Breast (Dec 2023)

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

Journal volume & issue
Vol. 72
p. 103578

Abstract

Read online

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