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He Y, Cazoulat G, Wu C, Svensson S, Almodovar-Abreu L, Rigaud B, McCollum E, Peterson C, Wooten Z, Rhee DJ, Balter P, Pollard-Larkin J, Cardenas C, Court L, Liao Z, Mohan R, Brock K. Quantifying the Effect of 4-Dimensional Computed Tomography-Based Deformable Dose Accumulation on Representing Radiation Damage for Patients with Locally Advanced Non-Small Cell Lung Cancer Treated with Standard-Fractionated Intensity-Modulated Radiation Therapy. Int J Radiat Oncol Biol Phys 2024; 118:231-241. [PMID: 37552151 DOI: 10.1016/j.ijrobp.2023.07.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 06/04/2023] [Accepted: 07/14/2023] [Indexed: 08/09/2023]
Abstract
PURPOSE The aim of this study was to investigate the dosimetric and clinical effects of 4-dimensional computed tomography (4DCT)-based longitudinal dose accumulation in patients with locally advanced non-small cell lung cancer treated with standard-fractionated intensity-modulated radiation therapy (IMRT). METHODS AND MATERIALS Sixty-seven patients were retrospectively selected from a randomized clinical trial. Their original IMRT plan, planning and verification 4DCTs, and ∼4-month posttreatment follow-up CTs were imported into a commercial treatment planning system. Two deformable image registration algorithms were implemented for dose accumulation, and their accuracies were assessed. The planned and accumulated doses computed using average-intensity images or phase images were compared. At the organ level, mean lung dose and normal-tissue complication probability (NTCP) for grade ≥2 radiation pneumonitis were compared. At the region level, mean dose in lung subsections and the volumetric overlap between isodose intervals were compared. At the voxel level, the accuracy in estimating the delivered dose was compared by evaluating the fit of a dose versus radiographic image density change (IDC) model. The dose-IDC model fit was also compared for subcohorts based on the magnitude of NTCP difference (|ΔNTCP|) between planned and accumulated doses. RESULTS Deformable image registration accuracy was quantified, and the uncertainty was considered for the voxel-level analysis. Compared with planned doses, accumulated doses on average resulted in <1-Gy lung dose increase and <2% NTCP increase (up to 8.2 Gy and 18.8% for a patient, respectively). Volumetric overlap of isodose intervals between the planned and accumulated dose distributions ranged from 0.01 to 0.93. Voxel-level dose-IDC models demonstrated a fit improvement from planned dose to accumulated dose (pseudo-R2 increased 0.0023) and a further improvement for patients with ≥2% |ΔNTCP| versus for patients with <2% |ΔNTCP|. CONCLUSIONS With a relatively large cohort, robust image registrations, multilevel metric comparisons, and radiographic image-based evidence, we demonstrated that dose accumulation more accurately represents the delivered dose and can be especially beneficial for patients with greater longitudinal response.
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Affiliation(s)
- Yulun He
- Graduate School of Biomedical Sciences, University of Texas MD Anderson Cancer Center UTHealth Houston, Houston, Texas; Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, Texas.
| | - Guillaume Cazoulat
- Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Carol Wu
- Department of Diagnostic Radiology, University of Texas MD Anderson Cancer Center, Houston, Texas
| | | | | | - Bastien Rigaud
- Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Emma McCollum
- Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Christine Peterson
- Department of Biostatistics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Zachary Wooten
- Department of Statistics, Rice University, Houston, Texas
| | - Dong Joo Rhee
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Peter Balter
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Julianne Pollard-Larkin
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Carlos Cardenas
- Department of Radiation Oncology, University of Alabama at Birmingham, Birmingham, Alabama
| | - Laurence Court
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Zhongxing Liao
- Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Radhe Mohan
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Kristy Brock
- Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
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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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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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Tepetam H, Karabulut Gul S, Alomari O, Caglayan M, Demircioglu O. Does shortening the duration of radiotherapy treatment in breast cancer increase the risk of radiation pneumonia: A retrospective study. Medicine (Baltimore) 2023; 102:e33303. [PMID: 36961146 PMCID: PMC10035996 DOI: 10.1097/md.0000000000033303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Accepted: 02/24/2023] [Indexed: 03/25/2023] Open
Abstract
Randomized studies evaluating hypofractionation and conventional fractionation radiotherapy treatments (RT) in patients with breast cancer have shown that hypofractionation achieves similar results to conventional fractionation in terms of survival and local control rates. It has also been shown that their long-term toxicities are similar. This study aimed to evaluate the effects of hypofractionated radiotherapy (H-RT) and conventional radiotherapy (C-RT) on lung toxicity and identify factors affecting this toxicity in patients with breast cancer. The study included 118 patients who underwent adjuvant RT following breast-conserving surgery (BCS). Out of these, 63 patients were assigned to receive C-RT, while the remaining 55 were assigned to receive H-RT. To clarify, we treated 63 patients with C-RT and 55 patients with H-RT. 60 patients were treated using 3-dimensional conformal radiotherapy (3DCRT) and 58 patients were treated using intensity modulated radiotherapy (IMRT). The patients were evaluated weekly for toxicity during radiotherapy (RT) treatment and were called every 3 months for routine controls after the treatment. The first control was performed 1 month after the treatment. Statistical analysis was performed using the SPSS20 program, and a P value of <.005 was considered statistically significant. The study found that the median age of the participants was 54.9 years and tomographic findings were observed in 70 patients. Radiological findings were detected at a median of 5 months after RT. The mean lung dose (MLD) on the treated breast side (referred to as ipsilateral lung or OAR) was 10.4 Gy for the entire group. Among patients who received 18 MV energy in RT, those with an area volume (V20) of the lung on the treated breast side >18.5%, those with a mean dose of the treated breast side lung (ipsilateral lung) >10.5 Gy, and those who received concurrent hormone therapy had significantly more tomographic findings. However, patients treated with YART had fewer tomographic findings. No symptomatic patients were observed during the follow-up period. Our findings show that the risk of lung toxicity is similar with H-RT and C-RT, and H-RT can be considered an effective and safe treatment option for breast cancer. The key factors affecting the development of lung toxicity were found to be the type of RT energy used, RT to the side breast, volume receiving 20 Gy in the side lung, side lung mean dose, and simultaneous hormonal therapy.
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Affiliation(s)
- Huseyin Tepetam
- Department of Radiation Oncology, Dr. Lutfi Kirdar Kartal Training and Research Hospital, Istanbul, Turkey
| | - Sule Karabulut Gul
- Department of Radiation Oncology, Dr. Lutfi Kirdar Kartal Training and Research Hospital, Istanbul, Turkey
| | - Omar Alomari
- Hamidiye International School of Medicine, University of Health Sciences, Istanbul, Turkey
| | - Merve Caglayan
- Department of Radiation Oncology, Dr. Lutfi Kirdar Kartal Training and Research Hospital, Istanbul, Turkey
| | - Ozlem Demircioglu
- Marmara University Research and Education Hospital, Department of Radiology, Istanbul, Turkey
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Forghani F, Castillo R, Castillo E, PhD BJ, Rusthoven C, Kwak J, Moiseenko V, Grills I, Miften M, Vinogradskiy Y, Guerrero T. Is individual perfusion dose-response different than ventilation dose-response for lung cancer patients treated with radiotherapy? Br J Radiol 2023; 96:20220119. [PMID: 36633096 PMCID: PMC9975372 DOI: 10.1259/bjr.20220119] [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: 01/27/2022] [Revised: 08/18/2022] [Accepted: 11/18/2022] [Indexed: 01/13/2023] Open
Abstract
OBJECTIVE Current ventilation and perfusion dose-response studies focus on single-modalities (ventilation or perfusion) and perform pulmonary-toxicity assessment related to radiotherapy on a population-based basis. This study aims at quantitative and clinical evaluation of intrapatient differences between ventilation and perfusion dose-responses among lung cancer patients treated with radiotherapy. METHODS 20 patients enrolled on a prospective functional avoidance protocol underwent single photon emission computed tomography-CT ventilation and perfusion scans pre- and post-radiotherapy. Relative changes in pre- to post-treatment ventilation and perfusion in lung regions receiving ≥20 Gy were calculated. In addition, the slopes of the linear fit to the relative ventilation and perfusion changes in regions receiving 0-60 Gy were calculated. A radiologist read and assigned a functional defect score to pre- and post-treatment ventilation/perfusion scans. RESULTS 25% of patients had a difference >35% between ventilation and perfusion pre- to post-treatment changes and 20-30% of patients had opposite directions for ventilation and perfusion pre- to post-treatment changes. Using a semi-quantitative scale, radiologist assessment showed that 20% of patients had different pre- to post-treatment ventilation changes when compared to pre- to post-treatment perfusion changes. CONCLUSION Our data showed that ventilation dose-response can differ from perfusion dose-response for 20-30% of patients. Therefore, when performing thoracic dose-response in cancer patients, it is insufficient to look at ventilation or perfusion alone; but rather both modes of functional imaging may be needed when predicting for clinical outcomes. ADVANCES IN KNOWLEDGE The significance of this study can be highlighted by the differences between the intrapatient dose-response assessments of this analysis compared to existing population-based dose-response analyses. Elucidating intrapatient ventilation and perfusion dose-response differences may be valuable in predicting pulmonary toxicity in lung cancer patients post-radiotherapy.
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Affiliation(s)
| | | | - Edward Castillo
- Department of Radiation Oncology, Beaumont Health System, Royal Oak, Michigan, United States
| | - Bernard Jones PhD
- Department of Radiation Oncology, University of Colorado School of Medicine, Aurora, CO
| | - Chad Rusthoven
- Department of Radiation Oncology, University of Colorado School of Medicine, Aurora, CO
| | - Jennifer Kwak
- Department of Radiology, University of Colorado School of Medicine, Aurora, CO
| | - Vitali Moiseenko
- Department of Radiation Medicine and Applies Sciences, University of California San Diego, San Diego, CA
| | - Inga Grills
- Department of Radiation Oncology, Beaumont Health System, Royal Oak, Michigan, United States
| | - Moyed Miften
- Department of Radiation Oncology, University of Colorado School of Medicine, Aurora, CO
| | | | - Thomas Guerrero
- Department of Radiation Oncology, Beaumont Health System, Royal Oak, Michigan, United States
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Patrick HM, Kildea J. Technical note: rtdsm-An open-source software for radiotherapy dose-surface map generation and analysis. Med Phys 2022; 49:7327-7335. [PMID: 35912447 DOI: 10.1002/mp.15900] [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: 03/16/2022] [Revised: 06/07/2022] [Accepted: 07/23/2022] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Dose-outcome studies in radiation oncology have historically excluded spatial information due to dose-volume histograms being the most dominant source of dosimetric information. In recent years, dose-surface maps (DSMs) have become increasingly popular for characterization of spatial dose distributions and identification of radiosensitive subregions for hollow organs. However, methodological variations and lack of open-source, publicly offered code-sharing between research groups have limited reproducibility and wider adoption. PURPOSE This paper presents rtdsm, an open-source software for DSM calculation with the intent to improve the reproducibility of and the access to DSM-based research in medical physics and radiation oncology. METHODS A literature review was conducted to identify essential functionalities and prevailing calculation approaches to guide development. The described software has been designed to calculate DSMs from DICOM data with a high degree of user customizability and to facilitate DSM feature analysis. Core functionalities include DSM calculation, equivalent dose conversions, common DSM feature extraction, and simple DSM accumulation. RESULTS A number of use cases were used to qualitatively and quantitatively demonstrate the use and usefulness of rtdsm. Specifically, two DSM slicing methods, planar and noncoplanar, were implemented and tested, and the effects of method choice on output DSMs were demonstrated. An example comparison of DSMs from two different treatments was used to highlight the use cases of various built-in analysis functions for equivalent dose conversion and DSM feature extraction. CONCLUSIONS We developed and implemented rtdsm as a standalone software that provides all essential functionalities required to perform a DSM-based study. It has been made freely accessible under an open-source license on Github to encourage collaboration and community use.
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Affiliation(s)
- Haley M Patrick
- Medical Physics Unit, McGill University, Montreal, Quebec, Canada.,Cancer Research Program, Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada
| | - John Kildea
- Medical Physics Unit, McGill University, Montreal, Quebec, Canada.,Cancer Research Program, Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada
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Li B, Zheng X, Zhang J, Lam S, Guo W, Wang Y, Cui S, Teng X, Zhang Y, Ma Z, Zhou T, Lou Z, Meng L, Ge H, Cai J. Lung Subregion Partitioning by Incremental Dose Intervals Improves Omics-Based Prediction for Acute Radiation Pneumonitis in Non-Small-Cell Lung Cancer Patients. Cancers (Basel) 2022; 14:cancers14194889. [PMID: 36230812 PMCID: PMC9564373 DOI: 10.3390/cancers14194889] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Revised: 09/19/2022] [Accepted: 09/27/2022] [Indexed: 11/16/2022] Open
Abstract
Purpose: To evaluate the effectiveness of features obtained from our proposed incremental-dose-interval-based lung subregion segmentation (IDLSS) for predicting grade ≥ 2 acute radiation pneumonitis (ARP) in lung cancer patients upon intensity-modulated radiotherapy (IMRT). (1) Materials and Methods: A total of 126 non-small-cell lung cancer patients treated with IMRT were retrospectively analyzed. Five lung subregions (SRs) were generated by the intersection of the whole lung (WL) and five sub-regions receiving incremental dose intervals. A total of 4610 radiomics features (RF) from pre-treatment planning computed tomographic (CT) and 213 dosiomics features (DF) were extracted. Six feature groups, including WL-RF, WL-DF, SR-RF, SR-DF, and the combined feature sets of WL-RDF and SR-RDF, were generated. Features were selected by using a variance threshold, followed by a Student t-test. Pearson’s correlation test was applied to remove redundant features. Subsequently, Ridge regression was adopted to develop six models for ARP using the six feature groups. Thirty iterations of resampling were implemented to assess overall model performance by using the area under the Receiver-Operating-Characteristic curve (AUC), accuracy, precision, recall, and F1-score. (2) Results: The SR-RDF model achieved the best classification performance and provided significantly better predictability than the WL-RDF model in training cohort (Average AUC: 0.98 ± 0.01 vs. 0.90 ± 0.02, p < 0.001) and testing cohort (Average AUC: 0.88 ± 0.05 vs. 0.80 ± 0.04, p < 0.001). Similarly, predictability of the SR-DF model was significantly stronger than that of the WL-DF model in training cohort (Average AUC: 0.88 ± 0.03 vs. 0.70 ± 0.030, p < 0.001) and in testing cohort (Average AUC: 0.74 ± 0.08 vs. 0.65 ± 0.06, p < 0.001). By contrast, the SR-RF model significantly outperformed the WL-RF model only in the training set (Average AUC: 0.93 ± 0.02 vs. 0.85 ± 0.03, p < 0.001), but not in the testing set (Average AUC: 0.79 ± 0.05 vs. 0.77 ± 0.07, p = 0.13). (3) Conclusions: Our results demonstrated that the IDLSS method improved model performance for classifying ARP with grade ≥ 2 when using dosiomics or combined radiomics-dosiomics features.
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Affiliation(s)
- Bing Li
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China
- Department of Radiation Oncology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou 450008, China
| | - Xiaoli Zheng
- Department of Radiation Oncology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou 450008, China
| | - Jiang Zhang
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China
| | - Saikit Lam
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China
| | - Wei Guo
- Department of Radiation Oncology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou 450008, China
| | - Yunhan Wang
- Department of Radiation Oncology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou 450008, China
| | - Sunan Cui
- Department of Radiation Oncology, Stanford University School of Medicine, Palo Alto, Stanford, CA 94305, USA
| | - Xinzhi Teng
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China
| | - Yuanpeng Zhang
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China
| | - Zongrui Ma
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China
| | - Ta Zhou
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China
| | - Zhaoyang Lou
- Department of Radiation Oncology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou 450008, China
| | - Lingguang Meng
- Department of Radiation Oncology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou 450008, China
| | - Hong Ge
- Department of Radiation Oncology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou 450008, China
- Correspondence: (H.G.); (J.C.); Tel.: +852-3400-8645 (J.C.)
| | - Jing Cai
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China
- Correspondence: (H.G.); (J.C.); Tel.: +852-3400-8645 (J.C.)
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8
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Zhou C, Yu J. Chinese expert consensus on diagnosis and treatment of radiation pneumonitis. PRECISION RADIATION ONCOLOGY 2022. [DOI: 10.1002/pro6.1169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Affiliation(s)
- Caicun Zhou
- Thoracic Oncology Branch of China International Exchange and Promotive Association for Medical and Health Care Shanghai China
| | - Jinming Yu
- Chinese Radiation Therapy Oncology Group Shandong China
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Thomas HMT, Hippe DS, Forouzannezhad P, Sasidharan BK, Kinahan PE, Miyaoka RS, Vesselle HJ, Rengan R, Zeng J, Bowen SR. Radiation and immune checkpoint inhibitor-mediated pneumonitis risk stratification in patients with locally advanced non-small cell lung cancer: role of functional lung radiomics? Discov Oncol 2022; 13:85. [PMID: 36048266 PMCID: PMC9437196 DOI: 10.1007/s12672-022-00548-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Accepted: 08/23/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND Patients undergoing chemoradiation and immune checkpoint inhibitor (ICI) therapy for locally advanced non-small cell lung cancer (NSCLC) experience pulmonary toxicity at higher rates than historical reports. Identifying biomarkers beyond conventional clinical factors and radiation dosimetry is especially relevant in the modern cancer immunotherapy era. We investigated the role of novel functional lung radiomics, relative to functional lung dosimetry and clinical characteristics, for pneumonitis risk stratification in locally advanced NSCLC. METHODS Patients with locally advanced NSCLC were prospectively enrolled on the FLARE-RT trial (NCT02773238). All received concurrent chemoradiation using functional lung avoidance planning, while approximately half received consolidation durvalumab ICI. Within tumour-subtracted lung regions, 110 radiomics features (size, shape, intensity, texture) were extracted on pre-treatment [99mTc]MAA SPECT/CT perfusion images using fixed-bin-width discretization. The performance of functional lung radiomics for pneumonitis (CTCAE v4 grade 2 or higher) risk stratification was benchmarked against previously reported lung dosimetric parameters and clinical risk factors. Multivariate least absolute shrinkage and selection operator Cox models of time-varying pneumonitis risk were constructed, and prediction performance was evaluated using optimism-adjusted concordance index (c-index) with 95% confidence interval reporting throughout. RESULTS Thirty-nine patients were included in the study and pneumonitis occurred in 16/39 (41%) patients. Among clinical characteristics and anatomic/functional lung dosimetry variables, only the presence of baseline chronic obstructive pulmonary disease (COPD) was significantly associated with the development of pneumonitis (HR 4.59 [1.69-12.49]) and served as the primary prediction benchmark model (c-index 0.69 [0.59-0.80]). Discrimination of time-varying pneumonitis risk was numerically higher when combining COPD with perfused lung radiomics size (c-index 0.77 [0.65-0.88]) or shape feature classes (c-index 0.79 [0.66-0.91]) but did not reach statistical significance compared to benchmark models (p > 0.26). COPD was associated with perfused lung radiomics size features, including patients with larger lung volumes (AUC 0.75 [0.59-0.91]). Perfused lung radiomic texture features were correlated with lung volume (adj R2 = 0.84-1.00), representing surrogates rather than independent predictors of pneumonitis risk. CONCLUSIONS In patients undergoing chemoradiation with functional lung avoidance therapy and optional consolidative immune checkpoint inhibitor therapy for locally advanced NSCLC, the strongest predictor of pneumonitis was the presence of baseline chronic obstructive pulmonary disease. Results from this novel functional lung radiomics exploratory study can inform future validation studies to refine pneumonitis risk models following combinations of radiation and immunotherapy. Our results support functional lung radiomics as surrogates of COPD for non-invasive monitoring during and after treatment. Further study of clinical, dosimetric, and radiomic feature combinations for radiation and immune-mediated pneumonitis risk stratification in a larger patient population is warranted.
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Affiliation(s)
- Hannah M T Thomas
- Department of Radiation Oncology, University of Washington School of Medicine, 1959 NE Pacific St, Box 356043, Seattle, WA, 98195, USA
- Department of Radiation Oncology, Christian Medical College Vellore, Vellore, Tamil Nadu, India
| | - Daniel S Hippe
- Clinical Research Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Parisa Forouzannezhad
- Department of Radiation Oncology, University of Washington School of Medicine, 1959 NE Pacific St, Box 356043, Seattle, WA, 98195, USA
| | - Balu Krishna Sasidharan
- Department of Radiation Oncology, Christian Medical College Vellore, Vellore, Tamil Nadu, India
| | - Paul E Kinahan
- Department of Radiology, University of Washington School of Medicine, Seattle, WA, USA
| | - Robert S Miyaoka
- Department of Radiology, University of Washington School of Medicine, Seattle, WA, USA
| | - Hubert J Vesselle
- Department of Radiology, University of Washington School of Medicine, Seattle, WA, USA
| | - Ramesh Rengan
- Department of Radiation Oncology, University of Washington School of Medicine, 1959 NE Pacific St, Box 356043, Seattle, WA, 98195, USA
| | - Jing Zeng
- Department of Radiation Oncology, University of Washington School of Medicine, 1959 NE Pacific St, Box 356043, Seattle, WA, 98195, USA
| | - Stephen R Bowen
- Department of Radiation Oncology, University of Washington School of Medicine, 1959 NE Pacific St, Box 356043, Seattle, WA, 98195, USA.
- Department of Radiology, University of Washington School of Medicine, Seattle, WA, USA.
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10
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Abdollahi H, Chin E, Clark H, Hyde DE, Thomas S, Wu J, Uribe CF, Rahmim A. Radiomics-guided radiation therapy: opportunities and challenges. Phys Med Biol 2022; 67. [DOI: 10.1088/1361-6560/ac6fab] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Accepted: 05/13/2022] [Indexed: 11/11/2022]
Abstract
Abstract
Radiomics is an advanced image-processing framework, which extracts image features and considers them as biomarkers towards personalized medicine. Applications include disease detection, diagnosis, prognosis, and therapy response assessment/prediction. As radiation therapy aims for further individualized treatments, radiomics could play a critical role in various steps before, during and after treatment. Elucidation of the concept of radiomics-guided radiation therapy (RGRT) is the aim of this review, attempting to highlight opportunities and challenges underlying the use of radiomics to guide clinicians and physicists towards more effective radiation treatments. This work identifies the value of RGRT in various steps of radiotherapy from patient selection to follow-up, and subsequently provides recommendations to improve future radiotherapy using quantitative imaging features.
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11
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YANG X, MEI T, YU M, GONG Y. Symptomatic Radiation Pneumonitis in NSCLC Patients Receiving EGFR-TKIs and Concurrent Once-daily Thoracic Radiotherapy: Predicting the Value of Clinical and Dose-volume Histogram Parameters. ZHONGGUO FEI AI ZA ZHI = CHINESE JOURNAL OF LUNG CANCER 2022; 25:409-419. [PMID: 35747920 PMCID: PMC9244499 DOI: 10.3779/j.issn.1009-3419.2022.102.17] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND The incidence of symptomatic radiation pneumonitis (RP) and its relationship with dose-volume histogram (DVH) parameters in non-small cell lung cancer (NSCLC) patients receiving epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) and concurrent once-daily thoracic radiotherapy (TRT) remain unclear. We aim to analyze the values of clinical factors and dose-volume histogram (DVH) parameters to predict the risk for symptomatic RP in these patients. METHODS Between 2011 and 2019, we retrospectively analyzed and identified 85 patients who had received EGFR-TKIs and once-daily TRT simultaneously (EGFR-TKIs group) and 129 patients who had received concurrent chemoradiotherapy (CCRT group). The symptomatic RP was recorded according to the Common Terminology Criteria for Adverse Event (CTCAE) criteria (grade 2 or above). Statistical analyses were performed using SPSS 26.0. RESULTS In total, the incidences of symptomatic (grade≥2) and severe RP (grade≥3) were 43.5% (37/85) and 16.5% (14/85) in EGFR-TKIs group vs 27.1% (35/129) and 10.1% (13/129) in CCRT group respectively. After 1:1 ratio between EGFR-TKIs group and CCRT group was matched by propensity score matching, chi-square test suggested that the incidence of symptomatic RP in the MATCHED EGFR-TKIs group was higher than that in the matched CCRT group (χ2=4.469, P=0.035). In EGFR-TKIs group, univariate and multivariate analyses indicated that the percentage of ipsilateral lung volume receiving ≥30 Gy (ilV30) [odds ratio (OR): 1.163, 95%CI: 1.036-1.306, P=0.011] and the percentage of total lung volume receiving ≥20 Gy (tlV20) (OR: 1.171, 95%CI: 1.031-1.330, P=0.015), with chronic obstructive pulmonary disease (COPD) or not (OR: 0.158, 95%CI: 0.041-0.600, P=0.007), were independent predictors of symptomatic RP. Compared to patients with lower ilV30/tlV20 values (ilV30 and tlV20<cut-off point values) and without COPD, patients with higher ilV30/tlV20 values (ilV30 and tlV20>cut-off point values) and COPD had a significantly higher risk for developing symptomatic RP, with a hazard ratio (HR) of 1.350 (95%CI: 1.190-1.531, P<0.001). CONCLUSIONS Patients receiving both EGFR-TKIs and once-daily TRT were more likely to develop symptomatic RP than patients receiving concurrent chemoradiotherapy. The ilV30, tlV20, and comorbidity of COPD may predict the risk of symptomatic RP among NSCLC patients receiving EGFR-TKIs and conventionally fractionated TRT concurrently.
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Affiliation(s)
- Xuexi YANG
- Department of Thoracic Oncology and State Key Laboratory of Biotherapy, Cancer Center, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Ting MEI
- Department of Thoracic Oncology and State Key Laboratory of Biotherapy, Cancer Center, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Min YU
- Department of Thoracic Oncology and State Key Laboratory of Biotherapy, Cancer Center, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Youling GONG
- Department of Thoracic Oncology and State Key Laboratory of Biotherapy, Cancer Center, West China Hospital, Sichuan University, Chengdu 610041, China,Youling GONG, E-mail:
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12
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Vicente EM, Modiri A, Kipritidis J, Yu KC, Sun K, Cammin J, Gopal A, Xu J, Mossahebi S, Hagan A, Yan Y, Owen DR, Mohindra P, Matuszak MM, Timmerman RD, Sawant A. Combining Serial and Parallel Functionality in Functional Lung Avoidance Radiation Therapy. Int J Radiat Oncol Biol Phys 2022; 113:456-468. [PMID: 35279324 DOI: 10.1016/j.ijrobp.2022.01.046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 01/10/2022] [Accepted: 01/26/2022] [Indexed: 10/18/2022]
Abstract
PURPOSE Functional lung avoidance (FLA) radiation therapy (RT) aims to minimize post-RT pulmonary toxicity by preferentially avoiding dose to high-functioning lung (HFL) regions. A common limitation is that FLA approaches do not consider the conducting architecture for gas exchange. We previously proposed the functionally weighted airway sparing (FWAS) method to spare airways connected to HFL regions, showing that it is possible to substantially reduce risk of radiation-induced airway injury. Here, we compare the performance of FLA and FWAS and propose a novel method combining both approaches. METHODS We used breath-hold computed tomography (BHCT) and simulation 4-dimensional computed tomography (4DCT) from 12 lung stereotactic ablative radiation therapy patients. Four planning strategies were examined: (1) Conventional: no sparing other than clinical dose-volume constraints; (2) FLA: using a 4DCT-based ventilation map to delineate the HFL, plans were optimized to reduce mean dose and V13.50 in HFL; (3) FWAS: we autosegemented 11 to 13 generations of individual airways from each patient's BHCT and assigned priorities based on the relative contribution of each airway to total ventilation. We used these priorities in the optimization along with airway dose constraints, estimated as a function of airway diameter and 5% probability of collapse; and (4) FLA + FWAS: we combined information from the 2 strategies. We prioritized clinical dose constraints for organs at risk and planning target volume in all plans. We performed the evaluation in terms of ventilation preservation accounting for radiation-induced damage to both lung parenchyma and airways. RESULTS We observed average ventilation preservation for FLA, FWAS, and FLA + FWAS as 3%, 8.5%, and 14.5% higher, respectively, than for Conventional plans for patients with ventilation preservation in Conventional plans <90%. Generalized estimated equations showed that all improvements were statistically significant (P ≤ .036). We observed no clinically relevant improvements in outcomes of the sparing techniques in patients with ventilation preservation in Conventional plans ≥90%. CONCLUSIONS These initial results suggest that it is crucial to consider the parallel and the serial nature of the lung to improve post-radiation therapy lung function and, consequently, quality of life for patients.
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Affiliation(s)
| | - Arezoo Modiri
- University of Maryland School of Medicine, Baltimore, Maryland
| | | | | | - Kai Sun
- University of Maryland School of Medicine, Baltimore, Maryland
| | - Jochen Cammin
- University of Maryland School of Medicine, Baltimore, Maryland
| | - Arun Gopal
- University of Maryland School of Medicine, Baltimore, Maryland
| | - Jingzhu Xu
- University of Maryland School of Medicine, Baltimore, Maryland
| | - Sina Mossahebi
- University of Maryland School of Medicine, Baltimore, Maryland
| | - Aaron Hagan
- University of Maryland School of Medicine, Baltimore, Maryland
| | - Yulong Yan
- UT Southwestern Medical Center, Dallas, Texas
| | | | | | | | | | - Amit Sawant
- University of Maryland School of Medicine, Baltimore, Maryland
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Matsuo Y, Hiraoka M, Karasawa K, Kokubo M, Sakamoto T, Mukumoto N, Nakamura M, Morita S, Mizowaki T. Multi-institutional phase II study on the safety and efficacy of dynamic tumor tracking-stereotactic body radiotherapy for lung tumors. Radiother Oncol 2022; 172:18-22. [PMID: 35513131 DOI: 10.1016/j.radonc.2022.04.028] [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: 03/12/2022] [Revised: 04/26/2022] [Accepted: 04/27/2022] [Indexed: 10/18/2022]
Abstract
BACKGROUND AND PURPOSE This study aimed to evaluate the safety and efficacy of dynamic tumor tracking-stereotactic body radiotherapy (DTT-SBRT) for lung tumors. MATERIALS AND METHODS Patients with cStage I primary lung cancer or metastatic lung cancer with an expected range of respiratory motion of ≥10 mm were eligible for the study. The prescribed dose was 50 Gy in four fractions. A gimbal-mounted linac was used for DTT-SBRT delivery. The primary endpoint was local control at 2 years. RESULTS Forty-eight patients from four institutions were enrolled in this study. Forty-two patients had primary non-small-cell lung cancer, and six had metastatic lung tumors. DTT-SBRT was delivered for 47 lesions in 47 patients with a median treatment time of 28 min per fraction. The median respiratory motion during the treatment was 13.7 mm (range: 4.5-28.1 mm). The motion-encompassing method was applied for the one remaining patient due to the poor correlation between the abdominal wall and tumor movement. The median follow-up period was 32.3 months, and the local control at 2 years was 95.2% (lower limit of the one-sided 85% confidence interval [CI]: 90.3%). The overall survival and progression-free survival at 2 years were 79.2% (95% CI: 64.7%-88.2%) and 75.0% (95% CI: 60.2%-85.0%), respectively. Grade 3 toxicity was observed in one patient (2.1%) with radiation pneumonitis. Grade 4 or 5 toxicity was not observed. CONCLUSION DTT-SBRT achieved excellent local control with low incidences of severe toxicities in lung tumors with respiratory motion.
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Affiliation(s)
- Yukinori Matsuo
- Department of Radiation Oncology and Image-Applied Therapy, Kyoto University Graduate School of Medicine, Kyoto, Japan.
| | - Masahiro Hiraoka
- Department of Radiation Oncology, Japanese Red Cross Wakayama Medical Center, Wakayama, Japan
| | - Katsuyuki Karasawa
- Division of Radiation Oncology, Department of Radiology, Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome Hospital, Tokyo, Japan
| | - Masaki Kokubo
- Department of Radiation Oncology, Kobe City Medical Center General Hospital, Kobe, Japan
| | - Takashi Sakamoto
- Department of Radiation Oncology, Kyoto Katsura Hospital, Kyoto, Japan
| | - Nobutaka Mukumoto
- Department of Radiation Oncology and Image-Applied Therapy, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Mitsuhiro Nakamura
- Division of Medical Physics, Department of Information Technology and Medical Engineering, Human Health Sciences, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Satoshi Morita
- Department of Biomedical Statistics and Bioinformatics, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Takashi Mizowaki
- Department of Radiation Oncology and Image-Applied Therapy, Kyoto University Graduate School of Medicine, Kyoto, Japan
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Yaremko BP, Capaldi DP, Sheikh K, Palma DA, Warner A, Dar AR, Yu E, Rodrigues GB, Louie AV, Landis M, Sanatani M, Vincent MD, Younus J, Kuruvilla S, Chen JZ, Erickson A, Gaede S, Parraga G, Hoover DA. Functional Lung Avoidance for Individualized Radiotherapy (FLAIR): Results of a Double-Blind, Randomized Controlled Trial. Int J Radiat Oncol Biol Phys 2022; 113:1072-1084. [DOI: 10.1016/j.ijrobp.2022.04.047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 04/29/2022] [Accepted: 04/30/2022] [Indexed: 10/18/2022]
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Palma G, Monti S, Pacelli R, Liao Z, Deasy JO, Mohan R, Cella L. Radiation Pneumonitis in Thoracic Cancer Patients: Multi-Center Voxel-Based Analysis. Cancers (Basel) 2021; 13:cancers13143553. [PMID: 34298767 PMCID: PMC8306650 DOI: 10.3390/cancers13143553] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 07/07/2021] [Accepted: 07/14/2021] [Indexed: 12/12/2022] Open
Abstract
Simple Summary The pathophysiology of radiation pneumonitis (RP) after thoracic cancer radiation treatments is still not completely understood although the identification of underlying RP mechanisms may improve the therapeutic window of thoracic cancer patients. The aim of our retrospective study was to explore the dose–response patterns associated with RP by a multi-center voxel-based analysis. In a heterogeneously treated population of 382 thoracic cancer patients, we confirmed the previously described heart–lung interaction in the development of RP. The empowerment of VBA with a novel description of dose map spatial properties based on probabilistic independent component analysis (PICA) and connectograms provided valuable additional and independent information on the radiobiology of RP. Abstract This study investigates the dose–response patterns associated with radiation pneumonitis (RP) in patients treated for thoracic malignancies with different radiation modalities. To this end, voxel-based analysis (VBA) empowered by a novel strategy for the characterization of spatial properties of dose maps was applied. Data from 382 lung cancer and mediastinal lymphoma patients from three institutions treated with different radiation therapy (RT) techniques were analyzed. Each planning CT and biologically effective dose map (α/β = 3 Gy) was spatially normalized on a common anatomical reference. The VBA of local dose differences between patients with and without RP was performed and the clusters of voxels with dose differences that significantly correlated with RP at a p-level of 0.05 were generated accordingly. The robustness of VBA inference was evaluated by a novel characterization for spatial properties of dose maps based on probabilistic independent component analysis (PICA) and connectograms. This lays robust foundations to the obtained findings that the lower parts of the lungs and the heart play a prominent role in the development of RP. Connectograms showed that the dataset can support a radiobiological differentiation between the main heart and lung substructures.
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Affiliation(s)
- Giuseppe Palma
- Institute of Biostructures and Bioimaging, National Research Council, 80145 Napoli, Italy;
- Correspondence: (G.P.); (L.C.)
| | - Serena Monti
- Institute of Biostructures and Bioimaging, National Research Council, 80145 Napoli, Italy;
| | - Roberto Pacelli
- Department of Advanced Biomedical Sciences, University of Naples “Federico II”, 80131 Napoli, Italy;
| | - Zhongxing Liao
- Department of Radiation Oncology, MD Anderson Cancer Center, Houston, TX 77030, USA;
| | - Joseph O. Deasy
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA;
| | - Radhe Mohan
- Department of Radiation Physics, MD Anderson Cancer Center, Houston, TX 77030, USA;
| | - Laura Cella
- Institute of Biostructures and Bioimaging, National Research Council, 80145 Napoli, Italy;
- Correspondence: (G.P.); (L.C.)
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Cui S, Ten Haken RK, El Naqa I. Integrating Multiomics Information in Deep Learning Architectures for Joint Actuarial Outcome Prediction in Non-Small Cell Lung Cancer Patients After Radiation Therapy. Int J Radiat Oncol Biol Phys 2021; 110:893-904. [PMID: 33539966 DOI: 10.1016/j.ijrobp.2021.01.042] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Revised: 11/10/2020] [Accepted: 01/23/2021] [Indexed: 12/14/2022]
Abstract
PURPOSE Novel actuarial deep learning neural network (ADNN) architectures are proposed for joint prediction of radiation therapy outcomes-radiation pneumonitis (RP) and local control (LC)-in stage III non-small cell lung cancer (NSCLC) patients. Unlike normal tissue complication probability/tumor control probability models that use dosimetric information solely, our proposed models consider complex interactions among multiomics information including positron emission tomography (PET) radiomics, cytokines, and miRNAs. Additional time-to-event information is also used in the actuarial prediction. METHODS AND MATERIALS Three architectures were investigated: ADNN-DVH considered dosimetric information only; ADNN-com integrated multiomics information; and ADNN-com-joint combined RP2 (RP grade ≥2) and LC prediction. In these architectures, differential dose-volume histograms (DVHs) were fed into 1D convolutional neural networks (CNN) for extracting reduced representations. Variational encoders were used to learn representations of imaging and biological data. Reduced representations were fed into Surv-Nets to predict time-to-event probabilities for RP2 and LC independently and jointly by incorporating time information into designated loss functions. RESULTS Models were evaluated on 117 retrospective patients and were independently tested on 25 newly accrued patients prospectively. A multi-institutional RTOG0617 data set of 327 patients was used for external validation. ADNN-DVH yielded cross-validated c-indexes (95% confidence intervals) of 0.660 (0.630-0.690) for RP2 prediction and 0.727 (0.700-0.753) for LC prediction, outperforming a generalized Lyman model for RP2 (0.613 [0.583-0.643]) and a generalized log-logistic model for LC (0.569 [0.545-0.594]). The independent internal test and external validation yielded similar results. ADNN-com achieved an even better performance than ADNN-DVH on both cross-validation and independent internal test. Furthermore, ADNN-com-joint, which yielded performance similar to ADNN-com, realized joint prediction with c-indexes of 0.705 (0.676-0.734) for RP2 and 0.740 (0.714-0.765) for LC and achieved an area under a free-response receiving operator characteristic curve (AU-FROC) of 0.729 (0.697-0.773) for the joint prediction of RP2 and LC. CONCLUSION Novel deep learning architectures that integrate multiomics information outperformed traditional normal tissue complication probability/tumor control probability models in actuarial prediction of RP2 and LC.
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Affiliation(s)
- Sunan Cui
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan; Applied Physics Program, University of Michigan, Ann Arbor, Michigan.
| | - Randall K Ten Haken
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Issam El Naqa
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
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Ebert MA, Gulliford S, Acosta O, de Crevoisier R, McNutt T, Heemsbergen WD, Witte M, Palma G, Rancati T, Fiorino C. Spatial descriptions of radiotherapy dose: normal tissue complication models and statistical associations. Phys Med Biol 2021; 66:12TR01. [PMID: 34049304 DOI: 10.1088/1361-6560/ac0681] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Accepted: 05/28/2021] [Indexed: 12/20/2022]
Abstract
For decades, dose-volume information for segmented anatomy has provided the essential data for correlating radiotherapy dosimetry with treatment-induced complications. Dose-volume information has formed the basis for modelling those associations via normal tissue complication probability (NTCP) models and for driving treatment planning. Limitations to this approach have been identified. Many studies have emerged demonstrating that the incorporation of information describing the spatial nature of the dose distribution, and potentially its correlation with anatomy, can provide more robust associations with toxicity and seed more general NTCP models. Such approaches are culminating in the application of computationally intensive processes such as machine learning and the application of neural networks. The opportunities these approaches have for individualising treatment, predicting toxicity and expanding the solution space for radiation therapy are substantial and have clearly widespread and disruptive potential. Impediments to reaching that potential include issues associated with data collection, model generalisation and validation. This review examines the role of spatial models of complication and summarises relevant published studies. Sources of data for these studies, appropriate statistical methodology frameworks for processing spatial dose information and extracting relevant features are described. Spatial complication modelling is consolidated as a pathway to guiding future developments towards effective, complication-free radiotherapy treatment.
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Affiliation(s)
- Martin A Ebert
- School of Physics, Mathematics and Computing, University of Western Australia, Crawley, Western Australia, Australia
- Department of Radiation Oncology, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
- 5D Clinics, Claremont, Western Australia, Australia
| | - Sarah Gulliford
- Department of Radiotherapy Physics, University College Hospitals London, United Kingdom
- Department of Medical Physics and Bioengineering, University College London, United Kingdom
| | - Oscar Acosta
- Univ Rennes, CLCC Eugène Marquis, INSERM, LTSI-UMR 1099, F-35000 Rennes, France
| | | | - Todd McNutt
- Johns Hopkins University, Baltimore, Maryland, United States of America
| | | | - Marnix Witte
- The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Giuseppe Palma
- Institute of Biostructures and Bioimaging, National Research Council, Napoli, Italy
| | - Tiziana Rancati
- Prostate Cancer Program, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Claudio Fiorino
- Medical Physics, San Raffaele Scientific Institute, Milano, Italy
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Cella L, Monti S, Xu T, Liuzzi R, Stanzione A, Durante M, Mohan R, Liao Z, Palma G. Probing thoracic dose patterns associated to pericardial effusion and mortality in patients treated with photons and protons for locally advanced non-small-cell lung cancer. Radiother Oncol 2021; 160:148-158. [PMID: 33979653 DOI: 10.1016/j.radonc.2021.04.025] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Revised: 03/26/2021] [Accepted: 04/29/2021] [Indexed: 12/25/2022]
Abstract
PURPOSE To investigate thoracic dose-response patterns for pericardial effusion (PCE) and mortality in patients treated for locally advanced Non-Small-Cell Lung Cancer (NSCLC) by Intensity Modulated RT (IMRT) or Passive-Scattering Proton Therapy (PSPT). METHODS Among 178 patients, 43.5% developed grade ≥ 2 PCE. Clinical and dosimetric factors associated with PCE or overall survival (OS) were identified via multi-variable Cox proportional hazards modeling. The Voxel-Based Analyses (VBAs) of local dose differences between patients with and without PCE and mortality was performed. The robustness of VBA results was assessed by a novel characterization of spatial properties of dose distributions based on probabilistic independent component analysis (PICA) and connectograms. RESULTS Several non-dosimetric variables were selected by the multivariable analysis for the considered outcomes, while the time-dependent PCE onset was uncorrelated with the OS (p = 0.34) at a multi-variable Cox analysis. Despite the significant PSPT dosimetric advantage, the RT technique did not affect the occurrence of PCE or OS. VBAs highlighted largely overlapping clusters significantly associated with PCE endpoints in heart and lungs. No significant dosimetric patterns related to mortality endpoints were found. PICA identified 43 components homogeneously scattered within thorax, while connectograms showed modest correlations between doses in main cardio-pulmonary substructures. CONCLUSIONS Spatially resolved analysis highlighted dose patterns related to radiation-induced cardiac toxiciy and the observed organ-based dose-response mismatch in PSPT and IMRT. Indeed, the thoracic regions spared by PSPT poorly overlapped with the areas involved in PCE development, as highlited by VBA. PICA and connectograms proved valuable tools for assessing the robusteness of obtained VBA inferences.
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Affiliation(s)
- Laura Cella
- National Research Council, Institute of Biostructures and Bioimaging, Napoli, Italy.
| | - Serena Monti
- National Research Council, Institute of Biostructures and Bioimaging, Napoli, Italy
| | - Ting Xu
- MD Anderson Cancer Center, Department of Radiation Oncology, Houston, USA
| | - Raffaele Liuzzi
- National Research Council, Institute of Biostructures and Bioimaging, Napoli, Italy
| | - Arnaldo Stanzione
- Department of Advanced Biomedical Sciences, Federico II University School of Medicine, Napoli, Italy
| | - Marco Durante
- GSI Helmholtz Centre for Heavy Ion Research, Department of Biophysics, Darmstadt, Germany
| | - Radhe Mohan
- MD Anderson Cancer Center, Department of Radiation Physics, Houston, USA
| | - Zhongxing Liao
- MD Anderson Cancer Center, Department of Radiation Oncology, Houston, USA
| | - Giuseppe Palma
- National Research Council, Institute of Biostructures and Bioimaging, Napoli, Italy.
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Wang L, Gao Z, Li C, Sun L, Li J, Yu J, Meng X. Computed Tomography-Based Delta-Radiomics Analysis for Discriminating Radiation Pneumonitis in Patients With Esophageal Cancer After Radiation Therapy. Int J Radiat Oncol Biol Phys 2021; 111:443-455. [PMID: 33974887 DOI: 10.1016/j.ijrobp.2021.04.047] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2020] [Revised: 04/24/2021] [Accepted: 04/28/2021] [Indexed: 12/24/2022]
Abstract
PURPOSE Our purpose was to construct a computed tomography (CT)-based delta-radiomics nomogram and corresponding risk classification system for individualized and accurate estimation of severe acute radiation pneumonitis (SARP) in patients with esophageal cancer (EC) after radiation therapy. METHODS AND MATERIALS Four hundred patients with EC were enrolled from 2 independent institutions and were divided into the training (n = 200) and validation (n = 200) cohorts. Eight hundred fifty radiomics features of lung were extracted from treatment planning images, including the positioning CT before radiation therapy (CT1) and the resetting CT after receiving 40 to 45 Gy (CT2). The longitudinal net changes in radiomics features from CT1 to CT2 were calculated and defined as delta-radiomics features. Least absolute shrinkage and selection operator algorithm was performed to features selection and delta-radiomics signature building. Integrating the signature with multidimensional clinicopathologic, dosimetric, and hematological predictors of SARP, a novel CT-based delta-radiomics nomogram was established according to multivariate analysis. The clinical application values of nomogram were both evaluated in the training and validation cohorts by concordance index, calibration curves, and decision curve analysis. Recursive partitioning analysis was used to generate a risk classification system. RESULTS The delta-radiomics signature consisting of 24 features was significantly associated with SARP status (P < .001). Incorporating it with other high-risk factors, Subjective Global Assessment score, pulmonary fibrosis score, mean lung dose, and systemic immune inflammation index, the developed delta-radiomics nomogram showed increased improvement in SARP discrimination accuracy with concordance index of 0.975 and 0.921 in the training and validation cohorts, respectively. Calibration curves and decision curve analysis confirmed the satisfactory clinical feasibility and utility of nomogram. The risk classification system displayed excellent performance on identifying SARP occurrence (P < .001). CONCLUSIONS The delta-radiomics nomogram and risk classification system as low-cost and noninvasive means exhibited superior predictive accuracy and provided individualized probability of SARP stratification for patients with EC.
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Affiliation(s)
- Lu Wang
- Cheeloo College of Medicine, Shandong University, Jinan, China; Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Zhenhua Gao
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Chengming Li
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Liangchao Sun
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Jianing Li
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Jinming Yu
- Cheeloo College of Medicine, Shandong University, Jinan, China; Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Xue Meng
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.
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Paganetti H, Beltran C, Both S, Dong L, Flanz J, Furutani K, Grassberger C, Grosshans DR, Knopf AC, Langendijk JA, Nystrom H, Parodi K, Raaymakers BW, Richter C, Sawakuchi GO, Schippers M, Shaitelman SF, Teo BKK, Unkelbach J, Wohlfahrt P, Lomax T. Roadmap: proton therapy physics and biology. Phys Med Biol 2021; 66. [DOI: 10.1088/1361-6560/abcd16] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Accepted: 11/23/2020] [Indexed: 12/12/2022]
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21
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Owen DR, Sun Y, Boonstra PS, McFarlane M, Viglianti BL, Balter JM, El Naqa I, Schipper MJ, Schonewolf CA, Ten Haken RK, Kong FMS, Jolly S, Matuszak MM. Investigating the SPECT Dose-Function Metrics Associated With Radiation-Induced Lung Toxicity Risk in Patients With Non-small Cell Lung Cancer Undergoing Radiation Therapy. Adv Radiat Oncol 2021; 6:100666. [PMID: 33817412 PMCID: PMC8010578 DOI: 10.1016/j.adro.2021.100666] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Accepted: 01/22/2021] [Indexed: 12/14/2022] Open
Abstract
Purpose Dose to normal lung has commonly been linked with radiation-induced lung toxicity (RILT) risk, but incorporating functional lung metrics in treatment planning may help further optimize dose delivery and reduce RILT incidence. The purpose of this study was to investigate the impact of the dose delivered to functional lung regions by analyzing perfusion (Q), ventilation (V), and combined V/Q single-photon-emission computed tomography (SPECT) dose-function metrics with regard to RILT risk in patients with non-small cell lung cancer (NSCLC) patients who received radiation therapy (RT). Methods and Materials SPECT images acquired from 88 patients with locally advanced NSCLC before undergoing conventionally fractionated RT were retrospectively analyzed. Dose was converted to the nominal dose equivalent per 2 Gy fraction, and SPECT intensities were normalized. Regional lung segments were defined, and the average dose delivered to each lung region was quantified. Three functional categorizations were defined to represent low-, normal-, and high-functioning lungs. The percent of functional lung category receiving ≥20 Gy and mean functional intensity receiving ≥20 Gy (iV20) were calculated. RILT was defined as grade 2+ radiation pneumonitis and/or clinical radiation fibrosis. A logistic regression was used to evaluate the association between dose-function metrics and risk of RILT. Results By analyzing V/Q normalized intensities and functional distributions across the population, a wide range in functional capability (especially in the ipsilateral lung) was observed in patients with NSCLC before RT. Through multivariable regression models, global lung average dose to the lower lung was found to be significantly associated with RILT, and Q and V iV20 were correlated with RILT when using ipsilateral lung metrics. Through a receiver operating characteristic analysis, combined V/Q low-function receiving ≥20 Gy (low-functioning V/Q20) in the ipsilateral lung was found to be the best predictor (area under the curce: 0.79) of RILT risk. Conclusions Irradiation of the inferior lung appears to be a locational sensitivity for RILT risk. The multivariable correlation between ipsilateral lung iV20 and RILT, as well as the association of low-functioning V/Q20 and RILT, suggest that irradiating low-functioning regions in the lung may lead to higher toxicity rates.
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Affiliation(s)
- Daniel R Owen
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Yilun Sun
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.,Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
| | - Philip S Boonstra
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
| | - Matthew McFarlane
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Benjamin L Viglianti
- Department of Radiology, University of Michigan, Ann Arbor, Michigan.,Veterans Administration, Nuclear Medicine Service, Ann Arbor Michigan
| | - James M Balter
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Issam El Naqa
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Matthew J Schipper
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
| | | | - Randall K Ten Haken
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Feng-Ming S Kong
- Hong Kong University Shenzhen Hospital and Queen Mary Hospital, Hong Kong University Li Ka Shing Medical School, Department of Clinical Oncology, Hong Kong.,Department of Radiation Oncology, Case Western Reserve University, Cleveland, Ohio
| | - Shruti Jolly
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Martha M Matuszak
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
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22
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Jarzebska N, Karetnikova ES, Markov AG, Kasper M, Rodionov RN, Spieth PM. Scarred Lung. An Update on Radiation-Induced Pulmonary Fibrosis. Front Med (Lausanne) 2021; 7:585756. [PMID: 33521012 PMCID: PMC7843914 DOI: 10.3389/fmed.2020.585756] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Accepted: 12/17/2020] [Indexed: 12/18/2022] Open
Abstract
Radiation-induced pulmonary fibrosis is a common severe long-time complication of radiation therapy for tumors of the thorax. Current therapeutic options used in the clinic include only supportive managements strategies, such as anti-inflammatory treatment using steroids, their efficacy, however, is far from being satisfactory. Recent studies have demonstrated that the development of lung fibrosis is a dynamic and complex process, involving the release of reactive oxygen species, activation of Toll-like receptors, recruitment of inflammatory cells, excessive production of nitric oxide and production of collagen by activated myofibroblasts. In this review we summarized the current state of knowledge on the pathophysiological processes leading to the development of lung fibrosis and we also discussed the possible treatment options.
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Affiliation(s)
- Natalia Jarzebska
- Department of Anesthesiology and Critical Care Medicine, University Hospital Dresden, Technische Universität Dresden, Dresden, Germany
- Division of Angiology, Department of Internal Medicine III, University Center for Vascular Medicine, University Hospital Dresden, Technische Universität Dresden, Dresden, Germany
| | | | - Alexander G. Markov
- Department of General Physiology, Saint-Petersburg State University, Saint Petersburg, Russia
| | - Michael Kasper
- Institute of Anatomy, Technische Universität Dresden, Dresden, Germany
| | - Roman N. Rodionov
- Division of Angiology, Department of Internal Medicine III, University Center for Vascular Medicine, University Hospital Dresden, Technische Universität Dresden, Dresden, Germany
| | - Peter M. Spieth
- Department of Anesthesiology and Critical Care Medicine, University Hospital Dresden, Technische Universität Dresden, Dresden, Germany
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23
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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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24
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Risk factors for symptomatic radiation pneumonitis after stereotactic body radiation therapy (SBRT) in patients with non-small cell lung cancer. Radiother Oncol 2020; 156:231-238. [PMID: 33096168 DOI: 10.1016/j.radonc.2020.10.015] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2020] [Revised: 10/11/2020] [Accepted: 10/12/2020] [Indexed: 02/05/2023]
Abstract
BACKGROUND AND PURPOSE Radiation pneumonitis (RP) can be a potential fatal toxicity of stereotactic body radiation therapy (SBRT) for medically inoperable non-small cell lung cancer (NSCLC). This study aimed to examine the risk factors that predict RP and explore dosimetric tolerance for safe practice in a large institutional series of NSCLC patients. MATERIALS AND METHODS Patients with early-stage and locally recurrent NSCLC who received lung SBRT between 2002 and 2015 formed the study population. The primary endpoint was grade 2 or above radiation pneumonitis (RP2). Lungs were re-contoured consistently by one radiation oncologist according to the RTOG atlas for organs at risk. Dosimetric factors were computed consistently with exclusion of gross tumor volume of either ipsilateral, contralateral, or total lungs. RESULTS A total of 339 patients were eligible. With a median follow-up of 47 months, RP2 was recorded in 10% patients. History of respiratory comorbidity, previous thoracic radiation, right lung location, mean lung doses of total or ipsilateral lung, and total lung volume receiving 20 Gy were all significantly associated with the risk of RP2. The dosimetric parameters of contralateral lung, including mean dose and volume receiving more than 5, 10, and 20 Gy, were not significantly associated with RP2 (ps > 0.05). A model of combining significant clinical and dosimetric factors had a predictive accuracy AUC of 0.76. According to this model, RP2 can be limited to <10% should the patient have no previous lung radiation and the mean dose of total and ipsilateral lungs be kept less than 6 Gy and 20 Gy, respectively. CONCLUSION Dosimetric factors of total or ipsilateral lung together with important clinical factors were significant risk factors for symptomatic radiation pneumonitis after SBRT. Constraining mean lung dose can limit clinically significant lung toxicity.
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25
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Song J, Tang T, Caudrelier JM, Bélec J, Chan J, Lacasse P, Aldosary G, Nair V. Dose-sparing effect of deep inspiration breath hold technique on coronary artery and left ventricle segments in treatment of breast cancer. Radiother Oncol 2020; 154:101-109. [PMID: 32950530 DOI: 10.1016/j.radonc.2020.09.019] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Revised: 08/21/2020] [Accepted: 09/10/2020] [Indexed: 12/25/2022]
Abstract
BACKGROUND AND PURPOSE The risk of radiation-induced cardiac injury remains a challenging problem in the treatment of breast cancer. Certain cardiac structures receive higher doses than others, which results in variable frequencies of radiation-induced injuries across these structures. Radiation dose can be reduced using the deep inspiration breath hold (DIBH) technique. We aimed to investigate the dose reductions from DIBH in individual cardiac segments. MATERIALS AND METHODS A dosimetric analysis was performed on left-sided breast cancer patients who underwent breast-conserving surgery and whole breast irradiation. Radiation doses to the cardiac structures were compared between the DIBH and free-breathing (FB) techniques and the dose reductions with DIBH were correlated to the lung expansion. RESULTS For the 75 patients included in our study, DIBH effectively reduced doses to the heart, left lung, left anterior descending coronary artery (LAD) and left ventricle (LV), but the degree of dose reductions was variable across different structures. The absolute dose reductions were greatest in the distal LAD (14.4 Gy) and apical LV (12.1 Gy) segments, compared with the other LAD (middle 9.7 Gy, proximal 1.6 Gy) and LV (anterior 5.3 Gy, lateral 2.9 Gy, septal 2.0 Gy, inferior 0.2 Gy) segments. Left lung expansion was significantly correlated with the dose reductions in the LAD (Spearman's rank correlation coefficient, ρ, 0.304) and LV (ρ, 0.420) segments. CONCLUSIONS Our study demonstrates the dose-sparing effects of DIBH in various cardiac structures, especially the distal LAD and apical LV segments. The large dose reductions seen in the distal LAD and apical LV segments could potentially translate into clinical benefit of reduced cardiac toxicity, as these structures have been previously shown to receive the highest doses and are associated with radiation-induced injury.
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Affiliation(s)
- Jiheon Song
- Division of Radiation Oncology, The Ottawa Hospital, Canada.
| | - Terence Tang
- Faculty of Medicine, University of Ottawa, Canada
| | | | - Jason Bélec
- Department of Medical Physics, The Ottawa Hospital, Canada
| | - Jessica Chan
- Division of Radiation Oncology, The Ottawa Hospital, Canada
| | | | | | - Vimoj Nair
- Division of Radiation Oncology, The Ottawa Hospital, Canada
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26
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Nakajima Y, Kadoya N, Kimura T, Hioki K, Jingu K, Yamamoto T. Variations Between Dose-Ventilation and Dose-Perfusion Metrics in Radiation Therapy Planning for Lung Cancer. Adv Radiat Oncol 2020; 5:459-465. [PMID: 32529141 PMCID: PMC7280081 DOI: 10.1016/j.adro.2020.03.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2019] [Revised: 02/20/2020] [Accepted: 03/05/2020] [Indexed: 12/25/2022] Open
Abstract
Purpose Currently, several active clinical trials of functional lung avoidance radiation therapy using different imaging modalities for ventilation or perfusion are underway. Patients with lung cancer often show ventilation-perfusion mismatch, whereas the significance of dose-function metric remains unclear. The aim of the present study was to compare dose-ventilation metrics with dose-perfusion metrics for radiation therapy plan evaluation. Methods and Materials Pretreatment 4-dimensional computed tomography and 99mTc-macroaggregated albumin single-photon emission computed tomography perfusion images of 60 patients with lung cancer treated with radiation therapy were analyzed. Ventilation images were created using the deformable image registration of 4-dimensional computed tomography image sets and image analysis for regional volume changes as a surrogate for ventilation. Ventilation and perfusion images were converted into percentile distribution images. Analyses included Pearson’s correlation coefficient and comparison of agreements between the following dose-ventilation and dose-perfusion metrics: functional mean lung dose and functional percent lung function receiving 5, 10, 20, 30, and 40 Gy (fV5, fV10, fV20, fV30, and fV40, respectively). Results Overall, the dose-ventilation metrics were greater than the dose-perfusion metrics (ie, fV20, 26.3% ± 9.9% vs 23.9% ± 9.8%). Correlations between the dose-ventilation and dose-perfusion metrics were strong (range, r = 0.94-0.97), whereas the agreements widely varied among patients, with differences as large as 6.6 Gy for functional mean lung dose and 11.1% for fV20. Paired t test indicated that the dose-ventilation and dose-perfusion metrics were significantly different. Conclusions Strong correlations were present between the dose-ventilation and dose-perfusion metrics. However, the agreement between the dose-ventilation and dose-perfusion metrics widely varied among patients, suggesting that ventilation-based radiation therapy plan evaluation may not be comparable to that based on perfusion. Future studies should elucidate the correlation of dose-function metrics with clinical pulmonary toxicity metrics.
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Affiliation(s)
- Yujiro Nakajima
- Department of Radiation Oncology, Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome Hospital, Tokyo, Japan.,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
| | - Tomoki Kimura
- Department of Radiation Oncology, Hiroshima University Graduate School of Biomedical Sciences, Hiroshima, Japan
| | - Kazunari Hioki
- Department of Clinical Support, Hiroshima University Hospital, Hiroshima, Japan.,Graduate School of Health Science, Kumamoto University, Kumamoto, Japan
| | - Keiichi Jingu
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Tokihiro Yamamoto
- Department of Radiation Oncology, University of California Davis School of Medicine, Sacramento, California
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27
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Lee BM, Chang JS, Kim SY, Keum KC, Suh CO, Kim YB. Hypofractionated Radiotherapy Dose Scheme and Application of New Techniques Are Associated to a Lower Incidence of Radiation Pneumonitis in Breast Cancer Patients. Front Oncol 2020; 10:124. [PMID: 32117771 PMCID: PMC7026386 DOI: 10.3389/fonc.2020.00124] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2019] [Accepted: 01/23/2020] [Indexed: 12/25/2022] Open
Abstract
Purpose: Radiation pneumonitis (RP) is one of the most severe toxicities experienced by patients with breast cancer after radiotherapy (RT). RT fractionation schemes and techniques for breast cancer have undergone numerous changes over the past decades. This study aimed to investigate the incidence of RP as a function of such changes in patients with breast cancer undergoing RT and to identify dosimetric markers that predict the risk of this adverse event. Methods and Materials: We identified 1,847 women with breast cancer who received adjuvant RT at our institution between 2015 and 2017. The RT technique was individually tailored based on each patient's clinicopathological features. Deep inspiration breath hold technique or prone positioning were used for patients who underwent left whole-breast irradiation for cardiac sparing, while those requiring regional lymph node irradiation underwent volumetric-modulated arc therapy (VMAT). Results: Of 1,847 patients who received RT, 21.2% received the conventional dose scheme, while 78.8% received the hypofractionated dose scheme (mostly 40 Gy in 15 fractions). The median follow-up period was 14.5 months, and the overall RP rate was 2.1%. The irradiated organ at risk was corrected concerning biologically equivalent dose. The ipsilateral lung V30 in equivalent dose in 2 Gy (EQD2) was the most significant dosimetric factor associated with RP development. Administering RT using VMAT, and hypofractionated dose scheme significantly reduced ipsilateral lung V30. Conclusions: Application of new RT techniques and hypofractionated scheme significantly reduce the ipsilateral lung dose. Our data demonstrated that ipsilateral lung V30 in EQD2 is the most relevant dosimetric predictor of RP in patients with breast cancer.
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Affiliation(s)
- Byung Min Lee
- Department of Radiation Oncology, Yonsei University College of Medicine, Seoul, South Korea
| | - Jee Suk Chang
- Department of Radiation Oncology, Yonsei University College of Medicine, Seoul, South Korea
| | - Se Young Kim
- Department of Radiation Oncology, Yonsei University College of Medicine, Seoul, South Korea
| | - Ki Chang Keum
- Department of Radiation Oncology, Yonsei University College of Medicine, Seoul, South Korea
| | - Chang-Ok Suh
- Department of Radiation Oncology, CHA Bundang Medical Center, CHA University, Bundang-gu, South Korea
| | - Yong Bae Kim
- Department of Radiation Oncology, Yonsei University College of Medicine, Seoul, South Korea
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28
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Palma G, Monti S, Cella L. Voxel-based analysis in radiation oncology: A methodological cookbook. Phys Med 2020; 69:192-204. [PMID: 31923757 DOI: 10.1016/j.ejmp.2019.12.013] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2019] [Revised: 12/16/2019] [Accepted: 12/17/2019] [Indexed: 12/20/2022] Open
Abstract
Recently, 2D or 3D methods for dose distribution analysis have been proposed as evolutions of the Dose Volume Histogram (DVH) approaches. Those methods, collectively referred to as pixel- or voxel-based (VB) methods, evaluate local dose response patterns and go beyond the organ-based philosophy of Normal Tissue Complication Probability (NTCP) modelling. VB methods have been introduced in the context of radiation oncology in the very last years following the virtuous example of neuroimaging experience. In radiation oncology setting, dose mapping is a suitable scheme to compare spatial patterns of local dose distributions between patients who develop toxicity and who do not. In this critical review, we present the methods that include spatial dose distribution information for evaluating different toxicity endpoints after radiation therapy. The review addresses two main topics. First, the critical aspects in dose map building, namely the spatial normalization of the dose distributions from different patients. Then, the issues related to the actual dose map comparison, i.e. the viable options for a robust VB statistical analysis and the potential pitfalls related to the adopted solutions. To elucidate the different theoretical and technical issues, the covered topics are illustrated in relation to practical applications found in the existing literature. We conclude the overview on the VB philosophy in radiation oncology by introducing new phenomenological approaches to NTCP modelling that accounts for inhomogeneous organ radiosensitivity.
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Affiliation(s)
- G Palma
- National Research Council, Institute of Biostructures and Bioimaging, Napoli, Italy.
| | - S Monti
- National Research Council, Institute of Biostructures and Bioimaging, Napoli, Italy
| | - L Cella
- National Research Council, Institute of Biostructures and Bioimaging, Napoli, Italy
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29
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Zhou Y, Yan T, Zhou X, Cao P, Luo C, Zhou L, Xu Y, Liu Y, Xue J, Wang J, Wang Y, Lu Y, Liang B, Gong Y. Acute severe radiation pneumonitis among non-small cell lung cancer (NSCLC) patients with moderate pulmonary dysfunction receiving definitive concurrent chemoradiotherapy: Impact of pre-treatment pulmonary function parameters. Strahlenther Onkol 2019; 196:505-514. [PMID: 31828393 DOI: 10.1007/s00066-019-01552-4] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2019] [Accepted: 11/14/2019] [Indexed: 02/05/2023]
Abstract
PURPOSE Severe acute radiation pneumonitis (SARP) is a life-threatening complication of thoracic radiotherapy. Pre-treatment pulmonary function (PF) may influence its incidence. We have previously reported on the incidence of SARP among patients with moderate pulmonary dysfunction who received definitive concurrent chemoradiotherapy (dCCRT) for non-small cell lung cancer (NSCLC). METHODS The clinical outcomes, dose-volume histograms (DVH), and PF parameters of 122 patients (forced expiratory volume in 1 s [FEV1%]: 60-69%) receiving dCCRT between 2013 and 2019 were recorded. SARP was defined as grade ≥3 RP occurring during or within 3 months after CCRT. Logistic regression, receiver operating characteristics curves (ROC), and hazard ratio (HR) analyses were performed to evaluate the predictive value of each factor for SARP. RESULTS Univariate and multivariate analysis indicated that the ratio of carbon monoxide diffusing capacity (DLCO%; odds ratio [OR]: 0.934, 95% confidence interval [CI] 0.896-0.974, p = 0.001) and mean lung dose (MLD; OR: 1.002, 95% CI 1.001-1.003, p = 0.002) were independent predictors of SARP. The ROC AUC of combined DLCO%/MLD was 0.775 (95% confidence interval [CI]: 0.688-0.861, p = 0.001), with a sensitivity and specificity of 0.871 and 0.637, respectively; this was superior to DLCO% (0.656) or MLD (0.667) alone. Compared to the MLD-low/DLCO%-high group, the MLD-high/DLCO%-low group had the highest risk for SARP, with an HR of 9.346 (95% CI: 2.133-40.941, p = 0.003). CONCLUSION The DLCO% and MLD may predict the risk for SARP among patients with pre-treatment moderate pulmonary dysfunction who receive dCCRT for NSCLC. Prospective studies are needed to validate our findings.
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Affiliation(s)
- Ying Zhou
- Department of Thoracic Oncology and State Key Laboratory of Biotherapy, Cancer Center, West China Hospital, Sichuan University, 610041, Chengdu, China
| | - Tiansheng Yan
- Department of Pulmonary and Critical Care Medicine, West China Hospital, Sichuan University, 610041, Chengdu, China
| | - Xiaojuan Zhou
- Department of Thoracic Oncology and State Key Laboratory of Biotherapy, Cancer Center, West China Hospital, Sichuan University, 610041, Chengdu, China.,Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, 610041, Chengdu, China
| | - Peng Cao
- Department of Thoracic Oncology and State Key Laboratory of Biotherapy, Cancer Center, West China Hospital, Sichuan University, 610041, Chengdu, China
| | - Chunli Luo
- Department of Thoracic Oncology and State Key Laboratory of Biotherapy, Cancer Center, West China Hospital, Sichuan University, 610041, Chengdu, China
| | - Lin Zhou
- Department of Thoracic Oncology and State Key Laboratory of Biotherapy, Cancer Center, West China Hospital, Sichuan University, 610041, Chengdu, China.,Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, 610041, Chengdu, China
| | - Yong Xu
- Department of Thoracic Oncology and State Key Laboratory of Biotherapy, Cancer Center, West China Hospital, Sichuan University, 610041, Chengdu, China.,Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, 610041, Chengdu, China
| | - Yongmei Liu
- Department of Thoracic Oncology and State Key Laboratory of Biotherapy, Cancer Center, West China Hospital, Sichuan University, 610041, Chengdu, China.,Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, 610041, Chengdu, China
| | - Jianxin Xue
- Department of Thoracic Oncology and State Key Laboratory of Biotherapy, Cancer Center, West China Hospital, Sichuan University, 610041, Chengdu, China.,Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, 610041, Chengdu, China
| | - Jin Wang
- Department of Thoracic Oncology and State Key Laboratory of Biotherapy, Cancer Center, West China Hospital, Sichuan University, 610041, Chengdu, China.,Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, 610041, Chengdu, China
| | - Yongsheng Wang
- Department of Thoracic Oncology and State Key Laboratory of Biotherapy, Cancer Center, West China Hospital, Sichuan University, 610041, Chengdu, China
| | - You Lu
- Department of Thoracic Oncology and State Key Laboratory of Biotherapy, Cancer Center, West China Hospital, Sichuan University, 610041, Chengdu, China.,Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, 610041, Chengdu, China
| | - Binmiao Liang
- Department of Pulmonary and Critical Care Medicine, West China Hospital, Sichuan University, 610041, Chengdu, China
| | - Youling Gong
- Department of Thoracic Oncology and State Key Laboratory of Biotherapy, Cancer Center, West China Hospital, Sichuan University, 610041, Chengdu, China. .,Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, 610041, Chengdu, China.
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Thomas HMT, Zeng J, Lee, Jr HJ, Sasidharan BK, Kinahan PE, Miyaoka RS, Vesselle HJ, Rengan R, Bowen SR. Comparison of regional lung perfusion response on longitudinal MAA SPECT/CT in lung cancer patients treated with and without functional tissue-avoidance radiation therapy. Br J Radiol 2019; 92:20190174. [PMID: 31364397 PMCID: PMC6849661 DOI: 10.1259/bjr.20190174] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2019] [Revised: 06/28/2019] [Accepted: 07/23/2019] [Indexed: 12/25/2022] Open
Abstract
OBJECTIVE The effect of functional lung avoidance planning on radiation dose-dependent changes in regional lung perfusion is unknown. We characterized dose-perfusion response on longitudinal perfusion single photon emission computed tomography (SPECT)/CT in two cohorts of lung cancer patients treated with and without functional lung avoidance techniques. METHODS The study included 28 primary lung cancer patients: 20 from interventional (NCT02773238) (FLARE-RT) and eight from observational (NCT01982123) (LUNG-RT) clinical trials. FLARE-RT treatment plans included perfused lung dose constraints while LUNG-RT plans adhered to clinical standards. Pre- and 3 month post-treatment macro-aggregated albumin (MAA) SPECT/CT scans were rigidly co-registered to planning four-dimensional CT scans. Tumour-subtracted lung dose was converted to EQD2 and sorted into 5 Gy bins. Mean dose and percent change between pre/post-RT MAA-SPECT uptake (%ΔPERF), normalized to total tumour-subtracted lung uptake, were calculated in each binned dose region. Perfusion frequency histograms of pre/post-RT MAA-SPECT were analyzed. Dose-response data were parameterized by sigmoid logistic functions to estimate maximum perfusion increase (%ΔPERFmaxincrease), maximum perfusion decrease (%ΔPERFmaxdecrease), dose midpoint (Dmid), and dose-response slope (k). RESULTS Differences in MAA perfusion frequency distribution shape between time points were observed in 11/20 (55%) FLARE-RT and 2/8 (25%) LUNG-RT patients (p < 0.05). FLARE-RT dose response was characterized by >10% perfusion increase in the 0-5 Gy dose bin for 8/20 patients (%ΔPERFmaxincrease = 10-40%), which was not observed in any LUNG-RT patients (p = 0.03). The dose midpoint Dmid at which relative perfusion declined by 50% trended higher in FLARE-RT compared to LUNG-RT cohorts (35 GyEQD2 vs 21 GyEQD2, p = 0.09), while the dose-response slope k was similar between FLARE-RT and LUNG-RT cohorts (3.1-3.2, p = 0.86). CONCLUSION Functional lung avoidance planning may promote increased post-treatment perfusion in low dose regions for select patients, though inter-patient variability remains high in unbalanced cohorts. These preliminary findings form testable hypotheses that warrant subsequent validation in larger cohorts within randomized or case-matched control investigations. ADVANCES IN KNOWLEDGE This novel preliminary study reports differences in dose-response relationships between patients receiving functional lung avoidance radiation therapy (FLARE-RT) and those receiving conventionally planned radiation therapy (LUNG-RT). Following further validation and testing of these effects in larger patient populations, individualized estimation of regional lung perfusion dose-response may help refine future risk-adaptive strategies to minimize lung function deficits and toxicity incidence.
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Affiliation(s)
- Hannah Mary T Thomas
- Department of Radiation Oncology, University of Washington School of Medicine, Seattle, USA
| | - Jing Zeng
- Department of Radiation Oncology, University of Washington School of Medicine, Seattle, USA
| | - Howard J Lee, Jr
- Department of Radiation Oncology, University of Washington School of Medicine, Seattle, USA
| | | | - Paul E Kinahan
- Department of Radiology, University of Washington School of Medicine, Seattle, USA
| | - Robert S Miyaoka
- Department of Radiology, University of Washington School of Medicine, Seattle, USA
| | - Hubert J. Vesselle
- Department of Radiology, University of Washington School of Medicine, Seattle, USA
| | - Ramesh Rengan
- Department of Radiation Oncology, University of Washington School of Medicine, Seattle, USA
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Giuranno L, Ient J, De Ruysscher D, Vooijs MA. Radiation-Induced Lung Injury (RILI). Front Oncol 2019; 9:877. [PMID: 31555602 PMCID: PMC6743286 DOI: 10.3389/fonc.2019.00877] [Citation(s) in RCA: 183] [Impact Index Per Article: 36.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2019] [Accepted: 08/23/2019] [Indexed: 12/12/2022] Open
Abstract
Radiation pneumonitis (RP) and radiation fibrosis (RF) are two dose-limiting toxicities of radiotherapy (RT), especially for lung, and esophageal cancer. It occurs in 5-20% of patients and limits the maximum dose that can be delivered, reducing tumor control probability (TCP) and may lead to dyspnea, lung fibrosis, and impaired quality of life. Both physical and biological factors determine the normal tissue complication probability (NTCP) by Radiotherapy. A better understanding of the pathophysiological sequence of radiation-induced lung injury (RILI) and the intrinsic, environmental and treatment-related factors may aid in the prevention, and better management of radiation-induced lung damage. In this review, we summarize our current understanding of the pathological and molecular consequences of lung exposure to ionizing radiation, and pharmaceutical interventions that may be beneficial in the prevention or curtailment of RILI, and therefore enable a more durable therapeutic tumor response.
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Affiliation(s)
- Lorena Giuranno
- Department of Radiotherapy, GROW School for Oncology Maastricht University Medical Centre, Maastricht, Netherlands
| | - Jonathan Ient
- Department of Radiotherapy, GROW School for Oncology Maastricht University Medical Centre, Maastricht, Netherlands
| | - Dirk De Ruysscher
- Department of Radiotherapy, GROW School for Oncology Maastricht University Medical Centre, Maastricht, Netherlands
| | - Marc A Vooijs
- Department of Radiotherapy, GROW School for Oncology Maastricht University Medical Centre, Maastricht, Netherlands
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Palma G, Monti S, Conson M, Pacelli R, Cella L. Normal tissue complication probability (NTCP) models for modern radiation therapy. Semin Oncol 2019; 46:210-218. [PMID: 31506196 DOI: 10.1053/j.seminoncol.2019.07.006] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/24/2019] [Accepted: 07/31/2019] [Indexed: 02/07/2023]
Abstract
Mathematical models of normal tissue complication probability (NTCP) able to robustly predict radiation-induced morbidities (RIM) play an essential role in the identification of a personalized optimal plan, and represent the key to maximizing the benefits of technological advances in radiation therapy (RT). Most modern RT techniques pose, however, new challenges in estimating the risk of RIM. The aim of this report is to schematically review NTCP models in the framework of advanced radiation therapy techniques. Issues relevant to hypofractionated stereotactic body RT and ion beam therapy are critically reviewed. Reirradiation scenarios for new or recurrent malignances and NTCP are also illustrated. A new phenomenological approach to predict RIM is suggested.
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Affiliation(s)
- Giuseppe Palma
- National Research Council, Institute of Biostructures and Bioimaging, Napoli, Italy
| | - Serena Monti
- National Research Council, Institute of Biostructures and Bioimaging, Napoli, Italy
| | - Manuel Conson
- Department of Advanced Biomedical Sciences, Federico II University School of Medicine, Naples, Italy
| | - Roberto Pacelli
- Department of Advanced Biomedical Sciences, Federico II University School of Medicine, Naples, Italy
| | - Laura Cella
- National Research Council, Institute of Biostructures and Bioimaging, Napoli, Italy.
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Hegi-Johnson F, de Ruysscher D, Keall P, Hendriks L, Vinogradskiy Y, Yamamoto T, Tahir B, Kipritidis J. Imaging of regional ventilation: Is CT ventilation imaging the answer? A systematic review of the validation data. Radiother Oncol 2019; 137:175-185. [DOI: 10.1016/j.radonc.2019.03.010] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2018] [Revised: 03/08/2019] [Accepted: 03/10/2019] [Indexed: 01/08/2023]
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Development and internal validation of a multinomial NTCP model for the severity of acute dyspnea after radiotherapy for lung cancer. Radiother Oncol 2019; 136:176-184. [PMID: 31015122 DOI: 10.1016/j.radonc.2019.03.034] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2018] [Revised: 02/22/2019] [Accepted: 03/29/2019] [Indexed: 12/23/2022]
Abstract
BACKGROUND AND PURPOSE Dyspnea evolution after radiotherapy for lung cancer is complex with potential symptom deterioration and improvement from baseline. We developed and internally validated a multinomial normal tissue complication probability (NTCP) model predicting dyspnea grade. MATERIALS AND METHODS Patient-reported dyspnea was collected pre-treatment and during 6 months follow-up for 182 stage I-IV lung cancer patients treated with radical (chemo)radiotherapy. Dyspnea changes (ΔDys) from the baseline grade (Dys0) to the follow-up grade (Dys) were evaluated. A multinomial logistic regression model simultaneously predicting 3 grades of Dys (Dys ≥ 3, Dys = 2 and Dys ≤ 1 (reference level)) was optimized. Reference NTCP models predicting Dys ≥ 2 and Dys ≥ 3 risks irrespective of Dys0 were generated for comparison. Models were shrunken and performance was assessed using optimism-corrected AUC (bootstrapping). RESULTS Rates of ΔDys ≥ 1 (deterioration) and ΔDys ≤ -1 (improvement) at 6 months were 31.9% and 12.6%. Dys ≥ 3, Dys = 2 and Dys ≤ 1 rates were 13.7%, 20.9% and 65.4%, respectively. The multinomial model (combining the risk factors Dys0 and MLD and the protective factor chemotherapy treatment) predicted Dys ≥ 3, Dys = 2 and Dys ≤ 1 with AUC (95% CI) of 0.72 (0.65-0.75) 0.76 (0.72-0.79) and 0.78 (0.74-0.80), respectively. Reference Dys ≥ 2 and Dys ≥ 3 models showed worse AUC: 0.64 (0.59-0.67) and 0.66 (0.50-0.70), respectively. CONCLUSIONS Dyspnea grade could be predicted with high accuracy using a multinomial NTCP model, yielding personalized dyspnea symptom improvement and deterioration risks.
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Yu H, Wu H, Wang W, Jolly S, Jin JY, Hu C, Kong FMS. Machine Learning to Build and Validate a Model for Radiation Pneumonitis Prediction in Patients with Non-Small Cell Lung Cancer. Clin Cancer Res 2019; 25:4343-4350. [PMID: 30992302 DOI: 10.1158/1078-0432.ccr-18-1084] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2018] [Revised: 12/29/2018] [Accepted: 04/12/2019] [Indexed: 11/16/2022]
Abstract
PURPOSE Radiation pneumonitis is an important adverse event in patients with non-small cell lung cancer (NSCLC) receiving thoracic radiotherapy. However, the risk of radiation pneumonitis grade ≥ 2 (RP2) has not been well predicted. This study hypothesized that inflammatory cytokines or the dynamic changes during radiotherapy can improve predictive accuracy for RP2. EXPERIMENTAL DESIGN Levels of 30 inflammatory cytokines and clinical information in patients with stages I-III NSCLC treated with radiotherapy were from our prospective studies. Statistical analysis was used to select predictive cytokine candidates and clinical covariates for adjustment. Machine learning algorithm was used to develop the generalized linear model for predicting risk RP2. RESULTS A total of 131 patients were eligible and 17 (13.0%) developed RP2. IL8 and CCL2 had significantly (Bonferroni) lower expression levels in patients with RP2 than without RP2. But none of the changes in cytokine levels during radiotherapy was significantly associated with RP2. The final predictive GLM model for RP2 was established, including IL8 and CCL2 at baseline level and two clinical variables. Nomogram was constructed based on the GLM model. The model's predicting ability was validated in the completely independent test set (AUC = 0.863, accuracy = 80.0%, sensitivity = 100%, specificity = 76.5%). CONCLUSIONS By machine learning, this study has developed and validated a comprehensive model integrating inflammatory cytokines with clinical variables to predict RP2 before radiotherapy that provides an opportunity to guide clinicians.
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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, Indianapolis, Indiana
| | - Huanmei Wu
- BioHealth Informatics, School Of Informatics and Computing, Indiana University - Purdue University Indianapolis, Indianapolis, Indiana
| | - Weili Wang
- University Hospitals/Cleveland Medical Center, Seidman Cancer Center and Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, Ohio
| | - Shruti Jolly
- Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Jian-Yue Jin
- University Hospitals/Cleveland Medical Center, Seidman Cancer Center and Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, Ohio
| | - Chen Hu
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Feng-Ming Spring Kong
- University Hospitals/Cleveland Medical Center, Seidman Cancer Center and Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, Ohio. .,Department of Clinical Oncology, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China.,Department of Clinical Oncology, The University of Hong Kong and Shenzhen Hospital, Hong Kong, China
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Vinogradskiy Y. CT-based ventilation imaging in radiation oncology. BJR Open 2019; 1:20180035. [PMID: 33178925 PMCID: PMC7592480 DOI: 10.1259/bjro.20180035] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2018] [Revised: 01/28/2019] [Accepted: 03/11/2019] [Indexed: 11/06/2022] Open
Abstract
A form of lung function imaging is emerging that uses phase-resolved four-dimensional CT (4DCT or breath-hold CT) images along with image processing techniques to generate lung function maps that provide a surrogate of lung ventilation. CT-based ventilation (referred to as CT-ventilation) research has gained momentum in Radiation Oncology because many lung cancer patients undergo four-dimensional CT simulation as part of the standard treatment planning process. Therefore, generating CT-ventilation images provides functional information without burdening the patient with an extra imaging procedure. CT-ventilation has progressed from an image processing calculation methodology, to validation efforts, to retrospective demonstration of clinical utility in Radiation Oncology. In particular, CT-ventilation has been proposed for two main clinical applications: functional avoidance radiation therapy and thoracic dose-response assessment. The idea of functional avoidance radiation therapy is to preferentially spare functional portions of the lung (as measured by CT-ventilation) during radiation therapy with the hypothesis that reducing dose to functional portions of the lung will lead to reduced rates of radiation-related thoracic toxicity. The idea of imaging-based dose-response assessment is to evaluate pre- to post-treatment CT-ventilation-based imaging changes. The hypothesis is that early, imaging-change-based response can be an early predictor of subsequent thoracic toxicity. Based on the retrospective evidence, the clinical applications of CT-ventilation have progressed from the retrospective setting to on-going prospective clinical trials. This review will cover basic CT-ventilation calculation methodologies, validation efforts, presentation of clinical applications, summarize on-going clinical trials, review potential uncertainties and shortcomings of CT-ventilation, and discuss future directions of CT-ventilation research.
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Affiliation(s)
- Yevgeniy Vinogradskiy
- Department of Radiation Oncology, University of Colorado School of Medicine, Aurora, CO
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Jang B, Chang JH, Park AJ, Wu H. Generation of virtual lung single‐photon emission computed tomography/CT fusion images for functional avoidance radiotherapy planning using machine learning algorithms. J Med Imaging Radiat Oncol 2019; 63:229-235. [DOI: 10.1111/1754-9485.12868] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2018] [Accepted: 02/04/2019] [Indexed: 01/08/2023]
Affiliation(s)
- Bum‐Sup Jang
- Department of Radiation Oncology Seoul National University Hospital Seoul Korea
| | - Ji Hyun Chang
- Department of Radiation Oncology SMG‐SNU Boramae Medical Center Seoul Korea
| | - Andrew J Park
- Artificial Intelligence Research and Development Laboratory SELVAS AI Incorporation Seoul Korea
| | - Hong‐Gyun Wu
- Department of Radiation Oncology Seoul National University Hospital Seoul Korea
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Tang X, Li Y, Tian X, Zhou X, Wang Y, Huang M, Ren L, Zhou L, Xue J, Ding Z, Zhu J, Xu Y, Peng F, Wang J, Lu Y, Gong Y. Predicting severe acute radiation pneumonitis in patients with non-small cell lung cancer receiving postoperative radiotherapy: Development and internal validation of a nomogram based on the clinical and dose–volume histogram parameters. Radiother Oncol 2019; 132:197-203. [DOI: 10.1016/j.radonc.2018.10.016] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2018] [Revised: 10/11/2018] [Accepted: 10/16/2018] [Indexed: 12/18/2022]
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Palma G, Monti S, Xu T, Scifoni E, Yang P, Hahn SM, Durante M, Mohan R, Liao Z, Cella L. Spatial Dose Patterns Associated With Radiation Pneumonitis in a Randomized Trial Comparing Intensity-Modulated Photon Therapy With Passive Scattering Proton Therapy for Locally Advanced Non-Small Cell Lung Cancer. Int J Radiat Oncol Biol Phys 2019; 104:1124-1132. [PMID: 30822531 DOI: 10.1016/j.ijrobp.2019.02.039] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2018] [Revised: 01/31/2019] [Accepted: 02/20/2019] [Indexed: 12/27/2022]
Abstract
PURPOSE Radiation pneumonitis (RP) is commonly associated with thoracic radiation therapy, and its incidence is related to dose and volume of the normal lung in the path of radiation. Our aim was to investigate dose patterns associated with RP in patients enrolled in a randomized trial of intensity modulated radiation therapy (IMRT) versus passive scattering proton therapy (PSPT) for locally advanced non-small cell lung cancer. METHODS We analyzed 178 patients prospectively treated with PSPT or IMRT for non-small cell lung cancer to a prescribed dose of 66 or 74 Gy in conventional daily fractionation with concurrent chemotherapy. Forty patients (22%) developed clinically symptomatic RP. Voxel-based analysis of local dose differences was done with a nonparametric permutation test accounting for multiple comparisons. From the obtained 3-dimensional significance maps, we derived clusters of voxels that exhibited dose differences between groups at a statistical significance level of 0.05. RESULTS The voxel-based analysis highlighted that (1) significant dose differences between patients with and without RP were found in the lower part of the lungs and in the heart and (2) the anatomic regions significantly spared by PSPT and the clusters in which doses were significantly correlated with RP development were disjoint. CONCLUSIONS The analyzed trial data provide an unprecedented opportunity to substantiate previous hypotheses regarding the role of the heart and the lower lungs in the development of RP. Knowledge of this relationship between RP and thoracic regional radiosensitivity should be considered in clinical practice and in the design of future trials.
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Affiliation(s)
- Giuseppe Palma
- National Research Council, Institute of Biostructures and Bioimaging, Napoli, Italy
| | - Serena Monti
- IRCCS SDN, Image Processing Department, Napoli, Italy
| | - Ting Xu
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Emanuele Scifoni
- Istituto Nazionale di Fisica Nucleare, Trento Institute for Fundamental Physics and Applications, Trento, Italy
| | - Pei Yang
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Stephen M Hahn
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Marco Durante
- Biophysics Department, GSI Helmholtzzentrum für Schwerionenforschung, Darmstadt, Germany; Technische Universität Darmstadt, Institut für Festkörperphysik, Darmstadt, Germany
| | - Radhe Mohan
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Zhongxing Liao
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
| | - Laura Cella
- National Research Council, Institute of Biostructures and Bioimaging, Napoli, Italy
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Abstract
Curative-intent lung cancer radiation therapy either alone (RT) or combined with immuno-chemotherapy is associated with potential risk of serious radiation-induced lung injury. This review provides a summary of the role of SPECT ventilation perfusion (V/Q) imaging as an emerging adjunct to lung cancer RT planning and treatment dosimetry. Denoted "functional lung avoidance RT" it is hypothesized that preferential dosimetric avoidance of physiologically functional lung may reduce the frequency of radiation-induced lung injury. SPECT V/Q imaging datasets available during the planning process allows the prioritization (or "personalization') of RT dose to minimize the volume of functional lung probabilistically exposed to injurious radiation dose. Selective escalation of target dose and adaptive planning and replanning is also enabled. The emergent importance of the tumor-lung microenvironment and its biologic relationship to local immune effectors in lung cancer provides further incentive to individualize RT planning and delivery. This review examines important normal tissue dosimetric constraints that are part of current standards-of-care and the new dosimetric parameters associated with functional lung avoidance RT. SPECT V/Q has been a valuable tool in investigating the feasibility and efficacy of functional lung avoidance RT but is yet to become main stream due to the lack of large clinical trials. It is encouraging however that functional lung avoidance is feasible in RT dose-target delineation and some of the more promising studies are discussed.
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Affiliation(s)
- Enid M Eslick
- Department of Nuclear Medicine, Royal North Shore Hospital, Sydney, NSW, Australia; Faculty of Health Sciences, University of Sydney, Sydney, NSW, Australia
| | - Mark J Stevens
- Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, NSW, Australia
| | - Dale L Bailey
- Department of Nuclear Medicine, Royal North Shore Hospital, Sydney, NSW, Australia; Faculty of Health Sciences, University of Sydney, Sydney, NSW, Australia.
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Menoux I, Le Fèvre C, Noël G, Antoni D. [Radiation-induced lung toxicity predictors after stereotactic radiation therapy for non-small cell lung carcinoma stage I]. Cancer Radiother 2018; 22:826-838. [PMID: 30337050 DOI: 10.1016/j.canrad.2017.12.007] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2017] [Revised: 11/08/2017] [Accepted: 12/22/2017] [Indexed: 12/19/2022]
Abstract
In case of refusal or contraindication for surgical management of a stage I non-small cell lung carcinoma, the validated alternative therapy is stereotactic irradiation. This technique reaches an equivalent tumour control rate than surgery and significantly higher than conventional radiotherapy. One of the dreaded complications is radiation induced lung toxicity (radiation pneumonitis and lung fibrosis), especially when it is symptomatic, occurring in about 10 % of cases. This article is a literature review of this complication's predictive factors.
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Affiliation(s)
- I Menoux
- Département universitaire de radiothérapie, centre Paul-Strauss, 3, rue de la Porte-de-l'Hôpital, BP 42, 67065 Strasbourg cedex, France.
| | - C Le Fèvre
- Département universitaire de radiothérapie, centre Paul-Strauss, 3, rue de la Porte-de-l'Hôpital, BP 42, 67065 Strasbourg cedex, France
| | - G Noël
- Département universitaire de radiothérapie, centre Paul-Strauss, 3, rue de la Porte-de-l'Hôpital, BP 42, 67065 Strasbourg cedex, France; EA 3430, laboratoire de radiobiologie, université de Strasbourg, fédération de médecine translationnelle de Strasbourg (FMTS), 67065 Strasbourg, France
| | - D Antoni
- Département universitaire de radiothérapie, centre Paul-Strauss, 3, rue de la Porte-de-l'Hôpital, BP 42, 67065 Strasbourg cedex, France; EA 3430, laboratoire de radiobiologie, université de Strasbourg, fédération de médecine translationnelle de Strasbourg (FMTS), 67065 Strasbourg, France
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Functional lung imaging in radiation therapy for lung cancer: A systematic review and meta-analysis. Radiother Oncol 2018; 129:196-208. [PMID: 30082143 DOI: 10.1016/j.radonc.2018.07.014] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2018] [Revised: 06/14/2018] [Accepted: 07/18/2018] [Indexed: 12/25/2022]
Abstract
RATIONALE Advanced imaging techniques allow functional information to be derived and integrated into treatment planning. METHODS A systematic review was conducted with the primary objective to evaluate the ability of functional lung imaging to predict risk of radiation pneumonitis. Secondary objectives were to evaluate dose-response relationships on post treatment functional imaging and assess the utility in including functional lung information into treatment planning. A structured search for publications was performed following PRISMA guidelines and registered on PROSPERO. RESULTS 814 articles were screened against review criteria and 114 publications met criteria. Methods of identifying functional lung included using CT, MRI, SPECT and PET to image ventilation or perfusion. Six studies compared differences between functional and anatomical lung imaging at predicting radiation pneumonitis. These found higher predictive values using functional lung imaging. Twenty-one studies identified a dose-response relationship on post-treatment functional lung imaging. Nineteen planning studies demonstrated the ability of functional lung optimised planning techniques to spare regions of functional lung. Meta-analysis of these studies found that mean (95% CI) functional volume receiving 20 Gy was reduced by 4.2% [95% CI: 2.3: 6.0] and mean lung dose by 2.2 Gy [95% CI: 1.2: 3.3] when plans were optimised to spare functional lung. There was significant variation between publications in the definition of functional lung. CONCLUSION Functional lung imaging may have potential utility in radiation therapy planning and delivery, although significant heterogeneity was identified in approaches and reporting. Recommendations have been made based on the available evidence for future functional lung trials.
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Rankine LJ, Wang Z, Driehuys B, Marks LB, Kelsey CR, Das SK. Correlation of Regional Lung Ventilation and Gas Transfer to Red Blood Cells: Implications for Functional-Avoidance Radiation Therapy Planning. Int J Radiat Oncol Biol Phys 2018; 101:1113-1122. [PMID: 29907488 PMCID: PMC6689416 DOI: 10.1016/j.ijrobp.2018.04.017] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2017] [Revised: 03/02/2018] [Accepted: 04/05/2018] [Indexed: 02/08/2023]
Abstract
PURPOSE To investigate the degree to which lung ventilation and gas exchange are regionally correlated, using the emerging technology of hyperpolarized (HP)-129Xe magnetic resonance imaging (MRI). METHODS AND MATERIALS Hyperpolarized-129Xe MRI studies were performed on 17 institutional review board-approved human subjects, including 13 healthy volunteers, 1 emphysema patient, and 3 non-small cell lung cancer patients imaged before and approximately 11 weeks after radiation therapy (RT). Subjects inhaled 1 L of HP-129Xe mixture, followed by the acquisition of interleaved ventilation and gas exchange images, from which maps were obtained of the relative HP-129Xe distribution in three states: (1) gaseous, in lung airspaces; (2) dissolved interstitially, in alveolar barrier tissue; and (3) transferred to red blood cells (RBCs), in the capillary vasculature. The relative spatial distributions of HP-129Xe in airspaces (regional ventilation) and RBCs (regional gas transfer) were compared. Further, we investigated the degree to which ventilation and RBC transfer images identified similar functional regions of interest (ROIs) suitable for functionally guided RT. For the RT patients, both ventilation and RBC functional images were used to calculate differences in the lung dose-function histogram and functional effective uniform dose. RESULTS The correlation of ventilation and RBC transfer was ρ = 0.39 ± 0.15 in healthy volunteers. For the RT patients, this correlation was ρ = 0.53 ± 0.02 before treatment and ρ = 0.39 ± 0.07 after treatment; for the emphysema patient it was ρ = 0.24. Comparing functional ROIs, ventilation and RBC transfer demonstrated poor spatial agreement: Dice similarity coefficient = 0.50 ± 0.07 and 0.26 ± 0.12 for the highest-33%- and highest-10%-function ROIs in healthy volunteers, and in RT patients (before treatment) these were 0.58 ± 0.04 and 0.40 ± 0.04. The average magnitude of the differences between RBC- and ventilation-derived functional effective uniform dose, fV20Gy, fV10Gy, and fV5Gy were 1.5 ± 1.4 Gy, 4.1% ± 3.8%, 5.0% ± 3.8%, and 5.3% ± 3.9%, respectively. CONCLUSION Ventilation may not be an effective surrogate for true regional lung function for all patients.
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Affiliation(s)
- Leith J Rankine
- Department of Radiation Oncology, University of North Carolina School of Medicine, Chapel Hill, North Carolina; Medical Physics Graduate Program, Duke University, Durham, North Carolina.
| | - Ziyi Wang
- Department of Biomedical Engineering, Duke University, Durham, North Carolina
| | - Bastiaan Driehuys
- Medical Physics Graduate Program, Duke University, Durham, North Carolina; Department of Biomedical Engineering, Duke University, Durham, North Carolina; Radiology, Duke University, Durham, North Carolina
| | - Lawrence B Marks
- Department of Radiation Oncology, University of North Carolina School of Medicine, Chapel Hill, North Carolina
| | - Chris R Kelsey
- Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina
| | - Shiva K Das
- Department of Radiation Oncology, University of North Carolina School of Medicine, Chapel Hill, North Carolina
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Miyakawa S, Tachibana H, Moriya S, Kurosawa T, Nishio T, Sato M. Design and development of a nonrigid phantom for the quantitative evaluation of DIR-based mapping of simulated pulmonary ventilation. Med Phys 2018; 45:3496-3505. [PMID: 29807393 DOI: 10.1002/mp.13017] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2016] [Revised: 05/16/2018] [Accepted: 05/16/2018] [Indexed: 12/25/2022] Open
Abstract
PURPOSE The validation of deformable image registration (DIR)-based pulmonary ventilation mapping is time consuming and prone to inaccuracies and is also affected by deformation parameters. In this study, we developed a nonrigid phantom as a quality assurance (QA) tool that simulates ventilation to evaluate DIR-based images quantitatively. METHODS The phantom consists of an acrylic cylinder filled with polyurethane foam designed to simulate pulmonic alveoli. A polyurethane membrane is attached to the inferior end of the phantom to simulate the diaphragm. In addition, tracheobronchial-tree-shaped polyurethane tubes are inserted through the foam and converge outside the phantom to simulate the trachea. Solid polyurethane is also used to model arteries, which closely follow the model airways. Two three-dimensional (3D) CT scans were performed during exhalation and inhalation phases using xenon (Xe) gas as the inhaled contrast agent. The exhalation 3D-CT image is deformed to an inhalation 3D-CT image using our in-house program based on the NiftyReg open-source package. The target registration error (TRE) between the two images was calculated for 16 landmarks located in the simulated lung volume. The DIR-based ventilation image was generated using Jacobian determinant (JD) metrics. Subsequently, differences in the Hounsfield unit (HU) values between the two images were measured. The correlation coefficient between the JD and HU differences was calculated. In addition, three 4D-CT scans are performed to evaluate the reproducibility of the phantom motion and Xe gas distribution. RESULTS The phantom exhibited a variety of displacements for each landmark (range: 1-20 mm). The reproducibility analysis indicated that the location differences were <1 mm for all landmarks, and the HU variation in the Xe gas distribution was close to zero. The mean TRE in the evaluation of spatial accuracy according to the DIR software was 1.47 ± 0.71 mm (maximum: 2.6 mm). The relationship between the JD and HU differences had a large correlation (R = -0.71) for the DIR software. CONCLUSION The phantom implemented new features, namely, deformation and simulated ventilation. To assess the accuracy of the DIR-based mapping of the simulated pulmonary ventilation, the phantom allows for simulation of Xe gas wash-in and wash-out. The phantom may be an effective QA tool, because the DIR algorithm can be quickly changed and its accuracy evaluated with a high degree of precision.
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Affiliation(s)
- Shin Miyakawa
- Department of Medical Physics, Graduate School of Medicine, Tokyo Women's Medical University, Tokyo, 162-8666, Japan
- Radiological Sciences, Graduate Division of Health Sciences, Komazawa University, Tokyo, 154-8525, Japan
| | - Hidenobu Tachibana
- Particle Therapy Division, Research Center for Innovative Oncology, National Cancer Center, Chiba, 277-8577, Japan
| | - Shunsuke Moriya
- Doctoral Program in Biomedical Sciences, Graduate School of Comprehensive Human Sciences, University of Tsukuba, Chiba, 305-8577, Japan
| | - Tomoyuki Kurosawa
- Department of Medical Physics, Graduate School of Medicine, Tokyo Women's Medical University, Tokyo, 162-8666, Japan
- Radiological Sciences, Graduate Division of Health Sciences, Komazawa University, Tokyo, 154-8525, Japan
| | - Teiji Nishio
- Department of Medical Physics, Graduate School of Medicine, Tokyo Women's Medical University, Tokyo, 162-8666, Japan
| | - Masanori Sato
- Radiological Sciences, Graduate Division of Health Sciences, Komazawa University, Tokyo, 154-8525, Japan
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Faught AM, Olsen L, Schubert L, Rusthoven C, Castillo E, Castillo R, Zhang J, Guerrero T, Miften M, Vinogradskiy Y. Functional-guided radiotherapy using knowledge-based planning. Radiother Oncol 2018; 129:494-498. [PMID: 29628292 DOI: 10.1016/j.radonc.2018.03.025] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2017] [Revised: 03/12/2018] [Accepted: 03/23/2018] [Indexed: 10/17/2022]
Abstract
BACKGROUND AND PURPOSE There are two significant challenges when implementing functional-guided radiotherapy using 4DCT-ventilation imaging: (1) lack of knowledge of realistic patient specific dosimetric goals for functional lung and (2) ensuring consistent plan quality across multiple planners. Knowledge-based planning (KBP) is positioned to address both concerns. MATERIAL AND METHODS A KBP model was created from 30 previously planned functional-guided lung patients. Standard organs at risk (OAR) in lung radiotherapy and a ventilation contour delineating areas of high ventilation were included. Model validation compared dose-metrics to standard OARs and functional dose-metrics from 20 independent cases that were planned with and without KBP. RESULTS A significant improvement was observed for KBP optimized plans in V20Gy and mean dose to functional lung (p = 0.005 and 0.001, respectively), V20Gy and mean dose to total lung minus GTV (p = 0.002 and 0.01, respectively), and mean doses to esophagus (p = 0.005). CONCLUSION The current work developed a KBP model for functional-guided radiotherapy. Modest, but statistically significant, improvements were observed in functional lung and total lung doses.
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Affiliation(s)
- Austin M Faught
- University of Colorado School of Medicine, Department of Radiation Oncology, Aurora, United States; St. Jude Children's Research Hospital, Department of Radiation Oncology, Memphis, United States.
| | - Lindsey Olsen
- Memorial Hospital, Department of Radiation Oncology, Colorado Springs, United States
| | - Leah Schubert
- University of Colorado School of Medicine, Department of Radiation Oncology, Aurora, United States
| | - Chad Rusthoven
- University of Colorado School of Medicine, Department of Radiation Oncology, Aurora, United States
| | - Edward Castillo
- Beaumont Health System, Department of Radiation Oncology, Royal Oak, United States
| | - Richard Castillo
- Emory University, Department of Radiation Oncology, Atlanta, United States
| | - Jingjing Zhang
- Beaumont Health System, Department of Radiation Oncology, Royal Oak, United States
| | - Thomas Guerrero
- Beaumont Health System, Department of Radiation Oncology, Royal Oak, United States
| | - Moyed Miften
- University of Colorado School of Medicine, Department of Radiation Oncology, Aurora, United States
| | - Yevgeniy Vinogradskiy
- University of Colorado School of Medicine, Department of Radiation Oncology, Aurora, United States
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MacManus M, Everitt S, Schimek-Jasch T, Li XA, Nestle U, Kong FMS. Anatomic, functional and molecular imaging in lung cancer precision radiation therapy: treatment response assessment and radiation therapy personalization. Transl Lung Cancer Res 2017; 6:670-688. [PMID: 29218270 DOI: 10.21037/tlcr.2017.09.05] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
This article reviews key imaging modalities for lung cancer patients treated with radiation therapy (RT) and considers their actual or potential contributions to critical decision-making. An international group of researchers with expertise in imaging in lung cancer patients treated with RT considered the relevant literature on modalities, including computed tomography (CT), magnetic resonance imaging (MRI) and positron emission tomography (PET). These perspectives were coordinated to summarize the current status of imaging in lung cancer and flag developments with future implications. Although there are no useful randomized trials of different imaging modalities in lung cancer, multiple prospective studies indicate that management decisions are frequently impacted by the use of complementary imaging modalities, leading both to more appropriate treatments and better outcomes. This is especially true of 18F-fluoro-deoxyglucose (FDG)-PET/CT which is widely accepted to be the standard imaging modality for staging of lung cancer patients, for selection for potentially curative RT and for treatment planning. PET is also more accurate than CT for predicting survival after RT. PET imaging during RT is also correlated with survival and makes response-adapted therapies possible. PET tracers other than FDG have potential for imaging important biological process in tumors, including hypoxia and proliferation. MRI has superior accuracy in soft tissue imaging and the MRI Linac is a rapidly developing technology with great potential for online monitoring and modification of treatment. The role of imaging in RT-treated lung cancer patients is evolving rapidly and will allow increasing personalization of therapy according to the biology of both the tumor and dose limiting normal tissues.
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Affiliation(s)
- Michael MacManus
- Department of Radiation Oncology, Division of Radiation Oncology and Cancer Imaging, Peter MacCallum Cancer Centre, Melbourne, Australia.,The Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, Australia
| | - Sarah Everitt
- Department of Radiation Oncology, Division of Radiation Oncology and Cancer Imaging, Peter MacCallum Cancer Centre, Melbourne, Australia.,The Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, Australia
| | - Tanja Schimek-Jasch
- Department of Radiation Oncology, Medical Center, Faculty of Medicine, University of Freiburg, German Cancer Consortium (DKTK) Partner Site Freiburg, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - X Allen Li
- Department of Radiation Oncology, Medical College of Wisconsin, WI, USA
| | - Ursula Nestle
- Department of Radiation Oncology, Medical Center, Faculty of Medicine, University of Freiburg, German Cancer Consortium (DKTK) Partner Site Freiburg, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Department of Radiation Oncology, Kliniken Maria Hilf, Moenchengladbach, Germany
| | - Feng-Ming Spring Kong
- Indiana University Simon Cancer Center, Indiana University School of Medicine, Indianapolis, IN, USA
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Blais E, Pichon B, Mampuya A, Antoine M, Lagarde P, Kantor G, Breton-Callu C, Lefebvre C, Gerard M, Aamarcha A, Ozsahin M, Bourhis J, Maingon P, Troussier I, Pourel N. Doses aux organes à risque en radiothérapie conformationnelle et en radiothérapie stéréotaxique : les poumons. Cancer Radiother 2017; 21:584-596. [DOI: 10.1016/j.canrad.2017.07.046] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2017] [Revised: 07/21/2017] [Accepted: 07/23/2017] [Indexed: 12/25/2022]
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Lee E, Zeng J, Miyaoka RS, Saini J, Kinahan PE, Sandison GA, Wong T, Vesselle HJ, Rengan R, Bowen SR. Functional lung avoidance and response-adaptive escalation (FLARE) RT: Multimodality plan dosimetry of a precision radiation oncology strategy. Med Phys 2017; 44:3418-3429. [PMID: 28453861 DOI: 10.1002/mp.12308] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2016] [Revised: 03/22/2017] [Accepted: 04/21/2017] [Indexed: 12/25/2022] Open
Abstract
PURPOSE Nonsmall cell lung cancer (NSCLC) patient radiation therapy (RT) is planned without consideration of spatial heterogeneity in lung function or tumor response. We assessed the dosimetric and clinical feasibility of functional lung avoidance and response-adaptive escalation (FLARE) RT to reduce dose to [99m Tc]MAA-SPECT/CT perfused lung while redistributing an escalated boost dose within [18 F]FDG-PET/CT-defined biological target volumes (BTV). METHODS Eight stage IIB-IIIB NSCLC patients underwent FDG-PET/CT and MAA-SPECT/CT treatment planning scans. Perfused lung objectives were derived from scatter/collimator/attenuation-corrected MAA-SPECT uptake relative to ITV-subtracted lung to maintain < 20 Gy mean lung dose (MLD). Prescriptions included 60 Gy to the planning target volume (PTV) and concomitant boost of 74 Gy mean to biological target volumes (BTV = GTV + PET gradient segmentation) scaled to each BTV voxel by relative FDG-PET SUV. Dose-painting-by-numbers prescriptions were integrated into commercial treatment planning systems via uptake threshold discretization. Dose constraints for lung, heart, cord, and esophagus were defined. FLARE RT plans were optimized with volumetric modulated arc therapy (VMAT), proton pencil beam scanning (PBS) with 3%-3 mm robust optimization, and combination of PBS (avoidance) plus VMAT (escalation). The high boost dose region was evaluated within a standardized SUVpeak structure. FLARE RT plans were compared to reference VMAT plans. Linear regression between radiation dose to BTV and normalized FDG PET SUV at every voxel was conducted, from which Pearson linear correlation coefficients and regression slopes were extracted. Spearman rank correlation coefficients were estimated between radiation dose to lung and normalized SPECT uptake. Dosimetric differences between treatment modalities were evaluated by Friedman nonparametric paired test with multiple sampling correction. RESULTS No unacceptable violations of PTV and normal tissue objectives were observed in 24 FLARE RT plans. Compared to reference VMAT plans, FLARE VMAT plans achieved a higher mean dose to BTV (73.7 Gy 98195. 61.3 Gy), higher mean dose to SUVpeak (89.7 Gy vs. 60.8 Gy), and lower mean dose to highly perfused lung (7.3 Gy vs. 14.9 Gy). These dosimetric gains came at the expense of higher mean heart dose (9.4 Gy vs. 5.8 Gy) and higher maximum cord dose (50.1 Gy vs. 44.6 Gy) relative to the reference VMAT plans. Between FLARE plans, FLARE VMAT achieved higher dose to the SUVpeak ROI than FLARE PBS (89.7 Gy vs. 79.2 Gy, P = 0.01), while FLARE PBS delivered lower dose to lung than FLARE VMAT (11.9 Gy vs. 15.6 Gy, P < 0.001). Voxelwise linear dose redistribution slope between BTV dose and FDG PET uptake was higher in magnitude for FLARE PBS + VMAT (0.36 Gy per %SUVmax ) compared to FLARE VMAT (0.27 Gy per %SUVmax ) or FLARE PBS alone (0.17 Gy per %SUVmax ). CONCLUSIONS FLARE RT is clinically feasible with VMAT and PBS. A combination of PBS for functional lung avoidance and VMAT for FDG PET dose escalation balanced target and normal tissue objective tradeoffs. These results provide a technical platform for testing of FLARE RT safety and efficacy within a precision radiation oncology trial.
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Affiliation(s)
- Eunsin Lee
- Department of Radiation Oncology, University of Washington School of Medicine, 1959 NE Pacific St, Seattle, WA, 98195, USA
| | - Jing Zeng
- Department of Radiation Oncology, University of Washington School of Medicine, 1959 NE Pacific St, Seattle, WA, 98195, USA
| | - Robert S Miyaoka
- Department of Radiology, University of Washington School of Medicine, 1959 NE Pacific St, Seattle, WA, 98195, USA
| | - Jatinder Saini
- Seattle Cancer Care Alliance Proton Therapy Center, 1570 N 115th Ave, Seattle, WA, 98133, USA
| | - Paul E Kinahan
- Department of Radiology, University of Washington School of Medicine, 1959 NE Pacific St, Seattle, WA, 98195, USA
| | - George A Sandison
- Department of Radiation Oncology, University of Washington School of Medicine, 1959 NE Pacific St, Seattle, WA, 98195, USA
| | - Tony Wong
- Seattle Cancer Care Alliance Proton Therapy Center, 1570 N 115th Ave, Seattle, WA, 98133, USA
| | - Hubert J Vesselle
- Department of Radiology, University of Washington School of Medicine, 1959 NE Pacific St, Seattle, WA, 98195, USA
| | - Ramesh Rengan
- Department of Radiation Oncology, University of Washington School of Medicine, 1959 NE Pacific St, Seattle, WA, 98195, USA
| | - Stephen R Bowen
- Departments of Radiation Oncology and Radiology, University of Washington School of Medicine, 1959 NE Pacific St, Seattle, WA, 98195, USA
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Waxweiler T, Schubert L, Diot Q, Faught A, Stuhr K, Castillo R, Castillo E, Guerrero T, Rusthoven C, Gaspar L, Kavanagh B, Miften M, Vinogradskiy Y. A complete 4DCT-ventilation functional avoidance virtual trial: Developing strategies for prospective clinical trials. J Appl Clin Med Phys 2017; 18:144-152. [PMID: 28436107 PMCID: PMC5689844 DOI: 10.1002/acm2.12086] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2016] [Revised: 01/30/2017] [Accepted: 03/08/2017] [Indexed: 12/25/2022] Open
Abstract
Introduction 4DCT‐ventilation is an exciting new imaging modality that uses 4DCT data to calculate lung‐function maps. Because 4DCTs are acquired as standard of care for lung cancer patients undergoing radiotherapy, 4DCT‐ventiltation provides functional information at no extra dosimetric or monetary cost to the patient. The development of clinical trials is underway to use 4DCT‐ventilation imaging to spare functional lung in patients undergoing radiotherapy. The purpose of this work was to perform a virtual trial using retrospective data to develop the practical aspects of a 4DCT‐ventilation functional avoidance clinical trial. Methods The study included 96 stage III lung cancer patients. A 4DCT‐ventilation map was calculated using the patient's 4DCT‐imaging, deformable registration, and a density‐change‐based algorithm. Clinical trial inclusion assessment used quantitative and qualitative metrics based on the patient's spatial ventilation profile. Clinical and functional plans were generated for 25 patients. The functional plan aimed to reduce dose to functional lung while meeting standard target and critical structure constraints. Standard and dose‐function metrics were compared between the clinical and functional plans. Results Our data showed that 69% and 59% of stage III patients have regional variability in function based on qualitative and quantitative metrics, respectively. Functional planning demonstrated an average reduction of 2.8 Gy (maximum 8.2 Gy) in the mean dose to functional lung. Conclusions Our work demonstrated that 60–70% of stage III patients would be eligible for functional planning and that a typical functional lung mean dose reduction of 2.8 Gy can be expected relative to standard clinical plans. These findings provide salient data for the development of functional clinical trials.
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Affiliation(s)
- Timothy Waxweiler
- Department of Radiation Oncology, University of Colorado School of Medicine, Aurora, CO, USA
| | - Leah Schubert
- Department of Radiation Oncology, University of Colorado School of Medicine, Aurora, CO, USA
| | - Quentin Diot
- Department of Radiation Oncology, University of Colorado School of Medicine, Aurora, CO, USA
| | - Austin Faught
- Department of Radiation Oncology, University of Colorado School of Medicine, Aurora, CO, USA
| | - Kelly Stuhr
- Department of Radiation Oncology, University of Colorado School of Medicine, Aurora, CO, USA
| | - Richard Castillo
- Department of Radiation Oncology, University of Texas Medical Branch, Galveston, TX, USA
| | - Edward Castillo
- Department of Radiation Oncology, Beaumont Health System, Royal Oak, MI, USA
| | - Thomas Guerrero
- Department of Radiation Oncology, Beaumont Health System, Royal Oak, MI, USA
| | - Chad Rusthoven
- Department of Radiation Oncology, University of Colorado School of Medicine, Aurora, CO, USA
| | - Laurie Gaspar
- Department of Radiation Oncology, University of Colorado School of Medicine, Aurora, CO, USA
| | - Brian Kavanagh
- Department of Radiation Oncology, University of Colorado School of Medicine, Aurora, CO, USA
| | - Moyed Miften
- Department of Radiation Oncology, University of Colorado School of Medicine, Aurora, CO, USA
| | - Yevgeniy Vinogradskiy
- Department of Radiation Oncology, University of Colorado School of Medicine, Aurora, CO, USA
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Lutz CM, Møller DS, Hoffmann L, Knap MM, Alber M. Reliability of dose volume constraint inference from clinical data. Phys Med Biol 2017; 62:3250-3262. [PMID: 28350545 DOI: 10.1088/1361-6560/aa63d4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Dose volume histogram points (DVHPs) frequently serve as dose constraints in radiotherapy treatment planning. An experiment was designed to investigate the reliability of DVHP inference from clinical data for multiple cohort sizes and complication incidence rates. The experimental background was radiation pneumonitis in non-small cell lung cancer and the DVHP inference method was based on logistic regression. From 102 NSCLC real-life dose distributions and a postulated DVHP model, an 'ideal' cohort was generated where the most predictive model was equal to the postulated model. A bootstrap and a Cohort Replication Monte Carlo (CoRepMC) approach were applied to create 1000 equally sized populations each. The cohorts were then analyzed to establish inference frequency distributions. This was applied to nine scenarios for cohort sizes of 102 (1), 500 (2) to 2000 (3) patients (by sampling with replacement) and three postulated DVHP models. The Bootstrap was repeated for a 'non-ideal' cohort, where the most predictive model did not coincide with the postulated model. The Bootstrap produced chaotic results for all models of cohort size 1 for both the ideal and non-ideal cohorts. For cohort size 2 and 3, the distributions for all populations were more concentrated around the postulated DVHP. For the CoRepMC, the inference frequency increased with cohort size and incidence rate. Correct inference rates >[Formula: see text] were only achieved by cohorts with more than 500 patients. Both Bootstrap and CoRepMC indicate that inference of the correct or approximate DVHP for typical cohort sizes is highly uncertain. CoRepMC results were less spurious than Bootstrap results, demonstrating the large influence that randomness in dose-response has on the statistical analysis.
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Affiliation(s)
- C M Lutz
- Department of Oncology, Aarhus University Hospital, Aarhus, Denmark
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