Ralph T H Leijenaar1, Sara Carvalho1, Frank J P Hoebers1, Hugo J W L Aerts1,2, Wouter J C van Elmpt1, Shao Hui Huang3, Biu Chan3, John N Waldron3, Brian O'sullivan3, Philippe Lambin1. 1. a Department of Radiation Oncology (MAASTRO) , GROW-School for Oncology and Developmental Biology, Maastricht University Medical Centre (MUMC+) , Maastricht , The Netherlands. 2. b Departments of Radiation Oncology and Radiology , Dana-Farber Cancer Institute, Brigham and Women's Hospital, Harvard Medical School , Boston , MA , USA. 3. c Department of Radiation Oncology , Princess Margaret Cancer Center, University of Toronto , Toronto, Ontario , Canada.
Abstract
BACKGROUND: Oropharyngeal squamous cell carcinoma (OPSCC) is one of the fastest growing disease sites of head and neck cancers. A recently described radiomic signature, based exclusively on pre-treatment computed tomography (CT) imaging of the primary tumor volume, was found to be prognostic in independent cohorts of lung and head and neck cancer patients treated in the Netherlands. Here, we further validate this signature in a large and independent North American cohort of OPSCC patients, also considering CT artifacts. METHODS: A total of 542 OPSCC patients were included for which we determined the prognostic index (PI) of the radiomic signature. We tested the signature model fit in a Cox regression and assessed model discrimination with Harrell's c-index. Kaplan-Meier survival curves between high and low signature predictions were compared with a log-rank test. Validation was performed in the complete cohort (PMH1) and in the subset of patients without (PMH2) and with (PMH3) visible CT artifacts within the delineated tumor region. RESULTS: We identified 267 (49%) patients without and 275 (51%) with visible CT artifacts. The calibration slope (β) on the PI in a Cox proportional hazards model was 1.27 (H0: β = 1, p = 0.152) in the PMH1 (n = 542), 0.855 (H0: β = 1, p = 0.524) in the PMH2 (n = 267) and 1.99 (H0: β = 1, p = 0.002) in the PMH3 (n = 275) cohort. Harrell's c-index was 0.628 (p = 2.72e-9), 0.634 (p = 2.7e-6) and 0.647 (p = 5.35e-6) for the PMH1, PMH2 and PMH3 cohort, respectively. Kaplan-Meier survival curves were significantly different (p < 0.05) between high and low radiomic signature model predictions for all cohorts. CONCLUSION: Overall, the signature validated well using all CT images as-is, demonstrating a good model fit and preservation of discrimination. Even though CT artifacts were shown to be of influence, the signature had significant prognostic power regardless if patients with CT artifacts were included.
BACKGROUND: Oropharyngeal squamous cell carcinoma (OPSCC) is one of the fastest growing disease sites of head and neck cancers. A recently described radiomic signature, based exclusively on pre-treatment computed tomography (CT) imaging of the primary tumor volume, was found to be prognostic in independent cohorts of lung and head and neck cancerpatients treated in the Netherlands. Here, we further validate this signature in a large and independent North American cohort of OPSCC patients, also considering CT artifacts. METHODS: A total of 542 OPSCC patients were included for which we determined the prognostic index (PI) of the radiomic signature. We tested the signature model fit in a Cox regression and assessed model discrimination with Harrell's c-index. Kaplan-Meier survival curves between high and low signature predictions were compared with a log-rank test. Validation was performed in the complete cohort (PMH1) and in the subset of patients without (PMH2) and with (PMH3) visible CT artifacts within the delineated tumor region. RESULTS: We identified 267 (49%) patients without and 275 (51%) with visible CT artifacts. The calibration slope (β) on the PI in a Cox proportional hazards model was 1.27 (H0: β = 1, p = 0.152) in the PMH1 (n = 542), 0.855 (H0: β = 1, p = 0.524) in the PMH2 (n = 267) and 1.99 (H0: β = 1, p = 0.002) in the PMH3 (n = 275) cohort. Harrell's c-index was 0.628 (p = 2.72e-9), 0.634 (p = 2.7e-6) and 0.647 (p = 5.35e-6) for the PMH1, PMH2 and PMH3 cohort, respectively. Kaplan-Meier survival curves were significantly different (p < 0.05) between high and low radiomic signature model predictions for all cohorts. CONCLUSION: Overall, the signature validated well using all CT images as-is, demonstrating a good model fit and preservation of discrimination. Even though CT artifacts were shown to be of influence, the signature had significant prognostic power regardless if patients with CT artifacts were included.
Authors: M Ravanelli; A Grammatica; M Maddalo; M Ramanzin; G M Agazzi; E Tononcelli; S Battocchio; P Bossi; M Vezzoli; R Maroldi; D Farina Journal: AJNR Am J Neuroradiol Date: 2020-07-30 Impact factor: 3.825
Authors: Michael MacManus; Sarah Everitt; Tanja Schimek-Jasch; X Allen Li; Ursula Nestle; Feng-Ming Spring Kong Journal: Transl Lung Cancer Res Date: 2017-12