Contouring variation affects estimates of normal tissue complication probability for breast fibrosis after radiotherapy
Background: Normal tissue complication probability (NTCP) models can be useful to estimate the risk of fibrosis after breast-conserving surgery (BCS) and radiotherapy (RT) to the breast. However, they are subject to uncertainties. We present the impact of contouring variation on the prediction of fi...
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th-mahidol.900752023-09-22T01:01:03Z Contouring variation affects estimates of normal tissue complication probability for breast fibrosis after radiotherapy Jaikuna T. Mahidol University Biochemistry, Genetics and Molecular Biology Background: Normal tissue complication probability (NTCP) models can be useful to estimate the risk of fibrosis after breast-conserving surgery (BCS) and radiotherapy (RT) to the breast. However, they are subject to uncertainties. We present the impact of contouring variation on the prediction of fibrosis. Materials and methods: 280 breast cancer patients treated BCS-RT were included. Nine Clinical Target Volume (CTV) contours were created for each patient: i) CTV_crop (reference), cropped 5 mm from the skin and ii) CTV_skin, uncropped and including the skin, iii) segmenting the 95% isodose (Iso95%) and iv) 3 different auto-contouring atlases generating uncropped and cropped contours (Atlas_skin/Atlas_crop). To illustrate the impact of contour variation on NTCP estimates, we applied two equations predicting fibrosis grade ≥ 2 at 5 years, based on Lyman-Kutcher-Burman (LKB) and Relative Seriality (RS) models, respectively, to each contour. Differences were evaluated using repeated-measures ANOVA. For completeness, the association between observed fibrosis events and NTCP estimates was also evaluated using logistic regression. Results: There were minimal differences between contours when the same contouring approach was followed (cropped and uncropped). CTV_skin and Atlas_skin contours had lower NTCP estimates (−3.92%, IQR 4.00, p < 0.05) compared to CTV_crop. No significant difference was observed for Atlas_crop and Iso95% contours compared to CTV_crop. For the whole cohort, NTCP estimates varied between 5.3% and 49.5% (LKB) or 2.2% and 49.6% (RS) depending on the choice of contours. NTCP estimates for individual patients varied by up to a factor of 4. Estimates from “skin” contours showed higher agreement with observed events. Conclusion: Contour variations can lead to significantly different NTCP estimates for breast fibrosis, highlighting the importance of standardising breast contours before developing and/or applying NTCP models. 2023-09-21T18:01:03Z 2023-09-21T18:01:03Z 2023-12-01 Article Breast Vol.72 (2023) 10.1016/j.breast.2023.103578 15323080 09609776 2-s2.0-85170699959 https://repository.li.mahidol.ac.th/handle/123456789/90075 SCOPUS |
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Biochemistry, Genetics and Molecular Biology Jaikuna T. Contouring variation affects estimates of normal tissue complication probability for breast fibrosis after radiotherapy |
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Background: Normal tissue complication probability (NTCP) models can be useful to estimate the risk of fibrosis after breast-conserving surgery (BCS) and radiotherapy (RT) to the breast. However, they are subject to uncertainties. We present the impact of contouring variation on the prediction of fibrosis. Materials and methods: 280 breast cancer patients treated BCS-RT were included. Nine Clinical Target Volume (CTV) contours were created for each patient: i) CTV_crop (reference), cropped 5 mm from the skin and ii) CTV_skin, uncropped and including the skin, iii) segmenting the 95% isodose (Iso95%) and iv) 3 different auto-contouring atlases generating uncropped and cropped contours (Atlas_skin/Atlas_crop). To illustrate the impact of contour variation on NTCP estimates, we applied two equations predicting fibrosis grade ≥ 2 at 5 years, based on Lyman-Kutcher-Burman (LKB) and Relative Seriality (RS) models, respectively, to each contour. Differences were evaluated using repeated-measures ANOVA. For completeness, the association between observed fibrosis events and NTCP estimates was also evaluated using logistic regression. Results: There were minimal differences between contours when the same contouring approach was followed (cropped and uncropped). CTV_skin and Atlas_skin contours had lower NTCP estimates (−3.92%, IQR 4.00, p < 0.05) compared to CTV_crop. No significant difference was observed for Atlas_crop and Iso95% contours compared to CTV_crop. For the whole cohort, NTCP estimates varied between 5.3% and 49.5% (LKB) or 2.2% and 49.6% (RS) depending on the choice of contours. NTCP estimates for individual patients varied by up to a factor of 4. Estimates from “skin” contours showed higher agreement with observed events. Conclusion: Contour variations can lead to significantly different NTCP estimates for breast fibrosis, highlighting the importance of standardising breast contours before developing and/or applying NTCP models. |
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Mahidol University |
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Mahidol University Jaikuna T. |
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Jaikuna T. |
title |
Contouring variation affects estimates of normal tissue complication probability for breast fibrosis after radiotherapy |
title_short |
Contouring variation affects estimates of normal tissue complication probability for breast fibrosis after radiotherapy |
title_full |
Contouring variation affects estimates of normal tissue complication probability for breast fibrosis after radiotherapy |
title_fullStr |
Contouring variation affects estimates of normal tissue complication probability for breast fibrosis after radiotherapy |
title_full_unstemmed |
Contouring variation affects estimates of normal tissue complication probability for breast fibrosis after radiotherapy |
title_sort |
contouring variation affects estimates of normal tissue complication probability for breast fibrosis after radiotherapy |
publishDate |
2023 |
url |
https://repository.li.mahidol.ac.th/handle/123456789/90075 |
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1781415297140391936 |