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Midroni J, Salunkhe R, Liu Z, Chow R, Boldt G, Palma D, Hoover D, Vinogradskiy Y, Raman S. Incorporation of Functional Lung Imaging Into Radiation Therapy Planning in Patients With Lung Cancer: A Systematic Review and Meta-Analysis. Int J Radiat Oncol Biol Phys 2024; 120:370-408. [PMID: 38631538 PMCID: PMC11580018 DOI: 10.1016/j.ijrobp.2024.04.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Revised: 03/27/2024] [Accepted: 04/02/2024] [Indexed: 04/19/2024]
Abstract
Our purpose was to provide an understanding of current functional lung imaging (FLI) techniques and their potential to improve dosimetry and outcomes for patients with lung cancer receiving radiation therapy (RT). Excerpta Medica dataBASE (EMBASE), PubMed, and Cochrane Library were searched from 1990 until April 2023. Articles were included if they reported on FLI in one of: techniques, incorporation into RT planning for lung cancer, or quantification of RT-related outcomes for patients with lung cancer. Studies involving all RT modalities, including stereotactic body RT and particle therapy, were included. Meta-analyses were conducted to investigate differences in dose-function parameters between anatomic and functional RT planning techniques, as well as to investigate correlations of dose-function parameters with grade 2+ radiation pneumonitis (RP). One hundred seventy-eight studies were included in the narrative synthesis. We report on FLI modalities, dose-response quantification, functional lung (FL) definitions, FL avoidance techniques, and correlations between FL irradiation and toxicity. Meta-analysis results show that FL avoidance planning gives statistically significant absolute reductions of 3.22% to the fraction of well-ventilated lung receiving 20 Gy or more, 3.52% to the fraction of well-perfused lung receiving 20 Gy or more, 1.3 Gy to the mean dose to the well-ventilated lung, and 2.41 Gy to the mean dose to the well-perfused lung. Increases in the threshold value for defining FL are associated with decreases in functional parameters. For intensity modulated RT and volumetric modulated arc therapy, avoidance planning results in a 13% rate of grade 2+ RP, which is reduced compared with results from conventional planning cohorts. A trend of increased predictive ability for grade 2+ RP was seen in models using FL information but was not statistically significant. FLI shows promise as a method to spare FL during thoracic RT, but interventional trials related to FL avoidance planning are sparse. Such trials are critical to understanding the effect of FL avoidance planning on toxicity reduction and patient outcomes.
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Affiliation(s)
- Julie Midroni
- Temerty Faculty of Medicine, University of Toronto, Toronto, Canada; Radiation Medicine Program, Princess Margaret Cancer Center, Toronto, Canada
| | - Rohan Salunkhe
- Radiation Medicine Program, Princess Margaret Cancer Center, Toronto, Canada; Department of Radiation Oncology, University of Toronto, Toronto, Canada
| | - Zhihui Liu
- Biostatistics, Princess Margaret Cancer Center, Toronto, Canada
| | - Ronald Chow
- Temerty Faculty of Medicine, University of Toronto, Toronto, Canada; Radiation Medicine Program, Princess Margaret Cancer Center, Toronto, Canada; London Regional Cancer Program, London Health Sciences Centre, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Canada
| | - Gabriel Boldt
- London Regional Cancer Program, London Health Sciences Centre, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Canada
| | - David Palma
- London Regional Cancer Program, London Health Sciences Centre, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Canada; Ontario Institute for Cancer Research, Toronto, Canada
| | - Douglas Hoover
- London Regional Cancer Program, London Health Sciences Centre, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Canada
| | - Yevgeniy Vinogradskiy
- Department of Radiation Oncology, University of Colorado School of Medicine, Aurora, United States of America; Department of Radiation Oncology, Thomas Jefferson University, Philadelphia, United States of America
| | - Srinivas Raman
- Radiation Medicine Program, Princess Margaret Cancer Center, Toronto, Canada; Department of Radiation Oncology, University of Toronto, Toronto, Canada.
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Han C, Qiu J, Bai L, Liu T, Chen J, Wang H, Dang J. Pneumonitis Risk After Chemoradiotherapy With and Without Immunotherapy in Patients With Locally Advanced Non-Small Cell Lung Cancer: A Systematic Review and Meta-Analysis. Int J Radiat Oncol Biol Phys 2024; 119:1179-1207. [PMID: 38360117 DOI: 10.1016/j.ijrobp.2024.01.217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2023] [Revised: 12/28/2023] [Accepted: 01/28/2024] [Indexed: 02/17/2024]
Abstract
PURPOSE Chemoradiotherapy (CRT) combined with immune checkpoint inhibitors (ICIs) is the standard of care for patients with unresectable and locally advanced non-small cell lung cancer. This study aimed to determine whether the addition of ICIs to CRT is associated with an increased risk of pneumonitis. METHODS AND MATERIALS The PubMed, Embase, Cochrane Library, and Web of Science databases were searched for eligible studies published between January 1, 2015, and July 31, 2023. The outcome of interest was the incidence rate of pneumonitis. A random-effects model was used for statistical analysis. RESULTS A total of 185 studies with 24,527 patients were included. The pooled rate of grade ≥2 pneumonitis for CRT plus ICIs was significantly higher than that for CRT alone (29.6%; 95% CI, 25.7%-33.6% vs 20.2%; 95% CI, 17.7%-22.8%; P < .0001) but not that of grade ≥3 (5.7%; 95% CI, 4.8%-6.6% vs 5.6%; 95% CI, 4.7%-6.5%; P = .64) or grade 5 (0.1%; 95% CI, 0.0%-0.2% vs 0.3%; 95% CI, 0.1%-0.4%; P = .68). The results from the subgroup analyses of prospective studies, retrospective studies, Asian and non-Asian studies, concurrent CRT (cCRT), and durvalumab consolidation were comparable to the overall results. However, CRT or cCRT plus PD-1 inhibitors not only significantly increased the incidence of grade ≥2 but also that of grade ≥3 pneumonitis compared to CRT alone or cCRT plus PD-L1 inhibitors. CONCLUSIONS Compared with CRT alone, durvalumab consolidation after CRT appears to be associated with a higher incidence of moderate pneumonitis and CRT plus PD-1 inhibitors with an increased risk of severe pneumonitis. Nevertheless, these findings are based on observational studies and need to be validated in future large head-to-head studies.
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Affiliation(s)
- Chong Han
- Department of Radiation Oncology, First Hospital of China Medical University, Shenyang, China
| | - Jingping Qiu
- Department of Radiation Oncology, First Hospital of China Medical University, Shenyang, China
| | - Lu Bai
- Department of Radiation Oncology, First Hospital of China Medical University, Shenyang, China
| | - Tingting Liu
- Department of Radiation Oncology, Anshan Cancer Hospital, Anshan, China
| | - Jun Chen
- Department of Radiation Oncology, Shenyang Tenth People's Hospital, Shenyang, China
| | - He Wang
- Department of Radiation Oncology, First Hospital of China Medical University, Shenyang, China
| | - Jun Dang
- Department of Radiation Oncology, First Hospital of China Medical University, Shenyang, China.
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Liu T, Li S, Ding S, Qiu J, Ren C, Chen J, Wang H, Wang X, Li G, He Z, Dang J. Comparison of post-chemoradiotherapy pneumonitis between Asian and non-Asian patients with locally advanced non-small cell lung cancer: a systematic review and meta-analysis. EClinicalMedicine 2023; 64:102246. [PMID: 37781162 PMCID: PMC10539643 DOI: 10.1016/j.eclinm.2023.102246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Revised: 08/28/2023] [Accepted: 09/13/2023] [Indexed: 10/03/2023] Open
Abstract
Background Pneumonitis is a common complication for patients with locally advanced non-small cell lung cancer undergoing definitive chemoradiotherapy (CRT). It remains unclear whether there is ethnic difference in the incidence of post-CRT pneumonitis. Methods PubMed, Embase, Cochrane Library, and Web of Science were searched for eligible studies from January 1, 2000 to April 30, 2023. The outcomes of interest were incidence rates of pneumonitis. The random-effect model was used for statistical analysis. This meta-analysis was registered with PROSPERO (CRD42023416490). Findings A total of 248 studies involving 28,267 patients were included. Among studies of CRT without immunotherapy, the pooled rates of pneumonitis for Asian patients were significantly higher than that for non-Asian patients (all grade: 66.8%, 95% CI: 59.2%-73.9% vs. 28.1%, 95% CI: 20.4%-36.4%; P < 0.0001; grade ≥2: 25.1%, 95% CI: 22.9%-27.3% vs. 14.9%, 95% CI: 12.0%-18.0%; P < 0.0001; grade ≥3: 6.5%, 95% CI: 5.6%-7.3% vs. 4.6%, 95% CI: 3.4%-5.9%; P = 0.015; grade 5: 0.6%, 95% CI: 0.3%-0.9% vs. 0.1%, 95% CI: 0.0%-0.2%; P < 0.0001). Regarding studies of CRT plus immunotherapy, Asian patients had higher rates of all-grade (74.8%, 95% CI: 63.7%-84.5% vs. 34.3%, 95% CI: 28.7%-40.2%; P < 0.0001) and grade ≥2 (34.0%, 95% CI: 30.7%-37.3% vs. 24.6%, 95% CI: 19.9%-29.3%; P = 0.001) pneumonitis than non-Asian patients, but with no significant differences in the rates of grade ≥3 and grade 5 pneumonitis. Results from subgroup analyses were generally similar to that from the all studies. In addition, the pooled median/mean of lung volume receiving ≥20 Gy and mean lung dose were relatively low in Asian studies compared to that in non-Asian studies. Interpretation Asian patients are likely to have a higher incidence of pneumonitis than non-Asian patients, which appears to be due to the poor tolerance of lung to radiation. Nevertheless, these findings are based on observational studies and with significant heterogeneity, and need to be validated in future large prospective studies focusing on the subject. Funding None.
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Affiliation(s)
- Tingting Liu
- Department of Radiation Oncology, The First Hospital of China Medical University, Shenyang, China
- Department of Radiation Oncology, Anshan Cancer Hospital, Anshan, China
| | - Sihan Li
- Department of Radiation Oncology, The First Hospital of China Medical University, Shenyang, China
| | - Silu Ding
- Department of Radiation Oncology, The First Hospital of China Medical University, Shenyang, China
| | - Jingping Qiu
- Department of Radiation Oncology, The First Hospital of China Medical University, Shenyang, China
| | - Chengbo Ren
- Department of Radiation Oncology, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei, China
| | - Jun Chen
- Department of Radiation Oncology, Shenyang Tenth People's Hospital, Shenyang, China
| | - He Wang
- Department of Radiation Oncology, The First Hospital of China Medical University, Shenyang, China
| | - Xiaoling Wang
- Department of Radiation Oncology, The First Hospital of China Medical University, Shenyang, China
| | - Guang Li
- Department of Radiation Oncology, The First Hospital of China Medical University, Shenyang, China
| | - Zheng He
- Department of Radiation Oncology, The First Hospital of China Medical University, Shenyang, China
| | - Jun Dang
- Department of Radiation Oncology, The First Hospital of China Medical University, Shenyang, China
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Zhou PX, Zhang SX. Functional lung imaging in thoracic tumor radiotherapy: Application and progress. Front Oncol 2022; 12:908345. [PMID: 36212454 PMCID: PMC9544588 DOI: 10.3389/fonc.2022.908345] [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: 03/30/2022] [Accepted: 08/17/2022] [Indexed: 12/12/2022] Open
Abstract
Radiotherapy plays an irreplaceable and unique role in treating thoracic tumors, but the occurrence of radiation-induced lung injury has limited the increase in tumor target doses and has influenced patients' quality of life. However, the introduction of functional lung imaging has been incorporating functional lungs into radiotherapy planning. The design of the functional lung protection plan, while meeting the target dose requirements and dose limitations of the organs at risk (OARs), minimizes the radiation dose to the functional lung, thus reducing the occurrence of radiation-induced lung injury. In this manuscript, we mainly reviewed the lung ventilation or/and perfusion functional imaging modalities, application, and progress, as well as the results based on the functional lung protection planning in thoracic tumors. In addition, we also discussed the problems that should be explored and further studied in the practical application based on functional lung radiotherapy planning.
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Affiliation(s)
- Pi-Xiao Zhou
- Radiotherapy Center, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou, China
- Department of Oncology, The First People's Hospital of Changde City, Changde, China
| | - Shu-Xu Zhang
- Radiotherapy Center, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou, China
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Li B, Ren G, Guo W, Zhang J, Lam SK, Zheng X, Teng X, Wang Y, Yang Y, Dan Q, Meng L, Ma Z, Cheng C, Tao H, Lei H, Cai J, Ge H. Function-Wise Dual-Omics analysis for radiation pneumonitis prediction in lung cancer patients. Front Pharmacol 2022; 13:971849. [PMID: 36199694 PMCID: PMC9528994 DOI: 10.3389/fphar.2022.971849] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Accepted: 08/04/2022] [Indexed: 11/13/2022] Open
Abstract
Purpose: This study investigates the impact of lung function on radiation pneumonitis prediction using a dual-omics analysis method. Methods: We retrospectively collected data of 126 stage III lung cancer patients treated with chemo-radiotherapy using intensity-modulated radiotherapy, including pre-treatment planning CT images, radiotherapy dose distribution, and contours of organs and structures. Lung perfusion functional images were generated using a previously developed deep learning method. The whole lung (WL) volume was divided into function-wise lung (FWL) regions based on the lung perfusion functional images. A total of 5,474 radiomics features and 213 dose features (including dosiomics features and dose-volume histogram factors) were extracted from the FWL and WL regions, respectively. The radiomics features (R), dose features (D), and combined dual-omics features (RD) were used for the analysis in each lung region of WL and FWL, labeled as WL-R, WL-D, WL-RD, FWL-R, FWL-D, and FWL-RD. The feature selection was carried out using ANOVA, followed by a statistical F-test and Pearson correlation test. Thirty times train-test splits were used to evaluate the predictability of each group. The overall average area under the receiver operating characteristic curve (AUC), accuracy, precision, recall, and f1-score were calculated to assess the performance of each group. Results: The FWL-RD achieved a significantly higher average AUC than the WL-RD group in the training (FWL-RD: 0.927 ± 0.031, WL-RD: 0.849 ± 0.064) and testing cohorts (FWL-RD: 0.885 ± 0.028, WL-RD: 0.762 ± 0.053, p < 0.001). When using radiomics features only, the FWL-R group yielded a better classification result than the model trained with WL-R features in the training (FWL-R: 0.919 ± 0.036, WL-R: 0.820 ± 0.052) and testing cohorts (FWL-R: 0.862 ± 0.028, WL-R: 0.750 ± 0.057, p < 0.001). The FWL-D group obtained an average AUC of 0.782 ± 0.032, obtaining a better classification performance than the WL-D feature-based model of 0.740 ± 0.028 in the training cohort, while no significant difference was observed in the testing cohort (FWL-D: 0.725 ± 0.064, WL-D: 0.710 ± 0.068, p = 0.54). Conclusion: The dual-omics features from different lung functional regions can improve the prediction of radiation pneumonitis for lung cancer patients under IMRT treatment. This function-wise dual-omics analysis method holds great promise to improve the prediction of radiation pneumonitis for lung cancer patients.
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Affiliation(s)
- Bing Li
- Department of Radiation Oncology, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China
| | - Ge Ren
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Wei Guo
- Department of Radiation Oncology, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China
| | - Jiang Zhang
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Sai-Kit Lam
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Xiaoli Zheng
- Department of Radiation Oncology, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China
| | - Xinzhi Teng
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Yunhan Wang
- Department of Radiation Oncology, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China
| | - Yang Yang
- Department of Radiation Oncology, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China
| | - Qinfu Dan
- Department of Radiation Oncology, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China
| | - Lingguang Meng
- Department of Radiation Oncology, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China
| | - Zongrui Ma
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Chen Cheng
- Department of Radiation Oncology, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China
| | - Hongyan Tao
- Department of Radiation Oncology, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China
| | - Hongchang Lei
- Department of Radiation Oncology, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China
| | - Jing Cai
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong SAR, China
- *Correspondence: Hong Ge, ; Jing Cai,
| | - Hong Ge
- Department of Radiation Oncology, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China
- *Correspondence: Hong Ge, ; Jing Cai,
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