Investigation of changes in thickness and reflectivity from layered retinal structures of healthy and diabetic eyes with optical coherence tomography

OCT is usually employed for the measurement of retinal thickness. However, coherent reflected light carries more information characterizing the optical properties of tissue. Therefore, optical property changes may provide further information regarding cellular layers and early damage in ocular diseases. We investigated the possibility of OCT in detecting changes in the optical backscattered signal from layered retinal structures. OCT images were obtained from diabetic patients without retinopathy (DM, n = 38 eyes) or mild diabetic retinopathy (MDR, n = 43 eyes) and normal healthy subjects (n = 74 eyes). The thickness and reflectivity of various layered structures were assessed using a custom-built algorithm. In addition, we evaluated the usefulness of quantifying the reflectivity of layered structures in the detection of retinal damage. Generalized estimating equations considering within-subject inter-eye relations were used to test for differences between the groups. A modified p value of <0.001 was considered statistically significant. Receiver operating characteristic (ROC) curves were constructed to describe the ability of each parameter to discriminate between the eyes of DM, MDR and healthy eyes. Thickness values of the GCL + IPL and OPL showed a significant decrease in the MDR eyes compared to controls. Significant decreases of total reflectance average values were observed in all layers in the MDR eyes compared with controls. The highest AUROC values estimated for the total reflectance were observed for the GCL + IPL, OPL and OS when comparing MDR eyes with controls. Total reflectance showed a better discriminating power between the MDR eyes and healthy eyes compared to thickness values. Our results suggest that the optical properties of the intraretinal layers may provide useful information to differentiate pathological from healthy eyes. Further research is warranted to determine how this approach may be used to improve diagnosis of early retinal neurodegeneration

Automated classifiers for early detection and diagnosis of retinopathy in diabetic eyes

BACKGROUND: Artificial neural networks (ANNs) have been used to classify eye diseases, such as diabetic retinopathy (DR) and glaucoma. DR is the leading cause of blindness in working-age adults in the developed world. The implementation of DR diagnostic routines could be feasibly improved by the integration of structural and optical property test measurements of the retinal structure that provide important and complementary information for reaching a diagnosis. In this study, we evaluate the capability of several structural and optical features (thickness, total reflectance and fractal dimension) of various intraretinal layers extracted from optical coherence tomography images to train a Bayesian ANN to discriminate between healthy and diabetic eyes with and with no mild retinopathy. RESULTS: When exploring the probability as to whether the subject's eye was healthy (diagnostic condition, Test 1), we found that the structural and optical property features of the outer plexiform layer (OPL) and the complex formed by the ganglion cell and inner plexiform layers (GCL + IPL) provided the highest probability (positive predictive value (PPV) of 91% and 89%, respectively) for the proportion of patients with positive test results (healthy condition) who were correctly diagnosed (Test 1). The true negative, TP and PPV values remained stable despite the different sizes of training data sets (Test 2). The sensitivity, specificity and PPV were greater or close to 0.70 for the retinal nerve fiber layer's features, photoreceptor outer segments and retinal pigment epithelium when 23 diabetic eyes with mild retinopathy were mixed with 38 diabetic eyes with no retinopathy (Test 3). CONCLUSIONS: A Bayesian ANN trained on structural and optical features from optical coherence tomography data can successfully discriminate between healthy and diabetic eyes with and with no retinopathy. The fractal dimension of the OPL and the GCL + IPL complex predicted by the Bayesian radial basis function network provides better diagnostic utility to classify diabetic eyes with mild retinopathy. Moreover, the thickness and fractal dimension parameters of the retinal nerve fiber layer, photoreceptor outer segments and retinal pigment epithelium show promise for the diagnostic classification between diabetic eyes with and with no mild retinopathy

Fertőzéses keratitisek diagnosztikája és kezelése | Diagnostics and treatment of infectious keratitis

Absztrakt: Munkánkban irodalmi adatok és néhány saját eset bemutatásán keresztül foglaljuk össze a fertőzéses keratitisek aktuális javasolt diagnosztikáját és kezelését. Bakteriális, herpeszes, gombás, valamint Acanthamoeba-keratitissel találkozunk a leggyakrabban a klinikai gyakorlatban. A diagnosztikában használatos réslámpás vizsgálat mellett végezzük még a szaruhártya érzékenységének vizsgálatát, in vivo konfokális mikroszkópiát, polimeráz láncreakciót (PCR), in vitro tenyésztést, valamint a szaruhártyaminta szövettani elemzését. Konzervatív kezelésként primeren lokális moxifloxacint vagy cefazolint erősített tobramycinnel vagy gentamycinnel alkalmazunk bakteriális, lokális (esetenként szisztémás), vírusellenes szert szükség szerint kortikoszteroidos cseppel kombinálva herpeszes, lokális voriconazolt vagy amphotericin-B-t gombás, valamint hármas terápiát (diamidin, biguanid és antibiotikum) Acanthamoeba-keratitisben. Korai diagnózis felállításával és a megfelelő konzervatív kezelés mellett a fertőzéses keratitisek többsége sikeresen gyógyítható. A konzervatív kezelés mellett azonban szükség lehet még perforáló keratoplasztikára, amnionmembrán-transzplantációra vagy crosslinking kezelésre. A crosslinking kezelés egyedül herpeszes keratitisben kontraindikált. Orv Hetil. 2017; 158(31): 1203–1212. | Abstract: We summarize up-to-date diagnostic and treatment of infectious keratitis using literature data and some clinical examples. In the clinical practice, most commonly bacterial, herpetic, mycotic and acanthamoeba keratitis occur. Beside slitlamp examination, for diagnostic purpose, we analyse corneal sensitivity, perform in vivo confocal microscopy, polymerase-chain-reaction (PCR), in vitro culture and histological examination of the corneal sample. As conservative treatment we use primarily topical moxifloxacin or cephasolin with fortified tobramycin or gentamycin in bacterial, topical antiviral gel (in some cases in combination with systemic antiviral treatment) in part in combination with topical corticosteroids in herpetic, voriconasole or amphotericin-B in mycotic, and topical-triple-therapy (diamidine, biguanid and antibiotics) in acanthamoeba keratitis. In case of early diagnosis and initiation of topical therapy, most cases of infectious keratitis recover successfully. However, beside conservative treatment, penetrating keratoplasty, amniotic membrane transplantation and crosslinking therapy may be necessary. Crosslinking is solely contraindicated in herpetic keratitis. Orv Hetil. 2017; 158(31): 1203–1212

Fertőzéses keratitisek diagnosztikája és kezelése

We summarize up-to-date diagnostic and treatment of infectious keratitis using literature data and some clinical examples. In the clinical practice, most commonly bacterial, herpetic, mycotic and acanthamoeba keratitis occur. Beside slitlamp examination, for diagnostic purpose, we analyse corneal sensitivity, perform in vivo confocal microscopy, polymerase-chain-reaction (PCR), in vitro culture and histological examination of the corneal sample. As conservative treatment we use primarily topical moxifloxacin or cephasolin with fortified tobramycin or gentamycin in bacterial, topical antiviral gel (in some cases in combination with systemic antiviral treatment) in part in combination with topical corticosteroids in herpetic, voriconasole or amphotericin-B in mycotic, and topical-triple-therapy (diamidine, biguanid and antibiotics) in acanthamoeba keratitis. In case of early diagnosis and initiation of topical therapy, most cases of infectious keratitis recover successfully. However, beside conservative treatment, penetrating keratoplasty, amniotic membrane transplantation and crosslinking therapy may be necessary. Crosslinking is solely contraindicated in herpetic keratitis. Orv Hetil. 2017; 158(31): 1203-1212

Investigating Tissue Optical Properties and Texture Descriptors of the Retina in Patients with Multiple Sclerosis

PURPOSE: To assess the differences in texture descriptors and optical properties of retinal tissue layers in patients with multiple sclerosis (MS) and to evaluate their usefulness in the detection of neurodegenerative changes using optical coherence tomography (OCT) image segmentation. PATIENTS AND METHODS: 38 patients with MS were examined using Stratus OCT. The raw macular OCT data were exported and processed using OCTRIMA software. The enrolled eyes were divided into two groups, based on the presence of optic neuritis (ON) in the history (MSON+ group, n = 36 and MSON- group, n = 31). Data of 29 eyes of 24 healthy subjects (H) were used as controls. A total of seven intraretinal layers were segmented and thickness as well as optical parameters such as contrast, fractal dimension, layer index and total reflectance were measured. Mixed-model ANOVA analysis was used for statistical comparisons. RESULTS: Significant thinning of the retinal nerve fiber layer (RNFL), ganglion cell/inner plexiform layer complex (GCL+IPL) and ganglion cell complex (GCC, RNFL+GCL+IPL) was observed between study groups in all comparisons. Significant difference was found in contrast in the RNFL, GCL+IPL, GCC, inner nuclear layer (INL) and outer plexiform layer when comparing MSON+ to the other groups. Higher fractal dimension values were observed in GCL+IPL and INL layers when comparing H vs. MSON+ groups. A significant difference was found in layer index in the RNFL, GCL+IPL and GCC layers in all comparisons. A significant difference was observed in total reflectance in the RNFL, GCL+IPL and GCC layers between the three examination groups. CONCLUSION: Texture and optical properties of the retinal tissue undergo pronounced changes in MS even without optic neuritis. Our results may help to further improve the diagnostic efficacy of OCT in MS and neurodegeneration

The assessment of fundus image quality labeling reliability among graders with different backgrounds

PurposeFor the training of machine learning (ML) algorithms, correctly labeled ground truth data are inevitable. In this pilot study, we assessed the performance of graders with different backgrounds in the labeling of retinal fundus image quality. MethodsColor fundus photographs were labeled using a Python-based tool using four image categories: excellent (E), good (G), adequate (A) and insufficient for grading (I). We enrolled 8 subjects (4 with and 4 without medical background, groups M and NM, respectively) to whom a tutorial was presented on image quality requirements. We randomly selected 200 images from a pool of 18,145 expert-labeled images (50/E, 50/G, 50/A, 50/I). The performance of the grading was timed and the agreement was assessed. An additional grading round was performed with 14 labels for a more objective analysis. ResultsThe median time (interquartile range) for the labeling task with 4 categories was 987.8 sec (418.6) for all graders and 872.9 sec (621.0) vs. 1019.8 sec (479.5) in the M vs. NM groups, respectively. Cohen's weighted kappa showed moderate agreement (0.564) when using four categories that increased to substantial (0.637) when using only three by merging the E and G groups. By the use of 14 labels, the weighted kappa values were 0.594 and 0.667 when assigning four or three categories, respectively. ConclusionImage grading with a Python-based tool seems to be a simple yet possibly efficient solution for the labeling of fundus images according to image quality that does not necessarily require medical background. Such grading can be subject to variability but could still effectively serve the robust identification of images with insufficient quality. This emphasizes the opportunity for the democratization of ML-applications among persons with both medical and non-medical background. However, simplicity of the grading system is key to successful categorization

Acanthamoeba keratitis – Clinical signs, differential diagnosis and treatment

Purpose: To summarize actual literature data on clinical signs, differential diagnosis, and treatment of acanthamoeba keratitis. Methods: Review of literature. Results: Clinical signs of acanthamoeba keratitis are in early stages grey-dirty epithelium, pseudodendritiformic epitheliopathy, perineuritis, multifocal stromal infiltrates, ring infiltrate and in later stages scleritis, iris atrophy, anterior synechiae, secondary glaucoma, mature cataract, and chorioretinitis. As conservative treatment, we use up to one year triple-topical therapy (polyhexamethylene-biguanide, propamidine-isethionate, neomycin). In therapy resistant cases, surgical treatment options such as corneal cryotherapy, amniotic membrane transplantation, riboflavin-UVA cross-linking, and penetrating keratoplasty are applied. Conclusion: With early diagnosis and conservative or surgical treatment, acanthamoeba keratitis heals in most cases. Keywords: Acanthamoeba, Keratitis, Cornea, Contact len

Investigation of changes in thickness and reflectivity from layered retinal structures of healthy and diabetic eyes with optical coherence tomography

OCT is usually employed for the measurement of retinal thickness. However, coherent reflected light carries more information characterizing the optical properties of tissue. Therefore, optical property changes may provide further information regarding cellular layers and early damage in ocular diseases. We investigated the possibility of OCT in detecting changes in the optical backscattered signal from layered retinal structures. OCT images were obtained from diabetic patients without retinopathy (DM, n = 38 eyes) or mild diabetic retinopathy (MDR, n = 43 eyes) and normal healthy subjects (n = 74 eyes). The thickness and reflectivity of various layered structures were assessed using a custom-built algorithm. In addition, we evaluated the usefulness of quantifying the reflectivity of layered structures in the detection of retinal damage. Generalized estimating equations considering within-subject inter-eye relations were used to test for differences between the groups. A modified p value of <0.001 was considered statistically significant. Receiver operating characteristic (ROC) curves were constructed to describe the ability of each parameter to discriminate between the eyes of DM, MDR and healthy eyes. Thickness values of the GCL + IPL and OPL showed a significant decrease in the MDR eyes compared to controls. Significant decreases of total reflectance average values were observed in all layers in the MDR eyes compared with controls. The highest AUROC values estimated for the total reflectance were observed for the GCL + IPL, OPL and OS when comparing MDR eyes with controls. Total reflectance showed a better discriminating power between the MDR eyes and healthy eyes compared to thickness values. Our results suggest that the optical properties of the intraretinal layers may provide useful information to differentiate pathological from healthy eyes. Further research is warranted to determine how this approach may be used to improve diagnosis of early retinal neurodegeneration