Contouring variation affects estimates of normal tissue complication probability for breast fibrosis after radiotherapy

Tanwiwat Jaikuna; Eliana Vasquez Osorio; David Azria; Jenny Chang-Claude; Maria Carmen De Santis; Sara Gutiérrez-Enríquez; Marcel van Herk; Peter Hoskin; Maarten Lambrecht; Zoe Lingard; Petra Seibold; Alejandro Seoane; Elena Sperk; R. Paul Symonds; Christopher J. Talbot; Tiziana Rancati; Tim Rattay; Victoria Reyes; Barry S. Rosenstein; Dirk de Ruysscher; Ana Vega; Liv Veldeman; Adam Webb; Catharine M.L. West; Marianne C. Aznar

doi:10.1016/j.breast.2023.103578

Contouring variation affects estimates of normal tissue complication probability for breast fibrosis after radiotherapy

Tanwiwat Jaikuna, Eliana Vasquez Osorio, David Azria, Jenny Chang-Claude, Maria Carmen De Santis, Sara Gutiérrez-Enríquez, Marcel van Herk, Peter Hoskin, Maarten Lambrecht, Zoe Lingard, Petra Seibold, Alejandro Seoane, Elena Sperk, R. Paul Symonds, Christopher J. Talbot, Tiziana Rancati, Tim Rattay, Victoria Reyes, Barry S. Rosenstein, Dirk de RuysscherAna Vega, Liv Veldeman, Adam Webb, Catharine M.L. West, Marianne C. Aznar^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

Abstract

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.

Original language	English
Article number	103578
Number of pages	9
Journal	Breast
Volume	72
Issue number	1
DOIs	https://doi.org/10.1016/j.breast.2023.103578
Publication status	Published - 1 Dec 2023

Keywords

Breast cancer
Fibrosis
Inter-observer variation
Late effects
NTCP modelling
Radiotherapy

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Jaikuna, T., Osorio, E. V., Azria, D., Chang-Claude, J., De Santis, M. C., Gutiérrez-Enríquez, S., van Herk, M., Hoskin, P., Lambrecht, M., Lingard, Z., Seibold, P., Seoane, A., Sperk, E., Symonds, R. P., Talbot, C. J., Rancati, T., Rattay, T., Reyes, V., Rosenstein, B. S., ... Aznar, M. C. (2023). Contouring variation affects estimates of normal tissue complication probability for breast fibrosis after radiotherapy. Breast, 72(1), Article 103578. https://doi.org/10.1016/j.breast.2023.103578

@article{4c6cc99697f346aab38ce174d55d560f,

title = "Contouring variation affects estimates of normal tissue complication probability for breast fibrosis after radiotherapy",

abstract = "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.",

keywords = "Breast cancer, Fibrosis, Inter-observer variation, Late effects, NTCP modelling, Radiotherapy",

author = "Tanwiwat Jaikuna and Osorio, {Eliana Vasquez} and David Azria and Jenny Chang-Claude and {De Santis}, {Maria Carmen} and Sara Guti{\'e}rrez-Enr{\'i}quez and {van Herk}, Marcel and Peter Hoskin and Maarten Lambrecht and Zoe Lingard and Petra Seibold and Alejandro Seoane and Elena Sperk and Symonds, {R. Paul} and Talbot, {Christopher J.} and Tiziana Rancati and Tim Rattay and Victoria Reyes and Rosenstein, {Barry S.} and {de Ruysscher}, Dirk and Ana Vega and Liv Veldeman and Adam Webb and West, {Catharine M.L.} and Aznar, {Marianne C.}",

note = "Funding Information: REQUITE received funding from the European Union's Seventh Framework Programme for research, technological development, and demonstration under grant agreement no. 601826. We thank all patients who participated in the REQUITE study and all study personnel involved in the REQUITE project. Marianne Aznar acknowledges the support of the Engineering and Physical Sciences Research Council (Grant number EP/T028017/1), This work was supported by Cancer Research UK RadNet Manchester [C1994/A28701] and the NIHR Manchester Biomedical Research Centre (NIHR203308). The researchers at DKFZ also thank Anusha M{\"u}ller, Irmgard Helmbold, Thomas Heger, Sabine Behrens, Juan Camilo Rosas. Petra Seibold was supported by ERA PerMed 2018 funding (BMBF #01KU1912) and BfS funding (#3619S42261). S. Guti{\'e}rrez-Enr{\'i}quez is supported by the Government of Catalonia 2021SGR01112. The VHIO authors acknowledge the Cellex Foundation for providing research equipment and facilities and thank CERCA Program/Generalitat de Catalunya for institutional support. Funding Information: Marianne Aznar acknowledges the support of the Engineering and Physical Sciences Research Council (Grant number EP/T028017/1) Funding Information: REQUITE received funding from the European Union's Seventh Framework Programme for research, technological development, and demonstration under grant agreement no. 601826. Funding Information: The researchers at DKFZ also thank Anusha M{\"u}ller, Irmgard Helmbold, Thomas Heger, Sabine Behrens, Juan Camilo Rosas. Petra Seibold was supported by ERA PerMed 2018 funding (BMBF #01KU1912 ) and BfS funding ( #3619S42261 ). Funding Information: S. Guti{\'e}rrez-Enr{\'i}quez is supported by the Government of Catalonia 2021SGR01112. Funding Information: This work was supported by Cancer Research UK RadNet Manchester [ C1994/A28701 ] and the NIHR Manchester Biomedical Research Centre ( NIHR203308 ). Publisher Copyright: {\textcopyright} 2023",

year = "2023",

month = dec,

day = "1",

doi = "10.1016/j.breast.2023.103578",

language = "English",

volume = "72",

journal = "Breast",

issn = "0960-9776",

publisher = "Churchill Livingstone",

number = "1",

}

Jaikuna, T, Osorio, EV, Azria, D, Chang-Claude, J, De Santis, MC, Gutiérrez-Enríquez, S, van Herk, M, Hoskin, P, Lambrecht, M, Lingard, Z, Seibold, P, Seoane, A, Sperk, E, Symonds, RP, Talbot, CJ, Rancati, T, Rattay, T, Reyes, V, Rosenstein, BS, de Ruysscher, D, Vega, A, Veldeman, L, Webb, A, West, CML & Aznar, MC 2023, 'Contouring variation affects estimates of normal tissue complication probability for breast fibrosis after radiotherapy', Breast, vol. 72, no. 1, 103578. https://doi.org/10.1016/j.breast.2023.103578

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 - Funding Information: REQUITE received funding from the European Union's Seventh Framework Programme for research, technological development, and demonstration under grant agreement no. 601826. We thank all patients who participated in the REQUITE study and all study personnel involved in the REQUITE project. Marianne Aznar acknowledges the support of the Engineering and Physical Sciences Research Council (Grant number EP/T028017/1), This work was supported by Cancer Research UK RadNet Manchester [C1994/A28701] and the NIHR Manchester Biomedical Research Centre (NIHR203308). The researchers at DKFZ also thank Anusha Müller, Irmgard Helmbold, Thomas Heger, Sabine Behrens, Juan Camilo Rosas. Petra Seibold was supported by ERA PerMed 2018 funding (BMBF #01KU1912) and BfS funding (#3619S42261). S. Gutiérrez-Enríquez is supported by the Government of Catalonia 2021SGR01112. The VHIO authors acknowledge the Cellex Foundation for providing research equipment and facilities and thank CERCA Program/Generalitat de Catalunya for institutional support. Funding Information: Marianne Aznar acknowledges the support of the Engineering and Physical Sciences Research Council (Grant number EP/T028017/1) Funding Information: REQUITE received funding from the European Union's Seventh Framework Programme for research, technological development, and demonstration under grant agreement no. 601826. Funding Information: The researchers at DKFZ also thank Anusha Müller, Irmgard Helmbold, Thomas Heger, Sabine Behrens, Juan Camilo Rosas. Petra Seibold was supported by ERA PerMed 2018 funding (BMBF #01KU1912 ) and BfS funding ( #3619S42261 ). Funding Information: S. Gutiérrez-Enríquez is supported by the Government of Catalonia 2021SGR01112. Funding Information: This work was supported by Cancer Research UK RadNet Manchester [ C1994/A28701 ] and the NIHR Manchester Biomedical Research Centre ( NIHR203308 ). Publisher Copyright: © 2023

PY - 2023/12/1

Y1 - 2023/12/1

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

U2 - 10.1016/j.breast.2023.103578

DO - 10.1016/j.breast.2023.103578

M3 - Article

SN - 0960-9776

VL - 72

JO - Breast

JF - Breast

IS - 1

M1 - 103578

ER -

Contouring variation affects estimates of normal tissue complication probability for breast fibrosis after radiotherapy

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