Robert Finnegan1, Ebbe Laugaard Lorenzen2, Jason Dowling3, Ingelise Jensen4, Martin Berg5, Mette Skovhus Thomsen6, Geoff P Delaney7, Eng-Siew Koh7, David Thwaites8, Carsten Brink9, Birgitte Vrou Offersen10, Lois Holloway11. 1. Institute of Medical Physics, School of Physics, University of Sydney, Australia; Ingham Institute for Applied Medical Research, Liverpool, Australia. Electronic address: robert.finnegan@sydney.edu.au. 2. Laboratory of Radiation Physics, Department of Oncology, Odense University Hospital, Odense C, Denmark. 3. Institute of Medical Physics, School of Physics, University of Sydney, Australia; University of Newcastle, School of Mathematical and Physical Sciences, Newcastle, Australia; CSIRO Health and Biosecurity, The Australian e-Health and Research Centre, Herston, Australia. 4. Department of Medical Physics, Aalborg University Hospital, Aalborg, Denmark. 5. Department of Medical Physics, Vejle Hospital, Vejle, Denmark. 6. Department of Medical Physics, Aarhus University Hospital, Aarhus, Denmark. 7. Ingham Institute for Applied Medical Research, Liverpool, Australia; University of New South Wales, South Western Sydney Clinical School, Sydney, Australia; Department of Radiation Oncology, Liverpool & Macarthur Cancer Therapy Centres, Liverpool, Australia. 8. Institute of Medical Physics, School of Physics, University of Sydney, Australia. 9. Laboratory of Radiation Physics, Department of Oncology, Odense University Hospital, Odense C, Denmark; Department of Clinical Research, University of Southern Denmark, Odense, Denmark. 10. Institute of Clinical Medicine, Aarhus University, Aarhus, Denmark; Department of Experimental Clinical Oncology, Aarhus University Hospital, Aarhus, Denmark. 11. Institute of Medical Physics, School of Physics, University of Sydney, Australia; Ingham Institute for Applied Medical Research, Liverpool, Australia; University of New South Wales, South Western Sydney Clinical School, Sydney, Australia; Department of Clinical Research, University of Southern Denmark, Odense, Denmark; Centre for Medical Radiation Physics, University of Wollongong, Wollongong, Australia.
Abstract
BACKGROUND AND PURPOSE: Radiotherapy for breast cancer can increase the risks of heart disease. Patient-specific risk assessment may be improved with the inclusion of doses to cardiac substructures. The purpose of this work was to use automatic segmentation to evaluate substructure doses and develop predictive models for these based on the dose to the whole heart. MATERIAL AND METHODS: Automatic segmentation was used to delineate cardiac substructures in a Danish breast cancer trial (DBCG HYPO) dataset comprising over 1500 Danish women treated between 2009 and 2014. Trends in contouring practices and cardiac doses over time were investigated, and models to predict substructure doses from whole heart dose parameters were fit to the data. RESULTS: Manual contouring consistency improved over the study period when compared with automatic segmentation; systematic differences between automatically and manually defined heart volume decreased from 106 cm3 to 12.0 cm3. Doses to the heart and cardiac substructures also decreased. Mean whole heart doses for left-sided treatments in 2009 and 2014 were 1.94±1.19 Gy and 1.29±0.69 Gy (average ± SD), respectively. Prediction of mean substructure doses is accurate, with R2 scores in the range 0.45-0.95 (average 0.77), depending on the particular structure. CONCLUSION: This study reports heart and cardiac substructure doses in a large breast cancer cohort. Predictive models generated in this work can be used to estimate mean cardiac substructure doses for datasets where patient imaging and dose distributions are not available, provided the tangential field techniques are consistent with those used in the trial.
BACKGROUND AND PURPOSE: Radiotherapy for breast cancer can increase the risks of heart disease. Patient-specific risk assessment may be improved with the inclusion of doses to cardiac substructures. The purpose of this work was to use automatic segmentation to evaluate substructure doses and develop predictive models for these based on the dose to the whole heart. MATERIAL AND METHODS: Automatic segmentation was used to delineate cardiac substructures in a Danish breast cancer trial (DBCG HYPO) dataset comprising over 1500 Danish women treated between 2009 and 2014. Trends in contouring practices and cardiac doses over time were investigated, and models to predict substructure doses from whole heart dose parameters were fit to the data. RESULTS: Manual contouring consistency improved over the study period when compared with automatic segmentation; systematic differences between automatically and manually defined heart volume decreased from 106 cm3 to 12.0 cm3. Doses to the heart and cardiac substructures also decreased. Mean whole heart doses for left-sided treatments in 2009 and 2014 were 1.94±1.19 Gy and 1.29±0.69 Gy (average ± SD), respectively. Prediction of mean substructure doses is accurate, with R2 scores in the range 0.45-0.95 (average 0.77), depending on the particular structure. CONCLUSION: This study reports heart and cardiac substructure doses in a large breast cancer cohort. Predictive models generated in this work can be used to estimate mean cardiac substructure doses for datasets where patient imaging and dose distributions are not available, provided the tangential field techniques are consistent with those used in the trial.
Authors: Shahed N Badiyan; Lindsay L Puckett; Gregory Vlacich; Walter Schiffer; Lauren N Pedersen; Joshua D Mitchell; Carmen Bergom Journal: Curr Treat Options Oncol Date: 2022-09-10
Authors: Robert Neil Finnegan; Lucia Orlandini; Xiongfei Liao; Jun Yin; Jinyi Lang; Jason Dowling; Davide Fontanarosa Journal: PLoS One Date: 2021-01-14 Impact factor: 3.240
Authors: M S Thomsen; M Berg; S Zimmermann; C M Lutz; S Makocki; I Jensen; M H B Hjelstuen; S Pensold; M P Hasler; M-B Jensen; B V Offersen Journal: Clin Transl Radiat Oncol Date: 2021-04-06