4^th World Congress on Ophthalmology and Vision Science March 27-28, 2023 Paris, France

Biography:

Josiane Mare Njoya is a 39 years old woman Cameroonian ophthalmologist working at regional hospital of Garoua Northern Cameroon. She is head of department of ophthalmology at the Regional Hospital of Garoua, assistant of ophthalmology at the Biomedical sciences and Medicine Faculty of University of Garoua, forensic expert in ophthalmology for the North region of Cameroon.

Abstract:

Introduction: Ocular surface disease frequently co-exists with glaucoma and may be initiated or exacerbated by topical glaucoma medications. The aim of our work is to evaluate dry eye disease in patients diagnosed as glaucomatous at the ophthalmology department of the Garoua regional hospital in northern Cameroon during the study period.

Materials and methods: We conduct a cross sectional prospective study from January 2022 to November 2022 at the ophthalmology department of Regional Hospital of Garoua. We took a consecutive sample. We included patients with confirmed diagnostic of glaucoma who accept to answer our questionnaire and seem to understand the questionnaire after given explanation.

For all glaucomatous patients who gave their informed consent, we completed the OSDI and DEQ5 questionnaires and performed a break up time. Data on age, sex, occupation, OSDI and DEQ5 score, antiglaucoma treatment taken, number of drops instilled per day, therapeutic class, results of the break up time examination, therapeutic compliance were recorded and analyzed by IBM SPSS software version 23.

Results: A total of 25 glaucomatous patients performed different test. Mean age 43.3 ± 17 ans. 52% of female 48% of male for sex ratio of 1.08. 68% of patients are treated with eye drops preserved. Break up time test is <10 second for 84% of patients, 64% of patients have punctuated superficial and filamentous keratitis. 76% of patients have OSDI score classify as moderate and severe dry eye disease. For DEQ5 score, 60% have dry eye disease.

Conclusion: Dry eye disease is frequent in glaucomatous patient and has to be screen before decision for type of treatment.

Biography:

Christine Nearchou is a Senior Lecturer (teaching specialist) and the clinical leader of paediatrics and binocular vision in the Department of Optometry and Vision Sciences at the University of Melbourne. She coordinates all areas of binocular vision and paediatrics in the OD program. Her research interests include paediatric eye health and vision care, in particular, visual development and learning in children.

Abstract:

Background: Early detection of visual deficits in children can lessen the impact of learning difficulties in the classroom. The aim of this study is to investigate a novel dot pattern task as a potential tool for school visual cognition screening programs.

Methods: This study was carried out among typically developing school children aged 5 to 12 years. Children with vision 6/9 or better without ocular comorbidities were included as a part of vision screening program. The visual cognition tests Novel Dot Pattern ‘A’ (NDPA), the Wold Visuo Motor Test (WVMT) and the Rosner Test for Visual Analysis Skills (TVAS) were administered in all subjects. Descriptive statistics, normative data and percentiles (median and IQR) and interclass correlation coefficient were computed.

Results: A total of 274 children were included of which 142 were females. The mean (SD) age was 8.57 (2.28) years. The median (IQR) of the NPDA was 5 (2) and TVPS was 10 (2). The mean R (95% CI) interclass correlation coefficient was 0.839 (0.602,0.941) for the TVAS and 0.885 (0.604,0.963) for the NDPA in the repeatability test.

Conclusions: The normative data and percentile scores of the three tests show a developmental trend in visual cognition. Therefore, NDPA can be used as a simple screening tool to screen for visual cognition deficits in children.

Biography:

Pedram Hamrah is a clinician-scientist focusing his research on Neuropathic Corneal Pain (NCP), Neurotrophic Keratopathy (NK) and dry eye disease. He trained at Schepens Eye Research Institute, Harvard Medical School, where his research resulted in findings that refuted a previous long-standing belief that the cornea is immune privileged due to the absence of bone marrow-derived cells resulting in a paradigm shift in corneal immunology. He has since focused on the area of corneal neuro-immune cross-talk, NCP and NK and has been spearheading diagnosis and treatment of NCP. His research has been supported by numerous NIH, foundation and industry grants. He has authored over 170 peer-reviewed articles and has been the recipient of numerous awards, including the Claes Dohlman Society Award, the Senior Achievement Award from the American Academy of Ophthalmology and the was awarded Gold Fellow at the Association for Research in Vision and Ophthalmology.

Abstract:

Statement of the problem: The diagnosis of Neuropathic Corneal Pain (NCP) is challenging, as it is often difficult to differentiate from conventional Dry Eye Disease (DED). We have recently identified a potential novel biomarker by corneal In Vivo Confocal Microscopy (IVCM), utilizing morphological nerve changes [Figure 1]. The purpose of this study is to describe analytical and biological validation of this biomarker and to develop utilize artificial intelligence for fully automated analysis of images in a rapid and consistent fashion.
Methodology & theoretical orientation: A database of 500,000 IVCM images was used to confirm that the presence of micro-neuromas is a biomarker for NCP by comparing the sensitivity and specificity of identification of NCP patients via micro-neuromas to other IVCM parameters. Inter and intra-observer precision was assessed and descriptive statistics of the IVCM datasets was performed to determine the minimum number of images necessary for high precision of micro-neuroma detection. Biological validation of micro-neuromas was then performed, correlating IVCM results to clinical. An Artificial Intelligence (AI) program was developed and validated for automated identification of micro-neuromas to allow rapid and wide-scale adoption by clinicians.

Findings: Analytical validation confirmed that the presence of micro-neuromas was a biomarker distinguishing NCP from DED, with good inter and intra-observer precision. The AI system program had high sensitivity and specificity. Our model showed excellent discriminative ability to detect micro-neuromas (AuROC: 0.97) and the ability to generalize to data from a new institution (AuROC: 0.90).

Conclusion: The AI system had a very high AUC for detecting micro-neuromas. The deep neural network shows great promise in identifying micro-neuromas associated with NCP, allowing for the standardization of IVCM image analysis. Our study suggests that artificial intelligence can rapidly evaluate IVCM images, while maintaining a high degree of accuracy.

Biography:

Christine Nearchou is a Senior Lecturer (teaching specialist) and the clinical leader of paediatrics and binocular vision in the Department of Optometry and Vision Sciences at the University of Melbourne. She coordinates all areas of binocular vision and paediatrics in the OD program. Her research interests include paediatric eye health and vision care, in particular, visual development and learning in children.

Abstract:

Background: Early detection of visual deficits in children can lessen the impact of learning difficulties in the classroom. The aim of this study is to investigate a novel dot pattern task as a potential tool for school visual cognition screening programs.

Methods: This study was carried out among typically developing school children aged 5 to 12 years. Children with vision 6/9 or better without ocular comorbidities were included as a part of vision screening program. The visual cognition tests Novel Dot Pattern ‘A’ (NDPA), the Wold Visuo Motor Test (WVMT) and the Rosner Test for Visual Analysis Skills (TVAS) were administered in all subjects. Descriptive statistics, normative data and percentiles (median and IQR) and interclass correlation coefficient were computed.

Results: A total of 274 children were included of which 142 were females. The mean (SD) age was 8.57 (2.28) years. The median (IQR) of the NPDA was 5 (2) and TVPS was 10 (2). The mean R (95% CI) interclass correlation coefficient was 0.839 (0.602,0.941) for the TVAS and 0.885 (0.604,0.963) for the NDPA in the repeatability test.

Conclusions: The normative data and percentile scores of the three tests show a developmental trend in visual cognition. Therefore, NDPA can be used as a simple screening tool to screen for visual cognition deficits in children.

Biography:

Pedram Hamrah is a clinician-scientist focusing his research on Neuropathic Corneal Pain (NCP), Neurotrophic Keratopathy (NK) and dry eye disease. He trained at Schepens Eye Research Institute, Harvard Medical School, where his research resulted in findings that refuted a previous long-standing belief that the cornea is immune privileged due to the absence of bone marrow-derived cells resulting in a paradigm shift in corneal immunology. He has since focused on the area of corneal neuro-immune cross-talk, NCP and NK and has been spearheading diagnosis and treatment of NCP. His research has been supported by numerous NIH, foundation and industry grants. He has authored over 170 peer-reviewed articles and has been the recipient of numerous awards, including the Claes Dohlman Society Award, the Senior Achievement Award from the American Academy of Ophthalmology and the was awarded Gold Fellow at the Association for Research in Vision and Ophthalmology.

Abstract:

Statement of the problem: The diagnosis of Neuropathic Corneal Pain (NCP) is challenging, as it is often difficult to differentiate from conventional Dry Eye Disease (DED). We have recently identified a potential novel biomarker by corneal In Vivo Confocal Microscopy (IVCM), utilizing morphological nerve changes [Figure 1]. The purpose of this study is to describe analytical and biological validation of this biomarker and to develop utilize artificial intelligence for fully automated analysis of images in a rapid and consistent fashion.
Methodology & theoretical orientation: A database of 500,000 IVCM images was used to confirm that the presence of micro-neuromas is a biomarker for NCP by comparing the sensitivity and specificity of identification of NCP patients via micro-neuromas to other IVCM parameters. Inter and intra-observer precision was assessed and descriptive statistics of the IVCM datasets was performed to determine the minimum number of images necessary for high precision of micro-neuroma detection. Biological validation of micro-neuromas was then performed, correlating IVCM results to clinical. An Artificial Intelligence (AI) program was developed and validated for automated identification of micro-neuromas to allow rapid and wide-scale adoption by clinicians.
Findings: Analytical validation confirmed that the presence of micro-neuromas was a biomarker distinguishing NCP from DED, with good inter and intra-observer precision. The AI system program had high sensitivity and specificity. Our model showed excellent discriminative ability to detect micro-neuromas (AuROC: 0.97) and the ability to generalize to data from a new institution (AuROC: 0.90).
Conclusion: The AI system had a very high AUC for detecting micro-neuromas. The deep neural network shows great promise in identifying micro-neuromas associated with NCP, allowing for the standardization of IVCM image analysis. Our study suggests that artificial intelligence can rapidly evaluate IVCM images, while maintaining a high degree of accuracy.

Biography:

Pedram Hamrah is a clinician-scientist focusing his research on Neuropathic Corneal Pain (NCP), Neurotrophic Keratopathy (NK) and dry eye disease. He trained at Schepens Eye Research Institute, Harvard Medical School, where his research resulted in findings that refuted a previous long-standing belief that the cornea is immune privileged due to the absence of bone marrow-derived cells resulting in a paradigm shift in corneal immunology. He has since focused on the area of corneal neuro-immune cross-talk, NCP and NK and has been spearheading diagnosis and treatment of NCP. His research has been supported by numerous NIH, foundation and industry grants. He has authored over 170 peer-reviewed articles and has been the recipient of numerous awards, including the Claes Dohlman Society Award, the Senior Achievement Award from the American Academy of Ophthalmology and the was awarded Gold Fellow at the Association for Research in Vision and Ophthalmology.

Abstract:

Statement of the problem: The diagnosis of Neuropathic Corneal Pain (NCP) is challenging, as it is often difficult to differentiate from conventional Dry Eye Disease (DED). We have recently identified a potential novel biomarker by corneal In Vivo Confocal Microscopy (IVCM), utilizing morphological nerve changes [Figure 1]. The purpose of this study is to describe analytical and biological validation of this biomarker and to develop utilize artificial intelligence for fully automated analysis of images in a rapid and consistent fashion.
Methodology & theoretical orientation: A database of 500,000 IVCM images was used to confirm that the presence of micro-neuromas is a biomarker for NCP by comparing the sensitivity and specificity of identification of NCP patients via micro-neuromas to other IVCM parameters. Inter and intra-observer precision was assessed and descriptive statistics of the IVCM datasets was performed to determine the minimum number of images necessary for high precision of micro-neuroma detection. Biological validation of micro-neuromas was then performed, correlating IVCM results to clinical. An Artificial Intelligence (AI) program was developed and validated for automated identification of micro-neuromas to allow rapid and wide-scale adoption by clinicians.

Findings: Analytical validation confirmed that the presence of micro-neuromas was a biomarker distinguishing NCP from DED, with good inter and intra-observer precision. The AI system program had high sensitivity and specificity. Our model showed excellent discriminative ability to detect micro-neuromas (AuROC: 0.97) and the ability to generalize to data from a new institution (AuROC: 0.90).

Conclusion: The AI system had a very high AUC for detecting micro-neuromas. The deep neural network shows great promise in identifying micro-neuromas associated with NCP, allowing for the standardization of IVCM image analysis. Our study suggests that artificial intelligence can rapidly evaluate IVCM images, while maintaining a high degree of accuracy.

Biography:

Dr. Zong-Ming Song is the vice president of Henan Eye Hospital. He is also one of the board members of Chinese Journal of Ocular Fundus Disease and Deputy editor-in-chief of the Chinese journal of experimental ophthalmology.   Dr. Song is specialized in complicated retinal detachment, ocular trauma, diabetic retinopathy, macular diseases and intractable retinal diseases.

Abstract:

Methods
A total of 221 patients (241 eyes) diagnosed with FTMH were enrolled over a 6-year period between 2013 to 2019. The chosen surgical methods for FTMH of different diameters included pars plana vitrectomy (PPV), gas tamponade, flute-needle aspiration, ILM operation (peeling, scraping, inverted ILM flap, insertion, transplantation), and autologous blood clot (ABC). Anatomical and functional outcomes pre- and post-surgery were evaluated.

Results
Based on clinical experience, the patients with FTMH were classified into five groups (small: <300μm; medium: ≥300μm and <600μm; large: ≥ 600μm and < 900μm; huge: ≥900μm; recurrent). Best-corrected visual acuity (BCVA) significantly improved from 0.88 ± 0.44 to 0.56 ± 0.49 in small MH (P = .0007), 0.98 ± 0.39 to 0.70 ± 0.41 in medium MH (P < .0001), 1.24 ± 0.48 to 0.98 ± 0.38 in large MH (P = .0004), 1.16 ± 0.25 to 0.91 ± 0.34 in huge MH (P = .044), and 1.16 ± 0.28 to 0.93 ± 0.21 in recurrent MH (P = .204). The closure rates of the five types were as follows: FTMH, 100% (37/37) in small MH; 97.9% (94/96) in medium MH; 94.1% (80/85) in large MH; 93.7% (15/16) in huge MH; 57.1% (4/7) in recurrent MH, with significant differences (P < .001).

Biography:

Qian Liu is affiliated to Henan Eye Institute, Henan Eye Hospital, Henan Provincial People's Hospital, Zhengzhou University People's Hospital, Zhengzhou, China.

Abstract:

Purpose: We aimed to describe the characteristics, epidemiology, management and outcomes of glaucoma in pediatric patients in central China.

Methods: This study retrospectively analyzed inpatients with pediatric glaucoma at Henan Provincial People’s Hospital, Henan Eye Institute and Henan Eye Hospital between 2017 and 2020.

Results: Overall, 239 cases (276 eyes) of pediatric glaucoma in patients, comprising 87 girls (36.40%) and 152 boys (63.60%) were analyzed. The mean age was 6.65 ± 4.46 and 2.93% of the patients had a family history of glaucoma. Primary Congenital Glaucoma (PCG) was the most common type of glaucoma, followed by traumatic glaucoma in 8.33% of the patients, which was considered secondary glaucoma. The most common signs and symptoms were elevated Intra Ocular Pressure (IOP) and eye pain. Trabeculotomy (Trab) and Microcatheter-Assisted 360° Trabeculotomy (MAT) combined with Trab were the most commonly performed surgeries. The IOP of patients with PCG, Juvenile Open-Angle Glaucoma (JOAG) and secondary glaucoma were 15.27 ± 7.48 mmHg, 17.16 ± 10.05 and 18.65 ± 8.55 respectively, at the final follow up. The rate of re-operations in patients with PCG, JOAG and secondary glaucoma were 9.15%, 6.78% and 4.69% respectively. The mean visual acuity of the eyes with PCG, JOAG and secondary glaucoma was 0.79 ± 0.68, 0.51 ± 0.48 and 0.53 ± 0.50 respectively. There were 135 cases (150 eyes) before the epidemic of novel coronavirus and 93 cases (105 eyes) after the epidemic of COVID-19. Primary Congenital Glaucoma (PCG) was the most common type before and after the epidemic of novel coronavirus, accounting for 67.41% and 67.74% respectively, while developmental glaucoma was the most significant difference before and after novel coronavirus's epidemic, 14.07% and 26.88% respectively. The most common signs of novel coronavirus before and after the epidemic were elevated IOP, which were 33.33% and 38.91% respectively. The other 11 cases were treated before and after the epidemic of novel coronavirus, 7 cases were treated with binocular therapy and 4 cases with the same eye.

Biography:

Dr. Zong-Ming Song is the vice president of Henan Eye Hospital. He is also one of the board members of Chinese Journal of Ocular Fundus Disease and Deputy editor-in-chief of the Chinese journal of experimental ophthalmology.   Dr. Song is specialized in complicated retinal detachment, ocular trauma, diabetic retinopathy, macular diseases and intractable retinal diseases.

Abstract:

Methods
A total of 221 patients (241 eyes) diagnosed with FTMH were enrolled over a 6-year period between 2013 to 2019. The chosen surgical methods for FTMH of different diameters included pars plana vitrectomy (PPV), gas tamponade, flute-needle aspiration, ILM operation (peeling, scraping, inverted ILM flap, insertion, transplantation), and autologous blood clot (ABC). Anatomical and functional outcomes pre- and post-surgery were evaluated.

Results
Based on clinical experience, the patients with FTMH were classified into five groups (small: <300μm; medium: ≥300μm and <600μm; large: ≥ 600μm and < 900μm; huge: ≥900μm; recurrent). Best-corrected visual acuity (BCVA) significantly improved from 0.88 ± 0.44 to 0.56 ± 0.49 in small MH (P = .0007), 0.98 ± 0.39 to 0.70 ± 0.41 in medium MH (P < .0001), 1.24 ± 0.48 to 0.98 ± 0.38 in large MH (P = .0004), 1.16 ± 0.25 to 0.91 ± 0.34 in huge MH (P = .044), and 1.16 ± 0.28 to 0.93 ± 0.21 in recurrent MH (P = .204). The closure rates of the five types were as follows: FTMH, 100% (37/37) in small MH; 97.9% (94/96) in medium MH; 94.1% (80/85) in large MH; 93.7% (15/16) in huge MH; 57.1% (4/7) in recurrent MH, with significant differences (P < .001).