Hepatocellular Carcinoma: Diagnosis and Surveillance

Hepatocellular carcinoma arises commonly on the background of liver cirrhosis. Patients presenting with clinical symptoms have advanced stage and often are unsuitable for curative therapies. Diagnosis of hepatocellular carcinoma is commonly performed by multiphase computed tomography (CT) and / or magnetic resonance imaging scans (MRI). Contrast enhanced ultrasound and MRI with hepatobiliary contrast agents are better in characterizing small lesions. Tumor markers play an adjunct role in diagnosis. For HCC in cirrhotic liver biopsy is seldom required and diagnosis is based on typical imaging features of non-rim arterial phase hyperenhancement and washout on delayed phase and pseudocapsule appearance. This is due to differential blood supply of liver parenchyma, regenerative nodules and tumor. Biopsy is only required in noncirrhotic liver, vascular liver diseases, atypical imaging features. Surveillance programs involving high risk groups can help in early detection of lesions which are amenable for curative therapies. Biannual ultrasound with or without alfa fetoprotein are commonly used surveillance tests. Multidisciplinary teams provide platform for care coordination, reassessments of clinical course, and fine changes in treatment plans required for management of this complex group of patients

Effectiveness of messaging apps in emergency room-online survey study

Background: Medical professionals communicate effectively and conveniently using mobile communication applications (Apps). With clinical details being transmitted quickly among multidisciplinary teams, the potential improvements in patient care and education are significant. However, there are also moral and legal concerns with sharing patient data in this manner.  This study aimed to quantify and categorize how often medical staff members used communication apps in clinical settings, their role in patient care, their knowledge of and attitudes toward safety, and the main advantages, potential drawbacks, and policy implications. Methods: A 16-question survey with an anonymous response was distributed to our 1500 bedded hospital's medical staff. The study gathered information on the demographics of the respondents, how they used communication apps in clinical settings, how they felt about such apps, how safe they thought their data was, and why they chose one app over another. The study period was January to March 2023. Results: From students to consultants, communication apps are widely utilized with WhatsApp being the most popular one. Although all respondents thought these apps were useful for swiftly exchanging information in a clinical context, they were all concerned about the privacy consequences. Overall, 62.5% use WhatsApp in the ER, and 70.8% found that it has helped reduce the communication gap between junior and senior orthopaedic surgeons. Conclusions: Messaging apps help medical professionals communicate more effectively, but their use poses compliance difficulties, particularly with privacy laws. Hence, a user-friendly design and privacy-compliant must be given top priority when creating apps

Building trust in real-world data: lessons from INSIGHT, the UK's health data research hub for eye health and oculomics

PURPOSE OF REVIEW: In this review, we consider the challenges of creating a trusted resource for real-world data in ophthalmology, based on our experience of establishing INSIGHT, the UK's Health Data Research Hub for Eye Health and Oculomics. RECENT FINDINGS: The INSIGHT Health Data Research Hub maximizes the benefits and impact of historical, patient-level UK National Health Service (NHS) electronic health record data, including images, through making it research-ready including curation and anonymisation. It is built around a shared 'north star' of enabling research for patient benefit. INSIGHT has worked to establish patient and public trust in the concept and delivery of INSIGHT, with efficient and robust governance processes that support safe and secure access to data for researchers. By linking to systemic data, there is an opportunity for discovery of novel ophthalmic biomarkers of systemic diseases ('oculomics'). Datasets that provide a representation of the whole population are an important tool to address the increasingly recognized threat of health data poverty. SUMMARY: Enabling efficient, safe access to routinely collected clinical data is a substantial undertaking, especially when this includes imaging modalities, but provides an exceptional resource for research. Research and innovation built on inclusive real-world data is an important tool in ensuring that discoveries and technologies of the future may not only favour selected groups, but also work for all patients

AI as a Medical Device for Ophthalmic Imaging in Europe, Australia, and the United States:Protocol for a Systematic Scoping Review of Regulated Devices

BACKGROUND: Artificial intelligence as a medical device (AIaMD) has the potential to transform many aspects of ophthalmic care, such as improving accuracy and speed of diagnosis, addressing capacity issues in high-volume areas such as screening, and detecting novel biomarkers of systemic disease in the eye (oculomics). In order to ensure that such tools are safe for the target population and achieve their intended purpose, it is important that these AIaMD have adequate clinical evaluation to support any regulatory decision. Currently, the evidential requirements for regulatory approval are less clear for AIaMD compared to more established interventions such as drugs or medical devices. There is therefore value in understanding the level of evidence that underpins AIaMD currently on the market, as a step toward identifying what the best practices might be in this area. In this systematic scoping review, we will focus on AIaMD that contributes to clinical decision-making (relating to screening, diagnosis, prognosis, and treatment) in the context of ophthalmic imaging.OBJECTIVE: This study aims to identify regulator-approved AIaMD for ophthalmic imaging in Europe, Australia, and the United States; report the characteristics of these devices and their regulatory approvals; and report the available evidence underpinning these AIaMD.METHODS: The Food and Drug Administration (United States), the Australian Register of Therapeutic Goods (Australia), the Medicines and Healthcare products Regulatory Agency (United Kingdom), and the European Database on Medical Devices (European Union) regulatory databases will be searched for ophthalmic imaging AIaMD through a snowballing approach. PubMed and clinical trial registries will be systematically searched, and manufacturers will be directly contacted for studies investigating the effectiveness of eligible AIaMD. Preliminary regulatory database searches, evidence searches, screening, data extraction, and methodological quality assessment will be undertaken by 2 independent review authors and arbitrated by a third at each stage of the process.RESULTS: Preliminary searches were conducted in February 2023. Data extraction, data synthesis, and assessment of methodological quality commenced in October 2023. The review is on track to be completed and submitted for peer review by April 2024.CONCLUSIONS: This systematic review will provide greater clarity on ophthalmic imaging AIaMD that have achieved regulatory approval as well as the evidence that underpins them. This should help adopters understand the range of tools available and whether they can be safely incorporated into their clinical workflow, and it should also support developers in navigating regulatory approval more efficiently.INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/52602.</p

Concordance of randomised controlled trials for artificial intelligence interventions with the CONSORT-AI reporting guidelines

The Consolidated Standards of Reporting Trials extension for Artificial Intelligence interventions (CONSORT-AI) was published in September 2020. Since its publication, several randomised controlled trials (RCTs) of AI interventions have been published but their completeness and transparency of reporting is unknown. This systematic review assesses the completeness of reporting of AI RCTs following publication of CONSORT-AI and provides a comprehensive summary of RCTs published in recent years. 65 RCTs were identified, mostly conducted in China (37%) and USA (18%). Median concordance with CONSORT-AI reporting was 90% (IQR 77–94%), although only 10 RCTs explicitly reported its use. Several items were consistently under-reported, including algorithm version, accessibility of the AI intervention or code, and references to a study protocol. Only 3 of 52 included journals explicitly endorsed or mandated CONSORT-AI. Despite a generally high concordance amongst recent AI RCTs, some AI-specific considerations remain systematically poorly reported. Further encouragement of CONSORT-AI adoption by journals and funders may enable more complete adoption of the full CONSORT-AI guidelines

Curr Opin Ophthalmol

The application of artificial intelligence (AI) technologies in screening and diagnosing retinal diseases may play an important role in telemedicine and has potential to shape modern healthcare ecosystems, including within ophthalmology. In this article, we examine the latest publications relevant to AI in retinal disease and discuss the currently available algorithms. We summarize four key requirements underlining the successful application of AI algorithms in real-world practice: processing massive data; practicability of an AI model in ophthalmology; policy compliance and the regulatory environment; and balancing profit and cost when developing and maintaining AI models. The Vision Academy recognizes the advantages and disadvantages of AI-based technologies and gives insightful recommendations for future directions