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Purpose: This study aimed to investigate the impact of distinctive capillary-large vessel (CLV) analysis in optical coherence tomography angiography (OCTA) on the classification performance of diabetic retinopathy (DR). Methods: This multicenter study analyzed 212 OCTA images from 146 patients, including 28 controls, 36 diabetic patients without DR (NoDR), 31 with mild non-proliferative DR (NPDR), 28 with moderate NPDR, and 23 with severe NPDR. Quantitative features were derived from the whole image as well as the parafovea and perifovea regions. A support vector machine classifier was employed for DR classification. The accuracy and area under the receiver operating characteristic curve were used to evaluate the classification performance, utilizing features derived from the whole image and specific regions, both before and after CLV analysis. Results: Differential CLV analysis significantly improved OCTA classification of DR. In binary classifications, accuracy improved by 11.81%, rising from 77.45% to 89.26%, when utilizing whole image features. For multiclass classifications, accuracy increased by 7.55%, from 78.68% to 86.23%. Incorporating features from the whole image, parafovea, and perifovea further improved binary classification accuracy from 83.07% to 93.80%, and multiclass accuracy from 82.64% to 87.92%. Conclusions: This study demonstrated that feature changes in capillaries are more sensitive during DR progression, and CLV analysis can significantly improve DR classification performance by extracting features that are specific to large vessels and capillaries in OCTA. Incorporating regional features further improves DR classification accuracy. Differential CLV analysis promises better disease screening, diagnosis, and treatment outcome assessment.
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Capilares , Retinopatía Diabética , Angiografía con Fluoresceína , Curva ROC , Vasos Retinianos , Tomografía de Coherencia Óptica , Humanos , Retinopatía Diabética/clasificación , Retinopatía Diabética/diagnóstico , Retinopatía Diabética/diagnóstico por imagen , Tomografía de Coherencia Óptica/métodos , Femenino , Capilares/patología , Capilares/diagnóstico por imagen , Masculino , Vasos Retinianos/diagnóstico por imagen , Vasos Retinianos/patología , Persona de Mediana Edad , Angiografía con Fluoresceína/métodos , Anciano , Estudios Retrospectivos , Fondo de Ojo , AdultoRESUMEN
BACKGROUND/AIM: Allostatic load (AL) is a measure of chronic stress that is associated with worse cancer outcomes. The purpose of this retrospective cohort study was to investigate the relationship between AL and uveal melanoma (UM) clinical features. PATIENTS AND METHODS: AL score was calculated as a composite of ten biomarkers in 111 patients with UM from the University of Illinois Hospital. One point was assigned to an AL score for each biomarker based on predetermined cutoff values. Linear and logistic regression analyses evaluated the relationship between AL score and several tumor clinical characteristics. RESULTS: High AL score had a significant relationship with extraocular extension (p=0.015). There was also a significant difference in mean blood glucose levels between the different tumor size groups (p=0.029). Higher AL scores also had a trend of being associated with a smaller tumor size (p=0.069). CONCLUSION: AL score was significantly associated with the presence of extraocular extension for uveal melanoma, while the smallest tumor size group was associated with the highest blood glucose level. No other significant correlations were found between AL and other clinical features of UM. The relationship between AL score and extraocular extension warrants further investigation. Additional research is needed to evaluate socioeconomic factors and their effect on the relationship between chronic stress and the clinical features of UM.
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Alostasis , Melanoma , Neoplasias de la Úvea , Humanos , Neoplasias de la Úvea/patología , Melanoma/patología , Masculino , Femenino , Persona de Mediana Edad , Estudios Retrospectivos , Anciano , Alostasis/fisiología , Adulto , Glucemia/metabolismo , Biomarcadores de Tumor/metabolismo , Biomarcadores de Tumor/sangre , Anciano de 80 o más AñosRESUMEN
This study investigates the impact of differential artery-vein (AV) analysis in optical coherence tomography angiography (OCTA) on machine learning classification of diabetic retinopathy (DR). Leveraging deep learning for arterial-venous area (AVA) segmentation, six quantitative features, including perfusion intensity density (PID), blood vessel density (BVD), vessel area flux (VAF), blood vessel caliber (BVC), blood vessel tortuosity (BVT), and vessel perimeter index (VPI) features, were derived from OCTA images before and after AV differentiation. A support vector machine (SVM) classifier was utilized to assess both binary and multiclass classifications of control, diabetic patients without DR (NoDR), mild DR, moderate DR, and severe DR groups. Initially, one-region features, i.e., quantitative features extracted from the entire OCTA, were evaluated for DR classification. Differential AV analysis improved classification accuracies from 78.86% to 87.63% and from 79.62% to 85.66% for binary and multiclass classifications, respectively. Additionally, three-region features derived from the entire image, parafovea, and perifovea, were incorporated for DR classification. Differential AV analysis further enhanced classification accuracies from 84.43% to 93.33% and from 83.40% to 89.25% for binary and multiclass classifications, respectively. These findings highlight the potential of differential AV analysis in augmenting disease diagnosis and treatment assessment using OCTA.
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BACKGROUND: Reliable differentiation of uveal melanoma and choroidal nevi is crucial to guide appropriate treatment, preventing unnecessary procedures for benign lesions and ensuring timely treatment for potentially malignant cases. The purpose of this study is to validate deep learning classification of uveal melanoma and choroidal nevi, and to evaluate the effect of colour fusion options on the classification performance. METHODS: A total of 798 ultra-widefield retinal images of 438 patients were included in this retrospective study, comprising 157 patients diagnosed with UM and 281 patients diagnosed with choroidal naevus. Colour fusion options, including early fusion, intermediate fusion and late fusion, were tested for deep learning image classification with a convolutional neural network (CNN). F1-score, accuracy and the area under the curve (AUC) of a receiver operating characteristic (ROC) were used to evaluate the classification performance. RESULTS: Colour fusion options were observed to affect the deep learning performance significantly. For single-colour learning, the red colour image was observed to have superior performance compared to green and blue channels. For multi-colour learning, the intermediate fusion is better than early and late fusion options. CONCLUSION: Deep learning is a promising approach for automated classification of uveal melanoma and choroidal nevi. Colour fusion options can significantly affect the classification performance.
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OBJECTIVE: Uveal melanoma is the most common intraocular malignancy in adults. Current screening and triaging methods for melanocytic choroidal tumours face inherent limitations, particularly in regions with limited access to specialized ocular oncologists. This study explores the potential of machine learning to automate tumour segmentation. We develop and evaluate a machine-learning model for lesion segmentation using ultra-wide-field fundus photography. METHOD: A retrospective chart review was conducted of patients diagnosed with uveal melanoma, choroidal nevi, or congenital hypertrophy of the retinal pigmented epithelium at a tertiary academic medical centre. Included patients had a single ultra-wide-field fundus photograph (Optos PLC, Dunfermline, Fife, Scotland) of adequate quality to visualize the lesion of interest, as confirmed by a single ocular oncologist. These images were used to develop and test a machine-learning algorithm for lesion segmentation. RESULTS: A total of 396 images were used to develop a machine-learning algorithm for lesion segmentation. Ninety additional images were used in the testing data set along with images of 30 healthy control individuals. Of the images with successfully detected lesions, the machine-learning segmentation yielded Dice coefficients of 0.86, 0.81, and 0.85 for uveal melanoma, choroidal nevi, and congenital hypertrophy of the retinal pigmented epithelium, respectively. Sensitivities for any lesion detection per image were 1.00, 0.90, and 0.87, respectively. For images without lesions, specificity was 0.93. CONCLUSION: Our study demonstrates a novel machine-learning algorithm's performance, suggesting its potential clinical utility as a widely accessible method of screening choroidal tumours. Additional evaluation methods are necessary to further enhance the model's lesion classification and diagnostic accuracy.
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Ultrasound A-scan is an important tool for quantitative assessment of ocular lesions. However, its usability is limited by the difficulty of accurately localizing the ultrasound probe to a lesion of interest. In this study, a transparent LiNbO3 single crystal ultrasound transducer was fabricated, and integrated with a widefield fundus camera to guide the ultrasound local position. The electrical impedance, phase spectrum, pulse-echo performance, and optical transmission spectrum of the ultrasound transducer were validated. The novel fundus camera-guided ultrasound probe was tested for in vivo measurement of rat eyes. Anterior and posterior segments of the rat eye could be unambiguously differentiated with the fundus photography-guided ultrasound measurement. A model eye was also used to verify the imaging performance of the prototype device in the human eye. The prototype shows the potential of being used in the clinic to accurately measure the thickness and echogenicity of ocular lesions in vivo.
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Angiografía con Fluoresceína , Ratas , Animales , Humanos , Angiografía con Fluoresceína/métodos , UltrasonografíaRESUMEN
Purpose: The purpose of this study was to investigate the spectral characteristics of choroidal nevi and assess the feasibility of quantifying the basal diameter of choroidal nevi using multispectral fundus images captured with trans-palpebral illumination. Methods: The study used a widefield fundus camera with multispectral (625 nm, 780 nm, 850 nm, and 970 nm) trans-palpebral illumination to examine eight subjects diagnosed with choroidal nevi. Geometric features of nevi, including border clarity, overlying drusen, and lesion basal diameter, were characterized. Clinical imagers, including scanning laser ophthalmoscopy (SLO), autofluorescence (AF), and optical coherence tomography (OCT), were utilized for comparative assessment. Results: Fundus images depicted nevi as dark regions with high contrast against the background. Near-infrared (NIR) fundus images provided enhanced visibility of lesion borders compared to visible fundus images and SLO images. Lesion-background contrast measurements revealed 635 nm SLO at 11% and 625 nm fundus at 42%. Significantly enhanced contrasts were observed in NIR fundus images at 780 nm (73%), 850 nm (63%), and 970 nm (67%). For quantifying the diameter of nevi, NIR fundus images at 780 nm and 850 nm yielded a deviation of less than 10% when compared to OCT measurements. Conclusions: NIR fundus photography with trans-palpebral illumination enhances nevi visibility and boundary definition compared to SLO. Agreement in diameter measurements with OCT validates the accuracy and reliability of this method for choroidal nevi assessment. Translational Relevance: Multispectral fundus imaging with trans-palpebral illumination improves choroidal nevi visibility and accurately measures basal diameter, promising to enhance clinical practices in screening, diagnosis, and monitoring of choroidal nevi.
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Neoplasias de la Coroides , Nevo Pigmentado , Nevo , Neoplasias Cutáneas , Humanos , Iluminación , Reproducibilidad de los Resultados , Nevo Pigmentado/diagnóstico por imagen , Nevo Pigmentado/patología , Neoplasias de la Coroides/diagnóstico por imagen , Neoplasias de la Coroides/patología , Nevo/diagnóstico por imagen , FotograbarRESUMEN
Purpose: To investigate the spectral characteristics of choroidal nevi and assess the feasibility of quantifying the basal diameter of choroidal nevi using multispectral fundus images captured with trans-palpebral illumination. Methods: The study employed a widefield fundus camera with multispectral (625 nm, 780 nm, 850 nm, and 970 nm) trans-palpebral illumination. Geometric features of choroidal nevi, including border clarity, overlying drusen, and lesion basal diameter, were characterized. Clinical imagers, including scanning laser ophthalmoscopy (SLO), autofluorescence (AF), and optical coherence tomography (OCT), were utilized for comparative assessment. Results: Fundus images captured with trans-palpebral illumination depicted nevi as dark regions with high contrast against the background. Near-infrared (NIR) fundus images provided enhanced visibility of lesion borders compared to visible light fundus images and SLO images. Lesion-background contrast measurements revealed 635 nm SLO at 11% and 625 nm fundus at 42%. Significantly enhanced contrasts were observed in NIR fundus images at 780 nm (73%), 850 nm (63%), and 970 nm (67%). For quantifying the basal diameter of nevi, NIR fundus images at 780 nm and 850 nm yielded a deviation of less than 10% when compared to OCT B-scan measurements. Conclusion: NIR fundus photography with trans-palpebral illumination enhances nevi visibility and boundary definition compared to SLO. Agreement in basal diameter measurements with OCT validates the accuracy and reliability of this method for choroidal nevi assessment.
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Multi-spectral widefield fundus photography is valuable for the clinical diagnosis and management of ocular conditions that may impact both central and peripheral regions of the retina and choroid. Trans-palpebral illumination has been demonstrated as an alternative to transpupillary illumination for widefield fundus photography without requiring pupil dilation. However, spectral efficiency can be complicated due to the spatial variance of the light property through the palpebra and sclera. This study aims to investigate the effect of light delivery location on spectral efficiency in trans-palpebral illumination. Four narrow-band light sources, covering both visible and near infrared (NIR) wavelengths, were used to evaluate spatial dependency of spectral illumination efficiency. Comparative analysis indicated a significant dependence of visible light efficiency on spatial location, while NIR light efficiency is only slightly affected by the illumination location. This study confirmed the pars plana as the optimal location for delivering visible light to achieve color imaging of the retina. Conversely, spatial location is not critical for NIR light imaging of the choroid.
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The purpose of this study is to demonstrate the feasibility of using polarization maintaining photons for enhanced contrast imaging of the retina. Orthogonal-polarization control has been frequently used in conventional fundus imaging systems to minimize reflection artifacts. However, the orthogonal-polarization configuration also rejects the directly reflected photons, which preserve the polarization condition of incident light, from the superficial layer of the fundus, i.e., the retina, and thus reduce the contrast of retinal imaging. We report here a portable fundus camera which can simultaneously perform orthogonal-polarization control to reject back-reflected light from the ophthalmic lens and parallel-polarization control to preserve the backscattered light from the retina which partially maintains the polarization state of the incoming light. This portable device utilizes miniaturized indirect ophthalmoscopy illumination to achieve non-mydriatic imaging, with a snapshot field of view of 101° eye-angle (67° visual-angle). Comparative analysis of retinal images acquired with a traditional orthogonal-polarization fundus camera from both normal and diseased eyes was conducted to validate the usefulness of the proposed design. The parallel-polarization control for enhanced contrast in high dynamic range imaging has also been validated.
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Due to its accessibility and ability for real-time image acquisition of ocular structures, ultrasound has high utility in the visualization of the eye, especially in ocular oncology. In this minireview, we summarize the technical rationale and applications of ultrasound modalities, A-scan, B-scan, high-frequency ultrasound biomicroscopy (UBM), and Doppler measurement. A-scan ultrasound uses a transducer of 7-11 MHz, making it useful for determining the echogenicity of ocular tumors (7-8 MHz) and measuring the axial length of the eye (10-11 MHz). B-scan ultrasound operates at 10-20 MHz, which can be used for measuring posterior ocular tumors while UBM operates at 40-100 MHz to evaluate anterior ocular structures. Doppler ultrasonography allows for the detection of tumor vascularization. While ultrasonography has numerous clinical applications due to its favorable penetration compared with optical coherence tomography, it is still limited by its relatively lower resolution. Ultrasound also requires an experienced sonographer due to the need for accurate probe localization to areas of interest.
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Oftalmopatías , Neoplasias , Humanos , Ojo/diagnóstico por imagen , Ultrasonografía , Oftalmopatías/diagnóstico por imagen , Tomografía de Coherencia ÓpticaRESUMEN
Fundus photography is indispensable for the clinical detection and management of eye diseases. Low image contrast and small field of view (FOV) are common limitations of conventional fundus photography, making it difficult to detect subtle abnormalities at the early stages of eye diseases. Further improvements in image contrast and FOV coverage are important for early disease detection and reliable treatment assessment. We report here a portable, wide FOV fundus camera with high dynamic range (HDR) imaging capability. Miniaturized indirect ophthalmoscopy illumination was employed to achieve the portable design for nonmydriatic, widefield fundus photography. Orthogonal polarization control was used to eliminate illumination reflectance artifacts. With independent power controls, three fundus images were sequentially acquired and fused to achieve HDR function for local image contrast enhancement. A 101° eye-angle (67° visual-angle) snapshot FOV was achieved for nonmydriatic fundus photography. The effective FOV was readily expanded up to 190° eye-angle (134° visual-angle) with the aid of a fixation target without the need for pharmacologic pupillary dilation. The effectiveness of HDR imaging was validated with both normal healthy and pathologic eyes, compared to a conventional fundus camera.
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Objective: This study aims to assess a machine learning (ML) algorithm using multimodal imaging to accurately identify risk factors for uveal melanoma (UM) and aid in the diagnosis of melanocytic choroidal tumors. Subjects and Methods: This study included 223 eyes from 221 patients with melanocytic choroidal lesions seen at the eye clinic of the University of Illinois at Chicago between 01/2010 and 07/2022. An ML algorithm was developed and trained on ultra-widefield fundus imaging and B-scan ultrasonography to detect risk factors of malignant transformation of choroidal lesions into UM. The risk factors were verified using all multimodal imaging available from the time of diagnosis. We also explore classification of lesions into UM and choroidal nevi using the ML algorithm. Results: The ML algorithm assessed features of ultra-widefield fundus imaging and B-scan ultrasonography to determine the presence of the following risk factors for malignant transformation: lesion thickness, subretinal fluid, orange pigment, proximity to optic nerve, ultrasound hollowness, and drusen. The algorithm also provided classification of lesions into UM and choroidal nevi. A total of 115 patients with choroidal nevi and 108 patients with UM were included. The mean lesion thickness for choroidal nevi was 1.6 mm and for UM was 5.9 mm. Eleven ML models were implemented and achieved high accuracy, with an area under the curve of 0.982 for thickness prediction and 0.964 for subretinal fluid prediction. Sensitivity/specificity values ranged from 0.900/0.818 to 1.000/0.727 for different features. The ML algorithm demonstrated high accuracy in identifying risk factors and differentiating lesions based on the analyzed imaging data. Conclusions: This study provides proof of concept that ML can accurately identify risk factors for malignant transformation in melanocytic choroidal tumors based on a single ultra-widefield fundus image or B-scan ultrasound at the time of initial presentation. By leveraging the efficiency and availability of ML, this study has the potential to provide a non-invasive tool that helps to prevent unnecessary treatment, improve our ability to predict malignant transformation, reduce the risk of metastasis, and potentially save patient lives.
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The diagnosis of primary vitreoretinal lymphoma and central nervous system lymphoma is challenging. In cases with intraocular involvement, vitreous biopsy plays a pivotal role. Several diagnostic tests are employed to confirm a diagnosis and include cytologic evaluation, immunohistochemistry, flow cytometry, and cytokine analysis. The limitations of these conventional diagnostic tests stem from the often paucicellular nature of vitreous biopsy specimens and the fragility of malignant cells ex vivo. Several emerging molecular techniques show promise in improving the diagnostic yield of intraocular biopsy, possibly enabling more accurate and timely diagnoses. This article will review existing diagnostic modalities for intraocular lymphoma, with an emphasis on currently available molecular tests.
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PURPOSE OF REVIEW: This article reviews the latest proteomic research on uveal melanoma. RECENT FINDINGS: Proteomic analysis of uveal melanoma cell lines and tissue specimens has improved our understanding of the pathophysiology of uveal melanoma and helped identify potential prognostic biomarkers. Circulating proteins in patient serum may aid in the surveillance of metastatic disease. The proteomes of aqueous and vitreous biopsy specimens may provide safer biomarkers for metastatic risk and candidate therapeutic targets in uveal melanoma. Proteomic analysis has the potential to benefit patient outcomes by improving diagnosis, prognostication, surveillance, and treatment of uveal melanoma. SUMMARY: These recent findings demonstrate that proteomic analysis is an important area of research to better understand the pathophysiology of uveal melanoma and improve the personalized management of our patients.
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Melanoma , Neoplasias de la Úvea , Biopsia , Humanos , Melanoma/diagnóstico , Melanoma/patología , Proteómica , Neoplasias de la Úvea/diagnóstico , Neoplasias de la Úvea/patologíaRESUMEN
PURPOSE: To use optical coherence tomography angiography (OCTA) to study longitudinal subclinical choroidal neovascularization (CNV) changes and their correlation with progression to exudation in age-related macular degeneration (AMD). METHODS: This study included a total of 34 patients with unilateral neovascular AMD who were evaluated prospectively using OCTA to detect subclinical CNV in their fellow eye. Eyes with baseline subclinical CNV were followed with serial OCTA for a minimum of one year (15.2±3.27 months) to monitor the development of exudation. RESULTS: Of the 34 fellow eyes studied, five were found to have baseline subclinical CNV. One of the five cases of baseline subclinical CNV converted to exudative AMD during the follow up period. The average surface area of baseline subclinical CNV on OCTA was 0.131±0.096 mm2 which progressed to 0.136±0.104 mm2 at the final follow up (P = 0.539). Geographic atrophy grew at a rate of 0.82±1.20mm2/year in four eyes without subclinical CNV and 0.02mm2/year in one eye with subclinical CNV. CONCLUSION AND IMPORTANCE: The rate of conversion to exudative AMD in eyes with subclinical CNV of 20% in our study is similar to previous reports and suggests the importance of vigilance in these eyes. The lower growth rate of geographic atrophy may suggest a protective effect of subclinical CNV that deserves further study.
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Neovascularización Coroidal/complicaciones , Neovascularización Coroidal/patología , Progresión de la Enfermedad , Degeneración Macular/complicaciones , Coroides/irrigación sanguínea , Coroides/patología , Humanos , PerfusiónRESUMEN
BACKGROUND AND OBJECTIVE: Advanced retinal imaging can improve understanding of retinal vein occlusion (RVO) pathology. The authors aimed to characterize the vascular pathology of RVO on en face optical coherence tomography (OCT) and OCT angiography (OCTA). PATIENT AND METHODS: This was a cross-sectional study including 17 eyes with RVO. The authors identified discordance between vasculature on en face OCT and flow on OCTA, which was correlated with structural findings at the corresponding location on OCT B-scans. RESULTS: Six eyes had vessels that were seen on OCT without flow on OCTA. The most clinically relevant finding was preserved inner retinal layers in areas where the en face OCT showed collaterals that appeared nonperfused on OCTA. CONCLUSIONS: The authors' findings indicate that collaterals can appear on en face OCT without flow on OCTA in RVO and may be associated with relatively preserved inner retinal structures. Clinicians should consider multimodal imaging to evaluate RVO, including both OCT and OCTA. [Ophthalmic Surg Lasers Imaging Retina. 2018;49:392-396.].