Automatic Screening for Ocular Anomalies Using Fundus Photographs.

SIGNIFICANCE: Screening for ocular anomalies using fundus photography is key to prevent vision impairment and blindness. With the growing and aging population, automated algorithms that can triage fundus photographs and provide instant referral decisions are relevant to scale-up screening and face the shortage of ophthalmic expertise. PURPOSE: This study aimed to develop a deep learning algorithm that detects any ocular anomaly in fundus photographs and to evaluate this algorithm for "normal versus anomalous" eye examination classification in the diabetic and general populations. METHODS: The deep learning algorithm was developed and evaluated in two populations: the diabetic and general populations. Our patient cohorts consist of 37,129 diabetic patients from the OPHDIAT diabetic retinopathy screening network in Paris, France, and 7356 general patients from the OphtaMaine private screening network, in Le Mans, France. Each data set was divided into a development subset and a test subset of more than 4000 examinations each. For ophthalmologist/algorithm comparison, a subset of 2014 examinations from the OphtaMaine test subset was labeled by a second ophthalmologist. First, the algorithm was trained on the OPHDIAT development subset. Then, it was fine-tuned on the OphtaMaine development subset. RESULTS: On the OPHDIAT test subset, the area under the receiver operating characteristic curve for normal versus anomalous classification was 0.9592. On the OphtaMaine test subset, the area under the receiver operating characteristic curve was 0.8347 before fine-tuning and 0.9108 after fine-tuning. On the ophthalmologist/algorithm comparison subset, the second ophthalmologist achieved a specificity of 0.8648 and a sensitivity of 0.6682. For the same specificity, the fine-tuned algorithm achieved a sensitivity of 0.8248. CONCLUSIONS: The proposed algorithm compares favorably with human performance for normal versus anomalous eye examination classification using fundus photography. Artificial intelligence, which previously targeted a few retinal pathologies, can be used to screen for ocular anomalies comprehensively.

Association of Sensitive Eyes with Sensitive Skin: A Worldwide Study of 10,743 Subjects.

INTRODUCTION: Sensitive eyes are commonly reported by patients, but there are very few epidemiological studies on this disorder. The aim of this study was the evaluation of the self-reported frequency of sensitive eyes and the association with sensitive skin. METHODS: A survey was performed on a representative sample of the population aged more than 18 years in five different countries (Brazil, China, France, Russia, and the USA). All participants answered a questionnaire on sociodemographic characteristics; skin phototype; eye color; tobacco consumption; exposure to sunlight, air pollution, or having pets; and sleep disorders. The presence of sensitive eyes, eyelids, or skin and their triggering factors were assessed with specific questions. RESULTS: A total of 10,743 individuals (5,285 men and 5,458 women) were included in the study. Among them, 48.2% reported having sensitive skin and 46.0% reported having sensitive eyes. Sensitive eyes were more frequently reported by women (46.5%) than men (39.4%) in all countries, with the exception of China. The presence of sensitive eyes was more frequent if skin was very sensitive. More than half of subjects with sensitive eyes declared that their triggering factors were exposure to sunlight, dust, touch pad screens, or computer screens or dry air. They were more exposed to pollution and tobacco. Their phototype (including eye color) was lighter. DISCUSSION/CONCLUSION: This large study shows that self-declared sensitive eyes are very frequent and commonly associated with sensitive skin. Triggering factors of sensitive eyes are more specific.

Femtosecond laser-assisted versus phacoemulsification cataract surgery (FEMCAT): a multicentre participant-masked randomised superiority and cost-effectiveness trial.

BACKGROUND: Cataract surgery is one of the most common operations in health care. Femtosecond laser-assisted cataract surgery (FLACS) enables more precise ocular incisions and lens fragmentation than does phacoemulsification cataract surgery (PCS). We hypothesised that FLACS might improve outcomes in cataract surgery compared with PCS despite having higher costs. METHODS: We did a participant-masked randomised superiority clinical trial comparing FLACS and PCS in two parallel groups (permuted block randomisation stratified on centres via a centralised web-based application, allocation ratio 1:1, block size of 2 or 4 for unilateral cases and 2 or 6 for bilateral cases). Five French University Hospitals enrolled consecutive patients aged 22 years or older who were eligible for unilateral or bilateral cataract surgery. Participants, outcome assessors, and technicians carrying out examinations were masked to the surgical treatment allocation until the last follow-up visit and a sham laser procedure was set up for participants randomly assigned to the PCS arm. The primary clinical endpoint was the success rate of surgery, defined as a composite of four outcomes at a 3-month postoperative visit: absence of severe perioperative complication, a best-corrected visual acuity (BCVA) of 0·0 LogMAR (logarithm of the minimum angle of resolution) or better, an absolute refractive error of 0·75 dioptres or less, and unchanged postoperative corneal astigmatism power (≤0·5 dioptres) and axis (≤20°). The primary economic endpoint was the incremental cost per additional patient who had treatment success at 3 months. Primary outcomes were assessed in all randomly assigned patients who met all eligibility criteria (missing data considered as failure). We used mixed logistic regression models or mixed linear regression models for statistical comparisons, adjusted on centres and whether cataract surgery was bilateral or unilateral. The study is registered with ClinicalTrials.gov, NCT01982006. FINDINGS: Of the 907 patients (1476 eyes) randomly assigned between Oct 9, 2013, and Oct 30, 2015, 870 (704 eyes in FLACS group and 685 eyes in the PCS group) were analysed. We identified no significant difference in the success rate of surgery between the FLACS and PCS groups (FLACS: 41·1% [289 eyes]; PCS: 43·6% [299 eyes]); adjusted odds ratio 0·85, 95% CI 0·64-1·12, p=0·250). The incremental cost-effectiveness ratio was €10 703 saved per additional patient who had treatment success with PCS compared with FLACS. We observed no severe adverse events during the femtosecond laser procedure, and most of the complications in the FLACS group related to the primary outcome measures occurred during the phacoemulsification phase or postoperatively. INTERPRETATION: Despite its advanced technology, femtosecond laser was not superior to phacoemulsification in cataract surgery and, with higher costs, did not provide an additional benefit over phacoemulsification for patients or health-care systems. FUNDING: French Ministry of Social Affairs and Health.

Intravenous high-dose methotrexate based systemic therapy in the treatment of isolated primary vitreoretinal lymphoma: An LOC network study.

The treatment of primary vitreoretinal lymphoma (PVRL) remains controversial regarding the use of local, systemic, or combined treatments. The aim of this study was to analyze the efficacy and toxicity of intravenous high-dose methotrexate (IV HD-MTX) based systemic therapy in a uniformly treated population of PVRL patients. From a nationwide French database, we retrospectively selected 59 patients (median age: 70 years, median Karnofsky Performance Status: 90%) with isolated PVRL at diagnosis who received first-line treatment with HD-MTX between 2011 and 2018. 8/59 patients also received a local treatment. No deaths or premature discontinuations of MTX due to toxicity were reported. A complete response was obtained in 40/57 patients after chemotherapy. Before treatment, IL-10 was elevated in the aqueous humor (AH) or in the vitreous in 89% of patients. After treatment, AH IL-10 was undetectable in 87% of patients with a CR/uCR/PR and detectable in 92% of patients with PD/SD. After a median follow-up of 61 months, 42/59 (71%) patients had relapsed, including 29 isolated ocular relapses as the first relapse and a total of 22 brain relapses. The median overall survival, progression-free survival, ocular-free survival and brain-free survival were 75, 18, 29 and 73 months, respectively. IV HD-MTX based systemic therapy as a first-line treatment for isolated PVRL is feasible, with acceptable toxicity, even in an elderly population. This strategy seems efficient to prevent brain relapse with prolonged overall survival. However, the ocular relapse rate remains high. New approaches are needed to improve local control of this disease, and ocular assessment could be completed by monitoring AH IL-10.

Refractive surgery.

Refractive surgery has evolved beyond laser refractive techniques over the past decade. Laser refractive surgery procedures (such as laser in-situ keratomileusis), surface ablation techniques (such as laser epithelial keratomileusis), and photorefractive keratectomy have now been established as fairly safe procedures that produce excellent visual outcomes for patients with low-to-moderate amounts of ametropia. Additionally, a broader selection of options are now available to treat a wider range of refractive errors. Small incision lenticule extraction uses a femtosecond laser to shape a refractive lenticule, which is removed through a small wound. The potential advantages of this procedure include greater tectonic strength and less dry eye. In the future, intracorneal implants could be used to treat hyperopia or presbyopia. Phakic intraocular implants and refractive lens exchange might be useful options in carefully selected patients for correcting high degrees of ametropia. Thus, physicians are now able to provide patients with the appropriate refractive corrective option based on the individual's risk-benefit profile.

Quality of life related variables measured for three multifocal diffractive intraocular lenses: a prospective randomised clinical trial.

IMPORTANCE: Quality of vision after multifocal intraocular lens (IOLs) implantation in relation to patient satisfaction. It is important to include the evaluation of visual quality and patient satisfaction in clinical practice. BACKGROUND: To evaluate and compare quality of life and patient satisfaction after implantation of three types of diffractive-refractive and apodized-diffractive bifocal and trifocal multifocal IOLs. DESIGN: Comparative, prospective, case series and randomized. PARTICIPANTS: Hundred and four eyes of 52 patients. METHODS: Three multifocal IOLs: AT LISA 809 M (Carl Zeiss Meditec) (AT LISA group, 38 eyes), AT LISAtri 839MP (Carl Zeiss Meditec) (AT LISAtri group, 32 eyes), and ReSTOR SN6AD1 (Alcon) (ReSTOR group, 34 eyes) were implanted after cataract surgery. MAIN OUTCOME MEASURES: Contrast sensitivity, photopic phenomena, patient satisfaction and quality of life criteria were evaluated. RESULTS: Patient of ≥ 88% were satisfied with near and intermediate visual outcomes. Better distance-corrected intermediate visual acuity at 90 cm was detected for AT LISA tri group (P < 0.04). No statistically significant differences were found among groups in postoperative contrast sensitivity (P ≥ 0.053). There were no significant differences in spectacle dependence scores among the groups (P ≥ 0.180). The addition of an intermediate focus did not statistically affect halo and glare size and intensity (P ≥ 0.256) or subjective impact (P ≥ 0.077). Patient satisfaction was consistently high for all groups (P ≥ 0.154). CONCLUSIONS AND RELEVANCE: Contrast sensitivity outcomes and patient satisfaction remained high in the trifocal group when compared to the bifocal IOL groups.

Sleep and mood changes in advanced age after blue-blocking (yellow) intra ocular lens (IOLs) implantation during cataract surgical treatment: a randomized controlled trial.

OBJECTIVES: Both advanced age and depression are characterized by changes in sleep patterns. Light exposure is one of the main synchronizers of circadian cycles and influences sleep by inhibiting melatonin secretion, which is mostly sensitive to light of low wavelengths (blue). Blue-blocking (yellow) intraocular lenses (IOLs) have supplanted the usual UV-blocking (clear) IOLs during cataract surgery to prevent age-related macular degeneration, however, the impact of yellow IOLs on sleep and mood is unclear. The purpose of this study was to compare the effects of yellow and clear IOLs on sleep and mood in aged patients undergoing bilateral cataract surgery. METHODS: A randomized controlled superiority study was conducted within three ophthalmic surgical wards in France. A total of 204 subjects (mean age 76.2 ± 7.5 years) were randomized into yellow or clear IOLs groups. Patients completed a sleep diary, the pictorial sleepiness scale and the Beck Depression Inventory (BDI) one week before and eight weeks after the last surgical procedure. RESULTS: According to an Intent To Treat (ITT) analysis, no significant difference was found between yellow and clear IOLs groups regarding sleep time, sleep latency, total sleep duration, quality of sleep and BDI scores. The rate of patients whose BDI score increased at the cutoff score of ≥5 after surgery was significantly higher in the yellow IOL group (n = 11, 13.1%) compared with the clear IOL group (n = 4; 4.7%); p = 0.02. CONCLUSIONS: Using yellow IOLs for cataract surgery doesn't significantly impact sleep but may induce mood changes in aging.

Clinical outcomes with a trifocal intraocular lens: a multicenter study.

PURPOSE: To evaluate the clinical results and safety obtained with a new type of multifocal intraocular lens (IOL) using a trifocal design to achieve pseudoaccommodation. METHODS: A pilot observational study of patients with a trifocal IOL (FineVision; PhysIOL, Liege, Belgium) implanted by 1 of 12 surgeons between March and December 2010. Visual outcomes that were assessed postoperatively included uncorrected and corrected distance, intermediate, and near visual acuity. RESULTS: One hundred ninety-eight eyes of 99 patients were analyzed. Patients were observed for an average of 6.44 ± 4.67 months (range: 0.2 to 17 months). Preoperative corrected distance visual acuity was 0.22 ± 0.26 logMAR. At the final follow-up visit, corrected distance visual acuity was 0.01 ± 0.10 logMAR, uncorrected distance visual acuity was 0.01 ± 0.06 logMAR, uncorrected intermediate visual acuity was 0.08 ± 0.10 logMAR, and mean uncorrected near visual acuity was 0.00 ± 0.04 logMAR. Postoperative binocular uncorrected distance visual acuity was 0.01 ± 0.07 logMAR, uncorrected intermediate visual acuity was 0.06 ± 0.08 logMAR, and uncorrected near visual acuity was -0.03 ± 0.04 logMAR. Postopeative mean residual sphere was 0.21 ± 0.48 diopters (D), with a residual cylinder of -0.24 ± 0.31 D. Postoperative spherical equivalent was 0.11 ± 0.36 D. CONCLUSIONS: The results demonstrated that the trifocal FineVision IOL is able to restore near, intermediate, and distance visual function.

Contribution of salivary gland ultrasonography to the diagnosis of Sjögren's syndrome: toward new diagnostic criteria?

OBJECTIVE: To determine the accuracy of salivary gland ultrasonography (SGUS) for diagnosing primary Sjögren's syndrome (SS) and to suggest modifications of the American-European Consensus Group (AECG) classification criteria. METHODS: We conducted a cross-sectional study in a prospective cohort of patients with suspected primary SS that was established between 2006 and 2011. The echostructure of the bilateral parotid and submandibular glands was graded from 0 to 4, and the gland size was measured; blood flow to the parotid gland was assessed using Doppler waveform analysis. The reference standard was a clinical diagnosis of primary SS as determined by a group of experts blinded to the results of SGUS. Receiver operating characteristic (ROC) curve analysis was performed to compare the diagnostic value of the 0-4-point echostructure grade for each of the 4 major salivary glands, the sum of the grades for the 4 glands, and the highest grade among the 4 glands. RESULTS: Of the 158 patients in the study, 78 had a diagnosis of primary SS according to the experts, including 61 patients (78.2%) who met the AECG criteria. Doppler waveform analysis and gland size measurement showed poor diagnostic performance. The results of ROC curve analysis showed that the highest grade among the 4 glands provided the best diagnostic value. The optimal grade cutoff was 2 (62.8% sensitivity and 95.0% specificity). A weighted score was constructed using scores for the 5 variables selected by logistic regression analysis, as follows: (salivary flow×1.5)+(Schirmer's test×1.5)+(salivary gland biopsy×3)+(SSA/SSB×4.5)+(SGUS×2). According to ROC curve analysis, a score of ≥5 of 12.5 had 85.7% sensitivity and 94.9% specificity, compared with 77.9% sensitivity and 98.7% specificity for the AECG criteria. The addition of SGUS to the AECG criteria increased sensitivity to 87.0% but did not change specificity. CONCLUSION: Modifications of the AECG criteria, including the addition of a SGUS score, notably improved diagnostic performance.

A review of deep learning-based information fusion techniques for multimodal medical image classification.

Multimodal medical imaging plays a pivotal role in clinical diagnosis and research, as it combines information from various imaging modalities to provide a more comprehensive understanding of the underlying pathology. Recently, deep learning-based multimodal fusion techniques have emerged as powerful tools for improving medical image classification. This review offers a thorough analysis of the developments in deep learning-based multimodal fusion for medical classification tasks. We explore the complementary relationships among prevalent clinical modalities and outline three main fusion schemes for multimodal classification networks: input fusion, intermediate fusion (encompassing single-level fusion, hierarchical fusion, and attention-based fusion), and output fusion. By evaluating the performance of these fusion techniques, we provide insight into the suitability of different network architectures for various multimodal fusion scenarios and application domains. Furthermore, we delve into challenges related to network architecture selection, handling incomplete multimodal data management, and the potential limitations of multimodal fusion. Finally, we spotlight the promising future of Transformer-based multimodal fusion techniques and give recommendations for future research in this rapidly evolving field.

Automated tear film break-up time measurement for dry eye diagnosis using deep learning.

In the realm of ophthalmology, precise measurement of tear film break-up time (TBUT) plays a crucial role in diagnosing dry eye disease (DED). This study aims to introduce an automated approach utilizing artificial intelligence (AI) to mitigate subjectivity and enhance the reliability of TBUT measurement. We employed a dataset of 47 slit lamp videos for development, while a test dataset of 20 slit lamp videos was used for evaluating the proposed approach. The multistep approach for TBUT estimation involves the utilization of a Dual-Task Siamese Network for classifying video frames into tear film breakup or non-breakup categories. Subsequently, a postprocessing step incorporates a Gaussian filter to smooth the instant breakup/non-breakup predictions effectively. Applying a threshold to the smoothed predictions identifies the initiation of tear film breakup. Our proposed method demonstrates on the evaluation dataset a precise breakup/non-breakup classification of video frames, achieving an Area Under the Curve of 0.870. At the video level, we observed a strong Pearson correlation coefficient (r) of 0.81 between TBUT assessments conducted using our approach and the ground truth. These findings underscore the potential of AI-based approaches in quantifying TBUT, presenting a promising avenue for advancing diagnostic methodologies in ophthalmology.

DISCOVER: 2-D multiview summarization of Optical Coherence Tomography Angiography for automatic diabetic retinopathy diagnosis.

Diabetic Retinopathy (DR), an ocular complication of diabetes, is a leading cause of blindness worldwide. Traditionally, DR is monitored using Color Fundus Photography (CFP), a widespread 2-D imaging modality. However, DR classifications based on CFP have poor predictive power, resulting in suboptimal DR management. Optical Coherence Tomography Angiography (OCTA) is a recent 3-D imaging modality offering enhanced structural and functional information (blood flow) with a wider field of view. This paper investigates automatic DR severity assessment using 3-D OCTA. A straightforward solution to this task is a 3-D neural network classifier. However, 3-D architectures have numerous parameters and typically require many training samples. A lighter solution consists in using 2-D neural network classifiers processing 2-D en-face (or frontal) projections and/or 2-D cross-sectional slices. Such an approach mimics the way ophthalmologists analyze OCTA acquisitions: (1) en-face flow maps are often used to detect avascular zones and neovascularization, and (2) cross-sectional slices are commonly analyzed to detect macular edemas, for instance. However, arbitrary data reduction or selection might result in information loss. Two complementary strategies are thus proposed to optimally summarize OCTA volumes with 2-D images: (1) a parametric en-face projection optimized through deep learning and (2) a cross-sectional slice selection process controlled through gradient-based attribution. The full summarization and DR classification pipeline is trained from end to end. The automatic 2-D summary can be displayed in a viewer or printed in a report to support the decision. We show that the proposed 2-D summarization and classification pipeline outperforms direct 3-D classification with the advantage of improved interpretability.

Sodium hyaluronate 0.30% ocular gel versus sodium hyaluronate 0.18% eye drop in the treatment of moderate to severe dry eye disease.

PURPOSE: Compare 0.30% sodium hyaluronate (0.30%HA) ocular gel with 0.18%HA eye drops in terms of improvement of ocular signs and symptoms, in patients with moderate to severe dry eye disease (DED). METHODS: This was a multicentric, randomized, investigator-masked, non-inferiority, comparative study conducted over 84 days. Three visits were scheduled, testing fluorescein corneal and conjunctival staining (Oxford and Van Bijsterveld scores), tear film break-up time (TBUT), Schirmer test, DED symptoms, 5-Item-Dry-Eye-Questionnaire (5-DEQ), patient and investigator satisfaction and frequency of instillation. RESULTS: At Day 35 (D35) and Day 84 (D84), both groups (n = 35 each) had a significant improvement in corneal staining (p < 0.001) with no inter-group difference. Van Bijsterveld score improved earlier (D35) for 0.30%HA suggesting a faster effect on conjunctival epithelium healing. There was no difference between the two concentrations in terms of TBUT or Schirmer improvements; however, the Schirmer test increase was only significant for 0.30%HA at D35 (p = 0.040). At D35 and D84, both groups showed similar improvements of DED symptoms and DEQ-5 score. Furthermore, treatment satisfaction was similar for the 2 formulations suggesting that daily use of 0.30%HA do not cause gel-related blurred vision disturbances. Frequency of instillation was similar for both groups. CONCLUSION: Our study demonstrates the non-inferiority of 0.30%HA gel compared to 0.18%HA solution in patients with moderate to severe DED. Because of its gel formulation and higher HA concentration providing prolonged comfort without causing visual disturbances, 0.30%HA gel might be adapted for bedtime use or during the day in more severe conditions.

Cost Utility and Value of Information Analysis of Femtosecond Laser-Assisted Cataract Surgery.

Importance: The efficacy and safety of femtosecond laser-assisted cataract surgery is well documented. An important requirement for decision makers is the evaluation of the cost-effectiveness of femtosecond laser-assisted cataract surgery (FLACS) over a sufficiently long horizon. Evaluating the cost-effectiveness of this treatment was a preplanned secondary objective of the Economic Evaluation of Femtosecond Laser Assisted Cataract Surgery (FEMCAT) trial. Objective: To estimate the cost utility of FLACS compared with phacoemulsification cataract surgery (PCS) on a 12-month time horizon. Design, Setting, and Participants: This multicenter randomized clinical trial compared FLACS with PCS in parallel groups. All FLACS procedures were performed using the CATALYS precision system. Participants were recruited and treated in ambulatory surgery settings in 5 university-hospital centers in France. All consecutive patients eligible for a unilateral or bilateral cataract surgery 22 years or older with written informed consent were included. Data were collected from October 2013 to October 2018, and data were analyzed from January 2020 to June 2022. Interventions: FLACS or PCS. Main Outcomes and Measures: Utility was measured through the Health Utility Index questionnaire. Costs of cataract surgery were estimated by microcosting. All inpatient and outpatient costs were collected from the French National Health Data System. Results: Of 870 randomized patients, 543 (62.4%) were female, and the mean (SD) age at surgery was 72.3 (8.6) years. A total of 440 patients were randomized to receive FLACS and 430 to receive PCS; the rate of bilateral surgery was 63.3% (551 of 870). The mean (SD) costs of cataract surgery were €1124.0 (€162.2; US $1235) for FLACS and €565.5 (€61.4; US $621) for PCS. The total mean (SD) cost of care at 12 months was €7085 (€6700; US $7787) in participants treated with FLACS and €6502 (€7323; US $7146) in participants treated with PCS. FLACS yielded a mean (SD) of 0.788 (0.009) quality-adjusted life-years (QALYs), and PCS yielded 0.792 (0.009) QALYs. The difference in mean costs was €545.9 (95% CI, -434.1 to 1525.8; US $600), and the difference in QALYs was -0.004 (95% CI, -0.028 to 0.021). The incremental cost-effectiveness ratio (ICER) was -€136 476 (US $150 000) per QALY. The cost-effectiveness probability of FLACS compared with PCS was 15.7% for a cost-effectiveness threshold of €30 000 (US $32 973) per QALY. At this threshold, the expected value of perfect information was €246 139 079 (US $270 530 231). Conclusions and Relevance: The ICER of FLACS compared with PCS was not within the $50 000 to $100 000 per QALY range frequently cited as cost-effective. Additional research and development on FLACS is needed to improve its effectiveness and lower its price. Trial Registration: ClinicalTrials.gov Identifier: NCT01982006.

Federated Learning for Diabetic Retinopathy Detection in a Multi-center Fundus Screening Network.

Federated learning (FL) is a machine learning framework that allows remote clients to collaboratively learn a global model while keeping their training data localized. It has emerged as an effective tool to solve the problem of data privacy protection. In particular, in the medical field, it is gaining relevance for achieving collaborative learning while protecting sensitive data. In this work, we demonstrate the feasibility of FL in the development of a deep learning model for screening diabetic retinopathy (DR) in fundus photographs. To this end, we conduct a simulated FL framework using nearly 700,000 fundus photographs collected from OPHDIAT, a French multi-center screening network for detecting DR. We develop two FL algorithms: 1) a cross-center FL algorithm using data distributed across the OPHDIAT centers and 2) a cross-grader FL algorithm using data distributed across the OPHDIAT graders. We explore and assess different FL strategies and compare them to a conventional learning algorithm, namely centralized learning (CL), where all the data is stored in a centralized repository. For the task of referable DR detection, our simulated FL algorithms achieved similar performance to CL, in terms of area under the ROC curve (AUC): AUC =0.9482 for CL, AUC = 0.9317 for cross-center FL and AUC = 0.9522 for cross-grader FL. Our work indicates that the FL algorithm is a viable and reliable framework that can be applied in a screening network.Clinical relevance- Given that data sharing is regarded as an essential component of modern medical research, achieving collaborative learning while protecting sensitive data is key.

Quantitative gait analysis and prediction using artificial intelligence for patients with gait disorders.

Quantitative Gait Analysis (QGA) is considered as an objective measure of gait performance. In this study, we aim at designing an artificial intelligence that can efficiently predict the progression of gait quality using kinematic data obtained from QGA. For this purpose, a gait database collected from 734 patients with gait disorders is used. As the patient walks, kinematic data is collected during the gait session. This data is processed to generate the Gait Profile Score (GPS) for each gait cycle. Tracking potential GPS variations enables detecting changes in gait quality. In this regard, our work is driven by predicting such future variations. Two approaches were considered: signal-based and image-based. The signal-based one uses raw gait cycles, while the image-based one employs a two-dimensional Fast Fourier Transform (2D FFT) representation of gait cycles. Several architectures were developed, and the obtained Area Under the Curve (AUC) was above 0.72 for both approaches. To the best of our knowledge, our study is the first to apply neural networks for gait prediction tasks.

Towards population-independent, multi-disease detection in fundus photographs.

Independent validation studies of automatic diabetic retinopathy screening systems have recently shown a drop of screening performance on external data. Beyond diabetic retinopathy, this study investigates the generalizability of deep learning (DL) algorithms for screening various ocular anomalies in fundus photographs, across heterogeneous populations and imaging protocols. The following datasets are considered: OPHDIAT (France, diabetic population), OphtaMaine (France, general population), RIADD (India, general population) and ODIR (China, general population). Two multi-disease DL algorithms were developed: a Single-Dataset (SD) network, trained on the largest dataset (OPHDIAT), and a Multiple-Dataset (MD) network, trained on multiple datasets simultaneously. To assess their generalizability, both algorithms were evaluated whenever training and test data originate from overlapping datasets or from disjoint datasets. The SD network achieved a mean per-disease area under the receiver operating characteristic curve (mAUC) of 0.9571 on OPHDIAT. However, it generalized poorly to the other three datasets (mAUC < 0.9). When all four datasets were involved in training, the MD network significantly outperformed the SD network (p = 0.0058), indicating improved generality. However, in leave-one-dataset-out experiments, performance of the MD network was significantly lower on populations unseen during training than on populations involved in training (p < 0.0001), indicating imperfect generalizability.

Hybrid Fusion of High-Resolution and Ultra-Widefield OCTA Acquisitions for the Automatic Diagnosis of Diabetic Retinopathy.

Optical coherence tomography angiography (OCTA) can deliver enhanced diagnosis for diabetic retinopathy (DR). This study evaluated a deep learning (DL) algorithm for automatic DR severity assessment using high-resolution and ultra-widefield (UWF) OCTA. Diabetic patients were examined with 6×6 mm2 high-resolution OCTA and 15×15 mm2 UWF-OCTA using PLEX®Elite 9000. A novel DL algorithm was trained for automatic DR severity inference using both OCTA acquisitions. The algorithm employed a unique hybrid fusion framework, integrating structural and flow information from both acquisitions. It was trained on data from 875 eyes of 444 patients. Tested on 53 patients (97 eyes), the algorithm achieved a good area under the receiver operating characteristic curve (AUC) for detecting DR (0.8868), moderate non-proliferative DR (0.8276), severe non-proliferative DR (0.8376), and proliferative/treated DR (0.9070). These results significantly outperformed detection with the 6×6 mm2 (AUC = 0.8462, 0.7793, 0.7889, and 0.8104, respectively) or 15×15 mm2 (AUC = 0.8251, 0.7745, 0.7967, and 0.8786, respectively) acquisitions alone. Thus, combining high-resolution and UWF-OCTA acquisitions holds the potential for improved early and late-stage DR detection, offering a foundation for enhancing DR management and a clear path for future works involving expanded datasets and integrating additional imaging modalities.

French national diagnostic and care protocol for Sjögren's disease.

Sjögren's disease (SD), also known as Sjögren's syndrome (SS) or Gougerot-Sjögren's syndrome in France, is a rare systemic autoimmune disease in its primary form and is characterised by tropism for the exocrine glandular epithelia, particularly the salivary and lacrimal glands. The lymphocytic infiltration of these epithelia will clinically translate into a dry syndrome which, associated with fatigue and pain, constitutes the symptom triad of the disease. In about one third of patients, SD is associated with systemic complications that can affect the joints, skin, lungs, kidneys, central or peripheral nervous system, and lymphoid organs with an increased risk of B-cell lymphoma. SD affects women more frequently than men (9/1). The peak frequency is around the age of 50. However, the disease can occur at any age, with paediatric forms occurring even though they remain rare. SD can occur alone or in association with other systemic autoimmune diseases. In its isolated or primary form, the prevalence of SD is estimated to be between 1 per 1000 and 1 per 10,000 inhabitants. The most recent classification criteria were developed in 2016 by EULAR and ACR. The course and prognosis of the disease are highly variable and depend on the presence of systemic involvement and the severity of the dryness of the eyes and mouth. The current approach is therefore to identify at an early stage those patients most at risk of systemic complications or lymphoma, who require close follow-up. On the other hand, regular monitoring of the ophthalmological damage and of the dental status should be ensured to reduce the consequences.

Keratoconus and the Impact of Treatment on Patients' Quality of Life: A Qualitative Study.

INTRODUCTION: Keratoconus has a significant impact on patients' quality of life (QoL), from diagnosis to the advanced stages of the disease. The aim of this research was to identify domains of QoL affected by this disease and its treatment. METHODS: Phone interviews were conducted using a semi-structured interview guide, with patients with keratoconus stratified according to their current treatment. A board of keratoconus experts helped identify the guide's main themes. RESULTS: Thirty-five patients (rigid contact lenses, n = 9; cross-linking, n = 9; corneal ring implants, n = 8; and corneal transplantation, n = 9) were interviewed by qualitative researchers. Phone interviews revealed several QoL domains affected by the disease and its treatments: "psychological", "social life", "professional life", "financial costs" and "student life". All domains were impacted, independently of the treatment history. Few differences were found between treatment regimens and keratoconus stages. Qualitative analysis enabled the development of a conceptual framework based on Wilson and Cleary's model for patient outcomes common to all patients. This conceptual model describes the relationship between patients' characteristics, their symptoms, their environment, their functional visual impairment and the impact on their QoL. CONCLUSIONS: These qualitative findings supported the generation of a questionnaire to evaluate the impact of keratoconus and its treatment on patients' QoL. Cognitive debriefings confirmed its content validity. The questionnaire is applicable for all stages of keratoconus and treatments and may help tracking change over time in regular clinical settings. Psychometric validation is yet to be performed before its use in research and clinical practices.