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Yap WK, Hsu KH, Wang TH, Lin CH, Kang CJ, Huang SM, Lin HC, Hung TM, Chang KP, Tsai TY. The prognostic value of lymph node to primary tumor standardized uptake value ratio in cancer patients: a meta-analysis. Ann Nucl Med 2024; 38:607-618. [PMID: 38724805 DOI: 10.1007/s12149-024-01933-5] [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: 03/22/2024] [Accepted: 04/16/2024] [Indexed: 07/28/2024]
Abstract
OBJECTIVE The lymph node to primary tumor standardized uptake value ratio (NTR) is an innovative parameter derived from positron emission tomography/computed tomography (PET/CT) scans that captures the intricate relationship between primary tumors and associated lymph nodes. This meta-analysis aimed to investigate the prognostic value of NTR in cancer patients. METHODS A systematic search of PubMed, Cochrane, and Embase databases was conducted to identify studies investigating the association between NTR and survival outcomes in cancer patients. The pooled adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) were calculated using a random-effects model. RESULTS Twelve studies comprising a total of 2037 patients were included in the meta-analysis. Elevated NTR was significantly associated with worse overall survival aHR (2.21, 95% CI 1.63 to 2.99), disease-free survival aHR (3.27, 95% CI 2.12 to 5.05), and distant metastasis-free survival aHR (2.07, 95% CI 1.55 to 2.78) in cancer patients. Subgroup analyses by cancer type showed consistent results across various malignancies, including head and neck squamous cell carcinoma, endometrial carcinoma, lung cancer, breast cancer, and nasopharyngeal carcinoma. CONCLUSIONS This meta-analysis provides evidence for a significant association between elevated NTR and worse survival outcomes in cancer patients. Elevated NTR may serve as a useful prognostic biomarker for cancer patients and could potentially be used to guide treatment decisions and monitor disease progression. Future studies should aim to validate these findings in larger and more diverse patient populations and investigate the underlying mechanisms for the observed association between NTR and survival outcomes.
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Affiliation(s)
- Wing-Keen Yap
- Proton and Radiation Therapy Center, Department of Radiation Oncology, Chang Gung Memorial Hospital-Linkou Medical Center, Chang Gung University, Taoyuan, 333423, Taiwan
| | - Ken-Hao Hsu
- Department of Otolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital, No. 5, Fu-Hsing St. Kwei-Shan, Taoyuan, 333423, Taiwan
| | - Ting-Hao Wang
- Department of Otolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital, No. 5, Fu-Hsing St. Kwei-Shan, Taoyuan, 333423, Taiwan
| | - Chia-Hsin Lin
- Proton and Radiation Therapy Center, Department of Radiation Oncology, Chang Gung Memorial Hospital-Linkou Medical Center, Chang Gung University, Taoyuan, 333423, Taiwan
| | - Chung-Jan Kang
- Department of Otolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital, No. 5, Fu-Hsing St. Kwei-Shan, Taoyuan, 333423, Taiwan
| | - Shih-Ming Huang
- Department of Radiation Oncology, Keelung Chang Gung Memorial Hospital, Keelung, 204, Taiwan
| | - Huan-Chun Lin
- Department of Nuclear Medicine, Chang Gung Memorial Hospital, Linkou Medical Center, Tao-Yuan, Taiwan
| | - Tsung-Min Hung
- Proton and Radiation Therapy Center, Department of Radiation Oncology, Chang Gung Memorial Hospital-Linkou Medical Center, Chang Gung University, Taoyuan, 333423, Taiwan
| | - Kai-Ping Chang
- Department of Otolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital, No. 5, Fu-Hsing St. Kwei-Shan, Taoyuan, 333423, Taiwan
- College of Medicine, Chang Gung University, Taoyuan, 333323, Taiwan
| | - Tsung-You Tsai
- Department of Otolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital, No. 5, Fu-Hsing St. Kwei-Shan, Taoyuan, 333423, Taiwan.
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Huang J, Wang J, Cui B, Yang H, Tian D, Ma J, Duan W, Chen Z, Lu J. The pons as an optimal background reference region for spinal 18F-FET PET/MRI evaluation. EJNMMI Res 2024; 14:69. [PMID: 39060564 PMCID: PMC11282009 DOI: 10.1186/s13550-024-01130-5] [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: 05/24/2024] [Accepted: 07/12/2024] [Indexed: 07/28/2024] Open
Abstract
BACKGROUND This study aims to evaluate the effect of various background reference regions on spinal 18F-FET PET imaging, with a focus on distinguishing between spinal tumors and myelitis. To enhance diagnostic accuracy, we investigated the pons and several other spinal cord area as potential references, given the challenges in interpreting spinal PET results. RESULTS A retrospective analysis was conducted on 30 patients, 15 with cervical myelitis and 15 with cervical tumors, who underwent O-(2-[18F]-fluoroethyl)-L-tyrosine (FET) PET/MR imaging. The stability of uptake across four regions, including the pons, C2, C2-C7, and T1-T3, was compared. The standardized uptake value ratio (SUVR) was then evaluated using various background regions, and their effectiveness in differentiating between spinal tumors and myelitis was compared. Additionally, we correlated the SUVR values derived from these regions with the Ki-67 proliferation index in tumor patients. The study found no significant difference in SUVmax (U = 110, p = 0.93) and SUVmean (U = 89, p = 0.35) values at lesion sites between myelitis and tumor patients. The pons had the highest average uptake (p < 0.001) compared to the other three regions. However, its coefficient of variation (CV) was significantly lower than that of the C2-C7 (p < 0.0001) and T1-T3 segments (p < 0.05). The SUVRmax values, calculated using the regions of pons, C2-C7 and T1-T3, were found to significantly differentiate between tumors and myelitis (p < 0.05). However, only the pons-based SUVRmean was able to significantly distinguish between the two groups (p < 0.05). Additionally, the pons-based SUVRmax (r = 0.63, p = 0.013) and SUVRmean (r = 0.67, p = 0.007) demonstrated a significant positive correlation with the Ki-67 index. CONCLUSIONS This study suggests that the pons may be considered a suitable reference region for spinal 18F-FET PET imaging, which can improve the differentiation between spinal tumors and myelitis. The significant correlation between pons-based SUVR values and the Ki-67 index further highlights the potential of this approach in assessing tumor cell proliferation.
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Affiliation(s)
- Jing Huang
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 45 Changchun Street, Xicheng District, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Capital Medical University, Beijing, China
| | - Jiyuan Wang
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 45 Changchun Street, Xicheng District, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Capital Medical University, Beijing, China
| | - Bixiao Cui
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 45 Changchun Street, Xicheng District, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Capital Medical University, Beijing, China
| | - Hongwei Yang
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 45 Changchun Street, Xicheng District, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Capital Medical University, Beijing, China
| | - Defeng Tian
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 45 Changchun Street, Xicheng District, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Capital Medical University, Beijing, China
| | - Jie Ma
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 45 Changchun Street, Xicheng District, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Capital Medical University, Beijing, China
| | - Wanru Duan
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Zan Chen
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jie Lu
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 45 Changchun Street, Xicheng District, Beijing, China.
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Capital Medical University, Beijing, China.
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Haider SP, Zeevi T, Sharaf K, Gross M, Mahajan A, Kann BH, Judson BL, Prasad ML, Burtness B, Aboian M, Canis M, Reichel CA, Baumeister P, Payabvash S. Impact of 18F-FDG PET Intensity Normalization on Radiomic Features of Oropharyngeal Squamous Cell Carcinomas and Machine Learning-Generated Biomarkers. J Nucl Med 2024; 65:803-809. [PMID: 38514087 DOI: 10.2967/jnumed.123.266637] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 02/13/2024] [Indexed: 03/23/2024] Open
Abstract
We aimed to investigate the effects of 18F-FDG PET voxel intensity normalization on radiomic features of oropharyngeal squamous cell carcinoma (OPSCC) and machine learning-generated radiomic biomarkers. Methods: We extracted 1,037 18F-FDG PET radiomic features quantifying the shape, intensity, and texture of 430 OPSCC primary tumors. The reproducibility of individual features across 3 intensity-normalized images (body-weight SUV, reference tissue activity ratio to lentiform nucleus of brain and cerebellum) and the raw PET data was assessed using an intraclass correlation coefficient (ICC). We investigated the effects of intensity normalization on the features' utility in predicting the human papillomavirus (HPV) status of OPSCCs in univariate logistic regression, receiver-operating-characteristic analysis, and extreme-gradient-boosting (XGBoost) machine-learning classifiers. Results: Of 1,037 features, a high (ICC ≥ 0.90), medium (0.90 > ICC ≥ 0.75), and low (ICC < 0.75) degree of reproducibility across normalization methods was attained in 356 (34.3%), 608 (58.6%), and 73 (7%) features, respectively. In univariate analysis, features from the PET normalized to the lentiform nucleus had the strongest association with HPV status, with 865 of 1,037 (83.4%) significant features after multiple testing corrections and a median area under the receiver-operating-characteristic curve (AUC) of 0.65 (interquartile range, 0.62-0.68). Similar tendencies were observed in XGBoost models, with the lentiform nucleus-normalized model achieving the numerically highest average AUC of 0.72 (SD, 0.07) in the cross validation within the training cohort. The model generalized well to the validation cohorts, attaining an AUC of 0.73 (95% CI, 0.60-0.85) in independent validation and 0.76 (95% CI, 0.58-0.95) in external validation. The AUCs of the XGBoost models were not significantly different. Conclusion: Only one third of the features demonstrated a high degree of reproducibility across intensity-normalization techniques, making uniform normalization a prerequisite for interindividual comparability of radiomic markers. The choice of normalization technique may affect the radiomic features' predictive value with respect to HPV. Our results show trends that normalization to the lentiform nucleus may improve model performance, although more evidence is needed to draw a firm conclusion.
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Affiliation(s)
- Stefan P Haider
- Department of Otorhinolaryngology, LMU Clinic of Ludwig Maximilians University of Munich, Munich, Germany;
- Section of Neuroradiology, Yale School of Medicine, New Haven, Connecticut
| | - Tal Zeevi
- Section of Neuroradiology, Yale School of Medicine, New Haven, Connecticut
| | - Kariem Sharaf
- Department of Otorhinolaryngology, LMU Clinic of Ludwig Maximilians University of Munich, Munich, Germany
| | - Moritz Gross
- Section of Neuroradiology, Yale School of Medicine, New Haven, Connecticut
- Charité Center for Diagnostic and Interventional Radiology, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Amit Mahajan
- Section of Neuroradiology, Yale School of Medicine, New Haven, Connecticut
| | - Benjamin H Kann
- Department of Radiation Oncology, Dana Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts
| | - Benjamin L Judson
- Division of Otolaryngology, Yale School of Medicine, New Haven, Connecticut
| | - Manju L Prasad
- Department of Pathology, Yale School of Medicine, New Haven, Connecticut; and
| | - Barbara Burtness
- Section of Medical Oncology, Yale School of Medicine, New Haven, Connecticut
| | - Mariam Aboian
- Section of Neuroradiology, Yale School of Medicine, New Haven, Connecticut
| | - Martin Canis
- Department of Otorhinolaryngology, LMU Clinic of Ludwig Maximilians University of Munich, Munich, Germany
| | - Christoph A Reichel
- Department of Otorhinolaryngology, LMU Clinic of Ludwig Maximilians University of Munich, Munich, Germany
| | - Philipp Baumeister
- Department of Otorhinolaryngology, LMU Clinic of Ludwig Maximilians University of Munich, Munich, Germany
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Cox MC, Jurcka T, Arens AIJ, van Rijk MC, Kaanders JHAM, van den Bosch S. Quantitative and clinical implications of the EARL2 versus EARL1 [ 18F]FDG PET-CT performance standards in head and neck squamous cell carcinoma. EJNMMI Res 2023; 13:91. [PMID: 37878160 PMCID: PMC10600079 DOI: 10.1186/s13550-023-01042-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Accepted: 10/13/2023] [Indexed: 10/26/2023] Open
Abstract
BACKGROUND The EANM Research Ltd. (EARL) guidelines give recommendations for harmonization of [18F]FDG PET-CT image acquisition and reconstruction, aiming to ensure reproducibility of quantitative data between PET scanners. Recent technological advancements in PET-CT imaging resulted in an updated version of the EARL guidelines (EARL2). The aim of this study is to compare quantitative [18F]FDG uptake metrics of the primary tumor and lymph nodes in patients with head and neck squamous cell carcinoma (HNSCC) on EARL2 versus EARL1 reconstructed images and to describe clinical implications for nodal staging and treatment. METHODS Forty-nine consecutive patients with HNSCC were included. For all, both EARL1 and EARL2 images were reconstructed from a singular [18F]FDG PET-CT scan. Primary tumors and non-necrotic lymph nodes ≥ 5 mm were delineated on CT-scan. In the quantitative analysis, maximum standardized uptake values (SUVmax) and standardized uptake ratios (SURmax, i.e., SUVmax normalized to cervical spinal cord uptake) were calculated for all lesions on EARL1 and EARL2 reconstructions. Metabolic tumor volume (MTV) and total lesion glycolysis were compared between EARL1 and EARL2 using different segmentation methods (adaptive threshold; SUV2.5/3.5/4.5; SUR2.5/3.5/4.5; MAX40%/50%). In the qualitative analysis, each lymph node was scored independently by two nuclear medicine physicians on both EARL1 and EARL2 images on different occasions using a 4-point scale. RESULTS There was a significant increase in SUVmax (16.5%) and SURmax (9.6%) of primary tumor and lymph nodes on EARL2 versus EARL1 imaging (p < 0.001). The proportional difference of both SUVmax and SURmax between EARL2 and EARL1 decreased with increasing tumor volume (p < 0.001). Absolute differences in MTVs between both reconstructions were small (< 1.0 cm3), independent of the segmentation method. MTVs decreased on EARL2 using relative threshold methods (adaptive threshold; MAX40%/50%) and increased using static SUV or SUR thresholds. With visual scoring of lymph nodes 38% (11/29) of nodes with score 2 on EARL1 were upstaged to score 3 on EARL2, which resulted in an alteration of nodal stage in 18% (6/33) of the patients. CONCLUSIONS Using the EARL2 method for PET image reconstruction resulted in higher SUVmax and SURmax compared to EARL1, with nodal upstaging in a significant number of patients.
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Affiliation(s)
- Maurice C. Cox
- Department of Radiation Oncology, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Tijn Jurcka
- Department of Radiation Oncology, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Anne I. J. Arens
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Maartje C. van Rijk
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands
| | | | - Sven van den Bosch
- Department of Radiation Oncology, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
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PET Imaging of Oral Cavity and Oropharyngeal Cancers. PET Clin 2022; 17:223-234. [DOI: 10.1016/j.cpet.2021.12.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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Marschner SN, Lombardo E, Minibek L, Holzgreve A, Kaiser L, Albert NL, Kurz C, Riboldi M, Späth R, Baumeister P, Niyazi M, Belka C, Corradini S, Landry G, Walter F. Risk Stratification Using 18F-FDG PET/CT and Artificial Neural Networks in Head and Neck Cancer Patients Undergoing Radiotherapy. Diagnostics (Basel) 2021; 11:diagnostics11091581. [PMID: 34573924 PMCID: PMC8468242 DOI: 10.3390/diagnostics11091581] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 08/27/2021] [Accepted: 08/28/2021] [Indexed: 12/24/2022] Open
Abstract
This study retrospectively analyzed the performance of artificial neural networks (ANN) to predict overall survival (OS) or locoregional failure (LRF) in HNSCC patients undergoing radiotherapy, based on 2-[18F]FDG PET/CT and clinical covariates. We compared predictions relying on three different sets of features, extracted from 230 patients. Specifically, (i) an automated feature selection method independent of expert rating was compared with (ii) clinical variables with proven influence on OS or LRF and (iii) clinical data plus expert-selected SUV metrics. The three sets were given as input to an artificial neural network for outcome prediction, evaluated by Harrell’s concordance index (HCI) and by testing stratification capability. For OS and LRF, the best performance was achieved with expert-based PET-features (0.71 HCI) and clinical variables (0.70 HCI), respectively. For OS stratification, all three feature sets were significant, whereas for LRF only expert-based PET-features successfully classified low vs. high-risk patients. Based on 2-[18F]FDG PET/CT features, stratification into risk groups using ANN for OS and LRF is possible. Differences in the results for different feature sets confirm the relevance of feature selection, and the key importance of expert knowledge vs. automated selection.
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Affiliation(s)
- Sebastian N. Marschner
- Department of Radiation Oncology, University Hospital, LMU Munich, 81377 Munich, Germany; (L.M.); (R.S.); (M.N.); (C.B.); (S.C.); (F.W.)
- Correspondence:
| | - Elia Lombardo
- Department of Radiation Oncology, University Hospital, LMU Munich, 81377 Munich, Germany; (L.M.); (R.S.); (M.N.); (C.B.); (S.C.); (F.W.)
- Department of Medical Physics, Ludwig-Maximilians-Universität München, Am Coulombwall 1, 85748 Garching, Germany; (E.L.); (C.K.); (M.R.); (G.L.)
| | - Lena Minibek
- Department of Radiation Oncology, University Hospital, LMU Munich, 81377 Munich, Germany; (L.M.); (R.S.); (M.N.); (C.B.); (S.C.); (F.W.)
| | - Adrien Holzgreve
- Department of Nuclear Medicine, University Hospital, LMU Munich, 81377 Munich, Germany; (A.H.); (L.K.); (N.L.A.)
| | - Lena Kaiser
- Department of Nuclear Medicine, University Hospital, LMU Munich, 81377 Munich, Germany; (A.H.); (L.K.); (N.L.A.)
| | - Nathalie L. Albert
- Department of Nuclear Medicine, University Hospital, LMU Munich, 81377 Munich, Germany; (A.H.); (L.K.); (N.L.A.)
| | - Christopher Kurz
- Department of Radiation Oncology, University Hospital, LMU Munich, 81377 Munich, Germany; (L.M.); (R.S.); (M.N.); (C.B.); (S.C.); (F.W.)
- Department of Medical Physics, Ludwig-Maximilians-Universität München, Am Coulombwall 1, 85748 Garching, Germany; (E.L.); (C.K.); (M.R.); (G.L.)
| | - Marco Riboldi
- Department of Medical Physics, Ludwig-Maximilians-Universität München, Am Coulombwall 1, 85748 Garching, Germany; (E.L.); (C.K.); (M.R.); (G.L.)
| | - Richard Späth
- Department of Radiation Oncology, University Hospital, LMU Munich, 81377 Munich, Germany; (L.M.); (R.S.); (M.N.); (C.B.); (S.C.); (F.W.)
| | - Philipp Baumeister
- Department of Otorhinolaryngology, Head and Neck Surgery, University Hospital, LMU Munich, 81377 Munich, Germany;
| | - Maximilian Niyazi
- Department of Radiation Oncology, University Hospital, LMU Munich, 81377 Munich, Germany; (L.M.); (R.S.); (M.N.); (C.B.); (S.C.); (F.W.)
| | - Claus Belka
- Department of Radiation Oncology, University Hospital, LMU Munich, 81377 Munich, Germany; (L.M.); (R.S.); (M.N.); (C.B.); (S.C.); (F.W.)
- German Cancer Consortium (DKTK), Partner Site Munich, 81377 Munich, Germany
| | - Stefanie Corradini
- Department of Radiation Oncology, University Hospital, LMU Munich, 81377 Munich, Germany; (L.M.); (R.S.); (M.N.); (C.B.); (S.C.); (F.W.)
| | - Guillaume Landry
- Department of Radiation Oncology, University Hospital, LMU Munich, 81377 Munich, Germany; (L.M.); (R.S.); (M.N.); (C.B.); (S.C.); (F.W.)
- Department of Medical Physics, Ludwig-Maximilians-Universität München, Am Coulombwall 1, 85748 Garching, Germany; (E.L.); (C.K.); (M.R.); (G.L.)
| | - Franziska Walter
- Department of Radiation Oncology, University Hospital, LMU Munich, 81377 Munich, Germany; (L.M.); (R.S.); (M.N.); (C.B.); (S.C.); (F.W.)
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van den Bosch S, Doornaert PAH, Dijkema T, Zwijnenburg EM, Verhoef LCG, Hoeben BAW, Kasperts N, Smid EJ, Terhaard CHJ, Kaanders JHAM. 18F-FDG-PET/CT-based treatment planning for definitive (chemo)radiotherapy in patients with head and neck squamous cell carcinoma improves regional control and survival. Radiother Oncol 2019; 142:107-114. [PMID: 31439447 DOI: 10.1016/j.radonc.2019.07.025] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2019] [Revised: 07/10/2019] [Accepted: 07/19/2019] [Indexed: 10/26/2022]
Abstract
BACKGROUND AND PURPOSE Multimodality imaging including 18F-FDG-PET has improved the detection threshold of nodal metastases in head and neck squamous cell carcinoma (HNSCC). The aim of this retrospective analysis is to investigate the impact of FDG-PET/CT-based nodal target volume definition (FDG-PET/CT-based NTV) on radiotherapy outcomes, compared to conventional CT-based nodal target volume definition (CT-based NTV). MATERIALS AND METHODS Six-hundred-thirty-three patients treated for HNSCC with definitive (chemo)radiotherapy using IMRT/VMAT techniques between 2008 and 2017 were analyzed. FDG-PET/CT-based NTV was performed in 46% of the patients. The median follow-up was 31 months. Diagnostic imaging depicting the regional recurrence was co-registered with the initial CT-scan to reconstruct the exact site of the recurrence. Multivariate Cox regression analysis was performed to identify variables associated with radiotherapy outcome. RESULTS FDG-PET/CT-based NTV improved control of disease in the CTVelective-nodal (HR: 0.33, p = 0.026), overall regional control (HR: 0.62, p = 0.027) and overall survival (HR: 0.71, p = 0.033) compared to CT-based NTV. The risk for recurrence in the CTVelective-nodal was increased in case of synchronous local recurrence of the primary tumor (HR: 12.4, p < 0.001). CONCLUSION FDG-PET/CT-based NTV significantly improved control of disease in the CTVelective-nodal, overall regional control and overall survival compared to CT-based NTV. A significant proportion of CTVelective-nodal recurrences are potentially new nodal manifestations from a synchronous local recurrent primary tumor. These results support the concept of target volume transformation and give an indication of the potential of FDG-PET to guide gradual radiotherapy dose de-escalation in elective neck treatment in HNSCC.
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Affiliation(s)
- Sven van den Bosch
- Department of Radiation Oncology, Radboud University Medical Center, Nijmegen, The Netherlands.
| | | | - Tim Dijkema
- Department of Radiation Oncology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Ellen M Zwijnenburg
- Department of Radiation Oncology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Lia C G Verhoef
- Department of Radiation Oncology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Bianca A W Hoeben
- Department of Radiation Oncology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Nicolien Kasperts
- Department of Radiation Oncology, University Medical Center Utrecht, The Netherlands
| | - Ernst J Smid
- Department of Radiation Oncology, University Medical Center Utrecht, The Netherlands
| | - Chris H J Terhaard
- Department of Radiation Oncology, University Medical Center Utrecht, The Netherlands
| | - Johannes H A M Kaanders
- Department of Radiation Oncology, Radboud University Medical Center, Nijmegen, The Netherlands
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van den Bosch S, Dijkema T, Kunze-Busch MC, Terhaard CHJ, Raaijmakers CPJ, Doornaert PAH, Hoebers FJP, Vergeer MR, Kreike B, Wijers OB, Oyen WJG, Kaanders JHAM. Uniform FDG-PET guided GRAdient Dose prEscription to reduce late Radiation Toxicity (UPGRADE-RT): study protocol for a randomized clinical trial with dose reduction to the elective neck in head and neck squamous cell carcinoma. BMC Cancer 2017; 17:208. [PMID: 28327089 PMCID: PMC5361684 DOI: 10.1186/s12885-017-3195-7] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2016] [Accepted: 03/14/2017] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND In definitive radiation therapy for head and neck cancer, clinically uninvolved cervical lymph nodes are irradiated with a so-called 'elective dose' in order to achieve control of clinically occult metastases. As a consequence of high-resolution diagnostic imaging, occult tumor volume has significantly decreased in the last decades. Since the elective dose is dependent on occult tumor volume, the currently used elective dose may be higher than necessary. Because bilateral irradiation of the neck contributes to dysphagia, xerostomia and hypothyroidism in a dose dependent way, dose de-escalation to these regions can open a window of opportunity to reduce toxicity and improve quality of life after treatment. METHODS UPGRADE-RT is a multicenter, phase III, single-blinded, randomized controlled trial. Patients to be treated with definitive radiation therapy for a newly diagnosed stage T2-4 N0-2 M0 squamous cell carcinoma of the oropharynx, hypopharynx or larynx are eligible. Exclusion criteria are recurrent disease, oncologic surgery to the head and neck area, concomitant chemotherapy or epidermal growth factor receptor inhibitors. In total, 300 patients will be randomized in a 2:1 ratio to a treatment arm with or without de-escalation of the elective radiation dose and introduction of an intermediate dose-level for selected lymph nodes. Radiation therapy planning FDG-PET/CT-scans will be acquired to guide risk assessment of borderline-sized cervical nodes that can be treated with the intermediate dose level. Treatment will be given with intensity-modulated radiation therapy or volumetric arc therapy with simultaneous-integrated boost using an accelerated fractionation schedule, 33 fractions in 5 weeks. The primary endpoint is 'normalcy of diet' at 1 year after treatment (toxicity). The secondary endpoint is the actuarial rate of recurrence in electively irradiated lymph nodes at 2 years after treatment (safety). DISCUSSION The objective of the UPGRADE-RT trial is to investigate whether de-escalation of elective radiation dose and the introduction of an intermediate dose-level for borderline sized lymph nodes in the treatment of head and neck cancer will result in less radiation sequelae and improved quality of life after treatment without compromising the recurrence rate in the electively treated neck. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT02442375 .
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Affiliation(s)
- Sven van den Bosch
- Department of radiation oncology, Radboud University Medical Center, huispost 874, P.O. Box 9101, Nijmegen, 6500 HB The Netherlands
| | - Tim Dijkema
- Department of radiation oncology, Radboud University Medical Center, huispost 874, P.O. Box 9101, Nijmegen, 6500 HB The Netherlands
| | - Martina C. Kunze-Busch
- Department of radiation oncology, Radboud University Medical Center, huispost 874, P.O. Box 9101, Nijmegen, 6500 HB The Netherlands
| | - Chris H. J. Terhaard
- Department of radiation oncology, University Medical Center Utrecht, Utrecht, The Netherlands
| | | | | | - Frank J. P. Hoebers
- Department of radiation oncology (MAASTRO), Research Institute GROW, Maastricht University, Maastricht, The Netherlands
| | - Marije R. Vergeer
- Department of radiation oncology, VU University Medical Center, Amsterdam, The Netherlands
| | - Bas Kreike
- Department of radiation oncology, Radiotherapiegroep, Arnhem, The Netherlands
| | - Oda B. Wijers
- Department of radiation oncology, Radiotherapeutisch Instituut Friesland, Leeuwarden, The Netherlands
| | - Wim J. G. Oyen
- Department of nuclear medicine, Radboud University Medical Center, Nijmegen, The Netherlands
- The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK
| | - Johannes H. A. M. Kaanders
- Department of radiation oncology, Radboud University Medical Center, huispost 874, P.O. Box 9101, Nijmegen, 6500 HB The Netherlands
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