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000282898 1001_ $$aJaikuna, Tanwiwat$$b0
000282898 245__ $$aContouring variation affects estimates of normal tissue complication probability for breast fibrosis after radiotherapy.
000282898 260__ $$aAmsterdam [u.a.]$$bElsevier$$c2023
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000282898 520__ $$aNormal tissue complication probability (NTCP) models can be useful to estimate the risk of fibrosis after breast-conserving surgery (BCS) and radiotherapy (RT) to the breast. However, they are subject to uncertainties. We present the impact of contouring variation on the prediction of fibrosis.280 breast cancer patients treated BCS-RT were included. Nine Clinical Target Volume (CTV) contours were created for each patient: i) CTV_crop (reference), cropped 5 mm from the skin and ii) CTV_skin, uncropped and including the skin, iii) segmenting the 95% isodose (Iso95%) and iv) 3 different auto-contouring atlases generating uncropped and cropped contours (Atlas_skin/Atlas_crop). To illustrate the impact of contour variation on NTCP estimates, we applied two equations predicting fibrosis grade ≥ 2 at 5 years, based on Lyman-Kutcher-Burman (LKB) and Relative Seriality (RS) models, respectively, to each contour. Differences were evaluated using repeated-measures ANOVA. For completeness, the association between observed fibrosis events and NTCP estimates was also evaluated using logistic regression.There were minimal differences between contours when the same contouring approach was followed (cropped and uncropped). CTV_skin and Atlas_skin contours had lower NTCP estimates (-3.92%, IQR 4.00, p < 0.05) compared to CTV_crop. No significant difference was observed for Atlas_crop and Iso95% contours compared to CTV_crop. For the whole cohort, NTCP estimates varied between 5.3% and 49.5% (LKB) or 2.2% and 49.6% (RS) depending on the choice of contours. NTCP estimates for individual patients varied by up to a factor of 4. Estimates from 'skin' contours showed higher agreement with observed events.Contour variations can lead to significantly different NTCP estimates for breast fibrosis, highlighting the importance of standardising breast contours before developing and/or applying NTCP models.
000282898 536__ $$0G:(DE-HGF)POF4-313$$a313 - Krebsrisikofaktoren und Prävention (POF4-313)$$cPOF4-313$$fPOF IV$$x0
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000282898 650_7 $$2Other$$aBreast cancer
000282898 650_7 $$2Other$$aFibrosis
000282898 650_7 $$2Other$$aInter-observer variation
000282898 650_7 $$2Other$$aLate effects
000282898 650_7 $$2Other$$aNTCP modelling
000282898 650_7 $$2Other$$aRadiotherapy
000282898 7001_ $$aOsorio, Eliana Vasquez$$b1
000282898 7001_ $$aAzria, David$$b2
000282898 7001_ $$0P:(DE-He78)c259d6cc99edf5c7bc7ce22c7f87c253$$aChang-Claude, Jenny$$b3$$udkfz
000282898 7001_ $$aDe Santis, Maria Carmen$$b4
000282898 7001_ $$aGutiérrez-Enríquez, Sara$$b5
000282898 7001_ $$avan Herk, Marcel$$b6
000282898 7001_ $$aHoskin, Peter$$b7
000282898 7001_ $$aLambrecht, Maarten$$b8
000282898 7001_ $$aLingard, Zoe$$b9
000282898 7001_ $$0P:(DE-He78)fd17a8dbf8d08ea5bb656dfef7398215$$aSeibold, Petra$$b10$$udkfz
000282898 7001_ $$aSeoane, Alejandro$$b11
000282898 7001_ $$aSperk, Elena$$b12
000282898 7001_ $$aSymonds, R Paul$$b13
000282898 7001_ $$aTalbot, Christopher J$$b14
000282898 7001_ $$aRancati, Tiziana$$b15
000282898 7001_ $$aRattay, Tim$$b16
000282898 7001_ $$aReyes, Victoria$$b17
000282898 7001_ $$aRosenstein, Barry S$$b18
000282898 7001_ $$ade Ruysscher, Dirk$$b19
000282898 7001_ $$aVega, Ana$$b20
000282898 7001_ $$aVeldeman, Liv$$b21
000282898 7001_ $$aWebb, Adam$$b22
000282898 7001_ $$aWest, Catharine M L$$b23
000282898 7001_ $$aAznar, Marianne C$$b24
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