RESUMEN
BACKGROUND: Diabetic retinopathy (DR), a chronic and progressive microvascular complication of diabetes mellitus, substantially threatens vision and is a leading cause of blindness among working-age individuals worldwide. Traditional diagnostic methods, such as ophthalmoscopy and fluorescein angiography are nonquantitative, invasive, and time consuming. Analysis of protein biomarkers in tear fluid offers noninvasive insights into ocular and systemic health, aiding in early DR detection. This study introduces a surface acoustic wave (SAW) microchip that rapidly enhances fluorescence in bead-based immunoassays for the sensitive and noninvasive DR detection from human tear samples. RESULTS: The device facilitated particle mixing for immunoassay formation and particle concentration in the droplet, resulting in an enhanced immunofluorescence signal. This detachable SAW microchip allows the disposal of the cover glass after every use, thereby improving the reusability of the interdigital transducer and minimizing potential cross-contamination. A preliminary clinical test was conducted on a cohort of 10 volunteers, including DR patients and healthy individuals. The results demonstrated strong agreement with ELISA studies, validating the high accuracy rate of the SAW microchip. SIGNIFICANCE: This comprehensive study offers significant insights into the potential application of a novel SAW microchip for the early detection of DR in individuals with diabetes. By utilizing protein biomarkers found in tear fluid, the device facilitates noninvasive, rapid, and sensitive detection, potentially revolutionizing DR diagnostics and improving patient outcomes through timely intervention and management of this vision-threatening condition.
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Retinopatía Diabética , Lágrimas , Humanos , Lágrimas/química , Retinopatía Diabética/diagnóstico , Inmunoensayo/métodos , Sonido , Técnicas Biosensibles/instrumentación , Biomarcadores/análisis , Propiedades de SuperficieRESUMEN
Early detection of diabetic retinopathy (DR) is an urgent ophthalmological problem in Russia and globally. PURPOSE: This study assesses the prevalence of asymptomatic retinopathy and attempts to identify risk groups for its development in patients with type 1 and 2 diabetes mellitus (T1DM and T2DM). MATERIAL AND METHODS: The study involved clinics from 5 cities in the Russian Federation and it included 367 patients with DM, 34.88% men and 65.12% women, aged 50.88±20.55 years. 34.88% of patients suffered from T1DM, 65.12% suffered from T2DM, the average duration of the disease was 9.02±7.22 years. 58.31% of patients had a history of arterial hypertension, 13.08% had a history of smoking. The primary endpoint was the frequency of detection of diabetic changes in the eye fundus of patients with T1DM and T2DM in general; the secondary endpoint - same but separately, and for T2DM patients depending on the duration of the disease. The exploratory endpoint was the assessment of the influence of various factors on the development of DR. The patients underwent visometry (modified ETDRS table), biomicroscopy, mydriatic fundus photography according to the «2 fields¼ protocol. RESULTS: The average detection rate of DR was 12.26%, primarily observed in patients with T2DM (13.81%), women (9.26%), in both eyes (8.17%). Among patients with DR, 26 (19.55%) had glycated hemoglobin (HbA1c) level exceeding 7.5% (p=0.002), indicating a direct relationship between this indicator and the incidence of DR. Logistic regression analysis showed that the duration of diabetes of more than 10 years has a statistically significant effect on the development of DR. In the modified model for odds estimation, the likelihood of developing DR is increased by the duration of DM for more than 10 years; increased blood pressure; HbA1c level >7.5%. CONCLUSION: The obtained results, some of which will be presented in subsequent publications, highlight the effectiveness of using two-field mydriatic fundus photography as a screening for DR.
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Diabetes Mellitus Tipo 2 , Retinopatía Diabética , Fondo de Ojo , Fotograbar , Humanos , Retinopatía Diabética/diagnóstico , Retinopatía Diabética/epidemiología , Femenino , Masculino , Persona de Mediana Edad , Federación de Rusia/epidemiología , Prevalencia , Fotograbar/métodos , Adulto , Diabetes Mellitus Tipo 2/epidemiología , Diabetes Mellitus Tipo 2/complicaciones , Diabetes Mellitus Tipo 2/diagnóstico , Anciano , Factores de Riesgo , Diabetes Mellitus Tipo 1/complicaciones , Diabetes Mellitus Tipo 1/epidemiología , Diabetes Mellitus Tipo 1/diagnóstico , Diagnóstico PrecozRESUMEN
Importance: Safe integration of artificial intelligence (AI) into clinical settings often requires randomized clinical trials (RCT) to compare AI efficacy with conventional care. Diabetic retinopathy (DR) screening is at the forefront of clinical AI applications, marked by the first US Food and Drug Administration (FDA) De Novo authorization for an autonomous AI for such use. Objective: To determine the generalizability of the 7 ethical research principles for clinical trials endorsed by the National Institute of Health (NIH), and identify ethical concerns unique to clinical trials of AI. Design, Setting, and Participants: This qualitative study included semistructured interviews conducted with 11 investigators engaged in the design and implementation of clinical trials of AI for DR screening from November 11, 2022, to February 20, 2023. The study was a collaboration with the ACCESS (AI for Children's Diabetic Eye Exams) trial, the first clinical trial of autonomous AI in pediatrics. Participant recruitment initially utilized purposeful sampling, and later expanded with snowball sampling. Study methodology for analysis combined a deductive approach to explore investigators' perspectives of the 7 ethical principles for clinical research endorsed by the NIH and an inductive approach to uncover the broader ethical considerations implementing clinical trials of AI within care delivery. Results: A total of 11 participants (mean [SD] age, 47.5 [12.0] years; 7 male [64%], 4 female [36%]; 3 Asian [27%], 8 White [73%]) were included, with diverse expertise in ethics, ophthalmology, translational medicine, biostatistics, and AI development. Key themes revealed several ethical challenges unique to clinical trials of AI. These themes included difficulties in measuring social value, establishing scientific validity, ensuring fair participant selection, evaluating risk-benefit ratios across various patient subgroups, and addressing the complexities inherent in the data use terms of informed consent. Conclusions and Relevance: This qualitative study identified practical ethical challenges that investigators need to consider and negotiate when conducting AI clinical trials, exemplified by the DR screening use-case. These considerations call for further guidance on where to focus empirical and normative ethical efforts to best support conduct clinical trials of AI and minimize unintended harm to trial participants.
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Inteligencia Artificial , Ensayos Clínicos como Asunto , Retinopatía Diabética , Humanos , Inteligencia Artificial/ética , Retinopatía Diabética/diagnóstico , Ensayos Clínicos como Asunto/ética , Femenino , Investigación Cualitativa , Proyectos de Investigación , Masculino , Estados UnidosRESUMEN
BACKGROUND: To analyse and compare the grading of diabetic retinopathy (DR) severity level using standard 35° ETDRS 7-fields photography and CLARUS™ 500 ultra-widefield imaging system. METHODS: A cross-sectional analysis of retinal images of patients with type 2 diabetes (n = 160 eyes) was performed for this study. All patients underwent 7-fields colour fundus photography (CFP) at 35° on a standard Topcon TRC-50DX® camera, and ultra-widefield (UWF) imaging at 200° on a CLARUS™ 500 (ZEISS, Dublin, CA, USA) by an automatic montage of two 133° images (nasal and temporal). 35° 7-fields photographs were graded by two graders, according to the Early Treatment Diabetic Retinopathy Study (ETDRS). For CLARUS UWF images, a prototype 7-fields grid was applied using the CLARUS review software, and the same ETDRS grading procedures were performed inside that area only. Grading of DR severity level was compared between these two methods to evaluate the agreement between both imaging techniques. RESULTS: Images of 160 eyes from 83 diabetic patients were considered for analysis. According to the 35° ETDRS 7-fields images, 22 eyes were evaluated as DR severity level 10-20, 64 eyes were evaluated as DR level 35, 41 eyes level 43, 21 eyes level 47, 7 eyes level 53, and 5 eyes level 61. The same DR severity level was achieved with CLARUS 500 UWF images in 92 eyes (57%), showing a perfect agreement (k > 0.80) with the 7-fields 35° technique. Fifty-seven eyes (36%) showed a higher DR level with CLARUS UWF images, mostly due to a better visualization of haemorrhages and a higher detection rate of intraretinal microvascular abnormalities (IRMA). Only 11 eyes (7%) showed a lower severity level with the CLARUS UWF system, due to the presence of artifacts or media opacities that precluded the correct evaluation of DR lesions. CONCLUSIONS: UWF CLARUS 500 device showed nearly perfect agreement with standard 35° 7-fields images in all ETDRS severity levels. Moreover, CLARUS images showed an increased ability to detect haemorrhages and IRMA helping with finer evaluation of lesions, thus demonstrating that a UWF photograph can be used to grade ETDRS severity level with a better visualization than the standard 7-fields images. TRIAL REGISTRATION: Approved by the AIBILI - Association for Innovation and Biomedical Research on Light and Image Ethics Committee for Health with number CEC/009/17- EYEMARKER.
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Diabetes Mellitus Tipo 2 , Retinopatía Diabética , Fotograbar , Índice de Severidad de la Enfermedad , Humanos , Retinopatía Diabética/diagnóstico , Retinopatía Diabética/diagnóstico por imagen , Estudios Transversales , Femenino , Masculino , Persona de Mediana Edad , Fotograbar/métodos , Anciano , Diabetes Mellitus Tipo 2/complicaciones , Fondo de Ojo , Técnicas de Diagnóstico Oftalmológico , Adulto , Reproducibilidad de los ResultadosRESUMEN
OBJECTIVE: This study seeks to explain the relationship between systemic conditions and hard exudate formations in diabetic macular edema patients. Besides, the study aimed to quantitatively examine changes in the area, location, and impact on visual function of hard exudates following intravitreal dexamethasone implant injections. METHODS: A retrospective analysis was conducted, including 40 patients (40 eyes) diagnosed with non-proliferative diabetic retinopathy and concurrent macular edema between January 1, 2022, and January 1, 2024. Preoperative evaluations included glycated hemoglobin, lipid profile, and renal function examinations. Based on the location of HE, patients were divided into two groups: Group A, with HE in 1 mm of the central fovea, and Group B, with HE outside 1 mm of the central fovea. Selected eyes were subject to pre- and postoperative examinations, including best-corrected visual acuity (BCVA), intraocular pressure, slit-lamp biomicroscopy, scanning laser ophthalmoscopy (SLO), optical coherence tomography, and multifocal electroretinography. Following screening and examination, patients received an immediate intravitreal injection of the DEX implant, with an injection administered at the four-month mark. Hard exudate (HE) areas were measured utilizing SLO fundus imaging. RESULTS: Total cholesterol, low-density lipoprotein, and triglyceride levels were found to be positively correlated with the presence of HE. Following surgical intervention, all patients demonstrated an improvement in BCVA. The mean BCVA increased from a preoperative measurement of 0.79 ± 0.04 to 0.39 ± 0.02 at the 6 month follow-up, indicating a statistically significant difference (p < 0.001). The baseline HE area for the entire patient cohort was 2.28 ± 0.22. One month post-operation, the HE area exhibited a slight increase to 2.27 ± 0.22. However, by the 6 month follow-up, the HE area had significantly decreased to 0.8 ± 0.87, representing a 35.09% reduction from the baseline measurement (p < 0.001). It is worth noting that Patient P1 did not exhibit a statistically significant difference between preoperative and six-month postoperative HE area (p = 0.032). Preoperative BCVA measurements for Group A and Group B were 0.81 ± 0.03 and 0.77 ± 0.03, respectively, with no statistically significant intergroup difference (p = 0.333). The baseline HE area for Group A was 2.61 ± 0.16, which decreased to 0.38 ± 0.20 at the six-month follow-up, representing a 14.60% reduction from the baseline total area. For Group B, the baseline HE area was measured at 1.95 ± 0.09, then decreasing to 1.21 ± 0.13 at the six-month follow-up, indicating a 62.05% reduction from the baseline total area. A statistically significant difference in the postoperative 6 month HE area was observed between Group A and Group B (p < 0.001). In Group A, the reduction in HE area (initial HE area-final HE area) was positively correlated with the improvement in P1 (initial P1-final P1) (r = 0.610, p = 0.004). In Group B, a similar positive correlation was found (initial HE area-final HE area with initial P1-final P1) (r = 0.488, p = 0.029). In Group B, the reduction in HE area (initial HE area-final HE area) correlated positively with the improvement in BCVA (initial BCVA-final BCVA) (r = 0.615, p = 0.004). Additionally, in Group B, the reduction in HE area (initial HE area-final HE area) was positively correlated with the improvement in CMT (initial CMT-final CMT) (r = -0.725, p< 0.001). Aggravated cataracts were observed in thirteen eyes during a follow-up examination 6 months later. CONCLUSION: HE formation is associated with lipid levels. Dexamethasone implants demonstrate effectiveness in reducing HE areas in the short term, reducing macular edema, improving retinal structure, and enhancing visual function. The incidence of postoperative complications such as cataracts and glaucoma remains low.
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Dexametasona , Retinopatía Diabética , Implantes de Medicamentos , Glucocorticoides , Inyecciones Intravítreas , Edema Macular , Tomografía de Coherencia Óptica , Agudeza Visual , Humanos , Edema Macular/tratamiento farmacológico , Edema Macular/etiología , Edema Macular/diagnóstico , Retinopatía Diabética/tratamiento farmacológico , Retinopatía Diabética/diagnóstico , Retinopatía Diabética/complicaciones , Masculino , Dexametasona/administración & dosificación , Estudios Retrospectivos , Persona de Mediana Edad , Femenino , Glucocorticoides/administración & dosificación , Tomografía de Coherencia Óptica/métodos , Anciano , Exudados y Transudados , Resultado del Tratamiento , Estudios de SeguimientoRESUMEN
OBJECTIVES: To identify the barriers and facilitators to the successful implementation of imaging-based diagnostic artificial intelligence (AI)-assisted decision-making software in China, using the updated Consolidated Framework for Implementation Research (CFIR) as a theoretical basis to develop strategies that promote effective implementation. DESIGN: This qualitative study involved semistructured interviews with key stakeholders from both clinical settings and industry. Interview guide development, coding, analysis and reporting of findings were thoroughly informed by the updated CFIR. SETTING: Four healthcare institutions in Beijing and Shanghai and two vendors of AI-assisted decision-making software for lung nodules detection and diabetic retinopathy screening were selected based on purposive sampling. PARTICIPANTS: A total of 23 healthcare practitioners, 6 hospital informatics specialists, 4 hospital administrators and 7 vendors of the selected AI-assisted decision-making software were included in the study. RESULTS: Within the 5 CFIR domains, 10 constructs were identified as barriers, 8 as facilitators and 3 as both barriers and facilitators. Major barriers included unsatisfactory clinical performance (Innovation); lack of collaborative network between primary and tertiary hospitals, lack of information security measures and certification (outer setting); suboptimal data quality, misalignment between software functions and goals of healthcare institutions (inner setting); unmet clinical needs (individuals). Key facilitators were strong empirical evidence of effectiveness, improved clinical efficiency (innovation); national guidelines related to AI, deployment of AI software in peer hospitals (outer setting); integration of AI software into existing hospital systems (inner setting) and involvement of clinicians (implementation process). CONCLUSIONS: The study findings contributed to the ongoing exploration of AI integration in healthcare from the perspective of China, emphasising the need for a comprehensive approach considering both innovation-specific factors and the broader organisational and contextual dynamics. As China and other developing countries continue to advance in adopting AI technologies, the derived insights could further inform healthcare practitioners, industry stakeholders and policy-makers, guiding policies and practices that promote the successful implementation of imaging-based diagnostic AI-assisted decision-making software in healthcare for optimal patient care.
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Inteligencia Artificial , Investigación Cualitativa , Humanos , China , Programas Informáticos , Hospitales , Retinopatía Diabética/diagnóstico , Retinopatía Diabética/diagnóstico por imagen , Entrevistas como AsuntoRESUMEN
BACKGROUND: We aimed to evaluate microaneurysms (MAs) after treatment with anti-vascular endothelial growth factor (anti-VEGF) therapy to understand causes of chronic edema and anti-VEGF resistance. METHODS: Patients with non-proliferative diabetic retinopathy, with or without macular edema were recruited. Optical coherence tomography angiography (OCTA) MAs-related parameters were observed, including the maximum diameter of overall dimensions, material presence, and flow signal within the lumen. OCTA parameters also included central macular thickness (CMT), foveal avascular zone, superficial and deep capillary plexuses, and non-flow area measurements on the superficial retinal slab. RESULTS: Overall, 48 eyes from 43 patients were evaluated. CMT differed significantly between the diabetic macular edema (DME ) and non-DME (NDME) groups at 1st, 2nd, 3rd, and 6th months of follow-up (P < 0.001; <0.001; 0.003; <0.001, respectively). A total of 55 and 59 MAs were observed in the DME (mean = 99.40 ± 3.18 µm) and NDME (mean maximum diameter = 74.70 ± 2.86 µm) groups at baseline, respectively (significant between-group difference: P < 0.001). Blood flow signal was measurable for 46 (83.6%) and 34 (59.3%) eyes in the DME and NDME groups, respectively (significant between-group difference: P < 0.001). CONCLUSIONS: Compared to the NDME group, the DME group had larger MAs and a higher blood-flow signal ratio. Following anti-VEGF therapy, changes in the diameter of MAs were observed before changes in CMT thickness.
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Inhibidores de la Angiogénesis , Retinopatía Diabética , Angiografía con Fluoresceína , Inyecciones Intravítreas , Edema Macular , Microaneurisma , Tomografía de Coherencia Óptica , Factor A de Crecimiento Endotelial Vascular , Agudeza Visual , Humanos , Tomografía de Coherencia Óptica/métodos , Retinopatía Diabética/tratamiento farmacológico , Retinopatía Diabética/diagnóstico , Edema Macular/tratamiento farmacológico , Edema Macular/etiología , Edema Macular/diagnóstico por imagen , Edema Macular/diagnóstico , Masculino , Microaneurisma/diagnóstico , Femenino , Persona de Mediana Edad , Inhibidores de la Angiogénesis/uso terapéutico , Angiografía con Fluoresceína/métodos , Factor A de Crecimiento Endotelial Vascular/antagonistas & inhibidores , Anciano , Ranibizumab/uso terapéutico , Ranibizumab/administración & dosificación , Vasos Retinianos/diagnóstico por imagen , Vasos Retinianos/patología , Fondo de Ojo , Estudios de SeguimientoRESUMEN
PURPOSE: To report the clinical features and outcomes in eyes that underwent vitreoretinal surgery for complications of concurrent sickle cell retinopathy and diabetic retinopathy. METHODS: Retrospective, consecutive case series of all eyes that underwent vitreoretinal surgery for complications secondary to concurrent sickle cell retinopathy and diabetic retinopathy between January 01, 2014, and December 31, 2021. RESULTS: The study included 20 eyes of 14 patients. Indications for surgery included tractional retinal detachment in 12 eyes (60%), combined tractional retinal detachment/rhegmatogenous retinal detachment in 6 eyes (30%), and vitreous hemorrhage in 2 eyes (10%). Pars plana vitrectomy was performed in all eyes. One eye received a scleral buckle at the same time as pars plana vitrectomy. There was no change in mean best-corrected visual acuity at the last follow-up examination (1.5 [20/678]) when compared with mean preoperative best-corrected visual acuity (1.6 [20/762], P = 0.83). Preoperative best-corrected visual acuity correlated with postoperative best-corrected visual acuity at the last follow-up examination in eyes with retinal detachment (r = 0.49, P = 0.04). Single operation anatomic success was achieved in 11 of 17 eyes (65%) with retinal detachment. CONCLUSION: Functional and anatomic outcomes after surgery in eyes with concurrent sickle cell retinopathy and diabetic retinopathy are relatively poor.
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Anemia de Células Falciformes , Retinopatía Diabética , Desprendimiento de Retina , Agudeza Visual , Vitrectomía , Humanos , Estudios Retrospectivos , Retinopatía Diabética/cirugía , Retinopatía Diabética/complicaciones , Retinopatía Diabética/fisiopatología , Retinopatía Diabética/diagnóstico , Masculino , Femenino , Agudeza Visual/fisiología , Anemia de Células Falciformes/complicaciones , Persona de Mediana Edad , Adulto , Vitrectomía/métodos , Desprendimiento de Retina/cirugía , Desprendimiento de Retina/etiología , Desprendimiento de Retina/diagnóstico , Resultado del Tratamiento , Estudios de Seguimiento , Adulto Joven , Anciano , Cirugía Vitreorretiniana/métodosRESUMEN
Reliable automatic diagnosis of Diabetic Retinopathy (DR) and Macular Edema (ME) is an invaluable asset in improving the rate of monitored patients among at-risk populations and in enabling earlier treatments before the pathology progresses and threatens vision. However, the explainability of screening models is still an open question, and specifically designed datasets are required to support the research. We present MAPLES-DR (MESSIDOR Anatomical and Pathological Labels for Explainable Screening of Diabetic Retinopathy), which contains, for 198 images of the MESSIDOR public fundus dataset, new diagnoses for DR and ME as well as new pixel-wise segmentation maps for 10 anatomical and pathological biomarkers related to DR. This paper documents the design choices and the annotation procedure that produced MAPLES-DR, discusses the interobserver variability and the overall quality of the annotations, and provides guidelines on using the dataset in a machine learning context.
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Retinopatía Diabética , Edema Macular , Retinopatía Diabética/diagnóstico por imagen , Retinopatía Diabética/diagnóstico , Humanos , Aprendizaje Automático , Variaciones Dependientes del ObservadorRESUMEN
PURPOSE: To assess the interactive relationship between blood pressure status and diabetic mellitus (DM) with ganglion cell complex (GCC) thickness in elderly individuals in rural China. METHODS: Participants aged 50 years and older in a rural area of Daxing District, Beijing, were recruited in this study from October 2018 to November 2018. All subjects underwent a comprehensive systemic and ocular examination. Blood pressure status was graded as normotension, controlled hypertension and uncontrolled hypertension according to blood pressure measurements and the use of any medication for hypertension treatment. GCC parameters were measured by spectral-domain optical coherence tomography (SD-OCT). Generalized linear models (GLM) adjusted for related potential confounders were used to assess the interaction between DM and blood pressure status. RESULTS: Among 1415 screened subjects (2830 eyes), a total of 1117 eyes were enrolled in the final analysis. GLM analysis showed a significant interactive relationship between DM with uncontrolled hypertension status (ß = 3.868, p = 0.011). GCC thickness would decrease 0.255 µm per year as the age increased (ß=-0.255, p < 0.001). In a subgroup of 574 subjects with uncontrolled hypertension, DM was associated with an increased average of GCC thickness (ß = 1.929, p = 0.022). CONCLUSIONS: The present results revealed a significant interactive relationship between blood pressure status and DM. The average GCC thickness increased in individuals with DM combined with uncontrolled hypertension, which should be considered in the measurement of GCC. Further studies are warranted to explore ganglion cells changes as a non-invasive method to detect neuron alterations in individuals with DM and uncontrolled hypertension. TRAIL REGISTRATION: The registration number of the present trial in the Chinese Clinical Trial Registry is ChiCTR2000037944.
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Presión Sanguínea , Hipertensión , Fibras Nerviosas , Células Ganglionares de la Retina , Tomografía de Coherencia Óptica , Humanos , Células Ganglionares de la Retina/patología , Masculino , Femenino , Persona de Mediana Edad , Tomografía de Coherencia Óptica/métodos , Hipertensión/complicaciones , Hipertensión/fisiopatología , Anciano , China/epidemiología , Presión Sanguínea/fisiología , Fibras Nerviosas/patología , Estudios Transversales , Retinopatía Diabética/diagnóstico , Diabetes Mellitus/epidemiología , Población Rural/estadística & datos numéricosRESUMEN
Infrared thermography (IRT) is a well-known imaging technique that provides a non-invasive displaying of the ocular surface temperature distribution. Currently, compact smartphone-based IRT devices, as well as special software for processing thermal images, have become available. The study aimed to determine the possible use of smartphone-based IRT devices for real-time ocular surface thermal imaging. This study involved 32 healthy individuals (64 eyes); 10 patients (10 eyes) with proliferative diabetic retinopathy (PDR) and absolute glaucoma; 10 patients (10 eyes) with PDR, who underwent vitreoretinal surgery. In all cases, simultaneous ocular surface IRT of both eyes was performed. In healthy individuals, the ocular surface temperature (OST) averaged 34.6 ± 0.8 °C and did not differ substantially between the paired eyes, in different age groups, and after pupil dilation. In our study, high intraocular pressure was accompanied by a decrease in OST in all cases. After vitreoretinal surgery in cases with confirmed subclinical inflammation, the OST was higher than the baseline and differed from that of the paired eye by more than 1.0 °C. These results highlight that smartphone-based IRT imaging could be useful for the non-invasive detection of OST asymmetry between paired eyes due to increased intraocular pressure or subclinical inflammation.
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Ojo , Rayos Infrarrojos , Teléfono Inteligente , Termografía , Humanos , Termografía/instrumentación , Termografía/métodos , Adulto , Persona de Mediana Edad , Masculino , Femenino , Ojo/diagnóstico por imagen , Anciano , Adulto Joven , Retinopatía Diabética/diagnóstico por imagen , Retinopatía Diabética/fisiopatología , Retinopatía Diabética/diagnóstico , Glaucoma/diagnóstico por imagen , Glaucoma/fisiopatologíaRESUMEN
BACKGROUND: For medical artificial intelligence (AI) training and validation, human expert labels are considered the gold standard that represents the correct answers or desired outputs for a given data set. These labels serve as a reference or benchmark against which the model's predictions are compared. OBJECTIVE: This study aimed to assess the accuracy of a custom deep learning (DL) algorithm on classifying diabetic retinopathy (DR) and further demonstrate how label errors may contribute to this assessment in a nationwide DR-screening program. METHODS: Fundus photographs from the Lifeline Express, a nationwide DR-screening program, were analyzed to identify the presence of referable DR using both (1) manual grading by National Health Service England-certificated graders and (2) a DL-based DR-screening algorithm with validated good lab performance. To assess the accuracy of labels, a random sample of images with disagreement between the DL algorithm and the labels was adjudicated by ophthalmologists who were masked to the previous grading results. The error rates of labels in this sample were then used to correct the number of negative and positive cases in the entire data set, serving as postcorrection labels. The DL algorithm's performance was evaluated against both pre- and postcorrection labels. RESULTS: The analysis included 736,083 images from 237,824 participants. The DL algorithm exhibited a gap between the real-world performance and the lab-reported performance in this nationwide data set, with a sensitivity increase of 12.5% (from 79.6% to 92.5%, P<.001) and a specificity increase of 6.9% (from 91.6% to 98.5%, P<.001). In the random sample, 63.6% (560/880) of negative images and 5.2% (140/2710) of positive images were misclassified in the precorrection human labels. High myopia was the primary reason for misclassifying non-DR images as referable DR images, while laser spots were predominantly responsible for misclassified referable cases. The estimated label error rate for the entire data set was 1.2%. The label correction was estimated to bring about a 12.5% enhancement in the estimated sensitivity of the DL algorithm (P<.001). CONCLUSIONS: Label errors based on human image grading, although in a small percentage, can significantly affect the performance evaluation of DL algorithms in real-world DR screening.
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Aprendizaje Profundo , Retinopatía Diabética , Retinopatía Diabética/diagnóstico , Humanos , Algoritmos , Tamizaje Masivo/métodos , Tamizaje Masivo/normas , Femenino , Masculino , Persona de Mediana EdadRESUMEN
INTRODUCTION: Diabetic microvascular complications such as retinopathy, nephropathy, and neuropathy are primary causes of blindness, terminal renal failure, and neuropathic disorders in type 2 diabetes mellitus patients. Identifying reliable biomarkers promptly is pivotal for early detection and intervention in these severe complications. AREAS COVERED: This review offers a thorough examination of the latest research concerning serum biomarkers for the prediction and assessment of diabetic microvascular complications. It encompasses biomarkers associated with glycation, oxidative stress, inflammation, endothelial dysfunction, basement membrane thickening, angiogenesis, and thrombosis. The review also highlights the potential of emerging biomarkers, such as microRNAs and long non-coding RNAs. EXPERT OPINION: Serum biomarkers are emerging as valuable tools for the early assessment and therapeutic guidance of diabetic microvascular complications. The biomarkers identified not only reflect the underlying pathophysiology but also align with the extent of the disease. However, further validation across diverse populations and improvement of the practicality of these biomarkers in routine clinical practice are necessary. Pursuing these objectives is essential to advance early diagnosis, risk assessment, and individualized treatment regimens for those affected by diabetes.
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Biomarcadores , Diabetes Mellitus Tipo 2 , Humanos , Biomarcadores/sangre , Diabetes Mellitus Tipo 2/sangre , Diabetes Mellitus Tipo 2/complicaciones , Diabetes Mellitus Tipo 2/diagnóstico , Angiopatías Diabéticas/sangre , Angiopatías Diabéticas/diagnóstico , Angiopatías Diabéticas/etiología , Retinopatía Diabética/sangre , Retinopatía Diabética/etiología , Retinopatía Diabética/diagnóstico , Estrés Oxidativo , Pronóstico , MicroARNs/sangreRESUMEN
INTRODUCTION: The aim of the study was to examine alterations in visual acuity in patients with diabetic macular edema (DME), classified according to the TCED-HFV optical coherence tomography (OCT) system, following anti-vascular epithelial growth factor (VEGF) therapy. METHODS: The medical records of patients with DME receiving anti-VEGF therapy were retrospectively reviewed. Patients were divided into four groups according to the TCED-HFV OCT classification. Patient demographic and clinical characteristics and best-corrected visual acuity (BCVA) before and after treatment were compared among the groups. RESULTS: The BCVA before treatment was 0.49 ± 0.18, 0.81 ± 0.41, 0.83 ± 0.41, and 0.82 ± 0.49 in the early DME, advanced DME, severe DME, and atrophic maculopathy groups, respectively. The BCVA in the early DME group was therefore significantly lower than that in the other three groups (p = 0.042). After treatment, the BCVA improved to 0.15 ± 0.17, 0.52 ± 0.31, 0.62 ± 0.32, and 0.69 ± 0.47 in the early DME, advanced DME, severe DME, and atrophic maculopathy groups, respectively (p < 0.005). There were some differences among patients in the four groups in terms of the duration of diabetes, percentage of hemoglobin A1c, and duration of hypertension. CONCLUSION: The TCED-HFV OCT classification of patients with DME is exact and functional and can allow the severity of DME, and its response to anti-VEGF therapy, to be estimated.
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Inhibidores de la Angiogénesis , Retinopatía Diabética , Inyecciones Intravítreas , Edema Macular , Tomografía de Coherencia Óptica , Factor A de Crecimiento Endotelial Vascular , Agudeza Visual , Humanos , Tomografía de Coherencia Óptica/métodos , Edema Macular/tratamiento farmacológico , Edema Macular/clasificación , Edema Macular/diagnóstico , Edema Macular/etiología , Masculino , Estudios Retrospectivos , Femenino , Retinopatía Diabética/tratamiento farmacológico , Retinopatía Diabética/clasificación , Retinopatía Diabética/diagnóstico , Retinopatía Diabética/fisiopatología , Inhibidores de la Angiogénesis/uso terapéutico , Inhibidores de la Angiogénesis/administración & dosificación , Persona de Mediana Edad , Factor A de Crecimiento Endotelial Vascular/antagonistas & inhibidores , Anciano , Ranibizumab/uso terapéutico , Ranibizumab/administración & dosificación , Mácula Lútea/patología , Mácula Lútea/diagnóstico por imagen , Bevacizumab/uso terapéutico , Estudios de Seguimiento , Angiografía con Fluoresceína/métodos , Resultado del TratamientoRESUMEN
Diabetic retinopathy (DR) is one of the leading causes of vision loss in adults and is one of the detrimental side effects of the mass prevalence of Diabetes Mellitus (DM). It is crucial to have an efficient screening method for early diagnosis of DR to prevent vision loss. This paper compares and analyzes the various Machine Learning (ML) techniques, from traditional ML to advanced Deep Learning models. We compared and analyzed the efficacy of Convolutional Neural Networks (CNNs), Capsule Networks (CapsNet), K-Nearest Neighbor (KNN), Support Vector Machine (SVM), decision trees, and Random Forests. This paper also considers determining factors in the evaluation, including contrast enhancements, noise reduction, grayscaling, etc We analyze recent research studies and compare methodologies and metrics, including accuracy, precision, sensitivity, and specificity. The findings highlight the advanced performance of Deep Learning (DL) models, with CapsNet achieving a remarkable accuracy of up to 97.98% and a high precision rate, outperforming other traditional ML methods. The Contrast Limited Adaptive Histogram Equalization (CLAHE) preprocessing technique substantially enhanced the model's efficiency. Each ML method's computational requirements are also considered. While most advanced deep learning methods performed better according to the metrics, they are more computationally complex, requiring more resources and data input. We also discussed how datasets like MESSIDOR could be more straightforward and contribute to highly evaluated performance and that there is a lack of consistency regarding benchmark datasets across papers in the field. Using the DL models facilitates accurate early detection for DR screening, can potentially reduce vision loss risks, and improves accessibility and cost-efficiency of eye screening. Further research is recommended to extend our findings by building models with public datasets, experimenting with ensembles of DL and traditional ML models, and considering testing high-performing models like CapsNet.
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Aprendizaje Profundo , Retinopatía Diabética , Diagnóstico Precoz , Redes Neurales de la Computación , Retinopatía Diabética/diagnóstico , Retinopatía Diabética/diagnóstico por imagen , Humanos , Máquina de Vectores de Soporte , Aprendizaje Automático , Algoritmos , Procesamiento de Imagen Asistido por Computador/métodos , Árboles de Decisión , Interpretación de Imagen Asistida por Computador/métodosRESUMEN
Purpose: This study aimed to reveal the altered expressions of transfer RNA (tRNA)-derived small RNAs (tsRNAs) in peripheral blood mononuclear cells and identify potential diagnostic biomarkers for nonproliferative diabetic retinopathy (NPDR) from patients with type 2 diabetes mellitus. Methods: Fifty-three patients diagnosed with type 2 diabetes mellitus were enrolled, including 25 patients with NPDR and 28 patients without diabetic retinopathy (DR) as the control group. A small RNA microarray was performed to screen the differentially expressed tsRNAs. Reverse transcriptase quantitative polymerase chain reaction was used to validate the significantly altered tsRNAs in a screening cohort and a verification cohort. The target genes, their enriched functions, and signaling pathways were predicted by bioinformatics analyses. Results: In total, 668 upregulated and 485 downregulated tsRNAs were found in the NPDR group by microarray. Eight tsRNAs were validated preliminarily to be altered significantly by reverse transcriptase quantitative polymerase chain reaction, and their target genes were enriched in cellular macromolecule metabolic process and ubiquitin-mediated proteolysis. The verification experiments confirmed the increased levels of 5'tiRNA-35-PheGAA-8, tRF3-28-PheGAA-1, and tRF3b-PheGAA-6, and the decreased levels of mt-tRF3-19-ArgTCG, mt-tRF3-20-ArgTCG, and mt-tRF3-21-ArgTCG in patients with NPDR, which may serve as potential biomarkers with clinical significance. Conclusions: The study recognized the tsRNA expression changes in peripheral blood mononuclear cells from patients with NPDR and discovered potential diagnostic biomarkers that hold clinical significance. Translational Relevance: The significantly altered tsRNAs identified in the study may serve as potential diagnostic biomarkers for patients with NPDR as well as possible molecular targets of the occurrence and development of DR.
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Biomarcadores , Diabetes Mellitus Tipo 2 , Retinopatía Diabética , Leucocitos Mononucleares , ARN de Transferencia , Humanos , Diabetes Mellitus Tipo 2/genética , Diabetes Mellitus Tipo 2/diagnóstico , Diabetes Mellitus Tipo 2/sangre , Diabetes Mellitus Tipo 2/complicaciones , Diabetes Mellitus Tipo 2/metabolismo , Masculino , Femenino , Leucocitos Mononucleares/metabolismo , Persona de Mediana Edad , Retinopatía Diabética/genética , Retinopatía Diabética/diagnóstico , Retinopatía Diabética/sangre , Retinopatía Diabética/metabolismo , Biomarcadores/sangre , Biomarcadores/metabolismo , ARN de Transferencia/genética , Anciano , Reacción en Cadena de la Polimerasa de Transcriptasa Inversa , Regulación de la Expresión GénicaRESUMEN
PURPOSE: To investigate the value of proprotein-converting subtilisin kexin type 9 (PCSK9) levels in type 2 diabetes mellitus (T2D) patients with different stages of diabetic retinopathy (DR) and to compare these findings with a healthy control group without diabetes mellitus (DM). METHODS: A total of 135 patients, 100 of whom were patients with T2D and 35 of whom were in the health control group, were included in this prospective study. T2D patients were divided into three groups: the first group included 34 people with T2D without DR, the second group had 32 people with non-proliferative DR (NPDR), and the third group had 34 people with proliferative DR (PDR). Serum PCSK9 levels were analyzed and compared between the groups. RESULTS: Forty-nine percent of the participants were female, and the mean age was 64 ± 9.1 years, with no statistically significant results between the four groups in terms of age and sex. The mean serum PCSK9 value was significantly different (p = 0.01) when all groups were evaluated, and statistically significant change was observed with the progression of DR. When serum PCSK9 levels were evaluated in all T2D patients (groups 1, 2, and 3), a medium-level correlation was observed with low-density lipoprotein (p < 0.05). CONCLUSION: Serum PCSK9 values differed significantly in diabetic patients compared to the control group. One should be clinically cautious about the usefulness of circulating PCSK9 concentrations as an indicator of the risk of diabetic retinopathy.
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Biomarcadores , Diabetes Mellitus Tipo 2 , Retinopatía Diabética , Proproteína Convertasa 9 , Humanos , Retinopatía Diabética/sangre , Retinopatía Diabética/diagnóstico , Masculino , Femenino , Proproteína Convertasa 9/sangre , Persona de Mediana Edad , Estudios Prospectivos , Diabetes Mellitus Tipo 2/sangre , Diabetes Mellitus Tipo 2/complicaciones , Biomarcadores/sangre , Anciano , Progresión de la Enfermedad , Ensayo de Inmunoadsorción Enzimática , Estudios de SeguimientoRESUMEN
Purpose: To explore the long-term effect of diabetic retinopathy on response to anti-vascular endothelial growth factor (VEGF) treatment in age-related macular degeneration-associated type 1 macular neovascularization (MNV) using optical coherence tomography angiography (OCTA). Methods: A total of 45 eyes with exudative neovascular age-related macular degeneration (nAMD) with type 1 MNV were included in the analysis. Among them, 24 eyes of 24 patients had no history of diabetes mellitus (DM) in their anamnesis and were assigned to the Not Diabetic group; 21 eyes of 21 patients had mild diabetic retinopathy and were included in the Diabetic group. We considered the following outcome measures: (1) best-corrected visual acuity changes; (2) central macular thickness; (3) MNV lesion area; and (4) MNV flow area. The OCTA acquisitions were performed at the following time points: (1) baseline visit, which corresponded to the day before the first injection; (2) post-loading phase (LP), which was scheduled at 1 month after the last LP injection; and (3) 12-month follow-up visit. Results: All morphofunctional parameters showed a significant improvement after the LP and at the 12-month follow-up visit. Specifically, both the Diabetic group and the Not Diabetic group displayed a significant reduction of MNV lesion areas at both the post-LP assessment (P = 0.026 and P = 0.016, respectively) and the 12-month follow-up (P = 0.039 and P = 0.025, respectively). Similarly, the MNV flow area was significantly decreased in both the Diabetic group and the Not Diabetic group at the post-LP assessment (P < 0.001 and P = 0.012, respectively) and at the 12-month follow-up (P = 0.01 and P = 0.035, respectively) compared to baseline. A smaller reduction in the MNV lesion area was observed in the Diabetic group at both the post-LP evaluation (P = 0.015) and the 12-month follow-up (P = 0.032). No other significant differences were found between the groups for the other parameters (P > 0.05). Conclusions: Our results indicated that the Diabetic group exhibited a smaller reduction in MNV lesion area after 12 months of anti-VEGF treatment. This highlights the importance of considering diabetic retinopathy as a potential modifier of treatment outcomes in nAMD management, with DM serving as a crucial risk factor during anti-angiogenic treatment.
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Inhibidores de la Angiogénesis , Retinopatía Diabética , Angiografía con Fluoresceína , Inyecciones Intravítreas , Tomografía de Coherencia Óptica , Factor A de Crecimiento Endotelial Vascular , Agudeza Visual , Degeneración Macular Húmeda , Humanos , Retinopatía Diabética/tratamiento farmacológico , Retinopatía Diabética/diagnóstico , Retinopatía Diabética/fisiopatología , Masculino , Femenino , Inhibidores de la Angiogénesis/uso terapéutico , Factor A de Crecimiento Endotelial Vascular/antagonistas & inhibidores , Agudeza Visual/fisiología , Anciano , Degeneración Macular Húmeda/tratamiento farmacológico , Degeneración Macular Húmeda/fisiopatología , Degeneración Macular Húmeda/diagnóstico , Estudios de Seguimiento , Persona de Mediana Edad , Ranibizumab/uso terapéutico , Ranibizumab/administración & dosificación , Bevacizumab/uso terapéutico , Estudios Retrospectivos , Receptores de Factores de Crecimiento Endotelial Vascular/uso terapéutico , Resultado del Tratamiento , Fondo de Ojo , Factores de Tiempo , Proteínas Recombinantes de FusiónRESUMEN
BACKGROUND: Cardiac autonomic neuropathy (CAN) in diabetes mellitus (DM) is independently associated with cardiovascular (CV) events and CV death. Diagnosis of this complication of DM is time-consuming and not routinely performed in the clinical practice, in contrast to fundus retinal imaging which is accessible and routinely performed. Whether artificial intelligence (AI) utilizing retinal images collected through diabetic eye screening can provide an efficient diagnostic method for CAN is unknown. METHODS: This was a single center, observational study in a cohort of patients with DM as a part of the Cardiovascular Disease in Patients with Diabetes: The Silesia Diabetes-Heart Project (NCT05626413). To diagnose CAN, we used standard CV autonomic reflex tests. In this analysis we implemented AI-based deep learning techniques with non-mydriatic 5-field color fundus imaging to identify patients with CAN. Two experiments have been developed utilizing Multiple Instance Learning and primarily ResNet 18 as the backbone network. Models underwent training and validation prior to testing on an unseen image set. RESULTS: In an analysis of 2275 retinal images from 229 patients, the ResNet 18 backbone model demonstrated robust diagnostic capabilities in the binary classification of CAN, correctly identifying 93% of CAN cases and 89% of non-CAN cases within the test set. The model achieved an area under the receiver operating characteristic curve (AUCROC) of 0.87 (95% CI 0.74-0.97). For distinguishing between definite or severe stages of CAN (dsCAN), the ResNet 18 model accurately classified 78% of dsCAN cases and 93% of cases without dsCAN, with an AUCROC of 0.94 (95% CI 0.86-1.00). An alternate backbone model, ResWide 50, showed enhanced sensitivity at 89% for dsCAN, but with a marginally lower AUCROC of 0.91 (95% CI 0.73-1.00). CONCLUSIONS: AI-based algorithms utilising retinal images can differentiate with high accuracy patients with CAN. AI analysis of fundus images to detect CAN may be implemented in routine clinical practice to identify patients at the highest CV risk. TRIAL REGISTRATION: This is a part of the Silesia Diabetes-Heart Project (Clinical-Trials.gov Identifier: NCT05626413).
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Aprendizaje Profundo , Neuropatías Diabéticas , Valor Predictivo de las Pruebas , Humanos , Masculino , Femenino , Persona de Mediana Edad , Anciano , Neuropatías Diabéticas/diagnóstico , Neuropatías Diabéticas/fisiopatología , Neuropatías Diabéticas/diagnóstico por imagen , Neuropatías Diabéticas/etiología , Reproducibilidad de los Resultados , Retinopatía Diabética/diagnóstico , Retinopatía Diabética/diagnóstico por imagen , Retinopatía Diabética/epidemiología , Interpretación de Imagen Asistida por Computador , Sistema Nervioso Autónomo/fisiopatología , Sistema Nervioso Autónomo/diagnóstico por imagen , Fondo de Ojo , Cardiopatías/diagnóstico por imagen , Cardiopatías/diagnóstico , Adulto , Inteligencia ArtificialRESUMEN
BACKGROUND: To explore the functional and morphological variations of retinal vessels in diabetes with no clinically detectable retinopathy (NDR) and mild non-proliferative diabetic retinopathy (NPDR) and to establish a high-performance mild NPDR diagnostic model. METHODS: Normal subjects and type 2 diabetes patients with NDR and mild NPDR were recruited. Oxygen-saturation-related functional parameter (optical density ratio ODR) and morphological characteristics (fractal dimension Df, vessel area rate VAR, mean vascular diameter Dm, vessel tortuosity τ) of different vascular areas were extracted with single fundus photography and comprehensively analyzed among groups. An interpretable model combining marine predator algorithm (MPA) and support vector machine (SVM) based on characteristic selection was proposed for mild NPDR diagnosis. RESULTS: A total of 91 NDR subjects, 75 mild NPDR subjects, and 111 sex- and age-matched normal controls were analyzed. Increased main vessels ODR, while lower VAR of all areas except outer ring macula, lower Dm of all vessels and decreased τ of all areas were associate with NDR (e.g. main vessels ODR: OR [95%CI] 1.42[1.07-1.89], full macula τ:0.53[0.38-0.74]). Increased ODR of all areas, higher Dm of all areas except inner ring macula, increased inner ring macula τ, while decreased Df of full and inner ring macula, lower VAR of all areas were associate with mild NPDR (e.g. main vessels ODR:5.68[3.03-10.65], inner ring macula VAR: 0.48[0.33-0.69]). The MPA-SVM model with selected characteristics obtained the best diagnosis performance (AUC:0.940 ± 0.014; Accuracy:90.4 ± 3.9%; Sensitivity:89.2 ± 6.4%; Specificity:91.3 ± 6.4%). CONCLUSIONS: More significant retinal vascular variations are associate with the incidence of mild NPDR than NDR. High-precision mild NPDR diagnosis is achieved combining the morphological and functional vascular characteristics based on characteristic selection.