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Advanced Automated Model for Robust Bone Marrow Segmentation in Whole-body MRI.
Acad Radiol
January 2025
Division of Radiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany (F.B., M.G., H.P.S., S.D.); Diagnostic and Interventional Radiology, University Hospital Heidelberg, 69120 Heidelberg, Germany (T.F.W., M.W.).
Rationale And Objectives: To establish an advanced automated bone marrow (BM) segmentation model on whole-body (WB-)MRI in monoclonal plasma cell disorders (MPCD), and to demonstrate its robust performance on multicenter datasets with severe myeloma-related pathologies.
Materials And Methods: The study cohort comprised multi-vendor, multi-protocol imaging data acquired with varying field strength across 8 different centers. In total, 210 WB-MRIs of 207 MPCD patients were included.
Photoacoustic Imaging with Attention-Guided Deep Learning for Predicting Axillary Lymph Node Status in Breast Cancer.
Acad Radiol
January 2025
Department of Ultrasound, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital), Shenzhen 518020, Guangdong, China (G.L., S.T., Z.H., M.W., S.M., J.X., F.D.); Department of Ultrasound, The First Affiliated Hospital, Southern University of Science and Technology (Shenzhen People's Hospital), Shenzhen 518020, Guangdong, China (H.T., H.W., J.X., F.D.). Electronic address:
Rationale And Objectives: Preoperative assessment of axillary lymph node (ALN) status is essential for breast cancer management. This study explores the use of photoacoustic (PA) imaging combined with attention-guided deep learning (DL) for precise prediction of ALN status.
Materials And Methods: This retrospective study included patients with histologically confirmed early-stage breast cancer from 2022 to 2024, randomly divided (8:2) into training and test cohorts.
Modern CT detector technology and innovations in image reconstruction enhance cardiovascular CT.
J Cardiovasc Comput Tomogr
January 2025
Department of Cardiac Imaging, Lee Health Heart Institute, Fort Myers, FL, United States. Electronic address:
Fluorescence lifetime imaging in drug delivery research.
Adv Drug Deliv Rev
January 2025
Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 117997, Moscow, Russia; School of Mathematical and Physical Sciences, Faculty of Science and Engineering, Macquarie University, Sydney, NSW 2109, Australia; Research Center for Translational Medicine, Sirius University of Science and Technology, 354340, Sochi, Russia; National Research Ogarev Mordovia State University, Saransk, Mordovia Republic 430005, Russia.
Once an exotic add-on to fluorescence microscopy for life science research, fluorescence lifetime imaging (FLIm) has become a powerful and increasingly utilised technique owing to its self-calibration nature, which affords superior quantification over conventional steady-state fluorescence imaging. This review focuses on the state-of-the-art implementation of FLIm related to the formulation, release, dosage, and mechanism of action of drugs aimed for innovative diagnostics and therapy. Quantitative measurements using FLIm have appeared instrumental for encapsulated drug delivery design, pharmacokinetics and pharmacodynamics, pathological investigations, early disease diagnosis, and evaluation of therapeutic efficacy.
View Article and Find Full Text PDFNote of concern regarding the sources of scientific evidence used to justify the Reclassification of Non-Invasive Brain Stimulation (NIBS) Devices without an intended medical purpose into Class III.
Brain Stimul
January 2025
Faculty of Medicine and Health Sciences, Department of Head and Skin, Ghent Experimental Psychiatry (GHEP) lab, Ghent University, Ghent, Belgium; Neuroprotection and Neuromodulation Research Group (NEUR), Center for Neurosciences (C4N), Vrije Universiteit Brussel (VUB), Brussels, Belgium; Department of Psychiatry, Universitair Ziekenhuis Brussel (UZ Brussel), Brussels, Belgium; Center for Care and Cure Technology (C3Te), Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands.
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