanaka
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, 1-1 Seiryo-machi, Aoba-ku, Sendai 980-8574, Japan; (N.K.); (Y.S.); (T.Y.); (K.T.); (S.T.); (K.J.)
| | - Keiichi Jingu
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, 1-1 Seiryo-machi, Aoba-ku, Sendai 980-8574, Japan; (N.K.); (Y.S.); (T.Y.); (K.T.); (S.T.); (K.J.)
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26
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Li F, Luo Y, Chen J, He L, Liang Y, Lai J, Guo F. Association between tumor morphology and dosimetric parameters of organs at risk after intensity-modulated radiotherapy in esophagus cancer. J Appl Clin Med Phys 2022; 23:e13612. [PMID: 35635800 PMCID: PMC9278670 DOI: 10.1002/acm2.13612] [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: 05/30/2021] [Revised: 02/26/2022] [Accepted: 03/28/2022] [Indexed: 11/10/2022] Open
Abstract
PURPOSE We explored the effects of geometrical topological properties of tumors such as tumor length and "axial cross-sectional area (ACSA)" of tumors (planning target volume [PTV] volume /PTV length) on the dosimetric parameters of organs at risk (lung and heart) in patients with esophagus cancer (EPC) treated by way of intensity-modulated radiation therapy (IMRT), so as to provide a guideline for the dosimetric limitation for organs at risk in IMRT treatment. METHODS A retrospective analysis was done on 103 cases of patients with EPC who were treated by IMRT from November 2010 to August 2019, in which PTV-G stood for the externally expanded planning target volume (PTV) of the gross tumor volume (GTV) and PTV-C for the externally expanded volume of the clinical target volume (CTV). A linear regression model was employed to analyze the several pairs of correlation: the 1st one between the relative length of tumors (PTV length/lung length) and pulmonary dose-volume parameters, the 2nd one between ACSA of tumors and pulmonary dose-volume parameters, the 3rd one between PTV length and the dosimetric parameters of the heart, and the last one between ACSA of tumors and the dosimetric parameters of the heart. RESULTS (i) There was a strong positive correlation between the relative length of tumors (PTV length/lung length) and V5 (p < 0.001, r = 0.73), and V10 (p < 0.001, r = 0.66) of the lung. There was a moderate positive correlation between the relative length of tumors and V30 (p < 0.001, r = 0.44) of the lung, and a weak positive correlation between the relative length of tumors and V20 (p < 0.001, r = 0.39) of the lung. (ii) There was a strong positive correlation between ACSA of tumors (PTV volume/PTV length) and V30 (p < 0.001, r = 0.67) of the lung, a moderate positive correlation between ACSA of tumors and V20 (p <0.001, r = 0.51) of the lung, and a weak positive correlation between ACSA of tumors and V10 (p = 0.019, r = 0.23) of the lung, yet there was not an obvious correlation between ACSA of tumors and V5 p > 0.05) of the lung. (iii) There was a moderate positive correlation between PTV length and V40 (p < 0.001, r = 0.58), and Dmean (p < 0.001, r = 0.52) of the heart, yet there was no obvious correlation between ACSA of tumors and Dmean and V40 of the heart (p > 0.05). CONCLUSIONS (i) Compared with the high-dose region of the lung, the relative length of tumors (PTV length/lung length) has a greater impact on the low-dose region of the lung. The linear regression equation of scatter plot showed that when the relative length of tumors increased by 0.1, the lung dose-volume parameters of V5 , V10 , V20 , and V30 increased by approximately 5.37%, 3.59%, 1.05%, and 1.08%, respectively. When PTV length increased by 1 cm, Dmean and V40 of the heart increased by approximately 153.6 cGy and 2.03%, respectively. (ii) Compared with the low-dose region of the lung, the value of ACSA of tumors (PTV volume/PTV length) has a greater impact on the high-dose region of the lung. However, the value of ACSA of tumors has no significant effect on the dosimetric parameters of the heart (Dmean and V40 ). The linear regression equation of scatter plot showed that when ACSA of tumors increased by 10 cm2 , the lung dose-volume parameters of V10 , V20, and V30 increased by approximately 3.11%, 3.37%, and 4.01%, respectively.
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Affiliation(s)
- Fahui Li
- Department of Radiotherapy, Cancer Center, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.,Key Laboratory of Radiation Biology of Fujian Higher Education Institutions, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
| | - Yuxuan Luo
- The Medical Technology and Engineering Academy of Fujian Medical University, Fuzhou, China
| | - Jing Chen
- The Medical Technology and Engineering Academy of Fujian Medical University, Fuzhou, China
| | - Liping He
- The Medical Technology and Engineering Academy of Fujian Medical University, Fuzhou, China
| | - Yiying Liang
- The Medical Technology and Engineering Academy of Fujian Medical University, Fuzhou, China
| | - Junjie Lai
- The Medical Technology and Engineering Academy of Fujian Medical University, Fuzhou, China
| | - Feibao Guo
- Department of Radiotherapy, Cancer Center, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.,Key Laboratory of Radiation Biology of Fujian Higher Education Institutions, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China.,The Medical Technology and Engineering Academy of Fujian Medical University, Fuzhou, China
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27
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Borghetti P, Guerini AE, Sangalli C, Piperno G, Franceschini D, La Mattina S, Arcangeli S, Filippi AR. Unmet needs in the management of unresectable stage III non-small cell lung cancer: a review after the 'Radio Talk' webinars. Expert Rev Anticancer Ther 2022; 22:549-559. [PMID: 35450510 DOI: 10.1080/14737140.2022.2069098] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
INTRODUCTION Stage III non-small cell lung cancer (NSCLC) is a variable entity, encompassing bulky primary tumors, nodal involvement or both. Multidisciplinary evaluation is essential to discuss multiple treatment options, to outline optimal management and to examine the main debated topics and critical issues not addressed by current trials and guidelines that influence daily clinical practice. AREAS COVERED From March to May 2021, 5 meetings were scheduled in a webinar format titled 'Radio Talk' due to the COVID-19 pandemic; the faculty was composed of 6 radiation oncologists from 6 different Institutions of Italy, all of them were the referring radiation oncologist for lung cancer treatment at their respective departments and were or had been members of AIRO (Italian Association of Radiation Oncology) Thoracic Oncology Study Group. The topics covered included: pulmonary toxicity, cardiac toxicity, radiotherapy dose, fractionation and volumes, unfit/elderly patients, multidisciplinary management. EXPERT OPINION The debate was focused on the unmet needs triggered by case reports, personal experiences and questions; the answers were often not univocal, however, the exchange of opinion and the contribution of different centers confirmed the role of multidisciplinary management and the necessity that the most critical issues should be investigated in clinical trials.
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Affiliation(s)
- Paolo Borghetti
- Department of Radiation Oncology, University and Spedali Civili Hospital, Piazzale Spedali Civili 1, 25123, Brescia, Italy
| | - Andrea Emanuele Guerini
- Department of Radiation Oncology, University and Spedali Civili Hospital, Piazzale Spedali Civili 1, 25123, Brescia, Italy
| | - Claudia Sangalli
- Department of Radiation Oncology 1, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Gaia Piperno
- Division of Radiotherapy, IEO European Institute of Oncology IRCCS, Milan, Italy
| | - Davide Franceschini
- Department of Radiotherapy and Radiosurgery, IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy
| | - Salvatore La Mattina
- Department of Radiation Oncology, University and Spedali Civili Hospital, Piazzale Spedali Civili 1, 25123, Brescia, Italy
| | - Stefano Arcangeli
- Department of Radiation Oncology, School of Medicine and Surgery, University of Milan Bicocca, Milan, Italy
| | - Andrea Riccardo Filippi
- Department of Radiation Oncology, Fondazione IRCCS Policlinico San Matteo and University of Pavia, Pavia, Italy
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Impact of Tobacco Smoking on Outcomes of Radiotherapy: A Narrative Review. Curr Oncol 2022; 29:2284-2300. [PMID: 35448160 PMCID: PMC9031077 DOI: 10.3390/curroncol29040186] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2022] [Revised: 03/19/2022] [Accepted: 03/22/2022] [Indexed: 11/16/2022] Open
Abstract
The carcinogenic role of tobacco smoking is well recognized, but the detrimental effects of continued smoking after a cancer diagnosis have been underestimated. Radiotherapy is among the main treatment modalities for cancer. We reviewed the literature data concerning the impact of tobacco smoking on treatment outcomes in radiotherapy-managed patients with various malignancies. Most of the analyzed studies demonstrated the detrimental effect of smoking on overall survival, tumor control, quality of life, treatment toxicity, and the incidence of second primary malignancies. Healthcare professionals should use the cancer diagnosis and treatment as a teachable moment and recommend their patients to immediately cease smoking. Wherever possible, cancer patients should undergo an intensive smoking-cessation program, including behavioral and pharmacologic therapy.
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Harris W, Yorke E, Li H, Czmielewski C, Chawla M, Lee RP, Hotca-Cho A, McKnight D, Rimner A, Lovelock DM. Can bronchoscopically implanted anchored electromagnetic transponders be used to monitor tumor position and lung inflation during deep inspiration breath-hold lung radiotherapy? Med Phys 2022; 49:2621-2630. [PMID: 35192211 PMCID: PMC9007909 DOI: 10.1002/mp.15565] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 01/22/2022] [Accepted: 02/05/2022] [Indexed: 11/09/2022] Open
Abstract
PURPOSE To evaluate the efficacy of using bronchoscopically implanted anchored electromagnetic transponders (EMTs) as surrogates for 1) tumor position and 2) repeatability of lung inflation during deep-inspiration breath-hold (DIBH) lung radiotherapy. METHODS 41 patients treated with either hypofractionated (HF) or conventional (CF) lung radiotherapy on an IRB approved prospective protocol using coached DIBH were evaluated for this study. Three anchored EMTs were bronchoscopically implanted into small airways near or within the tumor. DIBH treatment was gated by tracking the EMT positions. Breath-hold cone-beam-CTs (CBCTs) were acquired prior to every HF treatment or weekly for CF patients. Retrospectively, rigid registrations between each CBCT and the breath-hold planning CT were performed to match to 1) spine 2) EMTs and 3) tumor. Absolute differences in registration between EMTs and spine were analyzed to determine surrogacy of EMTs for lung inflation. Differences in registration between EMTs and tumor were analyzed to determine surrogacy of EMTs for tumor position. The stability of the EMTs was evaluated by analyzing the difference between inter-EMT displacements recorded at treatment from that of the plan for the CF patients, as well as the geometric residual (GR) recorded at the time of treatment. RESULTS 219 CBCTs were analyzed. The average differences between EMT centroid and spine registration among all CBCTs were 0.45±0.42cm, 0.29±0.28cm, and 0.18±0.15cm in superior-inferior (SI), anterior-posterior (AP) and lateral directions, respectively. Only 59% of CBCTs had differences in registration <0.5cm for EMT centroid compared to spine, indicating that lung inflation is not reproducible from simulation to treatment. The average differences between EMT centroid and tumor registration among all CBCTs were 0.13±0.13cm, 0.14±0.13cm and 0.12±0.12cm in SI, AP and lateral directions, respectively. 95% of CBCTs resulted in <0.5cm change between EMT centroid and tumor registration, indicating that EMT positions correspond well with tumor position during treatments. Six out of the 7 recorded CF patients had average differences in inter-EMT displacements to be ≤0.26cm and average GR ≤0.22cm, indicating that the EMTs are stable throughout treatment. CONCLUSIONS Bronchoscopically implanted anchored EMTs are good surrogates for tumor position and are reliable for maintaining tumor position when tracked during DIBH treatment, as long as the tumor size and shape are stable. Large differences in registration between EMTs and spine for many treatments suggest that lung inflation achieved at simulation is often not reproduced. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Wendy Harris
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, 10065
| | - Ellen Yorke
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, 10065
| | - Henry Li
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065
| | - Christian Czmielewski
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, 10065
| | - Mohit Chawla
- Department of Medicine, Pulmonary Service, Section of Interventional Pulmonology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065
| | - Robert P Lee
- Department of Medicine, Pulmonary Service, Section of Interventional Pulmonology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065
| | - Alexandra Hotca-Cho
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065
| | - Dominique McKnight
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065
| | - Andreas Rimner
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065
| | - D Michael Lovelock
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, 10065
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Karlsen J, Tandstad T, Sowa P, Salvesen Ø, Stenehjem JS, Lundgren S, Reidunsdatter RJ. Pneumonitis and fibrosis after breast cancer radiotherapy: occurrence and treatment-related predictors. Acta Oncol 2021; 60:1651-1658. [PMID: 34618657 DOI: 10.1080/0284186x.2021.1976828] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
BACKGROUND Radiation pneumonitis (RP) and radiation fibrosis (RF) are common side effects after breast cancer (BC) radiotherapy (RT). However, there is a great variation in the frequency of RP and RF. This study presents the occurrence of- and the treatment-related predictors for RP and RF. Further, physician- and patient-reported pulmonary symptoms during the first year after postoperative RT for BC are demonstrated. MATERIALS AND METHODS From 2007 to 2008, 250 BC patients referred for postoperative RT were included in a prospective cohort study and followed during the first year after RT. High-resolution computed tomography of the lungs and symptom registration were performed before RT and 3, 6, and 12 months after RT. Patient-reported symptoms were registered by standard quality of life questionnaires. Logistic regression analyses were applied to estimate treatment-related predictors for radiological RP (rRP), clinical RP (cRP), radiological RF (rRF), and clinical RF (cRF). RESULTS The occurrence of rRP and cRP at three months was 78% and 19%, while 12 months after RT rRF and cRF was 89% and 16%, respectively; all reported as grade 1. In multivariable analyses, mastectomy predicted cRP at three months (OR = 2.48, p = .03) and cRF at six months, ipsilateral lung volume receiving 20 Gray or more (V20), V30, and mean lung dose (MLD) predicted rRP at six months (OR = 1.06, p = .0003; OR = 1.10, p = .001; and OR = 1.03, p = .01, respectively). Endocrine treatment predicted cRF at 12 months (OR = 2.48, p = .02). Physicians reported significant more dyspnea at 3 months (p = .003) and patients reported 'a little dyspnea' more at 3 and 12 months compared to baseline (p = .007). CONCLUSION RP and RF are prevalent in the first year after BC radiation. Mastectomy predicted cRP at three months. V20, V30, D25, and MLD predicted rRP at 6 months, and endocrine treatment predicted cRF at 12 months. Patients and physicians reported dyspnea differently.
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Affiliation(s)
- Jarle Karlsen
- Department of Oncology, St. Olav's Hospital, Trondheim University Hospital, Trondheim, Norway
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Torgrim Tandstad
- Department of Oncology, St. Olav's Hospital, Trondheim University Hospital, Trondheim, Norway
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Piotr Sowa
- Department of Neuroradiology, Oslo University Hospital, Oslo, Norway
| | - Øyvind Salvesen
- Department of Cancer Research and Clinical Research, Norwegian University of Science and Technology, Trondheim, Norway
| | - Jo S. Stenehjem
- Department of Research, Cancer Registry of Norway, Oslo, Norway
| | - Steinar Lundgren
- Department of Oncology, St. Olav's Hospital, Trondheim University Hospital, Trondheim, Norway
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Randi J. Reidunsdatter
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
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31
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Qiu J, Zhang S, Lv B, Zheng X. Cardiac Dose Control and Optimization Strategy for Left Breast Cancer Radiotherapy With Non-Uniform VMAT Technology. Technol Cancer Res Treat 2021; 20:15330338211053752. [PMID: 34806481 PMCID: PMC8606722 DOI: 10.1177/15330338211053752] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Purpose: A novel in-house technology "Non-Uniform VMAT (NU-VMAT)" was developed for automated cardiac dose reduction and treatment planning optimization in the left breast radiotherapy. Methods: The NU-VMAT model based on IGM (gantry MLC Movement coefficient index) was established to optimize the volumetric modulated arc therapy (VMAT) MLC movement and modulation intensity in certain gantry angles. The ESAPI embedded in Eclipse® was employed to connect TPS and the optimization program via I/O relevant DICOM RT files. The adjuvant whole-breast radiotherapy of 14 patients with left breast cancer was replanned using our NU-VMAT technology in comparison with VMAT and IMRT technology. Dosimetric parameters including D1%, D99%, and Dmean of PTV, V5, V10, and V20 of ipisilateral lung, V5, D20, D30, and Dmean of heart, monitor units (MUs), and delivery time derived from IMRT, VMAT, and NU-VMAT plans were evaluated for plan quality and delivery efficiency. The quality assurance (QA) was conducted using both point-dose and planar-dose measurements for all treatment plans. Results: The IGM-NU-VMAT curves with plan optimization (range from 50% to 147%) were converged more significantly than IGM-VMAT curves (range from 0% to 297%). The dose distribution requirements of the target and normal tissues could be met using IMRT, VMAT, or NU-VMAT; the lowest Dmean was achieved in NU-VMAT plans (5.38 ± 0.46 Gy vs 5.63 ± 0.61 Gy in IMRT and 7.95 ± 0.52 Gy in VMAT plans). Statistically significant differences were found in terms of delivery time and MU when comparing IMRT with VMAT and NU-VMAT plans (P < .05). In comparison with IMRT plans, the MU and delivery time in NU-VMAT plans dramatically decreased by 69.8% and 28.4%, respectively. Moreover, NU-VMAT plans showed a high gamma passing rate (96.5% ± 1.11) in plane dose verification and minimal dose difference (2.4% ± 0.19) in point absolute dose verification. Conclusion: Our non-uniform VMAT facilitated the treatment strategy optimization for left breast cancer radiotherapy with dosimetric advantage in cardiac dose reduction and delivery efficiency in comparison with the conventional VMAT and IMRT.
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Affiliation(s)
- Jianjian Qiu
- Huadong Hospital, Fudan University, Shanghai, China
| | - Shujun Zhang
- Huadong Hospital, Fudan University, Shanghai, China
| | - Bo Lv
- Huadong Hospital, Fudan University, Shanghai, China
| | - Xiangpeng Zheng
- Huadong Hospital, Fudan University, Shanghai, China
- Xiangpeng Zheng, MD, Department of Radiation Oncology, Huadong Hospital, Fudan University, 221 West Yan’an Road, Shanghai 200040, China.
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Parekh AD, Indelicato DJ, Hoppe BS, Vega RBM, Rotondo RL, Bradley JA. Pulmonary dose tolerance in hemithorax radiotherapy for Ewing sarcoma of the chest wall: Are we overestimating the risk of radiation pneumonitis? Pediatr Blood Cancer 2021; 68:e29287. [PMID: 34398486 DOI: 10.1002/pbc.29287] [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: 02/23/2021] [Revised: 07/28/2021] [Accepted: 08/02/2021] [Indexed: 11/06/2022]
Abstract
BACKGROUND Children with chest wall Ewing sarcoma with malignant pulmonary effusion or pleural stranding require hemithorax radiation, often with plans that exceed lung constraints. We investigated disease control and pneumonitis in children requiring hemithorax radiation. PROCEDURE Eleven children (median age 13 years) received hemithorax radiotherapy. Symptomatic radiation pneumonitis was considered National Cancer Institute Common Terminology Criteria for Adverse Events (CTCAE) grade 1+ with respiratory symptoms. Mean lung dose (MLD), volume of lung exposed to a dose ≥5 Gy (V5), ≥20 Gy (V20), and ≥35 Gy (V35) were recorded. Adult and pediatric lung constraints were obtained from Quantitative Analysis of Normal Tissue Effects in the Clinic (QUANTEC) guidelines and Children's Oncology Group (COG) protocols, respectively. RESULTS Median hemithorax dose was 15 Gy (1.5 Gy/fraction). Median total dose was 51 Gy (1.8 Gy/fraction). Most plans delivered both protons and photons. The ipsilateral MLD, V5, and V20 were 27.2 Gy, 100%, and 48.3%; the bilateral MLD, V20, and V35 were 14.1 Gy, 22.8%, and 14.3%, respectively. One hundred percent, 36%, and 91% of treatments exceeded recommended adult ipsilateral lung constraints of V5 <65%, V20 <52%, and MLD of 22 Gy; 64%, 45%, and 82% exceeded COG bilateral lung constraints of V20 <20%, MLD <15 Gy, and MLD <12 Gy, respectively; 82% of treatments exceeded the COG ipsilateral lung constraint of V20 <30%. At a median 36 months (range 12-129), the symptomatic radiation pneumonitis incidence was 0%. Two patients progressed with nonpulmonary metastatic disease and died at a median 12 months following radiotherapy. CONCLUSIONS Existing guidelines may overestimate pneumonitis risk, even among young children receiving multiagent chemotherapy. For children with chest wall Ewing sarcoma and other thoracic malignancies, more data are needed to refine pediatric dose-effect models for pulmonary toxicity.
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Affiliation(s)
- Akash D Parekh
- Department of Radiation Oncology, University of Florida College of Medicine, Jacksonville, Florida, USA
| | - Daniel J Indelicato
- Department of Radiation Oncology, University of Florida College of Medicine, Jacksonville, Florida, USA
| | - Bradford S Hoppe
- Department of Radiation Oncology, Mayo Clinic, Jacksonville, Florida, USA
| | - Raymond B Mailhot Vega
- Department of Radiation Oncology, University of Florida College of Medicine, Jacksonville, Florida, USA
| | - Ronny L Rotondo
- Department of Radiation Oncology, University of Kansas School of Medicine, Kansas City, Kansas, USA
| | - Julie A Bradley
- Department of Radiation Oncology, University of Florida College of Medicine, Jacksonville, Florida, USA
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Modified VMAT Plans for Locally Advanced Centrally Located Non-Small Cell Lung Cancer (NSCLC). Life (Basel) 2021; 11:life11101085. [PMID: 34685456 PMCID: PMC8538695 DOI: 10.3390/life11101085] [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: 08/27/2021] [Revised: 10/10/2021] [Accepted: 10/11/2021] [Indexed: 12/25/2022] Open
Abstract
Objectives: This study aimed to find the optimal radiotherapy VMAT plans, that achieved high conformity and homogeneity to the planned target volume (PTV), and minimize the dose to nearby organs at risk including the non-PTV lung, heart and oesophagus for patients with centrally located non-small Cell Lung Cancer. Methods: A total of 18 patients who were treated for stage III centrally located non-small Cell Lung Cancer were selected retrospectively for this study. Identical CT datasets, 4D CT and structure dataset were used for radiotherapy planning based on single-planar VMAT (SP-VMAT), dual-planar VMAT (DP-VMAT) and Hybrid VMAT (H-VMAT). For SP-VMAT, one full arc and two half arcs were created on single-plane with couch at 0°. For DP-VMAT, one full arc was created with couch at 0°, and two half arcs with couch rotation of 330° or 30°. For H-VMAT, anterior-posterior opposing fixed beam and two half arcs were planned at couch at 0°. Dose constraints were adhered to the RTOG0617. Dose volumetric parameters were collected for statistical analysis. Results: There were no significant differences for the PTV, HI, CI between the SP-VMAT, DP-VMAT and H-VMAT. For the non-PTV lungs, Dmean, V20, V10, V5, D1500 and D1000 were significantly lower (2.05 Gy, 6.47%, 15.89%, 11.66% 4.17 Gy and 5.47 Gy respectively) in H-VMAT than that of SP-VMAT (all p < 0.001). For the oesophagus, Dmax, Dmean, V30 and V18.8 of H-VMAT were 0.08 Gy, 1.73 Gy, 5.54% and 7.17% lower than that of the SP-VMAT plan. For the heart, Dmean, V34, V28, V20 and V10 of DP-VMAT were lower than that of SP-VMAT by 1.45 Gy, 0.65%, 1.74%, 4.8% and 7.11% respectively. Conclusion: The proposed H-VMAT showed more favourable plan quality than the SP-VMAT for centrally located stage III NSCLC, in particular for non-PTV lungs and the oesophagus. It will benefit patients, especially those who planned for immunotherapy (Durvalumab) after standard chemo-irradiation. The proposed DP-VMAT plan showed significant dose reduction to the heart when compared to the H-VMAT plan.
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Gu H, Gan W, Zhang C, Feng A, Wang H, Huang Y, Chen H, Shao Y, Duan Y, Xu Z. A 2D-3D hybrid convolutional neural network for lung lobe auto-segmentation on standard slice thickness computed tomography of patients receiving radiotherapy. Biomed Eng Online 2021; 20:94. [PMID: 34556141 PMCID: PMC8461922 DOI: 10.1186/s12938-021-00932-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 09/13/2021] [Indexed: 11/26/2022] Open
Abstract
Background Accurate segmentation of lung lobe on routine computed tomography (CT) images of locally advanced stage lung cancer patients undergoing radiotherapy can help radiation oncologists to implement lobar-level treatment planning, dose assessment and efficacy prediction. We aim to establish a novel 2D–3D hybrid convolutional neural network (CNN) to provide reliable lung lobe auto-segmentation results in the clinical setting. Methods We retrospectively collected and evaluated thorax CT scans of 105 locally advanced non-small-cell lung cancer (NSCLC) patients treated at our institution from June 2019 to August 2020. The CT images were acquired with 5 mm slice thickness. Two CNNs were used for lung lobe segmentation, a 3D CNN for extracting 3D contextual information and a 2D CNN for extracting texture information. Contouring quality was evaluated using six quantitative metrics and visual evaluation was performed to assess the clinical acceptability. Results For the 35 cases in the test group, Dice Similarity Coefficient (DSC) of all lung lobes contours exceeded 0.75, which met the pass criteria of the segmentation result. Our model achieved high performances with DSC as high as 0.9579, 0.9479, 0.9507, 0.9484, and 0.9003 for left upper lobe (LUL), left lower lobe (LLL), right upper lobe (RUL), right lower lobe (RLL), and right middle lobe (RML), respectively. The proposed model resulted in accuracy, sensitivity, and specificity of 99.57, 98.23, 99.65 for LUL; 99.6, 96.14, 99.76 for LLL; 99.67, 96.13, 99.81 for RUL; 99.72, 92.38, 99.83 for RML; 99.58, 96.03, 99.78 for RLL, respectively. Clinician's visual assessment showed that 164/175 lobe contours met the requirements for clinical use, only 11 contours need manual correction. Conclusions Our 2D–3D hybrid CNN model achieved accurate automatic segmentation of lung lobes on conventional slice-thickness CT of locally advanced lung cancer patients, and has good clinical practicability.
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Affiliation(s)
- Hengle Gu
- Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Wutian Gan
- Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Chenchen Zhang
- Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Aihui Feng
- Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Hao Wang
- Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Ying Huang
- Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Hua Chen
- Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Yan Shao
- Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Yanhua Duan
- Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Zhiyong Xu
- Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
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Lucia F, Rehn M, Blanc-Béguin F, Le Roux PY. Radiation Therapy Planning of Thoracic Tumors: A Review of Challenges Associated With Lung Toxicities and Potential Perspectives of Gallium-68 Lung PET/CT Imaging. Front Med (Lausanne) 2021; 8:723748. [PMID: 34513884 PMCID: PMC8429617 DOI: 10.3389/fmed.2021.723748] [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: 06/11/2021] [Accepted: 08/09/2021] [Indexed: 12/13/2022] Open
Abstract
Despite the introduction of new radiotherapy techniques, such as intensity modulated radiation therapy or stereotactic body radiation therapy, radiation induced lung injury remains a significant treatment related adverse event of thoracic radiation therapy. Functional lung avoidance radiation therapy is an emerging concept in the treatment of lung disease to better preserve lung function and to reduce pulmonary toxicity. While conventional ventilation/perfusion (V/Q) lung scintigraphy is limited by a relatively low spatial and temporal resolution, the recent advent of 68Gallium V/Q lung PET/CT imaging offers a potential to increase the accuracy of lung functional mapping and to better tailor lung radiation therapy plans to the individual's lung function. Lung PET/CT imaging may also improve our understanding of radiation induced lung injury compared to the current anatomical based dose–volume constraints. In this review, recent advances in radiation therapy for the management of primary and secondary lung tumors and in V/Q PET/CT imaging for the assessment of functional lung volumes are reviewed. The new opportunities and challenges arising from the integration of V/Q PET/CT imaging in radiation therapy planning are also discussed.
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Affiliation(s)
- François Lucia
- Radiation Oncology Department, University Hospital, Brest, France
| | - Martin Rehn
- Radiation Oncology Department, University Hospital, Brest, France
| | - Frédérique Blanc-Béguin
- Service de médecine nucléaire, CHRU de Brest, EA3878 (GETBO), Université de Brest, Brest, France
| | - Pierre-Yves Le Roux
- Service de médecine nucléaire, CHRU de Brest, EA3878 (GETBO), Université de Brest, Brest, France
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Chen H, Huang Y, Wang H, Shao Y, Yue NJ, Gu H, Duan Y, Feng A, Xu Z. Dosimetric comparison and biological evaluation of fixed-jaw intensity-modulated radiation therapy for T-shaped esophageal cancer. Radiat Oncol 2021; 16:158. [PMID: 34412656 PMCID: PMC8375041 DOI: 10.1186/s13014-021-01882-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Accepted: 08/11/2021] [Indexed: 12/24/2022] Open
Abstract
Background To evaluate the dosimetric and biological benefits of the fixed-jaw (FJ) intensity-modulated radiation therapy (IMRT) technique for patients with T-shaped esophageal cancer. Methods FJ IMRT plans were generated for thirty-five patients and compared with jaw tracking (JT) IMRT, static jaw (SJ) IMRT and JT volumetric modulated arc therapy (VMAT). Dosimetric parameters, tumor control probability (TCP) and normal tissue complication probability (NTCP), monitor units (MUs), delivery time and gamma passing rate, as a measure of dosimetric verification, were compared. The correlation between the length of PTV-C below the upper boundary of lung tissue (PTV-Cinferior) and dosimetric parameters and NTCP of the lung tissue were analyzed. Results The homogeneity and conformity of the target in the four plans were basically equivalent. When compared to the JT IMRT and SJ IMRT plans, FJ IMRT plan led to a statistically significant improvement in the NTCP and low-middle dosimetric parameters of the lung, and the improvement had a moderately positive correlation with the length of PTV-Cinferior, with a correlation coefficient ranging from 0.523 to 0.797; the FJ IMRT plan exhibited better lung sparing in low-dose volumes than the JT VMAT plan. The FJ IMRT plan had similar MUs (888 ± 99) and delivery times (516.1 ± 54.7 s) as the JT IMRT plan (937 ± 194, 522 ± 5.6 s) but higher than SJ IMRT (713 ± 137, 488.8 ± 45.2 s) and JT VMAT plan (517 ± 59, 263.7 ± 43.3 s). Conclusions The FJ IMRT technique is superior in reducing the low-dose volumes of lung tissues for patients with T-shaped esophageal cancer.
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Affiliation(s)
- Hua Chen
- Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, No. 241 West Huaihai Road, Xuhui District, Shanghai, 200030, China
| | - Ying Huang
- Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, No. 241 West Huaihai Road, Xuhui District, Shanghai, 200030, China
| | - Hao Wang
- Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, No. 241 West Huaihai Road, Xuhui District, Shanghai, 200030, China
| | - Yan Shao
- Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, No. 241 West Huaihai Road, Xuhui District, Shanghai, 200030, China
| | - Ning J Yue
- Department of Radiation Oncology, Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, NJ, 08903, USA
| | - Hengle Gu
- Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, No. 241 West Huaihai Road, Xuhui District, Shanghai, 200030, China
| | - Yanhua Duan
- Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, No. 241 West Huaihai Road, Xuhui District, Shanghai, 200030, China
| | - Aihui Feng
- Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, No. 241 West Huaihai Road, Xuhui District, Shanghai, 200030, China
| | - Zhiyong Xu
- Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, No. 241 West Huaihai Road, Xuhui District, Shanghai, 200030, China.
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Yang LT, Zhou L, Chen L, Liang SX, Huang JQ, Zhu XD. Establishment and Verification of a Prediction Model for Symptomatic Radiation Pneumonitis in Patients with Esophageal Cancer Receiving Radiotherapy. Med Sci Monit 2021; 27:e930515. [PMID: 33953150 PMCID: PMC8112075 DOI: 10.12659/msm.930515] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND This study aimed to determine the value of the significant index in predicting symptomatic radiation pneumonitis (RP) in esophageal cancer patients, establish a nomogram prediction model, and verify the model. MATERIAL AND METHODS The patients enrolled were divided into 2 groups: a model group and a validation group. According to the logistic regression analysis, the independent predictors for symptomatic RP were obtained, and the nomogram prediction model was established according to these independent predictors. The consistency index (C-index) and calibration curve were used to evaluate the accuracy of the model, and the prediction ability of the model was verified in the validation group. Recursive partitioning analysis (RPA) was used for the risk stratification analysis. RESULTS The ratio of change regarding the pre-albumin at the end of treatment (P=0.001), platelet-to-lymphocyte ratio during treatment (P=0.027), and neutrophil-to-lymphocyte ratio at the end of treatment (P=0.001) were the independent predictors for symptomatic RP. The C-index of the nomogram model was 0.811. According to the risk stratification of RPA, the whole group was divided into 3 groups: a low-risk group, a medium-risk group, and a high-risk group. The incidence of symptomatic RP was 0%, 16.9%, and 57.6%, respectively. The receiver operating characteristic curve also revealed that the nomogram model has good accuracy in the validation group. CONCLUSIONS The developed nomogram and corresponding risk classification system have superior prediction ability for symptomatic RP and can predict the occurrence of RP in the early stage.
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Affiliation(s)
- Liu-Ting Yang
- Department of Radiation Oncology, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China (mainland)
| | - Lei Zhou
- Department of Radiation Oncology, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China (mainland)
| | - Long Chen
- Department of Radiation Oncology, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China (mainland)
| | - Shi-Xiong Liang
- Department of Radiation Oncology, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China (mainland)
| | - Jiang-Qiong Huang
- Department of Radiation Oncology, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China (mainland)
| | - Xiao-Dong Zhu
- Department of Radiation Oncology, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China (mainland).,Department of Oncology, Wuming Hospital of Guangxi Medical University, Nanning, Guangxi, China (mainland)
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Collie D, Wright SH, Del-Pozo J, Kay E, Schwarz T, Parys M, Lawrence J. Regional and organ-level responses to local lung irradiation in sheep. Sci Rep 2021; 11:9553. [PMID: 33953285 PMCID: PMC8099861 DOI: 10.1038/s41598-021-88863-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Accepted: 04/14/2021] [Indexed: 11/30/2022] Open
Abstract
Lung is a dose-limiting organ in radiotherapy. This may limit tumour control when effort is made in planning to limit the likelihood of radiation-induced lung injury (RILI). Understanding the factors that dictate susceptibility to radiation-induced pulmonary fibrosis will aid in the prevention and management of RILI, and may lead to more effective personalized radiotherapy treatment. As the interaction of regional and organ-level responses may shape the chronic consequences of RILI, we sought to characterise both aspects of the response in an ovine model. A defined volume of left pulmonary parenchyma was prescribed 5 fractions of 6 Gy within 14 days while the contralateral lung dose was constrained. Radiographic changes via computed tomography (CT) were documented to define differences in radio-exposed lung relative to non-exposed lung at d21, d63 and d171 (n = 2), and at d21, d147 and d227 (n = 2). Gross and histologic lung changes were evaluated in samples derived at necropsy examination to define the chronic pulmonary response to radiation. Irradiated lung demonstrated reduced radio-density and increased homogeneity as evidenced from texture based radiomic feature analysis, relative to the control lung. At necropsy, the radiation field was readily defined by pallor on the pleural surface, which was also evident on the cut surface of fixed lung specimens. The degree and homogeneity of pallor reflected the sparse presence of erythrocytes in alveolar septal capillaries of radiation-exposed lung. These changes contrasted with dilated and congested microvasculature in the contralateral control lung. Referencing data to measurements made in control lung volumes of sheep experiencing acute RILI indicated that interstitial collagen continues to deposit in the radio-exposed lung field. Overall lung vascularity increased during the chronic response, as evidenced by increased expression of endothelial cell marker (CD31); however, vascularity was consistently decreased in irradiated lung and was negatively correlated with lung collagen. Other organ-level responses included increased expression of alpha smooth muscle actin (ASMA), increased numbers of proliferating cells (Ki67 positive), and cells expressing the dendritic cell-lysosomal associated membrane protein (DC-LAMP) antigen. The chronic response to RILI in this model is effected at both the whole organ and local lung level. Whilst the long-term consequences of exposure to radiation involved the continued deposition of collagen in the radiation field, organ-level responses also included increased vascularization and increased expression of ASMA, Ki67 and DC-LAMP. Interrupting the interplay between these aspects may influence susceptibility to pulmonary fibrosis after radiotherapy. We advocate for the importance of large animal model systems in pursuing these opportunities to target local, organ-level and systemic mechanisms in parallel within the same subject over time.
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Affiliation(s)
- David Collie
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, Edinburgh, EH25 9RG, UK.
| | - Steven H Wright
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, Edinburgh, EH25 9RG, UK
| | - Jorge Del-Pozo
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, Edinburgh, EH25 9RG, UK
| | - Elaine Kay
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, Edinburgh, EH25 9RG, UK
- Small Animal Clinical Sciences, School of Veterinary Medicine, University of Glasgow, Glasgow, UK
| | - Tobias Schwarz
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, Edinburgh, EH25 9RG, UK
| | - Magdalena Parys
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, Edinburgh, EH25 9RG, UK
| | - Jessica Lawrence
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, Edinburgh, EH25 9RG, UK
- Department of Veterinary Clinical Sciences, University of Minnesota, St Paul, MN, USA
- Masonic Cancer Center, University of Minnesota, Minneapolis, MN, USA
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Paganetti H, Grassberger C, Sharp GC. Physics of Particle Beam and Hypofractionated Beam Delivery in NSCLC. Semin Radiat Oncol 2021; 31:162-169. [PMID: 33610274 PMCID: PMC7905707 DOI: 10.1016/j.semradonc.2020.11.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
The dosimetric advantages of particle therapy lead to significantly reduced integral dose to normal tissues, making it an attractive treatment option for body sites such as the thorax. With reduced normal tissue dose comes the potential for dose escalation, toxicity reduction, or hypofractionation. While proton and heavy ion therapy have been used extensively for NSCLC, there are challenges in planning and delivery compared with X-ray-based radiation therapy. Particularly, range uncertainties compounded by breathing motion have to be considered. This article summarizes the current state of particle therapy for NSCLC with a specific focus on the impact of dosimetric uncertainties in planning and delivery.
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Affiliation(s)
- Harald Paganetti
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA.
| | - Clemens Grassberger
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA
| | - Gregory C Sharp
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA
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Yu H, Lam KO, Wu H, Green M, Wang W, Jin JY, Hu C, Jolly S, Wang Y, Kong FMS. Weighted-Support Vector Machine Learning Classifier of Circulating Cytokine Biomarkers to Predict Radiation-Induced Lung Fibrosis in Non-Small-Cell Lung Cancer Patients. Front Oncol 2021; 10:601979. [PMID: 33598430 PMCID: PMC7883680 DOI: 10.3389/fonc.2020.601979] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Accepted: 12/08/2020] [Indexed: 01/06/2023] Open
Abstract
Background Radiation-induced lung fibrosis (RILF) is an important late toxicity in patients with non-small-cell lung cancer (NSCLC) after radiotherapy (RT). Clinically significant RILF can impact quality of life and/or cause non-cancer related death. This study aimed to determine whether pre-treatment plasma cytokine levels have a significant effect on the risk of RILF and investigate the abilities of machine learning algorithms for risk prediction. Methods This is a secondary analysis of prospective studies from two academic cancer centers. The primary endpoint was grade≥2 (RILF2), classified according to a system consistent with the consensus recommendation of an expert panel of the AAPM task for normal tissue toxicity. Eligible patients must have at least 6 months’ follow-up after radiotherapy commencement. Baseline levels of 30 cytokines, dosimetric, and clinical characteristics were analyzed. Support vector machine (SVM) algorithm was applied for model development. Data from one center was used for model training and development; and data of another center was applied as an independent external validation. Results There were 57 and 37 eligible patients in training and validation datasets, with 14 and 16.2% RILF2, respectively. Of the 30 plasma cytokines evaluated, SVM identified baseline circulating CCL4 as the most significant cytokine associated with RILF2 risk in both datasets (P = 0.003 and 0.07, for training and test sets, respectively). An SVM classifier predictive of RILF2 was generated in Cohort 1 with CCL4, mean lung dose (MLD) and chemotherapy as key model features. This classifier was validated in Cohort 2 with accuracy of 0.757 and area under the curve (AUC) of 0.855. Conclusions Using machine learning, this study constructed and validated a weighted-SVM classifier incorporating circulating CCL4 levels with significant dosimetric and clinical parameters which predicts RILF2 risk with a reasonable accuracy. Further study with larger sample size is needed to validate the role of CCL4, and this SVM classifier in RILF2.
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Affiliation(s)
- Hao Yu
- Biomedical Engineering, Shenzhen Polytechnic, Shenzhen, China.,BioHealth Informatics, School of Informatics and Computing, Indiana University - Purdue University Indianapolis (IUPUI), Indianapolis, IN, United States
| | - Ka-On Lam
- Department of Clinical Oncology, Li Ka Shing (LKS) Faculty of Medicine, The University of Hong Kong, Hong Kong, Hong Kong.,Clinical Oncology Center, The University of Hong Kong-Shenzhen Hospital, Shenzhen, China
| | - Huanmei Wu
- BioHealth Informatics, School of Informatics and Computing, Indiana University - Purdue University Indianapolis (IUPUI), Indianapolis, IN, United States
| | - Michael Green
- Radiation Oncology, Ann Arbor VA Health Care, Ann Arbor, MI, United States.,Radiation Oncology, University of Michigan, Ann Arbor, MI, United States
| | - Weili Wang
- University Hospitals, Cleveland Medical Center, Seidman Cancer Center and Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, OH, United States
| | - Jian-Yue Jin
- University Hospitals, Cleveland Medical Center, Seidman Cancer Center and Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, OH, United States
| | - Chen Hu
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Shruti Jolly
- Radiation Oncology, University of Michigan, Ann Arbor, MI, United States
| | - Yang Wang
- Biomedical Engineering, Shenzhen Polytechnic, Shenzhen, China
| | - Feng-Ming Spring Kong
- Department of Clinical Oncology, Li Ka Shing (LKS) Faculty of Medicine, The University of Hong Kong, Hong Kong, Hong Kong.,Clinical Oncology Center, The University of Hong Kong-Shenzhen Hospital, Shenzhen, China.,University Hospitals, Cleveland Medical Center, Seidman Cancer Center and Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, OH, United States
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Yakar M, Etiz D, Metintas M, Ak G, Celik O. Prediction of Radiation Pneumonitis With Machine Learning in Stage III Lung Cancer: A Pilot Study. Technol Cancer Res Treat 2021; 20:15330338211016373. [PMID: 33969761 PMCID: PMC8129486 DOI: 10.1177/15330338211016373] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
Background: Radiation pneumonitis (RP) is a dose-limiting toxicity in lung cancer radiotherapy (RT). As risk factors in the development of RP, patient and tumor characteristics, dosimetric parameters, and treatment features are intertwined, and it is not always possible to associate RP with a single parameter. This study aimed to determine the algorithm that most accurately predicted RP development with machine learning. Methods: Of the 197 cases diagnosed with stage III lung cancer and underwent RT and chemotherapy between 2014 and 2020, 193 were evaluated. The CTCAE 5.0 grading system was used for the RP evaluation. Synthetic minority oversampling technique was used to create a balanced data set. Logistic regression, artificial neural networks, eXtreme Gradient Boosting (XGB), Support Vector Machines, Random Forest, Gaussian Naive Bayes and Light Gradient Boosting Machine algorithms were used. After the correlation analysis, a permutation-based method was utilized for as a variable selection. Results: RP was seen in 51 of the 193 cases. Parameters affecting RP were determined as, total(t)V5, ipsilateral lung Dmax, contralateral lung Dmax, total lung Dmax, gross tumor volume, number of chemotherapy cycles before RT, tumor size, lymph node localization and asbestos exposure. LGBM was found to be the algorithm that best predicted RP at 85% accuracy (confidence interval: 0.73-0.96), 97% sensitivity, and 50% specificity. Conclusion: When the clinical and dosimetric parameters were evaluated together, the LGBM algorithm had the highest accuracy in predicting RP. However, in order to use this algorithm in clinical practice, it is necessary to increase data diversity and the number of patients by sharing data between centers.
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Affiliation(s)
- Melek Yakar
- Department of Radiation Oncology, Medical Faculty of Osmangazi University, Eskişehir, Turkey.,Eskisehir Osmangazi University Center of Research and Application for Computer Aided Diagnosis and Treatment in Health, Eskisehir, Turkey
| | - Durmus Etiz
- Department of Radiation Oncology, Medical Faculty of Osmangazi University, Eskişehir, Turkey.,Eskisehir Osmangazi University Center of Research and Application for Computer Aided Diagnosis and Treatment in Health, Eskisehir, Turkey
| | - Muzaffer Metintas
- Eskisehir Osmangazi University Center of Research and Application for Computer Aided Diagnosis and Treatment in Health, Eskisehir, Turkey.,Department of Chest Diseases, Medical Faculty of Osmangazi University, Eskişehir, Turkey
| | - Guntulu Ak
- Department of Chest Diseases, Medical Faculty of Osmangazi University, Eskişehir, Turkey
| | - Ozer Celik
- Eskisehir Osmangazi University Center of Research and Application for Computer Aided Diagnosis and Treatment in Health, Eskisehir, Turkey.,Department of Mathematics-Computer, Eskisehir Osmangazi University, Eskişehir, Turkey
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42
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Impact of Low-Dose Irradiation of the Lung and Heart on Toxicity and Pulmonary Function Parameters after Thoracic Radiotherapy. Cancers (Basel) 2020; 13:cancers13010022. [PMID: 33374564 PMCID: PMC7793060 DOI: 10.3390/cancers13010022] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Revised: 12/14/2020] [Accepted: 12/19/2020] [Indexed: 02/07/2023] Open
Abstract
Simple Summary To assess the impact of thoracic (low) dose irradiation on pulmonary function changes after thoracic radiotherapy (RT) data of 62 patients were analyzed. There were several significant correlations between pulmonary function and dose parameters of the lung and heart, most of which remained significant in the multivariate analysis. Abstract Objective: To assess the impact of (low) dose irradiation to the lungs and heart on the incidence of pneumonitis and pulmonary function changes after thoracic radiotherapy (RT). Methods/Material: Data of 62 patients treated with curative thoracic radiotherapy were analyzed. Toxicity data and pulmonary function tests (PFTs) were obtained before RT and at 6 weeks, at 12 weeks, and at 6 months after RT. PFTs included ventilation (e.g., vital capacity) and diffusion parameters (e.g., diffusion capacity for carbon monoxide (DLCO)). Dosimetric data of the lung and heart were extracted to assess the impact of dose on PFT changes and radiation pneumonitis (RP). Results: No statistically significant correlations between dose parameters and changes in ventilation parameters were found. There were statistically significant correlations between DLCO and low-dose parameters of the lungs (V5Gy–V30Gy (%)) and irradiation of the heart during the follow-up up to 6 months after RT, as well as a temporary correlation of the V60Gy (%) on the blood gas parameters at 12 weeks after RT. On multivariate analysis, both heart and lung parameters had a significant impact on DLCO. There was no statistically significant influence of any patient or treatment-related (including dose parameters) factors on the incidence of ≥G2 pneumonitis. Conclusion: There seems to be a lasting impact of low dose irradiation to the lung as well as irradiation to the heart on the DLCO after thoracic radiotherapy. No influence on RP was found in this analysis.
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Sardaro A, McDonald F, Bardoscia L, Lavrenkov K, Singh S, Ashley S, Traish D, Ferrari C, Meattini I, Asabella AN, Brada M. Dyspnea in Patients Receiving Radical Radiotherapy for Non-Small Cell Lung Cancer: A Prospective Study. Front Oncol 2020; 10:594590. [PMID: 33425746 PMCID: PMC7787051 DOI: 10.3389/fonc.2020.594590] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Accepted: 11/18/2020] [Indexed: 12/19/2022] Open
Abstract
Background and Purpose Dyspnea is an important symptomatic endpoint for assessment of radiation-induced lung injury (RILI) following radical radiotherapy in locally advanced disease, which remains the mainstay of treatment at the time of significant advances in therapy including combination treatments with immunotherapy and chemotherapy and the use of local ablative radiotherapy techniques. We investigated the relationship between dose-volume parameters and subjective changes in dyspnea as a measure of RILI and the relationship to spirometry. Material and Methods Eighty patients receiving radical radiotherapy for non-small cell lung cancer were prospectively assessed for dyspnea using two patient-completed tools: EORTC QLQ-LC13 dyspnea quality of life assessment and dyspnea visual analogue scale (VAS). Global quality of life, spirometry and radiation pneumonitis grade were also assessed. Comparisons were made with lung dose-volume parameters. Results The median survival of the cohort was 26 months. In the evaluable group of 59 patients there were positive correlations between lung dose-volume parameters and a change in dyspnea quality of life scale at 3 months (V30 p=0.017; V40 p=0.026; V50 p=0.049; mean lung dose p=0.05), and a change in dyspnea VAS at 6 months (V30 p=0.05; V40 p=0.026; V50 p=0.028) after radiotherapy. Lung dose-volume parameters predicted a 10% increase in dyspnea quality of life score at 3 months (V40; p=0.041, V50; p=0.037) and dyspnea VAS score at 6 months (V40; p=0.027) post-treatment. Conclusions Worsening of dyspnea is an important symptom of RILI. We demonstrate a relationship between lung dose-volume parameters and a 10% worsening of subjective dyspnea scores. Our findings support the use of subjective dyspnea tools in future studies on radiation-induced lung toxicity, particularly at doses below conventional lung radiation tolerance limits.
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Affiliation(s)
- Angela Sardaro
- Lung Research Unit, The Royal Marsden NHS Foundation Trust, Sutton, United Kingdom.,Interdisciplinary Department of Medicine, Nuclear Medicine Unit and Section of Radiology and Radiation Oncology, University of Bari Aldo Moro, Bari, Italy
| | - Fiona McDonald
- Lung Research Unit, The Royal Marsden NHS Foundation Trust, Sutton, United Kingdom.,Academic Radiotherapy Unit, The Institute of Cancer Research, Sutton, United Kingdom
| | - Lilia Bardoscia
- Radiation Therapy Unit, Department of Oncology and Advanced Technology, Azienda USL-IRCCS di Reggio Emilia, Reggio Emilia, Italy
| | - Konstantin Lavrenkov
- Lung Research Unit, The Royal Marsden NHS Foundation Trust, Sutton, United Kingdom.,Department of Oncology, Soroka University Medical Center, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel
| | - Shalini Singh
- Lung Research Unit, The Royal Marsden NHS Foundation Trust, Sutton, United Kingdom.,Sanjay Gandhi Post Graduate Institute of Medical Sciences (SGPGIMS), Department of Radiotherapy, Lucknow, India
| | - Sue Ashley
- Lung Research Unit, The Royal Marsden NHS Foundation Trust, Sutton, United Kingdom
| | - Daphne Traish
- Lung Research Unit, The Royal Marsden NHS Foundation Trust, Sutton, United Kingdom
| | - Cristina Ferrari
- Interdisciplinary Department of Medicine, Nuclear Medicine Unit and Section of Radiology and Radiation Oncology, University of Bari Aldo Moro, Bari, Italy
| | - Icro Meattini
- Lung Research Unit, The Royal Marsden NHS Foundation Trust, Sutton, United Kingdom.,Department of Biomedical, Experimental, and Clinical Sciences, University of Florence, Radiation Oncology Unit - Oncology Department, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Artor Niccoli Asabella
- Interdisciplinary Department of Medicine, Nuclear Medicine Unit and Section of Radiology and Radiation Oncology, University of Bari Aldo Moro, Bari, Italy
| | - Michael Brada
- Lung Research Unit, The Royal Marsden NHS Foundation Trust, Sutton, United Kingdom.,Academic Radiotherapy Unit, The Institute of Cancer Research, Sutton, United Kingdom.,Department of Radiation Oncology, University of Liverpool and Clatterbridge Cancer Centre NHS Foundation Trust, Wirral, United Kingdom
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44
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Liu YC, Chang HM, Lin HH, Lu CC, Lai LH. Dosimetric Comparison of Intensity-Modulated Radiotherapy, Volumetric Modulated Arc Therapy and Hybrid Three-Dimensional Conformal Radiotherapy/Intensity-Modulated Radiotherapy Techniques for Right Breast Cancer. J Clin Med 2020; 9:E3884. [PMID: 33260404 PMCID: PMC7760558 DOI: 10.3390/jcm9123884] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2020] [Revised: 11/23/2020] [Accepted: 11/26/2020] [Indexed: 12/21/2022] Open
Abstract
This study aimed to compare different types of right breast cancer radiotherapy planning techniques and to estimate the whole-body effective doses and the critical organ absorbed doses. The three planning techniques are intensity-modulated radiotherapy (IMRT), volumetric modulated arc therapy (VMAT; two methods) and hybrid 3D-CRT/IMRT (three-dimensional conformal radiotherapy/intensity-modulated radiotherapy). The VMAT technique includes two methods to deliver a dose: non-continuous partial arc and continuous partial arc. A thermoluminescent dosimeter (TLD) is placed in the RANDO phantom to estimate the organ absorbed dose. Each planning technique applies 50.4 Gy prescription dose and treats critical organs, including the lung and heart. Dose-volume histogram was used to show the planning target volume (V95%), homogeneity index (HI), conformity index (CI), and other optimized indices. The estimation of whole-body effective dose was based on the International Commission on Radiation Protection (ICRP) Publication 60 and 103. The results were as follows: Continuous partial arc and non-continuous partial arc showed the best CI and HI. The heart absorbed doses in the continuous partial arc and hybrid 3D-CRT/IMRT were 0.07 ± 0.01% and 0% (V5% and V10%, respectively). The mean dose of the heart was lowest in hybrid 3D-CRT/IMRT (1.47 Gy ± 0.02). The dose in the left contralateral lung (V5%) was lowest in continuous partial arc (0%). The right ipsilateral lung average dose and V20% are lowest in continuous partial arc. Hybrid 3D-CRT/IMRT has the lowest mean dose to contralateral breast (organs at risk). The whole-body effective doses for ICRP-60 and ICRP-103 were highest in continuous partial arc (2.01 Sv ± 0.23 and 2.89 Sv ± 0.15, respectively). In conclusion, the use of VMAT with continuous arc has a lower risk of radiation pneumonia, while hybrid 3D-CRT/IMRT attain lower secondary malignancy risk and cardiovascular complications.
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Affiliation(s)
- Yi-Chi Liu
- Institute of Nuclear Engineering and Science, National Tsing Hua University, Hsinchu 30015 Taiwan;
- Department of Radiation Oncology, Wei Gong Memorial Hospital, Miaoli 35148, Taiwan
| | - Hung-Ming Chang
- Department of General Surgery, Wei Gong Memorial Hospital, Miaoli 35159, Taiwan;
| | - Hsin-Hon Lin
- Medical Physics Research Center, Institute for Radiological Research, Chang Gung University/Chang Gung Memorial Hospital, Taoyuan 33302, Taiwan;
- Department of Radiation Oncology, Chang Gung Memorial Hospital, Taoyuan 33305, Taiwan
- Department of Nuclear Medicine, Keelung Chang Gung Memorial Hospital, Keelung 20401, Taiwan
| | - Chia-Chun Lu
- Department of Biomedical Engineering and Environmental Sciences, National Tsing Hua University, Hsinchu 30013, Taiwan;
| | - Lu-Han Lai
- Department of Medical Imaging and Radiological Technology, Yuanpei University of Medical Technology, Hsinchu 30015, Taiwan
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45
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Wang D, Chen J, Zhang X, Zhang T, Wang L, Feng Q, Zhou Z, Dai J, Bi N. Sparing Organs at Risk with Simultaneous Integrated Boost Volumetric Modulated Arc Therapy for Locally Advanced Non-Small Cell Lung Cancer: An Automatic Treatment Planning Study. Cancer Manag Res 2020; 12:9643-9653. [PMID: 33116824 PMCID: PMC7547766 DOI: 10.2147/cmar.s273197] [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: 07/21/2020] [Accepted: 08/28/2020] [Indexed: 12/25/2022] Open
Abstract
Background The technique of simultaneous integrated boost volumetric modulated arc therapy (SIB-VMAT) has been widely used in locally advanced non-small cell lung cancer; however, its dosimetric advantages are seldom reported. This study aimed to quantify dosimetric advantages of SIB-VMAT. Methods Forty patients with stage III non-small cell lung cancer in our hospital were retrospectively included. SIB-VMAT and conventional VMAT (C-VMAT) plans were generated for every patient using the automatic treatment planning system. A reduced dose was delivered to PTV in SIB-VAMT plans compared to C-VMAT plans (50.4Gy vs 60Gy). The prescribed dose was 50.4 Gy in 28 fractions to PTV and 59.92 Gy in 28 fractions to PGTV in SIB-VMAT plans, while 60 Gy in 30 fractions to PTV in C-VMAT plans. Dose-volume metrics of PTV, total lung, heart, esophagus and spinal cord were recorded. The quality score was used to evaluate organs at risk (OAR) protection for two type prescription plans. Results Conformal coverage of the targets (PGTV/PTV) by 95% of the prescription dose was well achieved in radiation plans. SIB-VMAT plans achieved significantly higher quality score than C-VMAT plans (Mean: 68.15±13.32 vs 49.15±13.35, P<0.001). More plans scored above sixty in SIB-VMAT group compared to C-VMAT group (72.5% vs 20%, P<0.001). Notable reductions in mean dose, V30, V40 and V50 of total lung were observed in SIB-VMAT plans compared to C-VMAT plans, with median decreased proportions of 6.5%, 8.7%, 19.6% and 32.1%, respectively. Statistically significant decrease in heart V30 and V40 was also achieved in SIB-VMAT plans, with median decreased proportions of 26.1% and 38.8%. SIB-VMAT plans achieved significant reductions in the maximum doses to both esophagus and spinal cord. Patients with CTV/(GTV+GTVnd) ≥8.6 showed more notable decrease in total lung V50 (median, 33.6% vs 28.8%, P=0.001) in SIB-VMAT plans compared to those with the ratio being less than 8.6. Conclusion SIB-VMAT technique could lead to a substantial sparing of normal organs, including lung, heart, esophagus and cord, mainly through reducing high and inter-median dose exposure. Patients with CTV/(GTV+GTVnd) ≥8.6 might benefit more from SIB-VMAT.
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Affiliation(s)
- Daquan Wang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China
| | - Jiayun Chen
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China
| | - Xiaodong Zhang
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Tao Zhang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China
| | - Luhua Wang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China
| | - Qinfu Feng
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China
| | - Zongmei Zhou
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China
| | - Jianrong Dai
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China
| | - Nan Bi
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China
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Higher Dose Volumes May Be Better for Evaluating Radiation Pneumonitis in Lung Proton Therapy Patients Compared With Traditional Photon-Based Dose Constraints. Adv Radiat Oncol 2020; 5:943-950. [PMID: 33083657 PMCID: PMC7557193 DOI: 10.1016/j.adro.2020.06.023] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2020] [Revised: 05/14/2020] [Accepted: 06/22/2020] [Indexed: 12/13/2022] Open
Abstract
Purpose The dosimetric parameters used clinically to reduce the likelihood of radiation pneumonitis (RP) for lung cancer radiation therapy have traditionally been V20Gy ≤ 30% to 35% and mean lung dose ≤ 20 to 23 Gy; however, these parameters are derived based on studies from photon therapy. The purpose of this study is to evaluate whether such dosimetric predictors for RP are applicable for locally advanced non-small cell lung cancer (LA-NSCLC) patients treated with proton therapy. Methods and Materials In the study, 160 (78 photon, 82 proton) patients with LA-NSCLC treated with chemoradiotherapy between 2011 and 2016 were retrospectively identified. Forty (20 photon, 20 proton) patients exhibited grade ≥2 RP after therapy. Dose volume histograms for the uninvolved lung were extracted for each patient. The percent lung volumes receiving above various dose levels were obtained in addition to V20Gy and Dmean. These dosimetric parameters and patient characteristics were evaluated with univariate and multivariate logistic regression tests. Receiver operating characteristic curves were generated to obtain the optimal dosimetric constraints through analyzing RP and non-RP sensitivity and specificity values. Results The multivariate analysis showed V40Gy and Dmean to be statistically significant for proton and photon patients, respectively. V35Gy to V50Gy were strongly correlated to V40Gy for proton patients. Based on the receiver operating characteristic curves, V35Gy to V50Gy had the highest area under the curve compared with other dose levels for proton patients. A potential dosimetric constraint for RP predictor in proton patients is V40Gy ≤ 23%. Conclusions In addition to V20Gy and Dmean, the lung volume receiving higher doses, such as V40Gy, may be used as an additional indicator for RP in LA-NSCLC patients treated with proton therapy.
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47
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Automatic feathering algorithm for VMAT craniospinal irradiation: A comprehensive comparison with other VMAT planning strategies. Med Dosim 2020; 46:103-110. [PMID: 32967789 DOI: 10.1016/j.meddos.2020.09.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Revised: 07/22/2020] [Accepted: 09/11/2020] [Indexed: 01/06/2023]
Abstract
In craniospinal irradiation, field matching is very sensitive to intrafraction positional uncertainties in cranio-caudal direction, which could lead to severe overdoses/underdoses inside the planning target volume. During the last decade, significant efforts were made to develop volumetric-modulated arc therapy strategies, which were less sensitive to setup uncertainties. In this study, a treatment planning system-integrated method, named automatic feathering (AF) algorithm, was compared against other volumetric-modulated arc therapy strategies. Three patients were retrospectively included. Five different planning techniques were compared, including overlap (O), staggered overlap (SO), gradient optimization (GO), overlap with AF algorithm turned on (O-AF), and staggered overlap with AF algorithm turned on (SO-AF). Three overlapping lengths were considered (5 cm, 7.5 cm, and 10 cm). The middle isocenter was shifted of ±1 mm, ±3 mm, and ±5 mm to simulate setup uncertainties. Plan robustness against simulated uncertainties was evaluated by calculating near maximum and near minimum dose differences between shifted and nonshifted plans (ΔD2%, ΔD98%). Dose differences among combinations of techniques and junction lengths were tested using Wilcoxon signed-rank test. Higher ΔD2% and ΔD98% were obtained using the overlap technique (ΔD2% = 15.4%, ΔD98% = 15.0%). O-AF and SO-AF provided comparable plan robustness to GO technique. Their performance improved significantly for grater overlapping length. For 10-cm overlap and 5-mm shift, GO, O-AF, and SO-AF yielded to the better plan robustness (5.7% < ΔD2% < 6.0%, 6.1% < ΔD98% < 7.6%). SO provided an intermediate plan robustness (9.8% < ΔD2% < 10.8%, 8.9% < ΔD98% < 10.3%). The addition of AF to the overlap technique significantly improves plan robustness especially if larger overlapping lengths are used. Using the AF algorithm, plans become as robust as plans optimized with more sophisticated and time-consuming approaches (like GO).
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48
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Lin Y, Shueng P, Lin H, Tien H, Lai L. An efficient treatment planning approach to reduce the critical organ dose in volumetric modulated arc therapy for synchronous bilateral breast cancer patients. Radiat Phys Chem Oxf Engl 1993 2020. [DOI: 10.1016/j.radphyschem.2020.108957] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
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49
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Jiao Y, Ren Y, Ge W, Zhang L, Zheng X. Adoption of Biologically Effective Dose of the Non-Target Lung Volume to Predict Symptomatic Radiation Pneumonitis After Stereotactic Body Radiation Therapy With Variable Fractionations for Lung Cancer. Front Oncol 2020; 10:1153. [PMID: 32850328 PMCID: PMC7411255 DOI: 10.3389/fonc.2020.01153] [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: 03/18/2020] [Accepted: 06/08/2020] [Indexed: 11/18/2022] Open
Abstract
Background: This study aims to establish lung biologically effective dose (BED)–based uniform dosimetric constraints for minimizing the risk of symptomatic radiation pneumonitis (SRP) from stereotactic body radiation therapy (SBRT) using variable fractionations in patients with lung tumors. Materials and Methods: A total of 102 patients with primary or oligometastatic lung tumors treated with SBRT in our institution were enrolled into this study. The associations between the clinical and dosimetric parameters and the incidences of SRP were analyzed using univariate and multivariate Cox regression hazard models. The receiver operating characteristic (ROC) curve was generated to evaluate the predictive performance of lung BED on the SRP risk compared with the physical dose. Results: SRP occurred in 11 patients (10.8%). In univariate analysis, the mean lung dose (p = 0.002), V5 (p = 0.005), V20 (p < 0.001), and the percentage of non-target normal lung volume receiving more than a BED of 5–170 Gy (VBED5−170, p < 0.05) were associated with SRP. Multivariate logistic regression analysis showed that there existed a significant statistical correlation between SRP and VBED70 (p < 0.001), which performed better than V5 or V20 on the ROC curves, resulting in an optimal cut-off value of lung VBED70 of 2.22%. Conclusions: This retrospective study indicated that non-target lung BED may better predict SRP from patients with SBRT-treated lung cancer. Limiting the lung VBED70 below 2.22% may be favorable to reduce the incidence of SRP, which warranted further prospective validation.
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Affiliation(s)
- Yuxin Jiao
- Department of Radiation Oncology, Huadong Hospital, Fudan University, Shanghai, China
| | - Yanping Ren
- Department of Radiation Oncology, Huadong Hospital, Fudan University, Shanghai, China
| | - Weiqiang Ge
- Department of Radiation Oncology, Huadong Hospital, Fudan University, Shanghai, China
| | - Libo Zhang
- Department of Radiation Oncology, Huadong Hospital, Fudan University, Shanghai, China
| | - Xiangpeng Zheng
- Department of Radiation Oncology, Huadong Hospital, Fudan University, Shanghai, China
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50
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Nithya L, Goel V, Sharma D, Vittal K, Marjara N. Dosimetric Comparison of Different Planning Techniques in Left-sided Whole-Breast Irradiation: A Planning Study. J Med Phys 2020; 45:148-155. [PMID: 33487927 PMCID: PMC7810142 DOI: 10.4103/jmp.jmp_49_20] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Revised: 08/24/2020] [Accepted: 08/24/2020] [Indexed: 12/25/2022] Open
Abstract
Purpose: This planning study compared the various dosimetric parameters of different types of intensity-modulated radiotherapy (IMRT) and volumetric-modulated arc therapy (VMAT) techniques for left-sided breast cancer radiotherapy. Materials and Methods: Treatment of 22 left-sided breast cases was planned using two IMRT and VMAT techniques for the prescription of 40 Gy in 15 fractions. For tangential IMRT (Tan_IMRT), five beams were placed as conventional tangential beams. For equally spaced IMRT (Equi_IMRT), six beams were placed equidistantly at 40° interval from 300° to 140°. For tangential VMAT (Tan_VMAT), two arcs were used with the avoidance sector in such a way that the beam covered like tangential fields. For full-arc VMAT (Full_VMAT), similar arcs as Tan_VMAT were used, without avoidance sector. All treatment plans were generated using Eclipse planning system for TrueBeam STx linear accelerator. For planning target volume (PTV), dose parameters including D95%, D99%, V105% homogeneity index (HI), and conformity index (CI) were analyzed. Different dose parameters for the left lung, heart, left anterior descending artery (LAD), right lung, and right breast were also analyzed. In addition, low-dose spillage in the normal tissues and the number of monitor units (MUs) required for the treatment were compared. Results: IMRT technique exhibited superior D95% and D99% for PTV compared with VMAT techniques. VMAT plans provided more V105% (6%) compared with that of IMRT plans (approximately 1%). HI was better in IMRT plans (Tan_IMRT, 0.085 ± 0.015; Equi_IMRT, 0.094 ± 0.011) than in VMAT plans. CI was better in VMAT plans. The mean lung dose (7.7 Gy ± 1.788 Gy) and V5Gy (34.99% ± 6.799%) were better achieved in Tan_IMRT plan than other plans. Right lung, heart, and right breast sparing were better achieved in Tan_IMRT plan. Moreover, low-dose spillage was very less in the Tan_IMRT compared with all other techniques. Conclusion: Dosimetric comparison in this study showed that tangential IMRT technique is superior in terms of target coverage, sparing of lung, heart, and right breast, and low-dose spillage control in the left-sided breast-only radiotherapy.
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Affiliation(s)
- L Nithya
- Department of Radiation Oncology, Max Super Speciality Hospital, Shalimarbagh, New Delhi, India
| | - Vineeta Goel
- Department of Radiation Oncology, Max Super Speciality Hospital, Shalimarbagh, New Delhi, India
| | - Deepti Sharma
- Department of Radiation Oncology, Max Super Speciality Hospital, Shalimarbagh, New Delhi, India.,Department of Radiation Oncology, Institute of Liver and Biliary Sciences, New Delhi, India
| | - Karthik Vittal
- Department of Radiation Oncology, Max Super Speciality Hospital, Shalimarbagh, New Delhi, India
| | - Nidhi Marjara
- Department of Radiation Oncology, Max Super Speciality Hospital, Shalimarbagh, New Delhi, India
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