Cataract grading systems

Gali, Helena E.; Sella, Ruti; Afshari, Natalie A.

doi:10.1097/icu.0000000000000542

Cited by 56 publications

(21 citation statements)

References 16 publications

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“…Exclusion criteria were: history of anti-VEGF therapy, evidence of type 2 or type 3 MNV, evidence of polypoidal vasculopathy, macular edema secondary to other causes than nAMD, and significant lens opacity, graded above NO3 or NC3. 20 Poor quality images with a signal strength index (SSI) lower than six for the PLEXElite SS-OCTA or with significant motion artifacts (seen as large dark or grey lines on the enface angiograms) were also excluded.…”

Section: Methodsmentioning

confidence: 99%

Imaging Biomarkers of 1-Year Activity in Type 1 Macular Neovascularization

Costanzo

Parravano

Giannini

et al. 2021

Trans. Vis. Sci. Tech.

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The purpose of this study was to evaluate the predictive value of optical coherence tomography (OCT) and OCT angiography (OCTA) parameters at baseline on lesion's activity at the 1-year follow-up in type 1 macular neovascularizations (MNVs) treated with 1-year fixed regimen of intravitreal aflibercept injections (q8 IAIs).Methods: All patients were imaged by structural OCT to evaluate central macular thickness (CMT), subretinal fluid (SRF), subretinal hyper-reflective material (SHRM), intraretinal fluid (IRF) and intraretinal hyper-reflective dots (HRDs), and by Swept-Source OCTA to measure baseline MNV area, perfusion density (PD), vessel length density (VLD), and vessel diameter index. At the end of q8 IAI, patients were classified in two groups: active-MNV (A-MNV) and inactive-MNV (I-MNV), considering the OCT signs of activity. Three binary logistic regression models were developed: (1) OCT-based, (2) OCTA-based, and(3) OCT/OCTA-based model.Results: Thirty-one treatment-naïve type 1 MNVs were enrolled (13 A-MNV and 18 I-MNV). No differences were observed in baseline OCT and OCTA characteristics between A-MNV and I-MNV. Among the models developed, model 3 that combined OCT/OCTA parameters showed a performance of 87.5% and excellent sensitivity for A-MNV lesions (100%). By analyzing the model, the A-MNV group appears more likely to show at baseline SRF, greater CMT, wider MNV area, and lower PD and VLD compared to I-MNV. Conclusions:Our study demonstrated that the combination of baseline OCT and OCTA parameters allowed to achieve a good models' performance in the prediction of MNV activity permitting to correctly classifying the active lesions at the end of follow-up period, with excellent sensitivity.

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Section: Methodsmentioning

confidence: 99%

Imaging Biomarkers of 1-Year Activity in Type 1 Macular Neovascularization

Costanzo

Parravano

Giannini

et al. 2021

Trans. Vis. Sci. Tech.

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“…Clinical examination consisted of visual acuity, slit-lamp biomicroscopy with photography (SL 9900, Haag-Streit type, CSO, Scandicci, Italy), and anterior eye segment spectral swept source optical coherence tomography (SS OCT; OCT CASIA2; Tomey, Nagoya, Japan). The cataract severity and type were determined in the dilated eye with 0.5% tropicamide and 10% phenylephrine hydrochloride 30 min before examination according to the Lens Opacities Classification System III (LOCS III) [29] using a slit lamp at maximum illumination without light filtering. Six degrees of the extent of nuclear opacity (NO1-NO6) and nuclear color (NC1-NC6) were used as the parameters to determine the cataract density.…”

Section: Methodsmentioning

confidence: 99%

Corneal Analysis with Swept Source Optical Coherence Tomography in Patients with Coexisting Cataract and Fuchs Endothelial Corneal Dystrophy

et al. 2021

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This study focused on defining the characteristic features of keratometry and pachymetry elevation maps based on swept source optical coherence tomography (SS OCT) in Fuchs endothelial corneal dystrophy (FECD) eyes with a coexisting cataract. 70 eyes of 35 patients diagnosed with FECD and a coexisting cataract and 70 control eyes were included in this prospective, controlled, observational, cross-sectional study. Features characteristic of intermediately affected eyes included an increased corneal thinnest thickness (CTT) (p = 0.01), 3 and 6 mm asymmetry (p < 0.0001), higher order Fourier indices (p < 0.05 and p ≤ 0.0001, respectively), chord µ, and a posterior Ectasia Screening Index (pESI) (p < 0.01). The lack of agreement between the anterior and posterior elevation map and a significant area of negative values in the posterior map were detected. In advanced FECD eyes, our study additionally revealed decreased posterior keratometry steep (Ks), keratometry flat (Kf), keratometry average (AvgK), eccentricity (Ecc), an increased corneal apex thickness (CAT), and decreased 3 and 6 mm posterior spherical indices (p < 0.0001 for all of the above). Characteristic features of subclinical FECD, independent of the corneal thickness, can be detected by SS OCT and should be considered during the preoperative assessment of patients with a coexisting cataract.

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“…Esquemas para a classificação objetiva de catarata usam padrões fotográficos para subdividir os principais tipos em diferentes graus, conforme exemplificado na figura 3. Esses graus podem ser baseados na densidade e na cor (no caso do núcleo) ou de acordo com a área anatômica da catarata (no caso de áreas cortical ou subcapsular posterior [8,14,17,18]. A capacidade visual do paciente é afetada de modo diferente de acordo com o tipo e grau de catarata.…”

Section: Figura 3: Sistema Locs III De Graduação De Opacidades [17]unclassified

“…Em [26] uma abordagem baseada em deep learning e imagens de fundo de olho mostrou bons resultados na detecção de estágios iniciais de catarata. Um panorama geral da pesquisa na área é apresentado em [14,15].…”

Section: Figura 3: Sistema Locs III De Graduação De Opacidades [17]unclassified

“…A segunda etapa tem por finalidade mensurar a opacidade no cristalino (lente do olho) através da análise da imagem segmentada da pupila e indicar a presença ou não de catarata. O objetivo do projeto é usar uma rede de aprendizagem profunda baseada em redes neurais do tipo convolutivas (CNNs) de modo similar a outros trabalhos na área [14,25,26].…”

Section: Figura 5: Algoritmo De Segmentação De Pupilaunclassified

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Desenvolvimento de uma Ferramenta para Auxílio ao Diagnóstico de Catarata em Telemedicina

Hüsemann¹,

Negreiros²,

Tomaggi³

et al. 2019

Anais Estendidos Do Simpósio Brasileiro De Sistemas Multimídia E Web (WebMedia)

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The use of videoconferencing technology for health systems has the potential to increase the number of patients treated while decreasing cost and allowing distributed local consultation facilities close to the target communities, minimizing the need for transportation and minimizing waiting times. One such initiative is the Teleoftalmo-RS videocolaboration program where ophthalmologic consultations are performed. In this paper, the development of an auxiliary tool to help expedite the diagnosis of cataracts in such a system is presented. This work is also part of the ongoing RNP and Microsoft Challenge: Artificial Intelligence R&D.

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Cataract grading systems

Cited by 56 publications

References 16 publications

Imaging Biomarkers of 1-Year Activity in Type 1 Macular Neovascularization

Imaging Biomarkers of 1-Year Activity in Type 1 Macular Neovascularization

Corneal Analysis with Swept Source Optical Coherence Tomography in Patients with Coexisting Cataract and Fuchs Endothelial Corneal Dystrophy

Desenvolvimento de uma Ferramenta para Auxílio ao Diagnóstico de Catarata em Telemedicina

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