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The role of medical physics professionals (MPPs) (medical physicists and medical physics experts) in physiological measurement and related therapies (PM&T) applied in e.g., critical care, neurophysiology, neurology, physiology, audiology, and neurotology has long been acknowledged. Given that the exact role and medical specialty fields in which MPP are involved vary between countries, this policy statement aims to provide direction towards improved definition, harmonisation, and development of the role. This policy statement considers the surveyed experiences from several European countries, state-of-the-art of PM&T, and anticipated future developments. We also present an inventory of competences, and associated knowledge and skills expected of MPPs working in these areas.
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http://dx.doi.org/10.1016/j.ejmp.2025.104923 | DOI Listing |
Brachytherapy
September 2025
Department of Radiological Sciences, School of Health Sciences, Fukushima Medical University, 10-6 Sakaemachi, Fukushima, Fukushima, 960-8516, Japan.
Purpose: This study presents the dose-based intra-preplan (DIP) method for intracavitary/interstitial brachytherapy (IC/ISBT) in cervical cancer, optimizing catheter configurations based on dose distribution. This study aimed to assess the DIP method's clinical feasibility and efficacy.
Methods And Materials: The DIP method incorporates the implant modeling function and the hybrid inverse planning optimization algorithm in Oncentra Brachy.
NMR Biomed
October 2025
Department of Radiology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, People's Republic of China.
Chronic kidney disease (CKD) is an increasing global health problem, resulting in gradual loss of renal function and irreversible renal injury. The noninvasive detection, monitoring, and timely intervention of CKD might benefit the patients' prognosis. This study aims to assess renal functional injury in CKD patients by using magnetic resonance imaging (MRI) of quantitative susceptibility mapping (QSM).
View Article and Find Full Text PDFInt J Biol Macromol
September 2025
Crystal Growth Centre, Anna University, Chennai, 600025, Tamil Nadu, India.
Increase in breast cancer has led to the search for systems that can enable, targeted, sustained and prolonged release of drugs while simultaneously reducing the side effects posed by them. In light of this, folic acid-conjugated 5-Fluorouracil and doxorubicin loaded chitosan/Fe₃O₄ (FA-dual@CS/Fe₃O₄) nanocomposite has been synthesized using the chemical method for targeted breast cancer therapy in addition to CS/FeO and dual drug encapsulated CS/FeO. FTIR and XPS studies confirm the successful drug encapsulation and FA conjugation.
View Article and Find Full Text PDFInt J Biol Macromol
September 2025
Nanotechnology Laboratory, TRANSCEND Research Center, Regional Institute of Oncology, 2-4 General Henri Mathias Berthelot Street, 700483, Iași, Romania; Faculty of Chemistry, Al. I. Cuza University, 11- Carol I Bvd., 700506, Iasi, Romania. Electronic address:
This contribution discusses the design of bionanocomposites based on chitosan and MgAl layered double hydroxides (LDH) for cancer therapy. Compared to other studies, our approach was to pre-adsorb the metal chloride precursors of LDH on chitosan while the solution of metal precursors with and without H provided the acidic environment for polymer dissolution. The structure, morphology and chemical composition of the bionanocomposites were characterized by XRD, FTIR, TG, etc.
View Article and Find Full Text PDFInt J Radiat Oncol Biol Phys
September 2025
Radiation Oncology, University of California, San Francisco, 505 Parnassus Ave, San Francisco, CA 94143. Electronic address:
Purpose: Accelerating MR acquisition is essential for image guided therapeutic applications. Compressed sensing (CS) has been developed to minimize image artifacts in accelerated scans, but the required iterative reconstruction is computationally complex and difficult to generalize. Convolutional neural networks (CNNs)/Transformers-based deep learning (DL) methods emerged as a faster alternative but face challenges in modeling continuous k-space, a problem amplified with non-Cartesian sampling commonly used in accelerated acquisition.
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