External validation of an 18F-FDG-PET radiomic model predicting survival after radiotherapy for oropharyngeal cancer

Mori, Martina, Deantoni, Chiara, Olivieri, Michela, Spezi, Emiliano ORCID: https://orcid.org/0000-0002-1452-8813, Chiara, Anna, Baroni, Simone, Picchio, Maria, Del Vecchio, Antonella, Di Muzio, Nadia Gisella, Fiorino, Claudio and Dell'Oca, Italo 2023. External validation of an 18F-FDG-PET radiomic model predicting survival after radiotherapy for oropharyngeal cancer. European Journal of Nuclear Medicine and Molecular Imaging 50 , pp. 1329-1336. 10.1007/s00259-022-06098-9

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Abstract

Purpose/objective The purpose of the study is to externally validate published 18F-FDG-PET radiomic models for outcome prediction in patients with oropharyngeal cancer treated with chemoradiotherapy. Material/methods Outcome data and pre-radiotherapy PET images of 100 oropharyngeal cancer patients (stage IV:78) treated with concomitant chemotherapy to 66–69 Gy/30 fr were available. Tumors were segmented using a previously validated semi-automatic method; 450 radiomic features (RF) were extracted according to IBSI (Image Biomarker Standardization Initiative) guidelines. Only one model for cancer-specific survival (CSS) prediction was suitable to be independently tested, according to our criteria. This model, in addition to HPV status, SUVmean and SUVmax, included two independent meta-factors (Fi), resulting from combining selected RF clusters. In a subgroup of 66 patients with complete HPV information, the global risk score R was computed considering the original coefficients and was tested by Cox regression as predictive of CSS. Independently, only the radiomic risk score RF derived from Fi was tested on the same subgroup to learn about the radiomics contribution to the model. The metabolic tumor volume (MTV) was also tested as a single predictor and its prediction performances were compared to the global and radiomic models. Finally, the validation of MTV and the radiomic score RF were also tested on the entire dataset. Results Regarding the analysis of the subgroup with HPV information, with a median follow-up of 41.6 months, seven patients died due to cancer. R was confirmed to be associated to CSS (p value = 0.05) with a C-index equal 0.75 (95% CI=0.62–0.85). The best cut-off value (equal to 0.15) showed high ability in patient stratification (p=0.01, HR=7.4, 95% CI=1.6–11.4). The 5-year CSS for R were 97% (95% CI: 93–100%) vs 74% (56–92%) for low- and high-risk groups, respectively. RF and MTV alone were also significantly associated to CSS for the subgroup with an almost identical C-index. According to best cut-off value (RF>0.12 and MTV>15.5cc), the 5-year CSS were 96% (95% CI: 89–100%) vs 65% (36–94%) and 97% (95% CI: 88–100%) vs 77% (58–93%) for RF and MTV, respectively. Results regarding RF and MTV were confirmed in the overall group. Conclusion A previously published PET radiomic model for CSS prediction was independently validated. Performances of the model were similar to the ones of using only the MTV, without improvement of prediction accuracy.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Engineering
Publisher:	Springer
ISSN:	1619-7070
Date of First Compliant Deposit:	8 January 2023
Date of Acceptance:	24 December 2022
Last Modified:	05 Jan 2024 17:49
URI:	https://orca.cardiff.ac.uk/id/eprint/155560

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