A dosiomics model for prediction of radiation-induced acute skin toxicity in breast cancer patients: machine learning-based study for a closed bore linac.

BACKGROUND: Radiation induced acute skin toxicity (AST) is considered as a common side effect of breast radiation therapy. The goal of this study was to design dosiomics-based machine learning (ML) models for prediction of AST, to enable creating optimized treatment plans for high-risk individuals. METHODS: Dosiomics features extracted using Pyradiomics tool (v3.0.1), along with treatment plan-derived dose volume histograms (DVHs), and patient-specific treatment-related (PTR) data of breast cancer patients were used for modeling. Clinical scoring was done using the Common Terminology Criteria for Adverse Events (CTCAE) V4.0 criteria for skin-specific symptoms. The 52 breast cancer patients were grouped into AST 2 + (CTCAE ≥ 2) and AST 2 - (CTCAE < 2) toxicity grades to facilitate AST modeling. They were randomly divided into training (70%) and testing (30%) cohorts. Multiple prediction models were assessed through multivariate analysis, incorporating different combinations of feature groups (dosiomics, DVH, and PTR) individually and collectively. In total, seven unique combinations, along with seven classification algorithms, were considered after feature selection. The performance of each model was evaluated on the test group using the area under the receiver operating characteristic curve (AUC) and f1-score. Accuracy, precision, and recall of each model were also studied. Statistical analysis involved features differences between AST 2 - and AST 2 + groups and cutoff value calculations. RESULTS: Results showed that 44% of the patients developed AST 2 + after Tomotherapy. The dosiomics (DOS) model, developed using dosiomics features, exhibited a noteworthy improvement in AUC (up to 0.78), when spatial information is preserved in the dose distribution, compared to DVH features (up to 0.71). Furthermore, a baseline ML model created using only PTR features for comparison with DOS models showed the significance of dosiomics in early AST prediction. By employing the Extra Tree (ET) classifiers, the DOS + DVH + PTR model achieved a statistically significant improved performance in terms of AUC (0.83; 95% CI 0.71-0.90), accuracy (0.70), precision (0.74) and sensitivity (0.72) compared to other models. CONCLUSIONS: This study confirmed the benefit of dosiomics-based ML in the prediction of AST. However, the combination of dosiomics, DVH, and PTR yields significant improvement in AST prediction. The results of this study provide the opportunity for timely interventions to prevent the occurrence of radiation induced AST.

Preventive effects of zinc sulfate on taste alterations in patients under irradiation for head and neck cancers: A randomized placebo-controlled trial.

BACKGROUND: Taste abnormalities are common among cancer patients after starting radiotherapy or chemotherapy. Considering the role of zinc and reports on its beneficial effects in taste perception, we evaluated the preventive effects of zinc sulfate on radiation-induced taste alterations. MATERIALS AND METHODS: In a randomized, placebo-controlled trial, adult patients with head and neck cancers who were on schedule for radiotherapy, with or without chemotherapy, were allocated to receive zinc sulfate (50 mg, three times a day) or placebo; started with beginning of radiotherapy and continued for one month later. Taste acuity was determined by measuring detection and recognition thresholds for four taste qualities at baseline, at the end of radiotherapy, and a month later using the Henkin method. RESULTS: Thirty-five patients (mean age = 59.2 ± 16.5, 60% male) completed the trial. The two groups were similar at baseline. After radiotherapy, and one month later, there was a significant increase in taste perception threshold for bitter, salty, sweet, and sour tastes in the placebo group (P = 0.001). In those who received zinc, there was only slight increase in threshold for perception of the salty taste (P = 0.046). No relevant side effects due to zinc sulfate were reported. CONCLUSION: Zinc supplementation in head/neck cancer patients under radiotherapy can prevent radiation-induced taste alterations. Further studies with longer follow-ups and with different doses of zinc supplementation are warranted in this regard.