Purpose: This study examines the relationship between dose to corneal substructures and incidence of corneal toxicity within 6 months of proton beam therapy (PBT) for uveal melanoma. We aim to develop clinically meaningful dose constraints that can be used to mitigate corneal toxicity.
Methods and materials: Ninety-two patients were treated with PBT between 2015 and 2017 and evaluated for grade 2+ (GR2+) intervention-requiring corneal toxicity in our prospectively maintained database. Most patients were treated with 50 Gy (relative biological effectiveness [RBE]) in 5 fractions, and all had complete six-month follow-up. Analyses included Mann-Whitney, χ2, Fisher exact, and receiver operating curve tests to identify risk factors for GR2+ toxicity. Bivariate logistic regression was used to identify independent dose-volume histogram (DVH) predictors of toxicity after adjustment for the most important clinical risk factor.
Results: The 6-month PBT GR2+ corneal toxicity rate was 10.9%, with half of patients experiencing grade 2 toxicity and half experiencing grade 3 toxicity, with no grade 4 events. Patients with anterior chamber tumors had a higher risk (58.3%) for toxicity than those with posterior tumors (0%) or posterior tumors extending past the equator (25%, P < .0001). On univariate analysis, larger size according to Collaborative Ocular Melanoma Studies was associated with increased toxicity rate (P < .004). DVH analysis revealed that cutoffs of 58% for V25, 32% for V45, 51.8 Gy (RBE) for maximum dose, and 32 Gy (RBE) for mean dose to the cornea separated patients into groups experiencing and not experiencing toxicity with 90% sensitivity and ≥96% specificity. Bivariate logistic regression indicated that corneal V25, V45, and mean dose independently predicted for toxicity after adjusting for tumor location.
Conclusions: Patients receiving PBT for anterior uveal melanomas experience a high rate of GR2+ corneal toxicity because of increased corneal dose. Anterior location and corneal DVH parameters independently predict toxicity risk. We propose dosimetric constraints to facilitate treatment planning and toxicity mitigation.
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