Quantification of Fundus Autofluorescence Features in a Molecularly Characterized Cohort of More Than 3000 Inherited Retinal Disease Patients from the United Kingdom.

Purpose: To quantify relevant fundus autofluorescence (FAF) image features cross-sectionally and longitudinally in a large cohort of inherited retinal diseases (IRDs) patients. Design: Retrospective study of imaging data (55-degree blue-FAF on Heidelberg Spectralis) from patients. Participants: Patients with a clinical and molecularly confirmed diagnosis of IRD who have undergone FAF 55-degree imaging at Moorfields Eye Hospital (MEH) and the Royal Liverpool Hospital (RLH) between 2004 and 2019. Methods: Five FAF features of interest were defined: vessels, optic disc, perimacular ring of increased signal (ring), relative hypo-autofluorescence (hypo-AF) and hyper-autofluorescence (hyper-AF). Features were manually annotated by six graders in a subset of patients based on a defined grading protocol to produce segmentation masks to train an AI model, AIRDetect, which was then applied to the entire imaging dataset. Main Outcome Measures: Quantitative FAF imaging features including area in mm 2 and vessel metrics, were analysed cross-sectionally by gene and age, and longitudinally to determine rate of progression. AIRDetect feature segmentation and detection were validated with Dice score and precision/recall, respectively. Results: A total of 45,749 FAF images from 3,606 IRD patients from MEH covering 170 genes were automatically segmented using AIRDetect. Model-grader Dice scores for disc, hypo-AF, hyper-AF, ring and vessels were respectively 0.86, 0.72, 0.69, 0.68 and 0.65. The five genes with the largest hypo-AF areas were CHM , ABCC6 , ABCA4 , RDH12 , and RPE65 , with mean per-patient areas of 41.5, 30.0, 21.9, 21.4, and 15.1 mm 2 . The five genes with the largest hyper-AF areas were BEST1 , CDH23 , RDH12 , MYO7A , and NR2E3 , with mean areas of 0.49, 0.45, 0.44, 0.39, and 0.34 mm 2 respectively. The five genes with largest ring areas were CDH23 , NR2E3 , CRX , EYS and MYO7A, with mean areas of 3.63, 3.32, 2.84, 2.39, and 2.16 mm 2 . Vessel density was found to be highest in EFEMP1 , BEST1 , TIMP3 , RS1 , and PRPH2 (10.6%, 10.3%, 9.8%, 9.7%, 8.9%) and was lower in Retinitis Pigmentosa (RP) and Leber Congenital Amaurosis genes. Longitudinal analysis of decreasing ring area in four RP genes ( RPGR, USH2A, RHO, EYS ) found EYS to be the fastest progressor at -0.18 mm 2 /year. Conclusions: We have conducted the first large-scale cross-sectional and longitudinal quantitative analysis of FAF features across a diverse range of IRDs using a novel AI approach.

Support Provided by Stop-Smoking Practitioners to Co-users of Tobacco and Cannabis: A Qualitative Study.

INTRODUCTION: Co-use of tobacco and cannabis is highly prevalent among cannabis users and is associated with poorer tobacco cessation outcomes. This study explored the barriers and enablers influencing stop-smoking practitioners' ability to provide optimal support to co-users. AIMS AND METHODS: Online semi-structured interviews were audio recorded. Interviewees (n = 20) were UK-based certified stop-smoking practitioners. An interview schedule informed by the "capability", "opportunity", "motivation" (COM-B) model was designed to explore participants' perceived barriers and enablers in better supporting co-users to achieve abstinence of both substances or tobacco harm reduction. The transcripts were analyzed using framework analysis. RESULTS: Capability: Practitioners' lack of knowledge and skills undermines their delivery of smoking cessation interventions to co-users. Interestingly, when cannabis is used for medicinal reasons, practitioners feel unable to provide adequate support. Opportunity: Service recording systems play an important role in screening for co-use and supporting co-users. When responding to clients' specific needs and practitioners' uncertainties, a positive therapeutic relationship and a support network of peers and other healthcare professionals are needed. Motivation: supporting co-users is generally perceived as part of practitioners' roles but there are concerns that co-users are less likely to successfully stop smoking. CONCLUSIONS: Practitioners are willing to support co-users, but their lack of knowledge and access to an appropriate recording system are barriers to doing so. Having a supportive team and a positive therapeutic relationship is perceived as important. Identified barriers can be mostly addressed with further training to improve tobacco cessation outcomes for co-users.

Usability of an artificially intelligence-powered triage platform for adult ophthalmic emergencies: a mixed methods study.

There is growing demand for emergency-based eyecare services where the majority of those attending do not require urgent ophthalmic management. The Royal College of Ophthalmologists have recommended upskilling and supporting of allied health professionals to support eyecare delivery, where machine learning algorithms could help. A mixed methods study was conducted to evaluate the usability of an artificial intelligence (AI) powered online triage platform for ophthalmology. The interface, usability, safety and acceptability were investigated using a Think Aloud interview and usability questionnaires. Twenty participants who actively examine patients in ophthalmic triage within a tertiary eye centre or primary care setting completed the interview and questionnaires. 90% or more of participants found the platform easy to use, reflected their triage process and were able to interpret the triage outcome, 85% found it safe to use and 95% felt the processing time was fast. A quarter of clinicians reported that they have experienced some uncertainty when triaging in their career and were unsure of using AI, after this study 95% of clinicians were willing to use the platform in their clinical workflow. This study showed the platform interface was acceptable and usable for clinicians actively working in ophthalmic emergency triage.

Can artificial intelligence accelerate the diagnosis of inherited retinal diseases? Protocol for a data-only retrospective cohort study (Eye2Gene).

INTRODUCTION: Inherited retinal diseases (IRD) are a leading cause of visual impairment and blindness in the working age population. Mutations in over 300 genes have been found to be associated with IRDs and identifying the affected gene in patients by molecular genetic testing is the first step towards effective care and patient management. However, genetic diagnosis is currently slow, expensive and not widely accessible. The aim of the current project is to address the evidence gap in IRD diagnosis with an AI algorithm, Eye2Gene, to accelerate and democratise the IRD diagnosis service. METHODS AND ANALYSIS: The data-only retrospective cohort study involves a target sample size of 10 000 participants, which has been derived based on the number of participants with IRD at three leading UK eye hospitals: Moorfields Eye Hospital (MEH), Oxford University Hospital (OUH) and Liverpool University Hospital (LUH), as well as a Japanese hospital, the Tokyo Medical Centre (TMC). Eye2Gene aims to predict causative genes from retinal images of patients with a diagnosis of IRD. For this purpose, 36 most common causative IRD genes have been selected to develop a training dataset for the software to have enough examples for training and validation for detection of each gene. The Eye2Gene algorithm is composed of multiple deep convolutional neural networks, which will be trained on MEH IRD datasets, and externally validated on OUH, LUH and TMC. ETHICS AND DISSEMINATION: This research was approved by the IRB and the UK Health Research Authority (Research Ethics Committee reference 22/WA/0049) 'Eye2Gene: accelerating the diagnosis of IRDs' Integrated Research Application System (IRAS) project ID: 242050. All research adhered to the tenets of the Declaration of Helsinki. Findings will be reported in an open-access format.

Collaborative Research and Development of a Novel, Patient-Centered Digital Platform (MyEyeSite) for Rare Inherited Retinal Disease Data: Acceptability and Feasibility Study.

BACKGROUND: Inherited retinal diseases (IRDs) are a leading cause of blindness in children and working age adults in the United Kingdom and other countries, with an appreciable socioeconomic impact. However, by definition, IRD data are individually rare, and as a result, this patient group has been underserved by research. Researchers need larger amounts of these rare data to make progress in this field, for example, through the development of gene therapies. The challenge has been how to find and make these data available to researchers in the most productive way. MyEyeSite is a research collaboration aiming to design and develop a digital platform (the MyEyeSite platform) for people with rare IRDs that will enable patients, doctors, and researchers to aggregate and share specialist eye health data. A crucial component of this platform is the MyEyeSite patient application, which will provide the means for patients with IRD to interact with the system and, in particular, to collate, manage, and share their personal specialist IRD data both for research and their own health care. OBJECTIVE: This study aims to test the acceptability and feasibility of the MyEyeSite platform in the target IRD population through a collaborative patient-centered study. METHODS: Qualitative data were generated through focus groups and workshops, and quantitative data were obtained through a survey of patients with IRD. Participants were recruited through clinics at Moorfields Eye Hospital National Health Service (NHS) Foundation Trust and the National Institute for Health Research (NIHR) Moorfields Biomedical Research Centre through their patient and public involvement databases. RESULTS: Our IRD focus group sample (n=50) highlighted the following themes: frustration with the current system regarding data sharing within the United Kingdom's NHS; positive expectations of the potential benefits of the MyEyeSite patient application, resulting from increased access to this specialized data; and concerns regarding data security, including potentially unethical use of the data outside the NHS. Of the surveyed 80 participants, 68 (85%) were motivated to have a more active role in their eye care and share their data for research purposes using a secure technology, such as a web application or mobile app. CONCLUSIONS: This study demonstrates that patients with IRD are highly motivated to be actively involved in managing their own data for research and their own eye care. It demonstrates the feasibility of involving patients with IRD in the detailed design of the MyEyeSite platform exemplar, with input from the patient with IRD workshops playing a key role in determining both the functionality and accessibility of the designs and prototypes. The development of a user-centered technological solution to the problem of rare health data has the potential to benefit not only the patient with IRD community but also others with rare diseases.

Phenogenon: Gene to phenotype associations for rare genetic diseases.

As high-throughput sequencing is increasingly applied to the molecular diagnosis of rare Mendelian disorders, a large number of patients with diverse phenotypes have their genetic and phenotypic data pooled together to uncover new gene-phenotype relations. We introduce Phenogenon, a statistical tool that combines, Human Phenotype Ontology (HPO) annotated patient phenotypes, gnomAD allele population frequency, and Combined Annotation Dependent Depletion (CADD) score for variant pathogenicity, in order to jointly predict the mode of inheritance and gene-phenotype associations. We ran Phenogenon on our cohort of 3,290 patients who had undergone whole exome sequencing. Among the top associations, we recapitulated previously known, such as "SRD5A3-Abnormal full-field electroretinogram-recessive" and "GRHL2 -Nail dystrophy-recessive", and discovered one potentially novel, "RRAGA-Abnormality of the skin-dominant". We also developed an interactive web interface available at https://phenogenon.phenopolis.org to visualise and explore the results.

Healthy eating beliefs and intentions of mothers and their adult children: An intergenerational transmission perspective.

This study examined the possible intergenerational transmission of eating beliefs and intentions between 60 mothers and their adult children. Maternal restrictive feeding practices were correlated with mothers' own healthy eating attitudes and subjective norms, and with their adult children's subjective norms. Mothers' beliefs and intentions were correlated with their adult children. Adult children's intentions to eat healthily were predicted by their attitudes and perceived behavioural control, and also by their mothers' intentions and perceived behavioural control. Mothers' own beliefs and intentions may be involved in shaping their children's beliefs and intentions into adulthood but their child feeding practices may have less of an influence.