Pathologic myopia: advances in imaging and the potential role of artificial intelligence
Pathologic myopia is a severe form of myopia that can lead to permanent visual impairment. The recent global increase in the prevalence of myopia has been projected to lead to a higher incidence of pathologic myopia in the future. Thus, imaging myopic eyes to detect early pathological changes, or pr...
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Veröffentlicht in: | British journal of ophthalmology 2023-05, Vol.107 (5), p.600-606 |
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container_title | British journal of ophthalmology |
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creator | Li, Yong Foo, Li-Lian Wong, Chee Wai Li, Jonathan Hoang, Quan V Schmetterer, Leopold Ting, Daniel S W Ang, Marcus |
description | Pathologic myopia is a severe form of myopia that can lead to permanent visual impairment. The recent global increase in the prevalence of myopia has been projected to lead to a higher incidence of pathologic myopia in the future. Thus, imaging myopic eyes to detect early pathological changes, or predict myopia progression to allow for early intervention, has become a key priority. Recent advances in optical coherence tomography (OCT) have contributed to the new grading system for myopic maculopathy and myopic traction maculopathy, which may improve phenotyping and thus, clinical management. Widefield fundus and OCT imaging has improved the detection of posterior staphyloma. Non-invasive OCT angiography has enabled depth-resolved imaging for myopic choroidal neovascularisation. Artificial intelligence (AI) has shown great performance in detecting pathologic myopia and the identification of myopia-associated complications. These advances in imaging with adjunctive AI analysis may lead to improvements in monitoring disease progression or guiding treatments. In this review, we provide an update on the classification of pathologic myopia, how imaging has improved clinical evaluation and management of myopia-associated complications, and the recent development of AI algorithms to aid the detection and classification of pathologic myopia. |
doi_str_mv | 10.1136/bjophthalmol-2021-320926 |
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The recent global increase in the prevalence of myopia has been projected to lead to a higher incidence of pathologic myopia in the future. Thus, imaging myopic eyes to detect early pathological changes, or predict myopia progression to allow for early intervention, has become a key priority. Recent advances in optical coherence tomography (OCT) have contributed to the new grading system for myopic maculopathy and myopic traction maculopathy, which may improve phenotyping and thus, clinical management. Widefield fundus and OCT imaging has improved the detection of posterior staphyloma. Non-invasive OCT angiography has enabled depth-resolved imaging for myopic choroidal neovascularisation. Artificial intelligence (AI) has shown great performance in detecting pathologic myopia and the identification of myopia-associated complications. These advances in imaging with adjunctive AI analysis may lead to improvements in monitoring disease progression or guiding treatments. In this review, we provide an update on the classification of pathologic myopia, how imaging has improved clinical evaluation and management of myopia-associated complications, and the recent development of AI algorithms to aid the detection and classification of pathologic myopia.</description><identifier>ISSN: 0007-1161</identifier><identifier>EISSN: 1468-2079</identifier><identifier>DOI: 10.1136/bjophthalmol-2021-320926</identifier><identifier>PMID: 35288438</identifier><language>eng</language><publisher>BMA House, Tavistock Square, London, WC1H 9JR: BMJ Publishing Group Ltd</publisher><subject>Age ; Artificial Intelligence ; Atrophy ; Classification ; Fundus Oculi ; Humans ; imaging ; macula ; Macular degeneration ; Macular Degeneration - complications ; Myopia ; Myopia, Degenerative - diagnostic imaging ; Optics ; retina ; Retrospective Studies ; Review ; Tomography ; Tomography, Optical Coherence - methods ; Vision Disorders - etiology</subject><ispartof>British journal of ophthalmology, 2023-05, Vol.107 (5), p.600-606</ispartof><rights>Author(s) (or their employer(s)) 2023. No commercial re-use. See rights and permissions. Published by BMJ.</rights><rights>2023 Author(s) (or their employer(s)) 2023. No commercial re-use. See rights and permissions. Published by BMJ.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-b388t-eb52cb000ac32e5885ed7628cd658376d823fc5411d08f13b7ed476114761fbd3</citedby><cites>FETCH-LOGICAL-b388t-eb52cb000ac32e5885ed7628cd658376d823fc5411d08f13b7ed476114761fbd3</cites><orcidid>0000-0002-5486-9292 ; 0000-0002-7189-1707 ; 0000-0003-2264-7174 ; 0000-0003-3022-0795</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35288438$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Li, Yong</creatorcontrib><creatorcontrib>Foo, Li-Lian</creatorcontrib><creatorcontrib>Wong, Chee Wai</creatorcontrib><creatorcontrib>Li, Jonathan</creatorcontrib><creatorcontrib>Hoang, Quan V</creatorcontrib><creatorcontrib>Schmetterer, Leopold</creatorcontrib><creatorcontrib>Ting, Daniel S W</creatorcontrib><creatorcontrib>Ang, Marcus</creatorcontrib><title>Pathologic myopia: advances in imaging and the potential role of artificial intelligence</title><title>British journal of ophthalmology</title><addtitle>Br J Ophthalmol</addtitle><addtitle>Br J Ophthalmol</addtitle><description>Pathologic myopia is a severe form of myopia that can lead to permanent visual impairment. The recent global increase in the prevalence of myopia has been projected to lead to a higher incidence of pathologic myopia in the future. Thus, imaging myopic eyes to detect early pathological changes, or predict myopia progression to allow for early intervention, has become a key priority. Recent advances in optical coherence tomography (OCT) have contributed to the new grading system for myopic maculopathy and myopic traction maculopathy, which may improve phenotyping and thus, clinical management. Widefield fundus and OCT imaging has improved the detection of posterior staphyloma. Non-invasive OCT angiography has enabled depth-resolved imaging for myopic choroidal neovascularisation. Artificial intelligence (AI) has shown great performance in detecting pathologic myopia and the identification of myopia-associated complications. These advances in imaging with adjunctive AI analysis may lead to improvements in monitoring disease progression or guiding treatments. In this review, we provide an update on the classification of pathologic myopia, how imaging has improved clinical evaluation and management of myopia-associated complications, and the recent development of AI algorithms to aid the detection and classification of pathologic myopia.</description><subject>Age</subject><subject>Artificial Intelligence</subject><subject>Atrophy</subject><subject>Classification</subject><subject>Fundus Oculi</subject><subject>Humans</subject><subject>imaging</subject><subject>macula</subject><subject>Macular degeneration</subject><subject>Macular Degeneration - complications</subject><subject>Myopia</subject><subject>Myopia, Degenerative - diagnostic imaging</subject><subject>Optics</subject><subject>retina</subject><subject>Retrospective Studies</subject><subject>Review</subject><subject>Tomography</subject><subject>Tomography, Optical Coherence - methods</subject><subject>Vision Disorders - etiology</subject><issn>0007-1161</issn><issn>1468-2079</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNqFkEtLxDAUhYMozjj6FyTgxk01jybNuBPxBQO6UHAX0iRtM7RNbTLC_HszzPjAjZtccjnnnsMHAMToAmPKL8ulH5rYqLbzbUYQwRklaE74HpjinIu0Kub7YIoQKjKMOZ6AoxCW6Us4Lg7BhDIiRE7FFLw9q9j41tdOw27tB6euoDIfqtc2QNdD16na9TVUvYGxsXDw0fbRqRaOvrXQV1CN0VVOb1auj7ZtXW2T-xgcVKoN9mQ3Z-D17vbl5iFbPN0_3lwvspIKETNbMqLL1ExpSiwTgllTcCK04UzQghtBaKVZjrFBosK0LKzJC47x5qlKQ2fgfHt3GP37yoYoOxd0qqF661dBEk7nhFDGaJKe_ZEu_WrsUztJBKKME5rSZkBsVXr0IYy2ksOYKIxriZHc0Je_6csNfbmln6ynu4BV2VnzbfzCnQT5VlB2y5_wf-9-An61lQ8</recordid><startdate>20230501</startdate><enddate>20230501</enddate><creator>Li, Yong</creator><creator>Foo, Li-Lian</creator><creator>Wong, Chee Wai</creator><creator>Li, Jonathan</creator><creator>Hoang, Quan V</creator><creator>Schmetterer, Leopold</creator><creator>Ting, Daniel S W</creator><creator>Ang, Marcus</creator><general>BMJ Publishing Group Ltd</general><general>BMJ Publishing Group LTD</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>BTHHO</scope><scope>CCPQU</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-5486-9292</orcidid><orcidid>https://orcid.org/0000-0002-7189-1707</orcidid><orcidid>https://orcid.org/0000-0003-2264-7174</orcidid><orcidid>https://orcid.org/0000-0003-3022-0795</orcidid></search><sort><creationdate>20230501</creationdate><title>Pathologic myopia: advances in imaging and the potential role of artificial intelligence</title><author>Li, Yong ; 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The recent global increase in the prevalence of myopia has been projected to lead to a higher incidence of pathologic myopia in the future. Thus, imaging myopic eyes to detect early pathological changes, or predict myopia progression to allow for early intervention, has become a key priority. Recent advances in optical coherence tomography (OCT) have contributed to the new grading system for myopic maculopathy and myopic traction maculopathy, which may improve phenotyping and thus, clinical management. Widefield fundus and OCT imaging has improved the detection of posterior staphyloma. Non-invasive OCT angiography has enabled depth-resolved imaging for myopic choroidal neovascularisation. Artificial intelligence (AI) has shown great performance in detecting pathologic myopia and the identification of myopia-associated complications. These advances in imaging with adjunctive AI analysis may lead to improvements in monitoring disease progression or guiding treatments. 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subjects | Age Artificial Intelligence Atrophy Classification Fundus Oculi Humans imaging macula Macular degeneration Macular Degeneration - complications Myopia Myopia, Degenerative - diagnostic imaging Optics retina Retrospective Studies Review Tomography Tomography, Optical Coherence - methods Vision Disorders - etiology |
title | Pathologic myopia: advances in imaging and the potential role of artificial intelligence |
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