Predicting response to neoadjuvant chemotherapy with liquid biopsies and multiparametric MRI in patients with breast cancer.

Autor: Janssen LM; Image Sciences Institute, University Medical Centre Utrecht, Utrecht University, Utrecht, The Netherlands., Janse MHA; Image Sciences Institute, University Medical Centre Utrecht, Utrecht University, Utrecht, The Netherlands., Penning de Vries BBL; Julius Center for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht University, Utrecht, The Netherlands., van der Velden BHM; Image Sciences Institute, University Medical Centre Utrecht, Utrecht University, Utrecht, The Netherlands., Wolters-van der Ben EJM; Department of Radiology, St Antonius Hospital, Nieuwegein, The Netherlands., van den Bosch SM; Philips Research, Eindhoven, The Netherlands., Sartori A; Agena Bioscience GmbH, Hamburg, Germany., Jovelet C; Stilla Technologies, Villejuif, France., Agterof MJ; Department of Medical Oncology, St. Antonius Hospital, Nieuwegein, The Netherlands., Ten Bokkel Huinink D; Department of Medical Oncology, Alexander Monro Hospital, Bilthoven, The Netherlands., Bouman-Wammes EW; Department of Medical Oncology, Albert Schweitzer Hospital, Dordrecht, The Netherlands., van Diest PJ; Department of Pathology, University Medical Centre Utrecht, Utrecht University, Utrecht, The Netherlands., van der Wall E; Department of Medical Oncology, University Medical Centre Utrecht, Utrecht University, Utrecht, The Netherlands., Elias SG; Julius Center for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht University, Utrecht, The Netherlands., Gilhuijs KGA; Image Sciences Institute, University Medical Centre Utrecht, Utrecht University, Utrecht, The Netherlands. K.G.A.Gilhuijs@umcutrecht.nl.

Publikováno v: NPJ breast cancer [NPJ Breast Cancer] 2024 Jan 20; Vol. 10 (1), pp. 10. Date of Electronic Publication: 2024 Jan 20.

Computed Tomography-Based Radiomics Using Tumor and Vessel Features to Assess Resectability in Cancer of the Pancreatic Head.

Autor: Litjens G; Department of Medical Imaging, Radboud Institute for Health Sciences, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands., Broekmans JPEA; Department of Electrical Engineering, Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands., Boers T; Department of Electrical Engineering, Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands., Caballo M; Department of Medical Imaging, Radboud Institute for Health Sciences, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands., van den Hurk MHF; Department of Plastic and Reconstructive Surgery, Saint Vincent's University Hospital, D04 T6F4 Dublin, Ireland., Ozdemir D; Department of Medical Imaging, Radboud Institute for Health Sciences, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands., van Schaik CJ; Department of Medical Imaging, Radboud Institute for Health Sciences, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands., Janse MHA; Image Sciences Institute, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands., van Geenen EJM; Department of Gastroenterology and Hepatology, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands., van Laarhoven CJHM; Department of Surgery, Radboud Institute for Health Sciences, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands., Prokop M; Department of Medical Imaging, Radboud Institute for Health Sciences, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands., de With PHN; Department of Electrical Engineering, Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands., van der Sommen F; Department of Electrical Engineering, Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands., Hermans JJ; Department of Medical Imaging, Radboud Institute for Health Sciences, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands.

Publikováno v: Diagnostics (Basel, Switzerland) [Diagnostics (Basel)] 2023 Oct 13; Vol. 13 (20). Date of Electronic Publication: 2023 Oct 13.

Deep Learning Analysis of Cardiac MRI in Legacy Datasets: Multi-Ethnic Study of Atherosclerosis.

Autor: Suinesiaputra A; Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand.; Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom., Mauger CA; Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand., Ambale-Venkatesh B; Johns Hopkins Medical Center, Baltimore, MD, United States., Bluemke DA; Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States., Dam Gade J; Department of Biomedical Engineering and Informatics, School of Medicine and Health, Aalborg University, Aalborg, Denmark., Gilbert K; Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand., Janse MHA; Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands., Hald LS; Department of Biomedical Engineering and Informatics, School of Medicine and Health, Aalborg University, Aalborg, Denmark., Werkhoven C; Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand., Wu CO; Division of Intramural Research, National Heart, Lung and Blood Institute, National Institutes of Health, Baltimore, MD, United States., Lima JAC; Johns Hopkins Medical Center, Baltimore, MD, United States., Young AA; Faculty of Life Sciences & Medicine, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.

Publikováno v: Frontiers in cardiovascular medicine [Front Cardiovasc Med] 2022 Jan 21; Vol. 8, pp. 807728. Date of Electronic Publication: 2022 Jan 21 (Print Publication: 2021).