Macrohistory of Moyamoya Disease Analyzed Using Artificial Intelligence

Abstract

Introduction: Moyamoya disease is characterized by progressive stenotic changes in the terminal segment of the internal carotid artery and the development of abnormal vascular networks called moyamoya vessels. The objective of this review was to provide a holistic view of the epidemiology, etiology, clinical findings, treatment, and pathogenesis of moyamoya disease. A literature search was performed in PubMed using the term “moyamoya disease,” for articles published until 2021. Results: Artificial intelligence (AI) clustering was used to classify the articles into 5 clusters: (1) pathophysiology (23.5%); (2) clinical background (37.3%); (3) imaging (13.2%); (4) treatment (17.3%); and (5) genetics (8.7%). Many articles in the “clinical background” cluster were published from the 1970s. However, in the “treatment” and “genetics” clusters, the articles were published from the 2010s through 2021. In 2011, it was confirmed that a gene called Ringin protein 213 ( RNF213) is a susceptibility gene for moyamoya disease. Since then, tremendous progress in genomic, transcriptomic, and epigenetic profiling (e.g., methylation profiling) has resulted in new concepts for classifying moyamoya disease. Our literature survey revealed that the pathogenesis involves aberrations of multiple signaling pathways through genetic mutations and altered gene expression. Conclusion: We analyzed the content vectors in abstracts using AI, and reviewed the pathophysiology, clinical background, radiological features, treatments, and genetic peculiarity of moyamoya disease.