Modeling and prediction of set‑up errors in breast cancer image‑guided radiotherapy using the Gaussian mixture model
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- Published online on: September 30, 2024 https://doi.org/10.3892/ol.2024.14706
- Article Number: 573
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Copyright: © Dong et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
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Abstract
The aim of the present study was to develop a prediction model for set‑up error distribution in breast cancer image‑guided radiotherapy (IGRT) using a Gaussian mixture model (GMM). To achieve this, the image‑guided set‑up errors data of 80 patients with breast cancer were selected, and the GMM was used to develop the set‑up errors distribution prediction model. The predicted error center points, covariance and probability were calculated and compared with the planning target volume (PTV) margin formula. A total of 1,200 sets of set‑up errors in IGRT for breast cancer were collected. The results of the Gaussian model parameters showed that the set‑up errors were mainly in the direction of µ1‑µ4 center points. All the raw errors in the lateral, longitudinal and vertical directions were ‑6.30‑4.60, ‑5.40‑1.47 and ‑2.70‑1.70 mm, respectively. According to the probability of each center, the set‑up error was most likely to shift in the µ1 direction, reaching 0.53. The set‑up errors of the other three centers, µ2, µ3 and µ4, were 0.11, 0.34 and 0.12, respectively. According to the covariance parameters of the GMM, the maximum statistical standard deviation of the set‑up errors reached 29.06. In conclusion, the results of the present study demonstrated that the GMM can be used to quantitatively describe and predict the distribution of set‑up errors in IGRT for breast cancer, and these findings could be useful as a reference for set‑up error control and tumor PTV expansion in breast cancer radiotherapy without routine, daily IGRT.