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Curro-Tafili K, Verbraak FD, de Vries R, van Nispen RMA, Ghyczy EAE. Diagnosing and monitoring the characteristics of Acanthamoeba keratitis using slit scanning and laser scanning in vivo confocal microscopy. Ophthalmic Physiol Opt 2024; 44:131-152. [PMID: 37916883 DOI: 10.1111/opo.13238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 09/09/2023] [Accepted: 09/23/2023] [Indexed: 11/03/2023]
Abstract
INTRODUCTION Acanthamoeba keratitis (AK) is a serious and potentially blinding ocular infection caused by the free-living amoeba, Acanthamoeba. In vivo confocal microscopy (IVCM) is a non-invasive device which has been proven of great use to diagnose Acanthamoeba infections immediately. The aim of this review was to establish different patterns and signs of AK that appear on the IVCM both before and after treatment. METHODS A systematic review of the literature from 1974 until September 2021 was performed using Embase and PubMed, following The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines. RESULTS Twenty different signs of AK were observed using IVCM. The included studies used vastly different criteria to diagnose infections, ranging from just 1 to 13 of the signs, demonstrating the current lack of a standardised diagnosis of this infection using the IVCM. The appearance of double wall cysts, trophozoites, signet rings, target signs and clusters were shown to be pathognomonic to AK infections. Bright spots located in the corneal epithelium were demonstrated as non-reliable predictors of AK. The presence of cysts in clusters and single file can predict the need for corneal transplantation. The morphological changes in cysts using the IVCM following treatment were described as breaking down to hollow forms and occasionally surrounded by black cavities. Using this information, a visual guideline for identifying AK signs in diagnosis and follow-up using IVCM was created. CONCLUSION Increased awareness of the different signs and patterns of AK that appear on the IVCM is crucial in order to correctly identify an infection and increase the potential of this device. Our guidelines presented here can be used, but further studies are needed in order to determine the relationship and aetiology of these signs and cellular changes on the IVCM both before and after anti-amoeba treatment.
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Affiliation(s)
- K Curro-Tafili
- Department of Ophthalmology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Quality of Care, Amsterdam, the Netherlands
| | - F D Verbraak
- Department of Ophthalmology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - R de Vries
- Medical Library, Vrije Universiteit, Amsterdam, the Netherlands
| | - R M A van Nispen
- Department of Ophthalmology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Quality of Care, Amsterdam, the Netherlands
| | - E A E Ghyczy
- Department of Ophthalmology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
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Chomicz L, Szaflik JP, Szostakowska B, Izdebska J, Baltaza W, Łazicka-Gałecka M, Kuligowska A, Machalińska A, Zawadzki PJ, Szaflik J. Successive Acanthamoeba Corneal Isolates Identified in Poland Monitored in Terms of In Vitro Dynamics. Microorganisms 2023; 11:1174. [PMID: 37317148 DOI: 10.3390/microorganisms11051174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 04/24/2023] [Accepted: 04/27/2023] [Indexed: 06/16/2023] Open
Abstract
BACKGROUND Amoebae of the genus Acanthamoeba cause a sight-threatening infection called Acanthamoeba keratitis. It is considered a rare disease in humans but poses an increasing threat to public health worldwide, including in Poland. We present successive isolates from serious keratitis preliminary examined in terms of the identification and monitoring of, among others, the in vitro dynamics of the detected strains. METHODS Clinical and combined laboratory methods were applied; causative agents of the keratitis were identified at the cellular and molecular levels; isolates were cultivated in an axenic liquid medium and regularly monitored. RESULTS In a phase-contrast microscope, Acanthamoeba sp. cysts and live trophozoites from corneal samples and in vitro cultures were assessed on the cellular level. Some isolates that were tested at the molecular level were found to correspond to A. mauritanensis, A. culbertsoni, A. castellanii, genotype T4. There was variability in the amoebic strain dynamics; high viability was expressed as trofozoites' long duration ability to intense multiply. CONCLUSIONS Some strains from keratitis under diagnosis verification and dynamics assessment showed enough adaptive capability to grow in an axenic medium, allowing them to exhibit significant thermal tolerance. In vitro monitoring that was suitable for verifying in vivo examinations, in particular, was useful to detect the strong viability and pathogenic potential of successive Acanthamoeba strains with a long duration of high dynamics.
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Affiliation(s)
- Lidia Chomicz
- Department of Medical Biology, Medical University of Warsaw, 00-575 Warsaw, Poland
| | - Jacek P Szaflik
- Department of Ophthalmology, Independent Public Clinical Ophthalmology Hospital, Medical University of Warsaw, 00-576 Warsaw, Poland
| | - Beata Szostakowska
- Department of Tropical Parasitology, Faculty of Health Sciences, Medical University of Gdansk, 80-210 Gdańsk, Poland
| | - Justyna Izdebska
- Department of Ophthalmology, Independent Public Clinical Ophthalmology Hospital, Medical University of Warsaw, 00-576 Warsaw, Poland
| | - Wanda Baltaza
- Department of Public Health, Medical University of Warsaw, 02-097 Warsaw, Poland
| | - Monika Łazicka-Gałecka
- Department of Ophthalmology, Independent Public Clinical Ophthalmology Hospital, Medical University of Warsaw, 00-576 Warsaw, Poland
| | - Agnieszka Kuligowska
- First Department of Ophthalmology, Pomeranian Medical University, 70-111 Szczecin, Poland
| | - Anna Machalińska
- First Department of Ophthalmology, Pomeranian Medical University, 70-111 Szczecin, Poland
| | - Paweł J Zawadzki
- Clinic of Cranio-Maxillo-Facial and Oral Surgery and Implantology, Medical University of Warsaw, 02-005 Warsaw, Poland
| | - Jerzy Szaflik
- Laser Eye Microsurgery Centre Clinic of Prof. Jerzy Szaflik, Brand Med Medical Research Centre, 00-215 Warsaw, Poland
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Zhang Y, Xu X, Wei Z, Cao K, Zhang Z, Liang Q. The global epidemiology and clinical diagnosis of Acanthamoeba keratitis. J Infect Public Health 2023; 16:841-852. [PMID: 37030037 DOI: 10.1016/j.jiph.2023.03.020] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 03/05/2023] [Accepted: 03/20/2023] [Indexed: 04/10/2023] Open
Abstract
Acanthamoeba keratitis is a rare parasitic infection of the cornea that can lead to permanent blindness if not diagnosed and treated promptly. We collected data on the incidences of Acanthamoeba keratitis from 20 countries and calculated an annual incidence of 23,561 cases, with the lowest rates in Tunisia and Belgium, and the highest in India. We analyzed 3755 Acanthamoeba sequences from the GenBank database across Asia, Europe, North America, South America, and Oceania and genotyped them into T1, T2, T3, T4, T5, T10, T11, T12, and T15. Many genotypes possess different characteristics, yet T4 is the most prevalent genotype. As efficient treatment against Acanthamoeba remains lacking, prevention from early diagnosis via staining, PCR, or in vivo confocal microscopy (IVCM) becomes significant for the condition's prognosis. IVCM is the most recommended approach for the early detection of Acanthamoeba. If IVCM is unavailable, PCR should be used as an alternative.
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Affiliation(s)
- Yuheng Zhang
- Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing 100005, China
| | - Xizhan Xu
- Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing 100005, China
| | - Zhenyu Wei
- Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing 100005, China
| | - Kai Cao
- Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing 100005, China
| | - Zijun Zhang
- Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing 100005, China
| | - Qingfeng Liang
- Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing 100005, China.
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Mesenchymal Stromal Cells-Derived Extracellular Vesicles Regulate Dendritic Cell Functions in Dry Eye Disease. Cells 2022; 12:cells12010033. [PMID: 36611828 PMCID: PMC9818747 DOI: 10.3390/cells12010033] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2022] [Revised: 12/11/2022] [Accepted: 12/15/2022] [Indexed: 12/24/2022] Open
Abstract
We explored the therapeutic efficacy of Mesenchymal stromal cells-derived extracellular vesicles (MSC-EVs) and its inhibition of the functions of dendritic cells (DCs) in dry eye disease (DED). MSC-EVs were isolated from the culture supernatants of mesenchymal stromal cells (MSCs) and characterized. In vitro, human corneal epithelial cells (HCECs) were cultured in hyperosmotic medium to simulate the DED hyperosmotic environment and treated with MSC-EVs. Cell viability was assessed, and the expression of inflammatory cytokines was quantified. Next, we induced DED in female C57BL/6 mice and divided the mice into groups treated with either MSC-EVs or phosphate buffer solution (PBS) eye drops. Disease severity was assessed; mRNA expression of inflammatory cytokines was analyzed by RT-PCR; and Th17 cells were detected by flow cytometry. Lastly, we evaluated DCs by immunofluorescence and flow cytometric analysis to assess its amounts and maturation. MSC-EVs showed protective effects on HCECs under hyperosmotic stress in vitro, suppressing the expression of inflammatory cytokines. In vivo, mice topically treated with MSC-Evs presented reduced DED disease severity compared to PBS-treated mice. MSC-Evs downregulated the expression of inflammatory cytokines, including TNF-α, IL-6, and IL-1β, as well as the frequency of Th17 cells. Further investigation showed that MSC-EVs suppressed the increase of amounts and the maturation of DCs in DED. Changes of morphological characters of DCs were also inhibited by MSC-EVs. Our study revealed that MSC-EVs suppressed ocular surface inflammation by inhibiting DCs activation-mediated Th17 immune responses, explicating the therapeutic potential of MSC-EVs in DED and other ocular surface diseases.
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Chao C, Tajbakhsh Z, Stapleton F, Mobeen R, Madigan MC, Jalbert I, Briggs N, Golebiowski B. Corneal epithelial dendritic cells, tear neuropeptides and corneal nerves continue to be affected more than 12 months after LASIK. Acta Ophthalmol 2022; 101:e302-e314. [PMID: 36250753 DOI: 10.1111/aos.15270] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 09/21/2022] [Accepted: 09/24/2022] [Indexed: 11/30/2022]
Abstract
PURPOSE LASIK causes corneal nerve damage and may affect the neuro-immune crosstalk. This study examined the effects of LASIK on corneal epithelial dendritic cells (CEDC) density and morphology and explored their relationships with corneal nerves and tear neuropeptides. A grading system was developed to assess CEDC morphology. METHODS Intra- and inter-observer repeatability of the CEDC morphology grading system was established using kappa (κ). In vivo confocal microscope images of the central cornea were captured from 20 participants who had undergone LASIK 12-16 months earlier and 20 controls (age 18-32 years, 55%F). CEDC density was counted manually, and CEDC morphology was assessed using a new grading system. CEDC sub-types (contacting nerves [CEDCc] and not contacting nerves [CEDCnc]) were also assessed. Differences in CEDC density and morphology were examined using mixed models and chi-squared test. Relationships between CEDC and corneal nerve parameters and tear substance P were explored using Spearman's correlation. RESULTS Excellent intra- and inter-observer repeatability was demonstrated for the grading system (κ = 0.82-0.97). In post-LASIK participants, CEDC density was lower compared with controls (5 [0-34] vs. 21 [7-77] cells/mm2 ; p = 0.01), and the proportion of CEDC with thick dendrites was higher (55%-73% vs. 11%-21%, p < 0.003). Higher tear substance P levels were associated with higher CEDC density (rho = 0.48, p = 0.003). Fewer nerve interconnections were observed in participants in whom CEDC had dendrites (p = 0.03). CEDC sub-types followed a similar pattern to CEDC. CONCLUSIONS The findings suggest that CEDC may remain altered more than 12 months post-LASIK. The association with substance P suggests a role for CEDC in corneal neurogenic inflammation.
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Affiliation(s)
- Cecilia Chao
- School of Optometry and Vision Science, UNSW Sydney, Sydney, Australia
| | - Zahra Tajbakhsh
- School of Optometry and Vision Science, UNSW Sydney, Sydney, Australia
| | - Fiona Stapleton
- School of Optometry and Vision Science, UNSW Sydney, Sydney, Australia
| | - Rabia Mobeen
- School of Optometry and Vision Science, UNSW Sydney, Sydney, Australia
| | - Michele C Madigan
- School of Optometry and Vision Science, UNSW Sydney, Sydney, Australia.,Save Sight Institute, University of Sydney, Sydney, Australia
| | - Isabelle Jalbert
- School of Optometry and Vision Science, UNSW Sydney, Sydney, Australia
| | - Nancy Briggs
- Stats Central, Mark Wainwright Analytical Centre, UNSW Sydney, Sydney, Australia
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Zhang XY, Wu M, Chinnery HR, Downie LE. Defining an Optimal Sample Size for Corneal Epithelial Immune Cell Analysis Using in vivo Confocal Microscopy Images. Front Med (Lausanne) 2022; 9:848776. [PMID: 35721066 PMCID: PMC9199001 DOI: 10.3389/fmed.2022.848776] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Accepted: 04/29/2022] [Indexed: 11/13/2022] Open
Abstract
Purpose In vivo confocal microscopy (IVCM) images are frequently used to quantify corneal epithelial immune cell (IC) density in clinical studies. There is currently limited evidence to inform the selection of a representative image sample size to yield a reliable IC density estimate, and arbitrary numbers of images are often used. The primary aim of this study was to determine the number of randomly selected, unique IVCM images required to achieve an acceptable level of accuracy when quantifying epithelial IC density, in both the central and peripheral cornea. The secondary aim was to evaluate the consistency and precision of an image selection approach where corneal epithelial IC density was quantified from "three representative images" selected independently by three experienced observers. Methods All combinations of two to 15 non-overlapping IVCM images were used for deriving IC density estimates, for both the central and peripheral cornea, in 20 healthy participants; the density value from averaging quantifications in the 16 images was defined as the "true mean". IC density estimates were compared with the true mean in each corneal region using a mean ratio. Intraclass correlation coefficients (ICCs) were used to evaluate the consistency of the mean ratios of IC density estimates derived from the method involving the manual selection of "three representative images" by the observers. The precision of the IC density estimates was compared to a scenario involving three randomly selected images. Results A total of 12 randomly selected, non-overlapping IVCM images were found to be required to produce a corneal epithelial IC density estimate that was within 30% of the true mean, 95% of the time, for the central cornea; seven such images produced an equivalent level of precision in the peripheral cornea. Mean ratios of corneal IC density estimates derived from "three representative images" methods had poor consistency between observers (ICC estimates <0.5) and similar levels of precision when compared with using three randomly selected images (p > 0.05 for all comparisons), in both the central and peripheral cornea. Conclusions Data presented in this study can inform image selection methods, and the sample size required for a preferred level of accuracy, when quantifying IC densities in the central and peripheral corneal epithelium using IVCM images.
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Affiliation(s)
- Xin Yuan Zhang
- Department of Optometry and Vision Sciences, University of Melbourne, Parkville, VIC, Australia
| | - Mengliang Wu
- Department of Optometry and Vision Sciences, University of Melbourne, Parkville, VIC, Australia
| | - Holly R Chinnery
- Department of Optometry and Vision Sciences, University of Melbourne, Parkville, VIC, Australia
| | - Laura E Downie
- Department of Optometry and Vision Sciences, University of Melbourne, Parkville, VIC, Australia
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Xu F, Jiang L, He W, Huang G, Hong Y, Tang F, Lv J, Lin Y, Qin Y, Lan R, Pan X, Zeng S, Li M, Chen Q, Tang N. The Clinical Value of Explainable Deep Learning for Diagnosing Fungal Keratitis Using in vivo Confocal Microscopy Images. Front Med (Lausanne) 2021; 8:797616. [PMID: 34970572 PMCID: PMC8712475 DOI: 10.3389/fmed.2021.797616] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Accepted: 11/25/2021] [Indexed: 12/14/2022] Open
Abstract
Background: Artificial intelligence (AI) has great potential to detect fungal keratitis using in vivo confocal microscopy images, but its clinical value remains unclarified. A major limitation of its clinical utility is the lack of explainability and interpretability. Methods: An explainable AI (XAI) system based on Gradient-weighted Class Activation Mapping (Grad-CAM) and Guided Grad-CAM was established. In this randomized controlled trial, nine ophthalmologists (three expert ophthalmologists, three competent ophthalmologists, and three novice ophthalmologists) read images in each of the conditions: unassisted, AI-assisted, or XAI-assisted. In unassisted condition, only the original IVCM images were shown to the readers. AI assistance comprised a histogram of model prediction probability. For XAI assistance, explanatory maps were additionally shown. The accuracy, sensitivity, and specificity were calculated against an adjudicated reference standard. Moreover, the time spent was measured. Results: Both forms of algorithmic assistance increased the accuracy and sensitivity of competent and novice ophthalmologists significantly without reducing specificity. The improvement was more pronounced in XAI-assisted condition than that in AI-assisted condition. Time spent with XAI assistance was not significantly different from that without assistance. Conclusion: AI has shown great promise in improving the accuracy of ophthalmologists. The inexperienced readers are more likely to benefit from the XAI system. With better interpretability and explainability, XAI-assistance can boost ophthalmologist performance beyond what is achievable by the reader alone or with black-box AI assistance.
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Affiliation(s)
- Fan Xu
- Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology & Research Center of Ophthalmology, Guangxi Academy of Medical Sciences & Department of Ophthalmology, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
| | - Li Jiang
- Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology & Research Center of Ophthalmology, Guangxi Academy of Medical Sciences & Department of Ophthalmology, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
| | - Wenjing He
- Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology & Research Center of Ophthalmology, Guangxi Academy of Medical Sciences & Department of Ophthalmology, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
| | - Guangyi Huang
- Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology & Research Center of Ophthalmology, Guangxi Academy of Medical Sciences & Department of Ophthalmology, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
| | - Yiyi Hong
- Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology & Research Center of Ophthalmology, Guangxi Academy of Medical Sciences & Department of Ophthalmology, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
| | - Fen Tang
- Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology & Research Center of Ophthalmology, Guangxi Academy of Medical Sciences & Department of Ophthalmology, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
| | - Jian Lv
- Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology & Research Center of Ophthalmology, Guangxi Academy of Medical Sciences & Department of Ophthalmology, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
| | - Yunru Lin
- Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology & Research Center of Ophthalmology, Guangxi Academy of Medical Sciences & Department of Ophthalmology, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
| | - Yikun Qin
- China-ASEAN Information Harbor Co., Ltd., Nanning, China
| | - Rushi Lan
- Guangxi Key Laboratory of Image and Graphic Intelligent Processing, Guilin University of Electronic Technology, Guilin, China
| | - Xipeng Pan
- Guangxi Key Laboratory of Image and Graphic Intelligent Processing, Guilin University of Electronic Technology, Guilin, China
- Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Siming Zeng
- Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology & Research Center of Ophthalmology, Guangxi Academy of Medical Sciences & Department of Ophthalmology, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
| | - Min Li
- Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology & Research Center of Ophthalmology, Guangxi Academy of Medical Sciences & Department of Ophthalmology, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
| | - Qi Chen
- Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology & Research Center of Ophthalmology, Guangxi Academy of Medical Sciences & Department of Ophthalmology, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
| | - Ningning Tang
- Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology & Research Center of Ophthalmology, Guangxi Academy of Medical Sciences & Department of Ophthalmology, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
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Chinnery HR, Zhang XY, Wu CY, Downie LE. Corneal immune cell morphometry as an indicator of local and systemic pathology: A review. Clin Exp Ophthalmol 2021; 49:729-740. [PMID: 34240800 DOI: 10.1111/ceo.13972] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Accepted: 07/03/2021] [Indexed: 11/26/2022]
Abstract
The corneal epithelium contains a population of resident immune cells commonly referred to as dendritic cells (DCs), or Langerhans cells. A unique advantage of the transparent cornea being situated at the surface of the eye is that these cells can be readily visualised using in vivo confocal microscopy. Over the past decade, interest in the involvement of corneal DCs in a range of ocular and systemic diseases has surged. For most studies, the number of corneal DCs has been the main outcome of interest. However, more recently attention has shifted towards understanding how DC morphology may provide insights into the inflammatory status of the cornea, and in some cases, the health of the peripheral nervous system. In this review, we provide examples of recent methodologies that have been used to classify and measure corneal DC morphology and discuss how this relates to local and systemic inflammatory conditions in humans and rodents.
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Affiliation(s)
- Holly R Chinnery
- Department of Optometry and Vision Sciences, University of Melbourne, Parkville, Victoria, Australia
| | - Xin Yuan Zhang
- Department of Optometry and Vision Sciences, University of Melbourne, Parkville, Victoria, Australia
| | - Ching Yi Wu
- Department of Optometry and Vision Sciences, University of Melbourne, Parkville, Victoria, Australia
| | - Laura E Downie
- Department of Optometry and Vision Sciences, University of Melbourne, Parkville, Victoria, Australia
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