Pre-treatment visualization of predicted radiation-induced acute alopecia in brain tumour patients.

Alopecia Brain tumour Hair loss Neuro-oncology Prediction Radiotherapy

Journal

Clinical and translational radiation oncology
ISSN: 2405-6308
Titre abrégé: Clin Transl Radiat Oncol
Pays: Ireland
ID NLM: 101713416

Informations de publication

Date de publication:
Mar 2022
Historique:
received: 27 12 2021
revised: 08 02 2022
accepted: 10 02 2022
entrez: 4 3 2022
pubmed: 5 3 2022
medline: 5 3 2022
Statut: epublish

Résumé

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. 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. 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. 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.

Sections du résumé

BACKGROUND AND PURPOSE OBJECTIVE
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 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 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 CONCLUSIONS
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.

Identifiants

pubmed: 35243020
doi: 10.1016/j.ctro.2022.02.003
pii: S2405-6308(22)00006-4
pmc: PMC8856945
doi:

Types de publication

Journal Article

Langues

eng

Pagination

106-111

Informations de copyright

© 2022 Published by Elsevier B.V. on behalf of European Society for Radiotherapy and Oncology.

Déclaration de conflit d'intérêts

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Auteurs

Lieke In 't Ven (L)

Department of Radiation Oncology (Maastro), GROW School for Oncology, Maastricht University Medical Centre+, Maastricht, The Netherlands.

Inge Compter (I)

Department of Radiation Oncology (Maastro), GROW School for Oncology, Maastricht University Medical Centre+, Maastricht, The Netherlands.

Kyra van Eijsden (K)

Department of Radiation Oncology (Maastro), GROW School for Oncology, Maastricht University Medical Centre+, Maastricht, The Netherlands.

Jaap Zindler (J)

Department of Radiation Oncology, Haaglanden Medical Centre, The Hague, The Netherlands.
Holland Proton Therapy Centre, Delft, The Netherlands.

Ans Swinnen (A)

Department of Radiation Oncology (Maastro), GROW School for Oncology, Maastricht University Medical Centre+, Maastricht, The Netherlands.

Dirk de Ruysscher (D)

Department of Radiation Oncology (Maastro), GROW School for Oncology, Maastricht University Medical Centre+, Maastricht, The Netherlands.

Tom Rozema (T)

Bernard Verbeeten Institute, Tilburg, The Netherlands.

Esther G C Troost (EGC)

Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.
Institute of Radiooncology-OncoRay, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany.
OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany.
National Center for Tumour Diseases (NCT), Partner Site Dresden, Germany.
German Cancer Research Center (DKFZ), Heidelberg, Germany.
Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.
Helmholtz Association / Helmholtz-Zentrum Dresden - Rossendorf (HZDR), Dresden, Germany.
German Cancer Consortium (DKTK), Partner Site Dresden, Germany.

Daniëlle B P Eekers (DBP)

Department of Radiation Oncology (Maastro), GROW School for Oncology, Maastricht University Medical Centre+, Maastricht, The Netherlands.

Classifications MeSH