Ryo Kurokawa 교수

Two AI models demonstrated a significantly improved diagnostic performance when inputting both key images and clinical history. The models' ability to identify important differential diagnoses under these conditions was also confirmed.

The World Health Organization (WHO) published the fifth edition of the <i>WHO Classification of Tumors of the Central Nervous System</i> (WHO CNS5) in 2021, as an update of the WHO central nervous system (CNS) classification system published in 2016. WHO CNS5 was drafted on the basis of recommendations from the Consortium to Inform Molecular and Practical Approaches to CNS Tumor Taxonomy (cIMPACT-NOW) and expounds the classification scheme of the previous edition, which emphasized the importance

DHGs-G34m occur most often in the supratentorial regions of adolescents. Prognosis varies among patients. Evaluation of tumor margins may provide prognostic value.

Pituitary geographic hypoenhancing lesions in the anterior lobe of the pituitary gland are characteristic and frequent MR imaging findings of immune checkpoint inhibitor-induced hypophysitis. They reflect fibrosis and are useful in distinguishing immune checkpoint inhibitor-induced hypophysitis from other types of hypophysitis/tumors.

Intratumoral T1-weighted high-intensity areas, stalk-like signs, and regional brain atrophy were frequent imaging features in AG. We also found that affected age was different between supratentorial and brainstem AGs.

Characterization of brain networks by diffusion MRI (dMRI) has rapidly evolved, and there are ongoing movements toward data sharing and multi-center studies. To extract meaningful information from multi-center data, methods to correct for the bias caused by scanner differences, that is, harmonization, are urgently needed. In this work, we report the cross-scanner differences in structural network analyses using data from nine traveling subjects (four males and five females, 21-49 years-old) who

Meningeal lesions can be caused by various conditions and pose diagnostic challenges. The authors review the anatomy of the meninges in the brain and spinal cord to provide a better understanding of the localization and extension of these diseases and summarize the clinical and imaging features of various conditions that cause dural and/or leptomeningeal enhancing lesions. These conditions include infectious meningitis (bacterial, tuberculous, viral, and fungal), autoimmune diseases (vasculitis,

Hypophysitis is an inflammatory disease affecting the pituitary gland. Hypophysitis can be classified into multiple types depending on the mechanisms (primary or secondary), histology (lymphocytic, granulomatous, xanthomatous, plasmacytic/IgG4 related, necrotizing, or mixed), and anatomy (adenohypophysitis, infundibulo-neurohypophysitis, or panhypophysitis). An appropriate diagnosis is vital for managing these potentially life-threatening conditions. However, physiological morphological alterati

Characteristic imaging features including hyperdense attenuation of the solid components and calcification along the inner rim on CT and susceptibility-weighted imaging may assist with preoperative diagnosis of CNS NB-FOXR2 in pediatric patients.

Detailed neuroimaging features were clarified, including tumor location, margin status, morphology, CT attenuation, MRI signal intensity, and contrast enhancement pattern. The classification of tumor morphology may help predict the tumor's histological grade, contributing to clinical care and future oncologic research.

Higher HARQ scores (≥13) may be useful in predicting not only poor asthma condition but also the presence of airway neuronal dysfunction in patients with asthma to some extent.

Eosinophils in NPs (≥70/high power fields) and preoperative FeNO may be significant biomarkers for predicting the development of asthma symptoms after ESS.