Pang CE, Freund KB. Pachychoroid neovasculopathy. Retina. 2015;35:1–9.
Article CAS PubMed Google Scholar
Warrow DJ, Hoang QV, Freund KB. Pachychoroid pigment epitheliopathy. Retina. 2013;33:1659–72.
Cheung CMG, Lee WK, Koizumi H, Dansingani K, Lai TYY, Freund KB. Pachychoroid disease. Eye (Lond). 2019;33:14–33.
Borooah S, Sim PY, Phatak S, Moraes G, Yang WuC, Cheung CMG, et al. Pachychoroid spectrum disease. Acta Ophthalmol. 2021;99:e806–22.
Brown RB, Mohan S, Chhablani J. Pachychoroid spectrum disorders: an updated review. J Ophthalmic Vis Res. 2023;18:212–29.
Yamashiro K, Yanagi Y, Koizumi H, Cheung CMG, Gomi F, Iida T, et al. Relationship between pachychoroid and polypoidal choroidal vasculopathy. J Clin Med. 2022;11:4614.
Article PubMed PubMed Central Google Scholar
Spaide RF, Cheung CMG, Matsumoto M. Venous overload choroidopathy: a hypothetical framework for central serous chorioretinopathy and allied disorders. Prog Retin Eye Res. 2022;86:100973.
Article CAS PubMed Google Scholar
Sonoda S, Sakamoto T, Kakiuchi N, Shiihara H, Sakoguchi T, Tomita M, et al. Semi-automated software to measure luminal and stromal areas of choroid in optical coherence tomographic images. Jpn J Ophthalmol. 2018;62:179–85.
Agrawal R, Salman M, Tan KA, Karampelas M, Sim DA, Kreane PA, et al. Choroidal vascularity index (CVI)—a novel optical coherence tomography parameter for monitoring patients with panuveitis? PLoS ONE. 2016;11:e0146344.
Article PubMed PubMed Central Google Scholar
Mori Y, Miyake M, Hosoda Y, Uji A, Nakano E, Takahashi A, et al. Distribution of choroidal thickness and choroidal vessel dilation in healthy Japanese individuals: the Nagahama study. Ophthalmol Sci. 2021;1:100033.
Article PubMed PubMed Central Google Scholar
Daizumoto E, Mitamura Y, Sano H, Akaiwa K, Niki M, Yamanaka C, et al. Changes of choroidal structure after intravitreal aflibercept therapy for polypoidal choroidal vasculopathy. Br J Ophthalmol. 2017;101:56–61.
Fukutsu K, Saito M, Noda K, Murata M, Kase S, Shiba R, et al. A deep learning architecture for vascular area measurement in fundus images. Ophthalmol Sci. 2021;1:100004.
Article PubMed PubMed Central Google Scholar
Fukutsu K, Saito M, Noda K, Murata M, Kase S, Shiba R, et al. Relationship between brachial-ankle pulse wave velocity and fundus arteriolar area calculated using a deep-learning algorithm. Curr Eye Res. 2022;47:1534–7.
Saito M, Mitamura M, Fukutsu K, Dong Z, Ando R, Kase S, et al. Retinal arteriovenous information improves the prediction accuracy of deep learning-based pulse wave velocity from color fundus photographs. Invest Ophthalmol Vis Sci. 2025;66:63.
Article PubMed PubMed Central Google Scholar
Mitamura M, Saito M, Fukutsu K, Dong Z, Ando R, Kase S, et al. Sex differences in age-related changes in retinal arteriovenous area based on deep learning segmentation model. Ophthalmol Sci. 2025;5:100719.
Article PubMed PubMed Central Google Scholar
Treder M, Lauermann JL, Eter N. Automated detection of exudative age-related macular degeneration in spectral domain optical coherence tomography using deep learning. Graefes Arch Clin Exp Ophthalmol. 2018;256:259–65.
Article CAS PubMed Google Scholar
Ting DSW, Cheung CY, Lim G, Tan GSW, Quang ND, Gan A, et al. Development and validation of a deep learning system for diabetic retinopathy and related eye diseases using retinal images from multiethnic populations with diabetes. JAMA. 2017;318:2211–23.
Article PubMed PubMed Central Google Scholar
Saito M, Mitamura M, Kimura M, Ito Y, Endo H, Katsuta S, et al. Grad-CAM-based investigation into acute-stage fluorescein angiography images to predict long-term visual prognosis of branch retinal vein occlusion. J Clin Med. 2024;13:5271.
Article CAS PubMed PubMed Central Google Scholar
Mitamura M, Saito M, Hirooka K, Dong Z, Ando R, Kase S, et al. Differences in artificial intelligence-based macular fluid parameters between clinical stages of diabetic macular edema and their relationship with visual acuity. J Clin Med. 2025;14:1007.
Article CAS PubMed PubMed Central Google Scholar
Rohm M, Tresp V, Müller M, Kern C, Manakov I, Weiss M, et al. Predicting visual acuity by using machine learning in patients treated for neovascular age-related macular degeneration. Ophthalmology. 2018;125:1028–36.
Hosoda Y, Miyake M, Yamashiro K, Ooto S, Takahashi A, Oishi A, et al. Deep phenotype unsupervised machine learning revealed the significance of pachychoroid features in etiology and visual prognosis of age-related macular degeneration. Sci Rep. 2020;10:18423.
Article CAS PubMed PubMed Central Google Scholar
Prahs P, Radeck V, Mayer C, Cvetkov Y, Cvetkova N, Helbig H, et al. OCT-based deep learning algorithm for the evaluation of treatment indication with anti-vascular endothelial growth factor medications. Graefes Arch Clin Exp Ophthalmol. 2018;256:91–8.
van Rijssen TJ, van Dijk EHC, Yzer S, Cvetkov Y, Cvetkova N, Helbig H, et al. Central serous chorioretinopathy: towards an evidence-based treatment guideline. Prog Retin Eye Res. 2019;73:100770.
Agrawal R, Chhablani J, Tan KA, Shah S, Sarvaiya C, Banker A, et al. Choroidal vascularity index in central serous chorioretinopathy. Retina. 2016;36:1646–51.
Hirooka K, Saito M, Yamashita Y, Hashimoto Y, Terao N, Koizumi H, et al. Imbalanced choroidal circulation in eyes with asymmetric dilated vortex vein. Jpn J Ophthalmol. 2022;66:14–8.
Hiroe T, Kishi S. Dilatation of asymmetric vortex vein in central serous chorioretinopathy. Ophthalmol Retina. 2018;2:152–61.
Kishi S, Matsumoto H, Sonoda S, Hiroe T, Sakamoto T, Akiyama H. Geographic filling delay of the choriocapillaris in the region of dilated asymmetric vortex veins in central serous chorioretinopathy. PLoS ONE. 2018;13:e0206646.
Article PubMed PubMed Central Google Scholar
Matsumoto H, Kishi S, Hoshino J, Nakamura K, Akiyama H. Inversion of asymmetric vortex vein dilatation in pachychoroid spectrum diseases. Ophthalmol Sci. 2024;4:100515.
Article PubMed PubMed Central Google Scholar
Tittl M, Polska E, Kircher K, Kruger A, Maar N, Stur M, et al. Topical fundus pulsation measurement in patients with active central serous chorioretinopathy. Arch Ophthalmol. 2003;121:975–8.
Saito M, Saito W, Hashimoto Y, Yoshizawa C, Fujiya A, Noda K, et al. Macular choroidal blood flow velocity decreases with regression of acute central serous chorioretinopathy. Br J Ophthalmol. 2013;97:775–80.
Saito M, Noda K, Saito W, Ishida S. Relationship between choroidal blood flow velocity and choroidal thickness in patients with regression of acute central serous chorioretinopathy. Graefes Arch Clin Exp Ophthalmol. 2018;256:227–9.
Saito M, Saito W, Hirooka K, Hashimoto Y, Mori S, Noda K, et al. Pulse waveform changes in macular choroidal hemodynamics with regression of acute central serous chorioretinopathy. Invest Ophthalmol Vis Sci. 2015;56:6515–22.
Zhou X, Fukuyama H, Sugisawa T, Okita Y, Kanda H, Yamamoto Y, et al. Pupillary light reflex and multimodal imaging in patients with central serous chorioretinopathy. Invest Ophthalmol Vis Sci. 2023;64:28.
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