Kentaro Nishioka

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.

Photon-counting detector computed tomography in thoracic oncology: revolutionizing tumor imaging through precision and detail - Diagnostic and Interventional Radiology

Recent advances in molecular genetics have revolutionized the classification of pediatric-type high-grade gliomas in the 2021 World Health Organization central nervous system tumor classification. This narrative review synthesizes current evidence on the following four tumor types: diffuse midline glioma, H3 K27-altered; diffuse hemispheric glioma, H3 G34-mutant; diffuse pediatric-type high-grade glioma, H3-wildtype and IDH-wildtype; and infant-type hemispheric glioma. We conducted a comprehensive literature search for articles published through January 2025. For each tumor type, we analyze characteristic clinical presentations, molecular alterations, conventional and advanced magnetic resonance imaging features, radiological-molecular correlations, and current therapeutic approaches. Emerging radiogenomic approaches utilizing artificial intelligence, including radiomics and deep learning, show promise in identifying imaging biomarkers that correlate with molecular features. This review highlights the importance of integrating radiological and molecular data for accurate diagnosis and treatment planning, while acknowledging limitations in current methodologies and the need for prospective validation in larger cohorts. Understanding these correlations is crucial for advancing personalized treatment strategies for these challenging tumors.

Lymphopenia during chemoradiotherapy (CRT) for glioblastoma has been shown to be a poor prognostic factor. However, the relationship between prolonged lymphopenia (PL) after CRT and prognosis remains unclear. This study aimed to explore the relationship between PL and glioblastoma prognosis and develop a predictive model for PL risk. We analyzed 87 patients with primary glioblastoma who underwent postoperative CRT with 60 Gy in 30 fractions of radiotherapy and temozolomide. PL was defined as grade 2 or higher lymphopenia 1 month after the completion of CRT. We conducted survival analysis, identified risk factors for PL, and developed a predictive model for PL risk. Of the 87 patients, 41 developed PL, and progression-free survival (PFS) was significantly shorter in the PL group (median 8.0 months vs 15.4 months, P = 0.003). However, there was no significant difference in overall survival between the two groups. PL was also a significant factor for shorter PFS in multivariable analysis (P = 0.040). Brain V20Gy (percentage of brain volume receiving ≥20 Gy), gross total resection (GTR), and preoperative Karnofsky performance status (KPS) were identified as significant risk factors for PL. The predictive model showed that the risk of PL could be predicted by brain V20Gy, sex, age, GTR and preoperative KPS. PL was identified as a PFS shortening factor. Our model suggests that reducing irradiated brain volume may help prevent PL and could potentially improve glioblastoma prognosis by preserving cancer immunity.

The fifth edition of the World Health Organization classification of central nervous system tumors represents a significant advancement in the molecular-genetic classification of pediatric-type diffuse gliomas. This article comprehensively summarizes the clinical, molecular, and radiological imaging features in pediatric-type low-grade gliomas (pLGGs), including MYB- or MYBL1-altered tumors, polymorphous low-grade neuroepithelial tumor of the young (PLNTY), and diffuse low-grade glioma, MAPK pathway-altered. Most pLGGs harbor alterations in the RAS/MAPK pathway, functioning as “one pathway disease”. Specific magnetic resonance imaging features, such as the T2-fluid-attenuated inversion recovery (FLAIR) mismatch sign in MYB- or MYBL1-altered tumors and the transmantle-like sign in PLNTYs, may serve as non-invasive biomarkers for underlying molecular alterations. Recent advances in radiogenomics have enabled the differentiation of BRAF fusion from BRAF V600E mutant tumors based on magnetic resonance imaging characteristics. Machine learning approaches have further enhanced our ability to predict molecular subtypes from imaging features. These radiology-molecular correlations offer potential clinical utility in treatment planning and prognostication, especially as targeted therapies against the MAPK pathway emerge. Continued research is needed to refine our understanding of genotype–phenotype correlations in less common molecular alterations and to validate these imaging biomarkers in larger cohorts.

The brain and spinal cord, which constitute the central nervous system, were historically considered immune-privileged sites, as it was believed they lacked an equivalent to the systemic lymphatic system. However, in 2013, a pathway facilitating the clearance of waste products through the brain parenchyma via the perivascular space was proposed, garnering attention as the ‘glymphatic system’. Similar to the systemic lymphatic system, the glymphatic system plays a critical role in immune responses and has been implicated not only in Alzheimer’s disease and inflammatory brain disorders but also in conditions such as hydrocephalus and glaucoma, which are associated with cerebrospinal fluid circulation impairments. Recent studies have suggested that dysfunction of the glymphatic system may promote the progression of brain tumors and reduce the efficacy of immune responses and pharmacological therapies targeting tumors. Radiotherapy is a major treatment option for brain tumors; however, while it can enhance immune responses against tumors, it may also suppress these responses at the same time. Additionally, cranial irradiation has been suggested to impair the function of the glymphatic system. This review provides an overview of the structure and functional evaluation methods of the glymphatic system, summarizes the effects of its dysfunction on brain tumor treatment, and explores recent findings on the impact of radiation therapy on glymphatic system functioning. Lastly, it also explores the potential for radiation therapy strategies that account for their effects on the glymphatic system.