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Bissonnette JP, Sun A, Grills IS, Almahariq MF, Geiger G, Vogel W, Sonke JJ, Everitt S, Manus MM. Non-small cell lung cancer stage migration as a function of wait times from diagnostic imaging: A pooled analysis from five international centres. Lung Cancer 2021; 155:136-143. [PMID: 33819859 DOI: 10.1016/j.lungcan.2021.03.017] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Revised: 03/10/2021] [Accepted: 03/21/2021] [Indexed: 12/24/2022]
Abstract
INTRODUCTION Patients with non-small cell lung cancer (NSCLC) can experience rapid disease progression between initial staging FDG-PET scans and commencement of curative-intent radiotherapy (RT). Previous studies that estimated stage migration rates by comparing staging PET/CT and treatment-planning PET/CT images were limited by small sample sizes. METHODS This multicenter, international study combined prospective data from five institutions for PET-staged patients with NSCLC who were intended to receive curative-intent RT. TNM status was compared for staging and RT planning scans and the probability of TNM status and overall stage migration was analyzed as a function of the interval between PET/CT scans. The impacts of N classification, overall stage, and pathology were also studied. RESULTS Pooled data from 181 patients were analyzed. The median interval between PET/CT scans was 42 days (range, 2-208). Upstaging occurred in 32 % of patients. The overall rate of stage migration was higher for patients presenting with initial stage IIIB/IIIC disease (p = 0.006) and patients with N2-3 nodal disease (p = 0.019). Upstaging to M1 disease was significantly associated with initial stage IIIB/IIIC disease (HR = 15.2) and adenocarcinoma (HR = 10) histology. CONCLUSION Longer intervals between imaging and treatment in patients with NSCLC were associated with high rates disease progression with consequent risks of geographic miss in RT planning and futile treatment in patients with M1 disease. Patients with more extensive initial nodal involvement and those with adenocarcinoma had the highest rates of stage migration. Dedicated RT planning PET/CT imaging is recommended, especially if >3 weeks have elapsed after initial staging.
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Affiliation(s)
- Jean-Pierre Bissonnette
- Department of Medical Physics, Princess Margaret Hospital Cancer Centre, Toronto, Ontario, Canada; Department of Radiation Oncology and Department of Medical Biophysics, University of Toronto, Techna Institute, Toronto, Ontario, Canada; Department of Radiation Oncology, Princess Margaret Hospital Cancer Centre, Toronto, Ontario, Canada; Department of Radiation Oncology, University of Toronto, Radiation Oncology, Toronto, Ontario, Canada. https://twitter.com/@JeanPierreBiss2
| | - Alexander Sun
- Department of Radiation Oncology, Princess Margaret Hospital Cancer Centre, Toronto, Ontario, Canada; Department of Radiation Oncology, University of Toronto, Radiation Oncology, Toronto, Ontario, Canada
| | - Inga S Grills
- Department of Radiation Oncology, Beaumont Hospitals, Royal Oak, MI, United States
| | - Muayad F Almahariq
- Department of Radiation Oncology, Beaumont Hospitals, Royal Oak, MI, United States
| | - Geoffrey Geiger
- Department of Radiation Oncology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - Wouter Vogel
- Department of Radiation Oncology, Netherlands Cancer Institute, Amsterdam, the Netherlands; Department of Nuclear Medicine, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Jan-Jakob Sonke
- Department of Radiation Oncology, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Sarah Everitt
- Department of Radiation Therapy, Peter MacCallum Cancer Centre, Melbourne, Australia; Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Australia
| | - Michael Mac Manus
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Australia; Department of Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, Australia
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2
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Duan C, Chaovalitwongse WA, Bai F, Hippe DS, Wang S, Thammasorn P, Pierce LA, Liu X, You J, Miyaoka RS, Vesselle HJ, Kinahan PE, Rengan R, Zeng J, Bowen SR. Sensitivity analysis of FDG PET tumor voxel cluster radiomics and dosimetry for predicting mid-chemoradiation regional response of locally advanced lung cancer. Phys Med Biol 2020; 65:205007. [PMID: 33027064 PMCID: PMC7593986 DOI: 10.1088/1361-6560/abb0c7] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
We investigated the sensitivity of regional tumor response prediction to variability in voxel clustering techniques, imaging features, and machine learning algorithms in 25 patients with locally advanced non-small cell lung cancer (LA-NSCLC) enrolled on the FLARE-RT clinical trial. Metabolic tumor volumes (MTV) from pre-chemoradiation (PETpre) and mid-chemoradiation fluorodeoxyglucose-positron emission tomography (FDG PET) images (PETmid) were subdivided into K-means or hierarchical voxel clusters by standardized uptake values (SUV) and 3D-positions. MTV cluster separability was evaluated by CH index, and morphologic changes were captured by Dice similarity and centroid Euclidean distance. PETpre conventional features included SUVmean, MTV/MTV cluster size, and mean radiation dose. PETpre radiomics consisted of 41 intensity histogram and 3D texture features (PET Oncology Radiomics Test Suite) extracted from MTV or MTV clusters. Machine learning models (multiple linear regression, support vector regression, logistic regression, support vector machines) of conventional features or radiomic features were constructed to predict PETmid response. Leave-one-out-cross-validated root-mean-squared-error (RMSE) for continuous response regression (ΔSUVmean) and area-under-receiver-operating-characteristic-curve (AUC) for binary response classification were calculated. K-means MTV 2-clusters (MTVhi, MTVlo) achieved maximum CH index separability (Friedman p < 0.001). Between PETpre and PETmid, MTV cluster pairs overlapped (Dice 0.70-0.87) and migrated 0.6-1.1 cm. PETmid ΔSUVmean response prediction was superior in MTV and MTVlo (RMSE = 0.17-0.21) compared to MTVhi (RMSE = 0.42-0.52, Friedman p < 0.001). PETmid ΔSUVmean response class prediction performance trended higher in MTVlo (AUC = 0.83-0.88) compared to MTVhi (AUC = 0.44-0.58, Friedman p = 0.052). Models were more sensitive to MTV/MTV cluster regions (Friedman p = 0.026) than feature sets/algorithms (Wilcoxon signed-rank p = 0.36). Top-ranked radiomic features included GLZSM-LZHGE (large-zone-high-SUV), GTSDM-CP (cluster-prominence), GTSDM-CS (cluster-shade) and NGTDM-CNT (contrast). Top-ranked features were consistent between MTVhi and MTVlo cluster pairs but varied between MTVhi-MTVlo clusters, reflecting distinct regional radiomic phenotypes. Variability in tumor voxel cluster response prediction can inform robust radiomic target definition for risk-adaptive chemoradiation in patients with LA-NSCLC. FLARE-RT trial: NCT02773238.
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Affiliation(s)
- Chunyan Duan
- Department of Mechanical Engineering, Tongji University School of Mechanical Engineering, Shanghai China
- Department of Industrial Engineering, University of Arkansas College of Engineering, Fayetteville AR
- Department of Radiation Oncology, University of Washington School of Medicine, Seattle WA
| | - W. Art Chaovalitwongse
- Department of Industrial Engineering, University of Arkansas College of Engineering, Fayetteville AR
| | - Fangyun Bai
- Department of Management Science and Engineering, Tongji University School of Economics and Management, Shanghai China
- Department of Industrial, Manufacturing, & Systems Engineering, University of Texas at Arlington College of Engineering, Arlington, TX
| | - Daniel S. Hippe
- Department of Radiology, University of Washington School of Medicine, Seattle WA
| | - Shouyi Wang
- Department of Industrial, Manufacturing, & Systems Engineering, University of Texas at Arlington College of Engineering, Arlington, TX
| | - Phawis Thammasorn
- Department of Industrial Engineering, University of Arkansas College of Engineering, Fayetteville AR
| | - Larry A. Pierce
- Department of Radiology, University of Washington School of Medicine, Seattle WA
| | - Xiao Liu
- Department of Industrial Engineering, University of Arkansas College of Engineering, Fayetteville AR
| | - Jianxin You
- Department of Management Science and Engineering, Tongji University School of Economics and Management, Shanghai China
| | - Robert S. Miyaoka
- Department of Radiology, University of Washington School of Medicine, Seattle WA
| | - Hubert J. Vesselle
- Department of Radiology, University of Washington School of Medicine, Seattle WA
| | - Paul E. Kinahan
- Department of Radiology, University of Washington School of Medicine, Seattle WA
| | - Ramesh Rengan
- Department of Radiation Oncology, University of Washington School of Medicine, Seattle WA
| | - Jing Zeng
- Department of Radiation Oncology, University of Washington School of Medicine, Seattle WA
| | - Stephen R. Bowen
- Department of Radiation Oncology, University of Washington School of Medicine, Seattle WA
- Department of Radiology, University of Washington School of Medicine, Seattle WA
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3
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Unterrainer M, Eze C, Ilhan H, Marschner S, Roengvoraphoj O, Schmidt-Hegemann NS, Walter F, Kunz WG, Rosenschöld PMA, Jeraj R, Albert NL, Grosu AL, Niyazi M, Bartenstein P, Belka C. Recent advances of PET imaging in clinical radiation oncology. Radiat Oncol 2020; 15:88. [PMID: 32317029 PMCID: PMC7171749 DOI: 10.1186/s13014-020-01519-1] [Citation(s) in RCA: 77] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2020] [Accepted: 03/19/2020] [Indexed: 12/25/2022] Open
Abstract
Radiotherapy and radiation oncology play a key role in the clinical management of patients suffering from oncological diseases. In clinical routine, anatomic imaging such as contrast-enhanced CT and MRI are widely available and are usually used to improve the target volume delineation for subsequent radiotherapy. Moreover, these modalities are also used for treatment monitoring after radiotherapy. However, some diagnostic questions cannot be sufficiently addressed by the mere use standard morphological imaging. Therefore, positron emission tomography (PET) imaging gains increasing clinical significance in the management of oncological patients undergoing radiotherapy, as PET allows the visualization and quantification of tumoral features on a molecular level beyond the mere morphological extent shown by conventional imaging, such as tumor metabolism or receptor expression. The tumor metabolism or receptor expression information derived from PET can be used as tool for visualization of tumor extent, for assessing response during and after therapy, for prediction of patterns of failure and for definition of the volume in need of dose-escalation. This review focuses on recent and current advances of PET imaging within the field of clinical radiotherapy / radiation oncology in several oncological entities (neuro-oncology, head & neck cancer, lung cancer, gastrointestinal tumors and prostate cancer) with particular emphasis on radiotherapy planning, response assessment after radiotherapy and prognostication.
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Affiliation(s)
- M Unterrainer
- Department of Nuclear Medicine, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany. .,Department of Radiology, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany. .,German Cancer Consortium (DKTK), partner site Munich; and German Cancer Research Center (DKFZ), Heidelberg, Germany.
| | - C Eze
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - H Ilhan
- Department of Nuclear Medicine, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany
| | - S Marschner
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - O Roengvoraphoj
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - N S Schmidt-Hegemann
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - F Walter
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - W G Kunz
- Department of Radiology, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany
| | - P Munck Af Rosenschöld
- Radiation Physics, Department of Hematology, Oncology and Radiation Physics, Skåne University Hospital, and Lund University, Lund, Sweden
| | - R Jeraj
- Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, USA
| | - N L Albert
- Department of Nuclear Medicine, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.,German Cancer Consortium (DKTK), partner site Munich; and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - A L Grosu
- Department of Radiation Oncology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.,German Cancer Consortium (DKTK), partner Site Freiburg, Freiburg, Germany
| | - M Niyazi
- German Cancer Consortium (DKTK), partner site Munich; and German Cancer Research Center (DKFZ), Heidelberg, Germany.,Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - P Bartenstein
- Department of Nuclear Medicine, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.,German Cancer Consortium (DKTK), partner site Munich; and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - C Belka
- German Cancer Consortium (DKTK), partner site Munich; and German Cancer Research Center (DKFZ), Heidelberg, Germany.,Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
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4
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Konert T, Vogel WV, Paez D, Polo A, Fidarova E, Carvalho H, Duarte PS, Zuliani AC, Santos AO, Altuhhova D, Karusoo L, Kapoor R, Sood A, Khader J, Al-Ibraheem A, Numair Y, Abubaker S, Soydal C, Kütük T, Le TA, Canh NX, Bieu BQ, Ha LN, Belderbos JSA, MacManus MP, Thorwarth D, Hanna GG. Introducing FDG PET/CT-guided chemoradiotherapy for stage III NSCLC in low- and middle-income countries: preliminary results from the IAEA PERTAIN trial. Eur J Nucl Med Mol Imaging 2019; 46:2235-2243. [PMID: 31367906 PMCID: PMC6717604 DOI: 10.1007/s00259-019-04421-5] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2019] [Accepted: 06/30/2019] [Indexed: 12/24/2022]
Abstract
Purpose Patients with stage III non-small-cell lung cancer (NSCLC) treated with chemoradiotherapy (CRT) in low- and middle-income countries (LMIC) continue to have a poor prognosis. It is known that FDG PET/CT improves staging, treatment selection and target volume delineation (TVD), and although its use has grown rapidly, it is still not widely available in LMIC. CRT is often used as sequential treatment, but is known to be more effective when given concurrently. The aim of the PERTAIN study was to assess the impact of introducing FDG PET/CT-guided concurrent CRT, supported by training and quality control (QC), on the overall survival (OS) and progression-free survival (PFS) of patients with stage III NSCLC. Methods The study included patients with stage III NSCLC from nine medical centres in seven countries. A retrospective cohort was managed according to local practices between January 2010 and July 2014, which involved only optional diagnostic FDG PET/CT for staging (not for TVD), followed by sequential or concurrent CRT. A prospective cohort between August 2015 and October 2018 was treated according to the study protocol including FDG PET/CT in treatment position for staging and multimodal TVD followed by concurrent CRT by specialists trained in protocol-specific TVD and with TVD QC. Kaplan–Meier analysis was used to assess OS and PFS in the retrospective and prospective cohorts. Results Guidelines for FDG PET/CT image acquisition and TVD were developed and published. All specialists involved in the PERTAIN study received training between June 2014 and May 2016. The PET/CT scanners used received EARL accreditation. In November 2018 a planned interim analysis was performed including 230 patients in the retrospective cohort with a median follow-up of 14 months and 128 patients in the prospective cohort, of whom 69 had a follow-up of at least 1 year. Using the Kaplan–Meier method, OS was significantly longer in the prospective cohort than in the retrospective cohort (23 vs. 14 months, p = 0.012). In addition, median PFS was significantly longer in the prospective cohort than in the retrospective cohort (17 vs. 11 months, p = 0.012). Conclusion In the PERTAIN study, the preliminary results indicate that introducing FDG PET/CT-guided concurrent CRT for patients with stage III NSCLC in LMIC resulted in a significant improvement in OS and PFS. The final study results based on complete data are expected in 2020. Electronic supplementary material The online version of this article (10.1007/s00259-019-04421-5) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- T Konert
- Nuclear Medicine Department, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands.
| | - W V Vogel
- Nuclear Medicine Department, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands.,Department of Radiation Oncology, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - D Paez
- Division of Human Health, Department of Nuclear Sciences and Applications, International Atomic Energy Agency, Vienna, Austria
| | - A Polo
- Division of Human Health, Department of Nuclear Sciences and Applications, International Atomic Energy Agency, Vienna, Austria
| | - E Fidarova
- Division of Human Health, Department of Nuclear Sciences and Applications, International Atomic Energy Agency, Vienna, Austria
| | - H Carvalho
- Department of Radiology and Oncology, Faculty of Medicine, University of São Paulo - Institute of Cancer of Sao Paulo State, São Paulo, Brazil
| | - P S Duarte
- Department of Radiology and Oncology, Faculty of Medicine, University of São Paulo - Institute of Cancer of Sao Paulo State, São Paulo, Brazil
| | - A C Zuliani
- Department of Radiation Oncology and Nuclear Medicine Department, Hospital das Clínicas, Campinas University, Campinas, Brazil
| | - A O Santos
- Department of Radiation Oncology and Nuclear Medicine Department, Hospital das Clínicas, Campinas University, Campinas, Brazil
| | - D Altuhhova
- Department of Radiation Oncology and Radiology Department, North Estonia Medical Center, Tallinn, Estonia
| | - L Karusoo
- Department of Radiation Oncology and Radiology Department, North Estonia Medical Center, Tallinn, Estonia
| | - R Kapoor
- Department of Radiation Oncology and Nuclear Medicine Department, Postgraduate Institute of Medical Education and Research, Chandigarh, India
| | - A Sood
- Department of Radiation Oncology and Nuclear Medicine Department, Postgraduate Institute of Medical Education and Research, Chandigarh, India
| | - J Khader
- Department of Radiation Oncology and Nuclear Medicine Department, King Hussein Cancer Center, Amman, Jordan
| | - A Al-Ibraheem
- Department of Radiation Oncology and Nuclear Medicine Department, King Hussein Cancer Center, Amman, Jordan
| | - Y Numair
- Department of Radiation Oncology and Nuclear Medicine Department, Institute of Nuclear Medicine and Oncology, Lahore, Pakistan
| | - S Abubaker
- Department of Radiation Oncology and Nuclear Medicine Department, Institute of Nuclear Medicine and Oncology, Lahore, Pakistan
| | - C Soydal
- Department of Radiation Oncology and Nuclear Medicine Department, Ankara University School of Medicine, Mamak/Ankara, Turkey
| | - T Kütük
- Department of Radiation Oncology and Nuclear Medicine Department, Ankara University School of Medicine, Mamak/Ankara, Turkey
| | - T A Le
- Department of Radiation Oncology and Nuclear Medicine Department, Cho Ray Hospital, University of Ho Chi Minh City, Ho Chi Minh City, Vietnam
| | - N X Canh
- Department of Radiation Oncology and Nuclear Medicine Department, Cho Ray Hospital, University of Ho Chi Minh City, Ho Chi Minh City, Vietnam
| | - B Q Bieu
- Department of Radiation Oncology and Radiosurgery, Tran Hung Dao Hospital, Hanoi, Vietnam
| | - L N Ha
- Department of Radiation Oncology and Radiosurgery, Tran Hung Dao Hospital, Hanoi, Vietnam
| | - J S A Belderbos
- Department of Radiation Oncology, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - M P MacManus
- Department of Radiation Oncology, Peter MacCallum Cancer Centre, 305 Grattan Street, Melbourne, VIC, 3000, Australia.,Sir Peter MacCallum Department of Oncology, University of Melbourne, Parkville, Australia
| | - D Thorwarth
- Section for Biomedical Physics, Department of Radiation Oncology, University Hospital Tübingen, Tübingen, Germany
| | - G G Hanna
- Department of Radiation Oncology, Peter MacCallum Cancer Centre, 305 Grattan Street, Melbourne, VIC, 3000, Australia. .,Sir Peter MacCallum Department of Oncology, University of Melbourne, Parkville, Australia.
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5
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Bissonnette JP, Yap ML, Clarke K, Shessel A, Higgins J, Vines D, Atenafu EG, Becker N, Leavens C, Bezjak A, Jaffray DA, Sun A. Serial 4DCT/4DPET imaging to predict and monitor response for locally-advanced non-small cell lung cancer chemo-radiotherapy. Radiother Oncol 2018; 126:347-354. [DOI: 10.1016/j.radonc.2017.11.023] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2017] [Revised: 11/07/2017] [Accepted: 11/27/2017] [Indexed: 12/12/2022]
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Positron emission tomography and computed tomographic imaging (PET/CT) for dose planning purposes of thoracic radiation with curative intent in lung cancer patients: A systematic review and meta-analysis. Radiother Oncol 2017; 123:71-77. [DOI: 10.1016/j.radonc.2017.02.011] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2016] [Revised: 02/07/2017] [Accepted: 02/20/2017] [Indexed: 12/25/2022]
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Multiple training interventions significantly improve reproducibility of PET/CT-based lung cancer radiotherapy target volume delineation using an IAEA study protocol. Radiother Oncol 2016; 121:39-45. [PMID: 27663950 DOI: 10.1016/j.radonc.2016.09.002] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2016] [Revised: 09/01/2016] [Accepted: 09/04/2016] [Indexed: 12/14/2022]
Abstract
BACKGROUND AND PURPOSE To assess the impact of a standardized delineation protocol and training interventions on PET/CT-based target volume delineation (TVD) in NSCLC in a multicenter setting. MATERIAL AND METHODS Over a one-year period, 11 pairs, comprised each of a radiation oncologist and nuclear medicine physician with limited experience in PET/CT-based TVD for NSCLC from nine different countries took part in a training program through an International Atomic Energy Agency (IAEA) study (NCT02247713). Teams delineated gross tumor volume of the primary tumor, during and after training interventions, according to a provided delineation protocol. In-house developed software recorded the performed delineations, to allow visual inspection of strategies and to assess delineation accuracy. RESULTS Following the first training, overall concordance indices for 3 repetitive cases increased from 0.57±0.07 to 0.66±0.07. The overall mean surface distance between observer and expert contours decreased from -0.40±0.03cm to -0.01±0.33cm. After further training overall concordance indices for another 3 repetitive cases further increased from 0.64±0.06 to 0.80±0.05 (p=0.01). Mean surface distances decreased from -0.34±0.16cm to -0.05±0.20cm (p=0.01). CONCLUSION Multiple training interventions improve PET/CT-based TVD delineation accuracy in NSCLC and reduce interobserver variation.
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8
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Fleckenstein J, Jelden M, Kremp S, Jagoda P, Stroeder J, Khreish F, Ezziddin S, Buecker A, Rübe C, Schneider GK. The Impact of Diffusion-Weighted MRI on the Definition of Gross Tumor Volume in Radiotherapy of Non-Small-Cell Lung Cancer. PLoS One 2016; 11:e0162816. [PMID: 27612171 PMCID: PMC5017760 DOI: 10.1371/journal.pone.0162816] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2016] [Accepted: 08/29/2016] [Indexed: 12/25/2022] Open
Abstract
Objective The study was designed to evaluate diffusion-weighted magnetic resonance imaging (DWI) vs. PET-CT of the thorax in the determination of gross tumor volume (GTV) in radiotherapy planning of non-small-cell lung cancer (NSCLC). Materials and Methods Eligible patients with NSCLC who were supposed to receive definitive radio(chemo)therapy were prospectively recruited. For MRI, a respiratory gated T2-weighted sequence in axial orientation and non-gated DWI (b = 0, 800, 1,400 and apparent diffusion coefficient map [ADC]) were acquired on a 1.5 Tesla scanner. Primary tumors were delineated on FDG-PET/CT (stGTV) and DWI images (dwGTV). The definition of stGTV was based on the CT and visually adapted to the FDG-PET component if indicated (e.g., in atelectasis). For DWI, dwGTV was visually determined and adjusted for anatomical plausibility on T2w sequences. Beside a statistical comparison of stGTV and dwGTB, spatial agreement was determined with the “Hausdorff-Distance” (HD) and the “Dice Similarity Coefficient” (DSC). Results Fifteen patients (one patient with two synchronous NSCLC) were evaluated. For 16 primary tumors with UICC stages I (n = 4), II (n = 3), IIIA (n = 2) and IIIB (n = 7) mean values for dwGTV were significantly larger than those of stGTV (76.6 ± 84.5 ml vs. 66.6 ± 75.2 ml, p<0.01). The correlation of stGTV and dwGTV was highly significant (r = 0.995, p<0.001). Yet, some considerable volume deviations between these two methods were observed (median 27.5%, range 0.4–52.1%). An acceptable agreement between dwGTV and stGTV regarding the spatial extent of primary tumors was found (average HD: 2.25 ± 0.7 mm; DC 0.68 ± 0.09). Conclusion The overall level of agreement between PET-CT and MRI based GTV definition is acceptable. Tumor volumes may differ considerably in single cases. DWI-derived GTVs are significantly, yet modestly, larger than their PET-CT based counterparts. Prospective studies to assess the safety and efficacy of DWI-based radiotherapy planning in NSCLC are warranted.
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Affiliation(s)
- Jochen Fleckenstein
- Department of Radiotherapy and Radiation Oncology, Saarland University Medical Center, Homburg, Germany
- * E-mail:
| | - Michael Jelden
- Department of Radiotherapy and Radiation Oncology, Saarland University Medical Center, Homburg, Germany
| | - Stephanie Kremp
- Department of Radiotherapy and Radiation Oncology, Saarland University Medical Center, Homburg, Germany
| | - Philippe Jagoda
- Department of Diagnostic and Interventional Radiology, Saarland University Medical Center, Homburg, Germany
| | - Jonas Stroeder
- Department of Diagnostic and Interventional Radiology, Saarland University Medical Center, Homburg, Germany
| | - Fadi Khreish
- Department of Nuclear Medicine, Saarland University Medical Center, Homburg, Germany
| | - Samer Ezziddin
- Department of Nuclear Medicine, Saarland University Medical Center, Homburg, Germany
| | - Arno Buecker
- Department of Nuclear Medicine, Saarland University Medical Center, Homburg, Germany
| | - Christian Rübe
- Department of Radiotherapy and Radiation Oncology, Saarland University Medical Center, Homburg, Germany
| | - Guenther K. Schneider
- Department of Diagnostic and Interventional Radiology, Saarland University Medical Center, Homburg, Germany
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9
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PET/CT imaging for target volume delineation in curative intent radiotherapy of non-small cell lung cancer: IAEA consensus report 2014. Radiother Oncol 2015; 116:27-34. [PMID: 25869338 DOI: 10.1016/j.radonc.2015.03.014] [Citation(s) in RCA: 106] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2014] [Revised: 03/09/2015] [Accepted: 03/15/2015] [Indexed: 12/20/2022]
Abstract
This document describes best practice and evidence based recommendations for the use of FDG-PET/CT for the purposes of radiotherapy target volume delineation (TVD) for curative intent treatment of non-small cell lung cancer (NSCLC). These recommendations have been written by an expert advisory group, convened by the International Atomic Energy Agency (IAEA) to facilitate a Coordinated Research Project (CRP) aiming to improve the applications of PET based radiation treatment planning (RTP) in low and middle income countries. These guidelines can be applied in routine clinical practice of radiotherapy TVD, for NSCLC patients treated with concurrent chemoradiation or radiotherapy alone, where FDG is used, and where a calibrated PET camera system equipped for RTP patient positioning is available. Recommendations are provided for PET and CT image visualization and interpretation, and for tumor delineation using planning CT with and without breathing motion compensation.
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Bongers ML, de Ruysscher D, Oberije C, Lambin P, Uyl-de Groot CA, Coupé VMH. Multistate Statistical Modeling: A Tool to Build a Lung Cancer Microsimulation Model That Includes Parameter Uncertainty and Patient Heterogeneity. Med Decis Making 2015; 36:86-100. [PMID: 25732723 DOI: 10.1177/0272989x15574500] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2013] [Accepted: 01/27/2015] [Indexed: 12/31/2022]
Abstract
With the shift toward individualized treatment, cost-effectiveness models need to incorporate patient and tumor characteristics that may be relevant to treatment planning. In this study, we used multistate statistical modeling to inform a microsimulation model for cost-effectiveness analysis of individualized radiotherapy in lung cancer. The model tracks clinical events over time and takes patient and tumor features into account. Four clinical states were included in the model: alive without progression, local recurrence, metastasis, and death. Individual patients were simulated by repeatedly sampling a patient profile, consisting of patient and tumor characteristics. The transitioning of patients between the health states is governed by personalized time-dependent hazard rates, which were obtained from multistate statistical modeling (MSSM). The model simulations for both the individualized and conventional radiotherapy strategies demonstrated internal and external validity. Therefore, MSSM is a useful technique for obtaining the correlated individualized transition rates that are required for the quantification of a microsimulation model. Moreover, we have used the hazard ratios, their 95% confidence intervals, and their covariance to quantify the parameter uncertainty of the model in a correlated way. The obtained model will be used to evaluate the cost-effectiveness of individualized radiotherapy treatment planning, including the uncertainty of input parameters. We discuss the model-building process and the strengths and weaknesses of using MSSM in a microsimulation model for individualized radiotherapy in lung cancer.
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Affiliation(s)
- Mathilda L Bongers
- Department of Epidemiology and Biostatistics, VU University Medical Center, the Netherlands (MLB, CAUG, VMHC)
| | - Dirk de Ruysscher
- Radiation Oncology, University Hospitals Leuven/KU Leuven, Belgium (DDR),Department of Radiation Oncology (MAASTRO), GROW Research Institute, Maastricht University Medical Centre, the Netherlands (DDR, CO, PL)
| | - Cary Oberije
- Department of Radiation Oncology (MAASTRO), GROW Research Institute, Maastricht University Medical Centre, the Netherlands (DDR, CO, PL)
| | - Philippe Lambin
- Department of Radiation Oncology (MAASTRO), GROW Research Institute, Maastricht University Medical Centre, the Netherlands (DDR, CO, PL)
| | - Carin A Uyl-de Groot
- Department of Epidemiology and Biostatistics, VU University Medical Center, the Netherlands (MLB, CAUG, VMHC),Institute for Medical Technology Assessment, Erasmus University Rotterdam, the Netherlands (CAUG)
| | - V M H Coupé
- Department of Epidemiology and Biostatistics, VU University Medical Center, the Netherlands (MLB, CAUG, VMHC)
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Defining Target Volumes for Stereotactic Ablative Radiotherapy of Early-stage Lung Tumours: A Comparison of Three-dimensional 18F-fluorodeoxyglucose Positron Emission Tomography and Four-dimensional Computed Tomography. Clin Oncol (R Coll Radiol) 2012; 24:e71-80. [DOI: 10.1016/j.clon.2012.03.002] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2011] [Revised: 01/15/2012] [Accepted: 03/08/2012] [Indexed: 12/21/2022]
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