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View article: Abstract RF2-05: Validation of the association between TILs, ER status and benefit of radiotherapy in node positive, breast cancer patients: a DBCG study
Abstract RF2-05: Validation of the association between TILs, ER status and benefit of radiotherapy in node positive, breast cancer patients: a DBCG study Open
Background: Studies of the Danish Breast Cancer Group (DBCG)82bc cohort of high-risk breast cancer (BC) patients randomized to +/- postmastectomy radiotherapy (RT) showed that high levels of tumor-infiltrating lymphocytes (TILs) in treatme…
View article: The effect of coronary artery calcifications and radiotherapy on the risk of coronary artery disease in high-risk breast cancer patients in the DBCG RT-Nation cohort
The effect of coronary artery calcifications and radiotherapy on the risk of coronary artery disease in high-risk breast cancer patients in the DBCG RT-Nation cohort Open
AS from planning CT-scans predicted CAD risk and overall survival in breast cancer patients receiving radiotherapy. The MHD remained the strongest predictor in patients with low CAC. For patients with high CAC, the high baseline risk from …
View article: Development and comprehensive evaluation of a national DBCG consensus-based auto-segmentation model for lymph node levels in breast cancer radiotherapy
Development and comprehensive evaluation of a national DBCG consensus-based auto-segmentation model for lymph node levels in breast cancer radiotherapy Open
DL models were developed on a national consensus cohort and performed on par with the IOV between BC experts and had a comparable or higher clinical acceptance than expert manual delineations.
View article: Data harvesting vs data farming: A study of the importance of variation vs sample size in deep learning-based auto-segmentation for breast cancer patients
Data harvesting vs data farming: A study of the importance of variation vs sample size in deep learning-based auto-segmentation for breast cancer patients Open
The aim of this study was to investigate the difference in output, when training a model in three different scenarios: a large clinical delineated data set (with 700/78 patients for training/testing, from the Danish Breast Cancer Group (DB…
View article: Shared decision making with breast cancer patients – does it work? Results of the cluster-randomized, multicenter DBCG RT SDM trial
Shared decision making with breast cancer patients – does it work? Results of the cluster-randomized, multicenter DBCG RT SDM trial Open
Patient engagement in medical decision making was significantly improved with the use of an in-consultation patient decision aid compared to standard. The DH on adjuvant whole breast irradiation is now recommended as standard of care in th…
View article: Development of a national deep learning-based auto-segmentation model for the heart on clinical delineations from the DBCG RT nation cohort
Development of a national deep learning-based auto-segmentation model for the heart on clinical delineations from the DBCG RT nation cohort Open
This study demonstrated a deep learning-based auto-segmentation model trained on curated clinical delineations which performs on par with a model trained on dedicated delineations, making it easier to develop multi-institutional auto-segme…