TY - JOUR
T1 - Contouring variation affects estimates of normal tissue complication probability for breast fibrosis after radiotherapy
AU - Jaikuna, Tanwiwat
AU - Osorio, Eliana Vasquez
AU - Azria, David
AU - Chang-Claude, Jenny
AU - De Santis, Maria Carmen
AU - Gutiérrez-Enríquez, Sara
AU - van Herk, Marcel
AU - Hoskin, Peter
AU - Lambrecht, Maarten
AU - Lingard, Zoe
AU - Seibold, Petra
AU - Seoane, Alejandro
AU - Sperk, Elena
AU - Symonds, R. Paul
AU - Talbot, Christopher J.
AU - Rancati, Tiziana
AU - Rattay, Tim
AU - Reyes, Victoria
AU - Rosenstein, Barry S.
AU - de Ruysscher, Dirk
AU - Vega, Ana
AU - Veldeman, Liv
AU - Webb, Adam
AU - West, Catharine M.L.
AU - Aznar, Marianne C.
N1 - Publisher Copyright:
© 2023
PY - 2023/12
Y1 - 2023/12
N2 - 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.
AB - 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.
KW - Breast cancer
KW - Fibrosis
KW - Inter-observer variation
KW - Late effects
KW - NTCP modelling
KW - Radiotherapy
UR - https://www.scopus.com/pages/publications/85170699959
U2 - 10.1016/j.breast.2023.103578
DO - 10.1016/j.breast.2023.103578
M3 - Article
C2 - 37713940
AN - SCOPUS:85170699959
SN - 0960-9776
VL - 72
JO - Breast
JF - Breast
M1 - 103578
ER -