Kyoto University · Medicine
마이케 교수의 연구실은 망막 질환, 특히 황반변성과 근시와 관련된 분자유전학 및 영상 기반 진단 기술을 중심으로 연구를 진행하고 있습니다. 특히 페치코리드 신경병변성과 노령성 황반변성의 임상적·유전적 차이를 규명하고, 고해상도 OCT를 활용한 눈 구조의 정량적 분석 기법을 개발하여 근시성 합병증의 기전을 밝혀내는 데 초점을 맞추고 있습니다. 또한 의료용 기계학습 및 딥러닝 기반 진단기기의 규제 동향 분석을 통해 첨단 기술의 임상 적용을 선도하고 있습니다.
Figures are computed from collected data and may differ slightly.
Pachychoroid neovasculopathy is a recently proposed clinical entity of choroidal neovascularization (CNV). As it often masquerades as neovascular age-related macular degeneration (AMD), it is currently controversial whether pachychoroid neovasculopathy should be distinguished from neovascular AMD. This is because its characteristics have yet to be well described. To estimate the relative prevalence of pachychoroid neovasculopathy in comparison with neovascular AMD and to investigate the phenotyp
Myopia can cause severe visual impairment. Here, we report a two-stage genome-wide association study for three myopia-related traits in 9,804 Japanese individuals, which was extended with trans-ethnic replication in 2,674 Chinese and 2,690 Caucasian individuals. We identify WNT7B as a novel susceptibility gene for axial length (rs10453441, Pmeta=3.9 × 10(-13)) and corneal curvature (Pmeta=2.9 × 10(-40)) and confirm the previously reported association between GJD2 and myopia. WNT7B significantly
We established a novel method to analyze posterior pole shape by using OCT images to construct curvature maps. Our quantitative analysis revealed that fundus shape is associated with myopic complications. These values were also effective in distinguishing eyes with staphylomas from those without. This tool for the quantitative evaluation of eye shape should facilitate future research of myopic complications.
In patients with CVH, type 1 CNV may occur frequently and sometimes accompanies type 2 CNV or polypoidal lesions. In terms of ARMS2 and CFH, genetic background of patients with CVH and type 1 CNV was different from those with AMD, but rather similar to the general Japanese population.
Machine learning (ML) and deep learning (DL) are changing the world and reshaping the medical field. Thus, we conducted a systematic review to determine the status of regulatory-approved ML/DL-based medical devices in Japan, a leading stakeholder in international regulatory harmonization. Information about the medical devices were obtained from the Japan Association for the Advancement of Medical Equipment search service. The usage of ML/DL methodology in the medical devices was confirmed using
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