Japanese Radiology 2025 Updates.
Authors
Affiliations (10)
Affiliations (10)
- Department of Fundamental Development for Advanced Low Invasive Diagnostic Imaging, Nagoya University Graduate School of Medicine, Nagoya, Japan.
- Department of Radiology, Institute of Medicine, University of Tsukuba, Ibaraki, Japan.
- Department of Radiology, Keio University School of Medicine Graduate School of Medicine, Tokyo, Japan.
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
- Department of Artificial Intelligence, Graduate School of Medicine, Osaka Metropolitan University, Osaka, Japan.
- Preemptive Medicine and Lifestyle-related Disease Research Center, Kyoto University Hospital, Kyoto, Japan.
- Radiation Oncology Division, Global Center for Biomedical Science and Engineering, Faculty of Medicine, Hokkaido University, Hokkaido, Japan.
- Department of Innovative BioMedical Visualization, Nagoya University Graduate School of Medicine, Nagoya, Japan.
- Department of Radiology, Kobe University Graduate School of Medicine, Hyogo, Japan.
- Department of Radiology, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Abstract
This review provides a comprehensive overview of recent transformative advancements in diagnostic imaging that position Japan at the forefront of radiological innovation. We highlight pivotal innovations that enhance diagnostic capabilities and redefine clinical workflows. The article begins with upright multidetector computed tomography (MDCT), a groundbreaking technology offering novel insights into posture-dependent anatomical and physiological changes. We then explore significant progress in breast and gynecologic imaging, including advancements in artificial intelligence computer-aided (AI-CAD) synthesized mammograms, automated breast ultrasound (ABUS), and abbreviated MRI protocols. These innovations address unique regional challenges in early cancer detection. Significant innovations in abdominal radiology, spanning advanced CT (including photon-counting detector CT), accelerated MRI, and AI applications, are also discussed. The review further delves into glymphatic system research, where advanced MRI techniques, particularly DTI-ALPS, are unraveling new insights into brain waste clearance and neurological disorders. Finally, we examine the future of Japanese radiology through the lens of AI, with a focus on Large Language Models (LLMs). We discuss their growing role in diagnostic support, report generation, and information extraction, as well as important societal and ethical considerations. These collective advancements underscore Japan's dynamic contributions to radiological innovation, poised to significantly impact global healthcare practices by improving disease detection, optimizing workflows, and extending healthy life expectancy in an aging society.