Aims and Scope
Founded in 2020, Medical hypothesis, discovery & innovation in optometry, is an international, open-access, double-blinded peer-reviewed, quarterly journal that considers publications related to optometry. The aim is to present a scientific medium of communication for researchers in the field of optometry. The journal is of interest to a broad audience of visual scientists and publishes original articles, reviews, case reports, and commentaries after a rigorous peer-review process. The journal is affiliated to and published by the "IVORC" (Registration File Number: 803630055), a registered non-profit corporation in Austin, Texas, United States. We provide English editing for papers as a complimentary free-of-charge service.

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Journal Info

A review of oculoplastic surgery and ocular surface disorders

Mukaddes Damla Ciftci, Ozlem Barut Selver

Medical hypothesis, discovery & innovation in optometry, Vol. 3 No. 1 (2022), 24 September 2022

Background: Ocular surface health is closely related to the condition of the ocular adnexa, particularly the eyelids. Both ocular adnexal disorders and oculoplastic procedures performed to treat them can cause ocular surface disorders (OSD). In this review, we aimed to summarize the relationship between oculoplastic procedures and OSD.
Methods: In this narrative review, an electronic search of the PubMed/MEDLINE database was conducted using various combinations of keywords including “oculoplastic surgery,” “ocular surface disorders,” “dry eye,” and “management,” without time or language limitations, to include studies concerning oculoplastic surgery and OSD.
Results: We included articles involving oculoplastic procedures and OSD with discussions of preventive approaches and management strategies in this context. For a systematic approach, the preoperative assessments and postoperative treatment of patients were retrieved and summarized. Preoperative preventive measures included evaluation of tear film break-up time, tear osmolarity, tear meniscus area and height measurement by anterior segment optic coherence tomography, lipid layer thickness by interferometer, corneal staining and Oxford Scheme, Schirmer test, blink rate and completeness, ocular surface disease index scoring, eyelid closure, and Bell’s phenomenon. Postoperative assessments included the presence and severity of dry eye and early management of dry eye with artificial tears, topical anti-inflammatory medications, and night taping; evaluation of the presence of chemosis, and, if present, management with pharmacologic, mechanical, or surgical therapies when needed; and prompt detection and treatment of lagophthalmos and consequent exposure keratopathy.
Conclusion: Careful preoperative examination of the ocular surface is mandatory to reduce or eliminate complications after oculoplastic surgery. Ocular surface-related complications that surgeons encounter after oculoplastic surgery should be promptly diagnosed and treated.

Multi-color imaging in a unilateral central retinal artery occlusion following dengue fever: a case report and literature review

Srinivasan Sanjay, Ankush Kawali, Nikhil Gopalakrishnan, Rohit Shetty, Padmamalini Mahendradas

Medical hypothesis, discovery & innovation in optometry, Vol. 3 No. 1 (2022), 24 September 2022

Background: Dengue fever is associated with various sight-threatening ocular manifestations, some of which can occur several months after fever. These include subconjunctival hemorrhage, vitreous hemorrhage, retinal hemorrhage, cotton wool spots, central and branch retinal artery occlusion, central scotoma, papilledema, optic neuropathy, retinal vasculitis, retinitis, retinal pigment epithelium mottling, foveolitis, choroidal effusion, exudative retinal detachment, anterior uveitis, endogenous endophthalmitis, and panophthalmitis. Herein, we report a patient with unilateral central retinal artery occlusion (CRAO) and raised dengue immunoglobulin G (IgG) titers who underwent serial multimodal imaging with fundus photography, spectral domain optical coherence tomography (SD-OCT), and optical coherence tomography angiography (OCTA). In addition to the case report, we summarize articles pertaining to MCI published during the years 2018–2022.
Case presentation: A 53-year-old Asian Indian woman complained of blurring of vision in the right eye (OD) two months after a bout of fever. Her best-corrected distance visual acuity was finger counting close to the face in the OD and 6/12 in the left eye. CRAO of the OD was diagnosed. Systemic investigations were normal except for elevated dengue IgG levels. Optical coherence tomography and fluorescein angiography confirmed this diagnosis. Multi-color imaging (MCI) and SD-OCT using Spectralis™ performed before and after treatment with oral steroids demonstrated improvement. MCI served as a noninvasive ancillary tool for monitoring the CRAO. We summarized articles pertaining to MCI published during the years 2018–2022. The list is not exhaustive but highlights salient features of different retinal and choroidal disorders evaluated using MCI. Our summary highlights the role of MCI in the diagnosis and serial monitoring of eye diseases.
Conclusions: A diagnosis of post-dengue fever retinal artery occlusion should be made after ruling out other causes of retinal artery vascular occlusion. We demonstrated retinal changes using serial imaging. MCI can be a useful tool, along with SD-OCT, to monitor clinical improvement. Optometrists can follow up patients with retinal vascular occlusions using noninvasive methods.

A review of artificial intelligence applications in anterior segment ocular diseases

Zahra Heidari, Mehdi Baharinia, Kiana Ebrahimi-Besheli, Hanieh Ahmadi

Medical hypothesis, discovery & innovation in optometry, Vol. 3 No. 1 (2022), 24 September 2022

Background: Artificial intelligence (AI) has great potential in interpreting and analyzing images and processing large numbers of data. There is growing interest in investigating the applications of AI in anterior segment ocular diseases. This narrative review aimed to assess the use of different AI-based algorithms in diagnosing and managing anterior segment entities.
Methods: We reviewed the application of different AI-based algorithms in the diagnosis and management of anterior segment entities such as keratoconus, corneal dystrophy, corneal nerves, corneal grafts, corneal transplantation, refractive surgery, conjunctiva and tear film, pterygium, infectious keratitis, anterior chamber angle and iris, and cataract. English-language databases PubMed/MEDLINE, Scopus, and Google Scholar were searched using the following keywords: artificial intelligence, deep learning, machine learning, neural network, anterior eye segment diseases, corneal disease, keratoconus, dry eye, refractive surgery, pterygium, infection keratitis, anterior chamber, cataract. Then, relevant articles were compared based on the use of AI models in the diagnosis and treatment of anterior segment diseases. Furthermore, we prepared a summary of the diagnostic performance of AI-based methods for anterior segment ocular entities.
Results: Various AI methods based on deep learning and machine learning can analyze image data obtained from corneal imaging modalities with acceptable diagnostic performance. Currently, there are complicated and time-consuming manual methods for diagnosing and treating eye diseases. While, AI methods could be time-saving and prevent avoidable vision impairment in eyes with corneal disease. 
Conclusions: AI-based models could be a surrogate for analyzing manual data with improving diagnostic performance. These methods could be a reliable tool in diagnosing and managing anterior segment ocular diseases, in near future, even in the form of teleophthalmology in remote areas. It is expected that future studies could design algorithms that use fewer data in a multitasking manner for the detection and management of corneal diseases.

Google Lens: a potential cost-effective screening tool for diabetic retinopathy

Pradeep Venkatesh

Medical hypothesis, discovery & innovation in optometry, Vol. 3 No. 1 (2022), 24 September 2022

Background: Diabetic retinopathy (DR) is a major, sight-threatening complication of diabetes mellitus. Blindness from DR can be prevented by successful and proactive screening. However, DR is screened in less than half of the patients because of barriers in availability, affordability, accessibility, and awareness. Although artificial intelligence (AI)-based algorithms are being evaluated for DR screening, they have limitations of infrastructure, accessibility, training, and manpower cost. Therefore, simpler and more practical DR screening tools should be explored.
Hypothesis: Google Lens, an easily available, vision- and AI-based application in most smartphones, is a potential tool for cost-effective DR screening. It recognises images through a visual analysis based on neural networking. Thus, it can recognize retinal disorders, such as DR, in images. The development and adoption of Google Lens-based DR screening would have several advantages over the conventional hospital/specialist/healthcare facility-based approach, including widespread accessibility, acceptable accuracy, reduction in the direct cost of healthcare for patients with diabetes mellitus, and active patient participation in self-care.
Conclusions: DR screening, detection, and grading using Google Lens is a feasible and effective option. Despite current limitations, it could transform DR screening from a costly, hospital- and expert-based method to a cost-effective, self-applicable, and home-based one. However, diagnostic accuracy studies comparing the index test with Google Lens-based screening are required to determine the usability and validity of this proposed screening tool for DR.

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