Definition and validation of a radiomics signature for loco-regional tumour control in patients with locally advanced head and neck squamous cell carcinoma. (January 2021)

• Record Type: Journal Article
• Authors: Rabasco Meneghetti, Asier; Zwanenburg, Alex; Leger, Stefan; Leger, Karoline; Troost, Esther G.C.; Linge, Annett; Lohaus, Fabian; Schreiber, Andreas; Kalinauskaite, Goda; Tinhofer, Inge; Guberina, Nika; Guberina, Maja; Balermpas, Panagiotis; von der Grün, Jens; Ganswindt, Ute; Belka, Claus; Peeken, Jan C.; Combs, Stephanie E.; Böke, Simon; Zips, Daniel; Krause, Mechthild; Baumann, Michael; Löck, Steffen
• Is Part Of: Clinical and translational radiation oncology. Volume 26(2021)
• Page Start: 62
• Page End: 70
• Publication Date: 2021-01
• Subjects: HNSCC -- Radiomics -- Validation -- Biomarker -- Machine learning -- Loco-regional control; Cancer -- Radiotherapy -- Periodicals; Oncology -- Periodicals; Cancer -- Radiotherapy; Oncology; Radiation Oncology; Neoplasms -- radiotherapy; Translational Medical Research; Periodicals; Electronic journals; Periodicals; 616.9940642
• DOI: 10.1016/j.ctro.2020.11.011
• Languages: English
• ISSNs: 2405-6308

Abstract

Highlights: A prognostic signature for LRC in locally-advanced HNSCC was developed and validated. Signature development was based on advanced machine-learning methods. Tumour volume was combined with radiomic features related to tumour heterogeneity. Patients were classified in risk groups with significant differences in LRC. Abstract: Purpose: To develop and validate a CT-based radiomics signature for the prognosis of loco-regional tumour control (LRC) in patients with locally advanced head and neck squamous cell carcinoma (HNSCC) treated by primary radiochemotherapy (RCTx) based on retrospective data from 6 partner sites of the German Cancer Consortium - Radiation Oncology Group (DKTK-ROG). Material and methods: Pre-treatment CT images of 318 patients with locally advanced HNSCC were collected. Four-hundred forty-six features were extracted from each primary tumour volume and then filtered through stability analysis and clustering. First, a baseline signature was developed from demographic and tumour-associated clinical parameters. This signature was then supplemented by CT imaging features. A final signature was derived using repeated 3-fold cross-validation on the discovery cohort. Performance in external validation was assessed by the concordance index (C-Index). Furthermore, calibration and patient stratification in groups with low and high risk for loco-regional recurrence were analysed. Results: For the clinical baseline signature, only the primary tumour volume was selected. The final signature combined the tumour volume with two independent radiomics features. It achieved moderately good discriminatory performance (C-Index [95% confidence interval]: 0.66 [0.55–0.75]) on the validation cohort along with significant patient stratification (p = 0.005) and good calibration. Conclusion: We identified and validated a clinical-radiomics signature for LRC of locally advanced HNSCC using a multi-centric retrospective dataset. Prospective validation will be performed on the primary cohort of the HNprädBio trial of the DKTK-ROG once follow-up is completed.