Miki Atsuya

Miki Atsuya, Araie Makoto, Leung Christopher Kai Shun, Nishigaki Masashi, Murata Hiroshi, Kikawa Tsutomu et al.

This study found that in glaucoma patients, the extent of retinal nerve fiber layer defects detected by ROTA was associated with optic nerve head gamma zone area, suggesting this structural change reflects axonal damage.

Enomoto Nobuko, Saito Hitomi, Araie Makoto, Kambayashi Mitsuki, Murata Hiroshi, Kikawa Tsutomu et al.

This study found deep ONH structures in healthy eyes correlate with scleral canal size and other factors, crucial for distinguishing normal from glaucomatous changes.

Sit Arthur J, Aihara Makoto, Khawaja Anthony P, Lin Shan C, Mansouri Kaweh, Miki Atsuya et al.

An expert group found lowering episcleral venous pressure (EVP), even modestly, may benefit glaucoma patients, especially those with low intraocular pressure or normal-tension glaucoma, offering individualized treatment.

Kambayashi Mitsuki, Saito Hitomi, Araie Makoto, Enomoto Nobuko, Murata Hiroshi, Kikawa Tsutomu et al.

This study found that deep optic nerve structures, like lamina cribrosa depth and scleral canal shape, significantly influence both BMO-MRW and pRNFLT, highlighting their complex relationship in healthy eyes.

Saito Hitomi, Ueta Takashi, Araie Makoto, Enomoto Nobuko, Kambayashi Mitsuki, Murata Hiroshi et al.

This study found Bergmeister papilla strongly predicts more severe prelaminar schisis in both healthy and glaucomatous eyes, suggesting traction. PLS severity also correlated with glaucoma-related optic nerve head structures.

Saito Hitomi, Kambayashi Mitsuki, Araie Makoto, Murata Hiroshi, Enomoto Nobuko, Kikawa Tsutomu et al.

This study found that longer axial length in healthy myopic eyes is associated with specific optic nerve head structural changes, including misalignment, choroid thinning, and scleral bowing, which is crucial for distinguishing myopia from glaucoma.

Tanikawa Akira, Soma Takeshi, Miki Atsuya, Koh Shizuka, Kitaguchi Yoshiyuki, Maeda Naoyuki et al.

GCD2 eyes have softer corneas, with a biomechanical index correlating to lesion deposition. This suggests potential IOP underestimation, requiring careful glaucoma management.

Fujimoto Satoko, Miki Atsuya, Maruyama Kazuichi, Mei Song, Mao Zaixing, Wang Zhenguo et al.

This study found that larger 3D volume of intrachoroidal cavitations (ICCs), measured with deep-learning-enhanced OCT, correlates with worse visual field sensitivity, improving ICC assessment in high myopia.

Miki Atsuya, Okazaki Tomoyuki, Weinreb Robert N, Morota Misa, Tanimura Aki, Kawashima Rumi et al.

This study found standard visual field progression metrics underestimate severe glaucoma worsening. A targeted metric excluding undetectable points better reflects true progression, improving monitoring in advanced disease.

Sugimoto Ikki, Usui Shinichi, Okazaki Tomoyuki, Kawashima Rumi, Miki Atsuya, Kawasaki Ryo et al.

Ex-PRESS blebs in exfoliation glaucoma show smaller fluid spaces and more fibrosis than in POAG, indicating worse surgical outcomes and poorer IOP control due to differing healing.

Yasukura Yuichi, Miki Atsuya, Maeda Naoyuki, Koh Shizuka, Nishida Kohji

Topical PGAs for glaucoma increase corneal compliance, potentially leading to overestimation of their IOP-lowering effect due to altered corneal measurements.

Hashimoto Yohei, Kiwaki Taichi, Sugiura Hiroki, Asano Shotaro, Murata Hiroshi, Fujino Yuri et al.

Deep learning predicting 10-2 visual fields from OCT improved significantly when corrected with 24-2/30-2 visual fields, potentially reducing the need for additional 10-2 tests.

Aoki Shuichiro, Miki Atsuya, Omoto Takashi, Fujino Yuri, Matsuura Masato, Murata Hiroshi et al.

This study found corneal hysteresis (CH), not biomechanical glaucoma factor (BGF), was associated with visual field progression in treated POAG, indicating CH has more clinical utility for monitoring glaucoma.

Asano Shotaro, Murata Hiroshi, Fujino Yuri, Yamashita Takehiro, Miki Atsuya, Ikeda Yoko et al.

Researchers developed a new "hybrid" method for detecting glaucoma progression with 10-2 visual fields. This method offers higher sensitivity and earlier detection than existing ones, improving clinical monitoring for glaucoma patients.

Omoto Takashi, Murata Hiroshi, Fujino Yuri, Matsuura Masato, Yamashita Takehiro, Miki Atsuya et al.

Sectorwise regression predicted glaucoma visual field progression more accurately than pointwise methods, especially with fewer initial tests, offering a potentially improved monitoring tool.

Omoto Takashi, Murata Hiroshi, Fujino Yuri, Matsuura Masato, Fujishiro Takashi, Hirasawa Kazunori et al.

This study found that narrower retinal artery angles, indicating more ocular elongation, correlated with significantly thinner macular ganglion cell layers, highlighting a potential structural impact of myopia.

Hashimoto Yohei, Asaoka Ryo, Kiwaki Taichi, Sugiura Hiroki, Asano Shotaro, Murata Hiroshi et al.

A deep learning model accurately predicted central 10° visual fields from SD-OCT scans in glaucoma, offering a potential objective tool for assessing functional loss.

Xu Linchuan, Asaoka Ryo, Kiwaki Taichi, Murata Hiroshi, Fujino Yuri, Matsuura Masato et al.

This study predicted central 10-degree visual fields from OCT using deep learning. CNN-TR models showed superior accuracy, offering a potential tool for glaucoma monitoring and diagnosis by correlating structural and functional damage.

Miki Atsuya, Yasukura Yuichi, Weinreb Robert N, Maeda Naoyuki, Yamada Tomomi, Koh Shizuka et al.

Untreated normal tension glaucoma eyes showed more compliant corneas than healthy eyes. This increased corneal compliance may elevate optic nerve damage risk, highlighting biomechanical assessment relevance in glaucoma.

Asaoka Ryo, Murata Hiroshi, Matsuura Masato, Fujino Yuri, Miki Atsuya, Tanito Masaki et al.

Studying glaucoma progression, data augmentation significantly improved visual field prediction, especially with short series. This enhances early detection and monitoring of glaucoma progression.

Asano Shotaro, Murata Hiroshi, Matsuura Masato, Fujino Yuri, Miki Atsuya, Tanito Masaki et al.

This study validated binomial PLR for detecting glaucoma visual field progression. It found binomial PLR detects progression significantly earlier than other methods, improving clinical management and trial efficacy.

Miki Atsuya, Yasukura Yuichi, Weinreb Robert N, Yamada Tomomi, Koh Shizuka, Asai Tomoko et al.

Medically controlled glaucoma eyes were more deformable than healthy eyes, potentially leading to underestimated IOP and increased optic nerve damage risk.

Sakimoto Susumu, Okazaki Tomoyuki, Usui Shinichi, Ishibashi Tomoyuki, Oura Yoshihito, Nishida Kentaro et al.

This study found epiretinal membranes are associated with worse glaucoma severity (thinner RNFL, larger cupping, worse visual fields) in POAG, suggesting ERMs may be a risk factor for progression.

Winegarner Andrew, Miki Atsuya, Kumoi Miho, Ishida Yuichiro, Wakabayashi Taku, Sakimoto Susumu et al.

Anterior segment Scheimpflug imaging, particularly anterior chamber depth, accurately detects primary angle closure disease. This non-invasive, reproducible method is a powerful screening tool for PACD.

Asaoka Ryo, Murata Hiroshi, Hirasawa Kazunori, Fujino Yuri, Matsuura Masato, Miki Atsuya et al.

Deep learning with macular OCT images accurately diagnosed early glaucoma (93.7% AROC), significantly outperforming other methods. This offers improved early detection for patients.