Pre-treatment visualization of predicted radiation-induced acute alopecia in brain tumour patients. (March 2022)

• Record Type: Journal Article
• Authors: in 't Ven, Lieke; Compter, Inge; van Eijsden, Kyra; Zindler, Jaap; Swinnen, Ans; de Ruysscher, Dirk; Rozema, Tom; Troost, Esther G.C.; Eekers, Daniëlle B.P.
• Is Part Of: Clinical and translational radiation oncology. Volume 33(2022)
• Page Start: 106
• Page End: 111
• Publication Date: 2022-03
• Subjects: Radiotherapy -- Neuro-oncology -- Brain tumour -- Alopecia -- Hair loss -- Prediction; Cancer -- Radiotherapy -- Periodicals; Oncology -- Periodicals; Cancer -- Radiotherapy; Oncology; Radiation Oncology; Neoplasms -- radiotherapy; Translational Medical Research; Periodicals; Electronic journals; Periodicals; 616.9940642
• DOI: 10.1016/j.ctro.2022.02.003
• Languages: English
• ISSNs: 2405-6308

Abstract

Highlights: Alopecia as a side effect of radiotherapy beholds a significant psychological burden for brain tumor patients. Prediction of occurrence and location of alopecia can prepare patients both mentally and practically. We demonstrate a model within our treatment planning system to visualize expected alopecia 4 weeks after radiation treatment for brain tumors. The validation cohort consisted of 147 brain tumor patients and showed a 100% accuracy of expected alopecia in 90% of all cases treated with photon beam radiotherapy. Abstract: Background and purpose: Temporary alopecia is a common side-effect in brain tumour patients receiving cranial radiotherapy with a significant psychological burden for the affected patient. The purpose of this study was to generate a method in our treatment planning system (TPS) to visualize the expected radiation-induced alopecia 4 weeks after treatment, in order to inform the patients thereupon before the start of radiotherapy. Material and methods: A pilot study was conducted in ten patients receiving hypo- (HF) or conventionally fractionated (CF) photon beam Volumetric Modulated Arc Therapy (VMAT) for an intracranial lesion. Dose calculations were correlated to visible alopecia four weeks after the end of treatment to create a structure predictive of alopecia in our TPS. These alopecia structures for both fractionation schedules were validated in two cohorts of 69 HF and 78 CF patients undergoing radiotherapy between 2016 and 2019. Results: In the pilot cohort, a total physical dose of 4 Gy for HF and 12.6 Gy for CF radiotherapy were found to be predictive of alopecia 4 weeks after treatment. Applying these doses to our validation cohort, we found an accurate prediction of alopecia in 59/69 (86%) HF and 73/78 (96%) CF patients. For the total patient group of 147 patients, the predicted amount of alopecia was accurate in 90% of the cases. All inaccurate predictions overestimated the expected extent of alopecia. Conclusion: The presented straightforward method to visualize predicted alopecia 4 weeks after treatment has proven to predict the extent alopecia highly accurate in the vast majority of patients. Sharing these results with the patients pre-treatment may result in stress reduction before cranial irradiation.