Hugo C Temperley, Fariba Tohidinezhad, Niall J O'Sullivan, Benjamin M Mac Curtain, Brian J Mehigan, Colm Kerr, John O Larkin, Peter Beddy, Paul H McCormick, David Gallagher, Alison Corr, Colm Bergin, Charles Gillham, Michael E Kelly
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引用次数: 0
Abstract
Introduction: Treatment response to definitive chemoradiation(dCRT) in patients with anal cancer varies significantly, with a subset experiencing persistent or progressive disease despite therapy. Radiomics extracts quantitative features from medical images, with the potential to develop predictive tools to assess treatment response. We aim to develop and validate an MRI-based radiomics nomogram to predict response to dCRT in patients with anal cancer.
Methods: A single-institutional retrospective analysis of 45 patients with anal cancer treated with dCRT was performed. Radiomic features were extracted from pre-treatment T2-weighted MRI scans and predictive models were constructed. Clinical and radiomic features were analysed to develop the nomogram. Internal validation with 1000 bootstrap samples was performed to calculate optimism-corrected performance measures.
Results: 30/45(66.7%) achieved a complete treatment response. Male gender was found to be an independent predictor of incomplete response to dCRT (OR4.763,95%CI : 1.170-19.384,*P = 0.029). Two radiomic signatures emerged as strong predictors of treatment response to dCRT. The combined model outperformed the clinical and radiomic models. The combined model showed the highest predictive accuracy, achieving an apparent AUC : 0.87(0.75-0.99) and an optimism-corrected AUC: 0.85, mean absolute error : 0.029, PPV(0.68)and NPV(0.92), indicating excellent discriminative performance. It demonstrated a positive net benefit in decision analysis. The optimism-corrected calibration curves demonstrate that the radiomic and combined model provide well-calibrated predictions.
Conclusion: This MRI-based radiomics nomogram offers a promising approach to predict response to dCRT in patients with anal cancer.
Advances in knowledge: This study is the first to integrate radiomics and clinical features into a validated predictive model for anal cancer.
期刊介绍：
BJR is the international research journal of the British Institute of Radiology and is the oldest scientific journal in the field of radiology and related sciences.
Dating back to 1896, BJR’s history is radiology’s history, and the journal has featured some landmark papers such as the first description of Computed Tomography "Computerized transverse axial tomography" by Godfrey Hounsfield in 1973. A valuable historical resource, the complete BJR archive has been digitized from 1896.
Quick Facts:
- 2015 Impact Factor – 1.840
- Receipt to first decision – average of 6 weeks
- Acceptance to online publication – average of 3 weeks
- ISSN: 0007-1285
- eISSN: 1748-880X
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