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@ARTICLE{Jaikuna:282898,
author = {T. Jaikuna and E. V. Osorio and D. Azria and J.
Chang-Claude$^*$ and M. C. De Santis and S.
Gutiérrez-Enríquez and M. van Herk and P. Hoskin and M.
Lambrecht and Z. Lingard and P. Seibold$^*$ and A. Seoane
and E. Sperk and R. P. Symonds and C. J. Talbot and T.
Rancati and T. Rattay and V. Reyes and B. S. Rosenstein and
D. de Ruysscher and A. Vega and L. Veldeman and A. Webb and
C. M. L. West and M. C. Aznar},
title = {{C}ontouring variation affects estimates of normal tissue
complication probability for breast fibrosis after
radiotherapy.},
journal = {The breast},
volume = {72},
issn = {0960-9776},
address = {Amsterdam [u.a.]},
publisher = {Elsevier},
reportid = {DKFZ-2023-01891},
pages = {103578},
year = {2023},
abstract = {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.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.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.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 (Other) / Fibrosis (Other) / Inter-observer
variation (Other) / Late effects (Other) / NTCP modelling
(Other) / Radiotherapy (Other)},
cin = {C020},
ddc = {610},
cid = {I:(DE-He78)C020-20160331},
pnm = {313 - Krebsrisikofaktoren und Prävention (POF4-313)},
pid = {G:(DE-HGF)POF4-313},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:37713940},
doi = {10.1016/j.breast.2023.103578},
url = {https://inrepo02.dkfz.de/record/282898},
}