RobOCTNet: Robotics and Deep Learning for Referable Posterior Segment Pathology Detection in an Emergency Department Population.

Purpose: To evaluate the diagnostic performance of a robotically aligned optical coherence tomography (RAOCT) system coupled with a deep learning model in detecting referable posterior segment pathology in OCT images of emergency department patients. Methods: A deep learning model, RobOCTNet, was trained and internally tested to classify OCT images as referable versus non-referable for ophthalmology consultation. For external testing, emergency department patients with signs or symptoms warranting evaluation of the posterior segment were imaged with RAOCT. RobOCTNet was used to classify the images. Model performance was evaluated against a reference standard based on clinical diagnosis and retina specialist OCT review. Results: We included 90,250 OCT images for training and 1489 images for internal testing. RobOCTNet achieved an area under the curve (AUC) of 1.00 (95% confidence interval [CI], 0.99-1.00) for detection of referable posterior segment pathology in the internal test set. For external testing, RAOCT was used to image 72 eyes of 38 emergency department patients. In this set, RobOCTNet had an AUC of 0.91 (95% CI, 0.82-0.97), a sensitivity of 95% (95% CI, 87%-100%), and a specificity of 76% (95% CI, 62%-91%). The model's performance was comparable to two human experts' performance. Conclusions: A robotically aligned OCT coupled with a deep learning model demonstrated high diagnostic performance in detecting referable posterior segment pathology in a cohort of emergency department patients. Translational Relevance: Robotically aligned OCT coupled with a deep learning model may have the potential to improve emergency department patient triage for ophthalmology referral.

Contactless, autonomous robotic alignment of optical coherence tomography for in vivo evaluation of diseased retinas.

During the COVID-19 pandemic, an emphasis was placed on contactless, physical distancing and improved telehealth; contrariwise, standard-of-care ophthalmic imaging of patients required present, trained personnel. Here, we introduce contactless, autonomous robotic alignment of optical coherence tomography (RAOCT) for in vivo imaging of retinal disease and compare measured retinal thickness and diagnostic readability to technician operated clinical OCT. In a powered study, we found no statistically significant difference in retinal thickness in both healthy and diseased retinas (p > 0.7) or across a variety of demographics (gender, race, and age) between RAOCT and clinical OCT. In a secondary study, a retina specialist labeled a given volume as normal/abnormal. Compared to the clinical diagnostic label, sensitivity/specificity for RAOCT were equal or improved over clinical OCT. Contactless, autonomous RAOCT, that improves upon current clinical OCT, could play a role in both ophthalmic care and non-ophthalmic settings that would benefit from improved eye care.

Robotic Optical Coherence Tomography Retinal Imaging for Emergency Department Patients: A Pilot Study for Emergency Physicians' Diagnostic Performance.

STUDY OBJECTIVE: To evaluate the diagnostic performance of emergency physicians' interpretation of robotically acquired retinal optical coherence tomography images for detecting posterior eye abnormalities in patients seen in the emergency department (ED). METHODS: Adult patients presenting to Duke University Hospital emergency department from November 2020 through October 2021 with acute visual changes, headache, or focal neurologic deficit(s) who received an ophthalmology consultation were enrolled in this pilot study. Emergency physicians provided standard clinical care, including direct ophthalmoscopy, at their discretion. Retinal optical coherence tomography images of these patients were obtained with a robotic, semi-autonomous optical coherence tomography system. We compared the detection of abnormalities in optical coherence tomography images by emergency physicians with a reference standard, a combination of ophthalmology consultation diagnosis and retina specialist optical coherence tomography review. RESULTS: Nine emergency physicians reviewed the optical coherence tomography images of 72 eyes from 38 patients. Based on the reference standard, 33 (46%) eyes were normal, 16 (22%) had at least 1 urgent/emergency abnormality, and the remaining 23 (32%) had at least 1 nonurgent abnormality. Emergency physicians' optical coherence tomography interpretation had 69% (95% confidence interval [CI], 49% to 89%) sensitivity for any abnormality, 100% (95% CI, 79% to 100%) sensitivity for urgent/emergency abnormalities, 48% (95% CI, 28% to 68%) sensitivity for nonurgent abnormalities, and 64% (95% CI, 44% to 84%) overall specificity. In contrast, emergency physicians providing standard clinical care did not detect any abnormality with direct ophthalmoscopy. CONCLUSION: Robotic, semi-autonomous optical coherence tomography enabled ocular imaging of emergency department patients with a broad range of posterior eye abnormalities. In addition, emergency provider optical coherence tomography interpretation was more sensitive than direct ophthalmoscopy for any abnormalities, urgent/emergency abnormalities, and nonurgent abnormalities in this pilot study with a small sample of patients and emergency physicians.

Practice Patterns of Fundoscopic Examination for Diabetic Retinopathy Screening in Primary Care.

Importance: Primary care professionals (PCPs) have a central role in screening for diabetic retinopathy (DR), especially in settings where access to specialty eye care is limited. Data on current DR screening practice patterns in primary care are needed to inform screening strategies. Objectives: To assess the practice patterns of fundoscopic examination for DR screening in a large primary care network and to evaluate the sensitivity and accuracy of PCP fundoscopy for detecting DR. Design, Setting, and Participants: A retrospective cohort study was performed using random sampling and manual review of electronic health records of PCP fundoscopic examination documentation compared with documentation of an examination performed by an eye care professional (ophthalmologist or optometrist) within 2 years before or after primary care encounters. From a single-institution primary care network of 28 clinics, 7449 adult patients with diabetes seen at least once in the primary care network in 2019 were eligible for this study. Data from 2001 encounters were abstracted from the electronic health record for a random sample of 767 patients. Data analysis was performed from January 2021 to May 2022. Exposure: Fundoscopic examination by PCPs. Main Outcomes and Measures: The frequency of PCPs performing fundoscopy at least once in the calendar year for patients with diabetes. Univariate and multivariable logistic regression analyses were performed to identify patient, clinician, and clinic factors associated with PCPs performing fundoscopy at least once in the calendar year. The PCP examination results were compared with diagnoses made by eye care professionals to assess the sensitivity and accuracy of the findings from PCP examinations. Results: Among the 767 adult patients with diabetes included in the analysis, 387 (50.5%) were female, and the median age was 64 years (IQR, 54-71 years). Primary care professionals documented a fundoscopic examination for 93 patients (12.1%); all results were documented as normal. When eye care professional examination results were used as the reference standard, the accuracy of PCP fundoscopic examination was 62.7% (95% CI, 50.0%-73.9%) and sensitivity for detecting disease was 0.0% (95% CI, 0.0%-14.9%). No patient demographic or clinical characteristics were associated with PCPs performing fundoscopy. In multivariable logistic regression, the number of PCP years in practice was associated with greater odds of patients receiving fundoscopy at least once in the year (adjusted odds ratio per 10 years in practice, 1.26; 95% CI, 1.01-1.59; P = .04); having nurse practitioner credentials was associated with lower odds of receiving fundoscopy (adjusted odds ratio, 0.23; 95% CI, 0.04-0.79; P = .049; compared with having physician credentials); after adjusting for rural clinic location, clinic location in a primary care shortage area, and documentation of an up-to-date eye care professional examination by a PCP in the study year. Conclusions and Relevance: In this cohort study, fundoscopic examination was rarely performed and was not sensitive for detecting DR in primary care practice. Because the rate of DR screening by eye care professionals remains low, research to explore and break down barriers to the implementation of effective primary care-based DR screening strategies, such as teleretinal imaging, is needed to prevent vision loss from undiagnosed DR.

Phosphoprotein phosphatase 1CB (PPP1CB), a novel adipogenic activator, promotes 3T3-L1 adipogenesis.

Understanding the molecular networks that regulate adipogenesis is crucial for gaining insight into obesity and identifying medicinal targets thereof is necessary for pharmacological interventions. However, the identity and molecular actions of activators that promote the early development of adipocytes are still largely unknown. Here, we demonstrate a novel role for phosphoprotein phosphatase 1CB (PPP1CB) as a potent adipogenic activator that promotes adipocyte differentiation. PPP1CB expression increased in vitro during the early phase of 3T3-L1 adipogenesis and in the murine model of high-fat diet-induced obesity. Depletion of PPP1CB dramatically suppressed the differentiation of 3T3-L1 cells into mature adipocytes, with a concomitant change in adipocyte marker genes and significantly inhibited clonal expansion. We also showed that knockdown of PPP1CB caused a significant decrease in C/EBPδ expression, which in turn resulted in attenuation of PPARγ, C/EBPα, adiponectin, and aP2. In addition, we elucidated the functional significance of PPP1CB by linking p38 activation to C/EBPδ expression in early adipogenesis. Overall, our findings demonstrate a novel function of PPP1CB in promoting adipogenesis and suggest that PPP1CB may be a promising therapeutic target for treatment of obesity and obesity-related diseases.