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Predicting radiotherapy-induced xerostomia in head and neck cancer patients using day-to-day kinetics of radiomics features
Berger, T. Noble, D. J. Shelley, L. E. A. McMullan, T. Bates, A. Thomas, S. Carruthers, L. J. Beckett, G. Duffton, A. Paterson, C.
Berger, T.
Noble, D. J.
Shelley, L. E. A.
McMullan, T.
Bates, A.
Thomas, S.
Carruthers, L. J.
Beckett, G.
Duffton, A.
Paterson, C.
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Abstract
Background and purpose: The images acquired during radiotherapy for image-guidance purposes could be used to monitor patient-specific response to irradiation and improve treatment personalisation. We investigated whether the kinetics of radiomics features from daily mega-voltage CT image-guidance scans (MVCT) improve prediction of moderate-to-severe xerostomia compared to dose/volume parameters in radiotherapy of head-and-neck cancer (HNC).
Materials and methods: All included HNC patients (N = 117) received 30 or more fractions of radiotherapy with daily MVCTs. Radiomics features were calculated on the contra-lateral parotid glands of daily MVCTs. Their variations over time after each complete week of treatment were used to predict moderate-to-severe xerostomia (CTCAEv4.03 grade ≥ 2) at 6, 12 and 24 months post-radiotherapy. After dimensionality reduction, backward/forward selection was used to generate combinations of predictors.Three types of logistic regression model were generated for each follow-up time: 1) a pre-treatment reference model using dose/volume parameters, 2) a combination of dose/volume and radiomics-based predictors, and 3) radiomics-based predictors. The models were internally validated by cross-validation and bootstrapping and their performance evaluated using Area Under the Curve (AUC) on separate training and testing sets.
Results: Moderate-to-severe xerostomia was reported by 46 %, 33 % and 26 % of the patients at 6, 12 and 24 months respectively. The selected models using radiomics-based features extracted at or before mid-treatment outperformed the dose-based models with an AUCtrain/AUCtest of 0.70/0.69, 0.76/0.74, 0.86/0.86 at 6, 12 and 24 months, respectively.
Conclusion: Our results suggest that radiomics features calculated on MVCTs from the first half of the radiotherapy course improve prediction of moderate-to-severe xerostomia in HNC patients compared to a dose-based pre-treatment model.
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2022
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Berger T, Noble DJ, Shelley LEA, McMullan T, Bates A, Thomas S, et al. Predicting radiotherapy-induced xerostomia in head and neck cancer patients using day-to-day kinetics of radiomics features. Physics and imaging in radiation oncology. 2022 Oct;24:95-101. PubMed PMID: 36386445. Pubmed Central PMCID: PMC9647222. Epub 2022/11/18. eng.