Definition and validation of a radiomics signature for loco-regional tumour control in patients with locally advanced head and neck squamous cell carcinoma
Research output: Contribution to journal › Research article › Contributed › peer-review
Contributors
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.
Details
Original language | English |
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Pages (from-to) | 62-70 |
Number of pages | 9 |
Journal | Clinical and translational radiation oncology |
Volume | 26 |
Publication status | Published - Jan 2021 |
Peer-reviewed | Yes |
External IDs
ORCID | /0000-0002-7017-3738/work/146646042 |
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ORCID | /0000-0003-1776-9556/work/171065753 |
Keywords
Sustainable Development Goals
ASJC Scopus subject areas
Keywords
- Biomarker, HNSCC, Loco-regional control, Machine learning, Radiomics, Validation