Spatial dose-distribution-based risk mapping to predict moist desquamation in breast radiotherapy

<i>Objective.</i>A relationship between the regional spatial distribution of skin dose and the development of moist desquamation (MD) was established for patients treated with breast radiotherapy.<i>Approach.</i>A 56-patient dataset was used to develop and validate a dose-distance based metric to predict MD. Dose distributions for the skin were extracted from AcurosXB treatment plans, and patient reported outcomes were used to classify the incidence of MD across the whole breast and then more specifically in the inferior breast. The sensitivity and specificity of the metric was compared against dose-area (A38 Gy ⩽ 50 cm<sup>2</sup>) and dose-volume (V105% ⩽ 2% of the breast volume) predictive metrics with the same dataset.<i>Main results.</i>With a sensitivity of 70% and a specificity of 72%, the dose-distance metric outperformed the dose-area (45%, 55%) and dose-volume (43%, 56%) predictive metrics. The test performance improves to a sensitivity and specificity of 81% when excluding the full coverage breast support devices that confounded the skin dose identification in the analysis.<i>Significance.</i>This metric offers regional MD prediction and risk mapping to highlight regions at high risk of developing severe skin toxicity and is suitable for implementation within the treatment planning process.This work is based on data acquired for the following clinical trials: ClinicalTrials.gov NCT04543851 and NCT04257396.

Authors

Institutions

Publication Details

Journal
Physics in Medicine and Biology
Published
2025-05-15
DOI
https://doi.org/10.1088/1361-6560/add985
Primary Topic
Effects of Radiation Exposure
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Spatial dose-distribution-based risk mapping to predict moist desquamation in breast radiotherapy

Cheryl Duzenli, A. Malhotra, Alan Nichol, Elisa Chan
Physics in Medicine and Biology
Effects of Radiation Exposure
article

Spatial dose-distribution-based risk mapping to predict moist desquamation in breast radiotherapy

Cheryl Duzenli, A. Malhotra, Alan Nichol, Elisa Chan
article en

Abstract

<i>Objective.</i>A relationship between the regional spatial distribution of skin dose and the development of moist desquamation (MD) was established for patients treated with breast radiotherapy.<i>Approach.</i>A 56-patient dataset was used to develop and validate a dose-distance based metric to predict MD. Dose distributions for the skin were extracted from AcurosXB treatment plans, and patient reported outcomes were used to classify the incidence of MD across the whole breast and then more specifically in the inferior breast. The sensitivity and specificity of the metric was compared against dose-area (A38 Gy ⩽ 50 cm<sup>2</sup>) and dose-volume (V105% ⩽ 2% of the breast volume) predictive metrics with the same dataset.<i>Main results.</i>With a sensitivity of 70% and a specificity of 72%, the dose-distance metric outperformed the dose-area (45%, 55%) and dose-volume (43%, 56%) predictive metrics. The test performance improves to a sensitivity and specificity of 81% when excluding the full coverage breast support devices that confounded the skin dose identification in the analysis.<i>Significance.</i>This metric offers regional MD prediction and risk mapping to highlight regions at high risk of developing severe skin toxicity and is suitable for implementation within the treatment planning process.This work is based on data acquired for the following clinical trials: ClinicalTrials.gov NCT04543851 and NCT04257396.

Physics in Medicine and BiologyVol. 70(11)
BC Cancer Agency (CA), University of British Columbia (CA)
Canadian Cancer Society
Good health and well-being
Openalex Percentile: Top 84%
Effects of Radiation Exposure
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Spatial dose-distribution-based risk mapping to predict moist desquamation in breast radiotherapy — Cheryl Duzenli, A. Malhotra, et al. · Physics in Medicine and Biology (2025) | TGRS Research Map | TGRS