A novel approach to predict acute radiation dermatitis in patients with head and neck cancer using a model based on Bayesian probability.

Autor: Hamada K; Department of Radiological Technology, National Hospital Organization Kyushu Cancer Center, 3-1-1, Notame, Minami-ku, Fukuoka City, Fukuoka 811-1395, Japan; Department of Health Sciences, Graduate School of Medicine, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan. Electronic address: hamada.keisuke.we@mail.hosp.go.jp., Fujibuchi T; Department of Health Sciences, Faculty of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan. Electronic address: fujibuchi.toshioh.294@m.kyushu-u.ac.jp., Arakawa H; Department of Health Sciences, Faculty of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan. Electronic address: arakawa.hiroyuki.306@m.kyushu-u.ac.jp., Yokoyama Y; Department of Radiological Technology, National Hospital Organization Kyushu Cancer Center, 3-1-1, Notame, Minami-ku, Fukuoka City, Fukuoka 811-1395, Japan. Electronic address: yokoyama.yuichi.jx@mail.hosp.go.jp., Yoshida N; Department of Radiological Technology, National Hospital Organization Kyushu Cancer Center, 3-1-1, Notame, Minami-ku, Fukuoka City, Fukuoka 811-1395, Japan. Electronic address: yoshida.naoki.hb@mail.hosp.go.jp., Ohura H; Department of Radiological Technology, National Hospital Organization Kyushu Medical Center, 1-8-1 Jigyohama, Chuo-ku, Fukuoka City, Fukuoka 810-8563, Japan. Electronic address: ooura.hiroki.uy@mail.hosp.go.jp., Kunitake N; Department of Radiation Oncology, National Hospital Organization Kyushu Cancer Center, 3-1-1, Notame, Minami-ku, Fukuoka City, Fukuoka 811-1395, Japan. Electronic address: kunitake.naonobu.nb@mail.hosp.go.jp., Masuda M; Department of Head and Neck Surgery, National Hospital Organization Kyushu Cancer Center, 3-1-1, Notame, Minami-ku, Fukuoka City, Fukuoka 811-1395, Japan. Electronic address: mmuneyuki@icloud.com., Honda T; Department of Radiological Technology, National Hospital Organization Kyushu Cancer Center, 3-1-1, Notame, Minami-ku, Fukuoka City, Fukuoka 811-1395, Japan. Electronic address: honda.takeo.mn@mail.hosp.go.jp., Tokuda S; Research Institute for Information Technology, Kyushu University, 6-1, Kasuga koen, Kasuga City, Fukuoka 816-8580, Japan. Electronic address: s.tokuda.a96@m.kyushu-u.ac.jp., Sasaki M; College of Industrial Technology, Nihon University, 1-2-1 Izumi-cho, Narashino City, Chiba 275-8575, Japan. Electronic address: sasaki.makoto@nihon-u.ac.jp.
Jazyk: angličtina
Zdroj: Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) [Phys Med] 2023 Dec; Vol. 116, pp. 103181. Date of Electronic Publication: 2023 Nov 24.
DOI: 10.1016/j.ejmp.2023.103181
Abstrakt: Purpose: In this study, we aimed to establish a method for predicting the probability of each acute radiation dermatitis (ARD) grade during the head and neck Volumetric Modulated Arc Therapy (VMAT) radiotherapy planning phase based on Bayesian probability.
Methods: The skin dose volume >50 Gy (V 50 ), calculated using the treatment planning system, was used as a factor related to skin toxicity. The empirical distribution of each ARD grade relative to V 50 was obtained from the ARD grades of 119 patients (55, 50, and 14 patients with G1, G2, and G3, respectively) determined by head and neck cancer specialists. Using Bayes' theorem, the Bayesian probabilities of G1, G2, and G3 for each value of V 50 were calculated with an empirical distribution. Conversely, V 50 was obtained based on the Bayesian probabilities of G1, G2, and G3.
Results: The empirical distribution for each graded patient group demonstrated a normal distribution. The method predicted ARD grades with 92.4 % accuracy and provided a V 50 value for each grade. For example, using the graph, we could predict that V 50 should be ≤24.5 cm 3 to achieve G1 with 70 % probability.
Conclusions: The Bayesian probability-based ARD prediction method could predict the ARD grade at the treatment planning stage using limited patient diagnostic data that demonstrated a normal distribution. If the probability of an ARD grade is high, skin care can be initiated in advance. Furthermore, the V 50 value during treatment planning can provide radiation oncologists with data for strategies to reduce ARD.
Competing Interests: Declaration of Competing Interest 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.
(Copyright © 2023. Published by Elsevier Ltd.)
Databáze: MEDLINE
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