Validation of an established deep learning auto-segmentation tool for cardiac substructures in 4D radiotherapy planning scans

[1]  E. Ford,et al.  Improving the Quality of Care in Radiation Oncology using Artificial Intelligence. , 2021, Clinical oncology (Royal College of Radiologists (Great Britain)).

[2]  R. He,et al.  Evaluation of deep learning-based multiparametric MRI oropharyngeal primary tumor auto-segmentation and investigation of input channel effects: Results from a prospective imaging registry , 2021, Clinical and translational radiation oncology.

[3]  J. Bussink,et al.  Deep Learning Model for Automatic Contouring of Cardiovascular Substructures on Radiotherapy Planning CT Images: Dosimetric Validation and Reader Study based Clinical Acceptability Testing. , 2021, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[4]  J. Fenwick,et al.  Associations between cardiac irradiation and survival in patients with non-small cell lung cancer: validation and new discoveries in an independent dataset. , 2021, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[5]  M. Viergever,et al.  AI-based quantification of planned radiotherapy dose to cardiac structures and coronary arteries in breast cancer patients. , 2021, International journal of radiation oncology, biology, physics.

[6]  M. Roumeliotis,et al.  Increasing demand on human capital and resource utilization in radiotherapy: The past decade. , 2021, International journal of radiation oncology, biology, physics.

[7]  S. Petit,et al.  The impact of organ-at-risk contour variations on automatically generated treatment plans for NSCLC. , 2021, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[8]  A. van der Schaaf,et al.  Validation of separate multi-atlases for auto segmentation of cardiac substructures in CT-scans acquired in deep inspiration breath hold and free breathing. , 2021, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[9]  T. Bortfeld,et al.  Automated clinical target volume delineation using deep 3D neural networks in radiation therapy of Non-small Cell Lung Cancer , 2021, Physics and imaging in radiation oncology.

[10]  Xiaohui Xie,et al.  A deep learning-based auto-segmentation system for organs-at-risk on whole-body computed tomography images for radiation therapy. , 2021, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[11]  H. Zaidi,et al.  Deep learning-based Auto-segmentation of Organs at Risk in High-Dose Rate Brachytherapy of Cervical Cancer. , 2021, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[12]  C. Glide-Hurst,et al.  Quantifying inter-fraction cardiac substructure displacement during radiotherapy via magnetic resonance imaging guidance , 2021, Physics and imaging in radiation oncology.

[13]  Anurag K. Singh,et al.  Autosegmentation of cardiac substructures in respiratory-gated, non-contrasted computed tomography images , 2021, World journal of clinical oncology.

[14]  G. Dhonneur,et al.  A radiotherapy contouring atlas for cardiac conduction node delineation. , 2021, Practical radiation oncology.

[15]  R. Mak,et al.  Association of Left Anterior Descending Coronary Artery Radiation Dose With Major Adverse Cardiac Events and Mortality in Patients With Non-Small Cell Lung Cancer. , 2020, JAMA oncology.

[16]  M. Aznar,et al.  Cardiac Toxicity of Thoracic Radiotherapy: Existing Evidence and Future Directions , 2020, Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer.

[17]  J. Deasy,et al.  Using auto-segmentation to reduce contouring and dose inconsistency in clinical trials: the simulated impact on RTOG 0617. , 2020, International journal of radiation oncology, biology, physics.

[18]  S. Teoh,et al.  Proton vs photon: A model-based approach to patient selection for reduction of cardiac toxicity in locally advanced lung cancer , 2020, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[19]  P Loap,et al.  Evaluation of a delineation software for cardiac atlas-based autosegmentation: An example of the use of artificial intelligence in modern radiotherapy. , 2020, Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique.

[20]  R. Steenbakkers,et al.  Assessment of manual adjustment performed in clinical practice following deep learning contouring for head and neck organs at risk in radiotherapy , 2020, Physics and imaging in radiation oncology.

[21]  M. V. van Herk,et al.  Protecting the heart: a practical approach to account for the full extent of heart motion in radiotherapy planning. , 2020, International journal of radiation oncology, biology, physics.

[22]  M. V. van Herk,et al.  Dose surface maps of the heart can identify regions associated with worse survival for lung cancer patients treated with radiotherapy , 2020, Physics and imaging in radiation oncology.

[23]  M. V. van Herk,et al.  Novel methodology to investigate the impact of radiation dose to heart sub-structures on overall survival. , 2020, International journal of radiation oncology, biology, physics.

[24]  C. Hansen,et al.  Delineation of whole heart and substructures in thoracic radiation therapy: National guidelines and contouring atlas by the danish multidisciplinary cancer groups. , 2020, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[25]  Joseph O. Deasy,et al.  Cardio-pulmonary substructure segmentation of radiotherapy computed tomography images using convolutional neural networks for clinical outcomes analysis , 2020, Physics and imaging in radiation oncology.

[26]  M. Viergever,et al.  Deep Learning for Automatic Calcium Scoring in CT: Validation Using Multiple Cardiac CT and Chest CT Protocols. , 2020, Radiology.

[27]  Gabriele Guidi,et al.  Hierarchical clustering applied to automatic atlas based segmentation of 25 cardiac sub-structures. , 2019, Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics.

[28]  E. Yorke,et al.  Toward personalized dose-prescription in locally advanced non-small cell lung cancer: Validation of published normal tissue complication probability models. , 2019, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[29]  C. Fiandra,et al.  Inclusion of heart substructures in the optimization process of volumetric modulated arc therapy techniques may reduce the risk of heart disease in Hodgkin's lymphoma patients. , 2019, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[30]  A. D'Amico,et al.  Cardiac Radiation Dose, Cardiac Disease, and Mortality in Patients With Lung Cancer. , 2019, Journal of the American College of Cardiology.

[31]  D. Landau,et al.  Assessment of contour variability in target volumes and organs at risk in lung cancer radiotherapy , 2019, Technical innovations & patient support in radiation oncology.

[32]  Jason Dowling,et al.  Feasibility of multi-atlas cardiac segmentation from thoracic planning CT in a probabilistic framework , 2019, Physics in medicine and biology.

[33]  Johannes A. Langendijk,et al.  Development and evaluation of an auto-segmentation tool for the left anterior descending coronary artery of breast cancer patients based on anatomical landmarks. , 2019, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[34]  Eric D Morris,et al.  Cardiac Substructure Segmentation and Dosimetry Using a Novel Hybrid Magnetic Resonance and Computed Tomography Cardiac Atlas. , 2019, International journal of radiation oncology, biology, physics.

[35]  Robert Kaderka,et al.  Geometric and dosimetric evaluation of atlas based auto-segmentation of cardiac structures in breast cancer patients. , 2019, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[36]  P. Tchou,et al.  Analysis of cardiac motion without respiratory motion for cardiac stereotactic body radiation therapy , 2018, Journal of applied clinical medical physics.

[37]  Daniel Gomez,et al.  Automatic segmentation of cardiac substructures from noncontrast CT images: accurate enough for dosimetric analysis? , 2018, Acta oncologica.

[38]  Sinae Kim,et al.  Dosimetric Predictors of Symptomatic Cardiac Events After Conventional‐Dose Chemoradiation Therapy for Inoperable NSCLC , 2018, Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer.

[39]  Marcel van Herk,et al.  Radiation dose to heart base linked with poorer survival in lung cancer patients. , 2017, European journal of cancer.

[40]  M. Socinski,et al.  Heart dosimetric analysis of three types of cardiac toxicity in patients treated on dose-escalation trials for Stage III non-small-cell lung cancer. , 2017, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[41]  D. Landau,et al.  The Impact of Cardiac Radiation Dosimetry on Survival After Radiation Therapy for Non-Small Cell Lung Cancer , 2017, International journal of radiation oncology, biology, physics.

[42]  Kazem Rahimi,et al.  A cardiac contouring atlas for radiotherapy , 2017, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[43]  Cheng-Bo Han,et al.  Is pulmonary artery a dose-limiting organ at risk in non-small cell lung cancer patients treated with definitive radiotherapy? , 2017, Radiation oncology.

[44]  J. Bradley,et al.  Heart Dose Is an Independent Dosimetric Predictor of Overall Survival in Locally Advanced Non–Small Cell Lung Cancer , 2017, Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer.

[45]  M. Harbinson,et al.  Cardiotoxicity Following Cancer Treatment , 2017, The Ulster medical journal.

[46]  L. Holloway,et al.  Uncertainties in volume delineation in radiation oncology: A systematic review and recommendations for future studies. , 2016, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[47]  Michael G Jameson,et al.  Correlation of contouring variation with modeled outcome for conformal non-small cell lung cancer radiotherapy. , 2014, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[48]  L. Quint,et al.  Pulmonary artery invasion, high-dose radiation, and overall survival in patients with non-small cell lung cancer. , 2014, International journal of radiation oncology, biology, physics.

[49]  A J Cole,et al.  Motion management for radical radiotherapy in non-small cell lung cancer. , 2014, Clinical oncology (Royal College of Radiologists (Great Britain)).

[50]  Andre Dekker,et al.  Radiomics: the process and the challenges. , 2012, Magnetic resonance imaging.

[51]  Andras Lasso,et al.  SlicerRT: radiation therapy research toolkit for 3D Slicer. , 2012, Medical physics.

[52]  Joseph O Deasy,et al.  CERR: a computational environment for radiotherapy research. , 2003, Medical physics.

[53]  Tinsu Pan,et al.  Cardiac atlas development and validation for automatic segmentation of cardiac substructures. , 2017, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[54]  Aamer Chughtai,et al.  Development and validation of a heart atlas to study cardiac exposure to radiation following treatment for breast cancer. , 2011, International journal of radiation oncology, biology, physics.

[55]  Vitali Moiseenko,et al.  Radiation dose-volume effects in the heart. , 2010, International journal of radiation oncology, biology, physics.