By Dr. Minnu Ittiachen Kinattingal

POCUS AI is a rapidly evolving field in healthcare. It can enhance quality assurance, automate image acquisition, interpretation, and increase the efficiency of novice clinicians in obtaining high-quality images. The time it takes to diagnose cardiac diseases can be shortened by the recent significant advancements in cardiology.

In August of 2024, AISAP announced that its AI-powered point-of-care ultrasound software, AISAP CARDIO, had received 510(k) clearance from the FDA.

In early 2022, a team from Israel’s elite 8200 intelligence unit, led by CEO Adiel Am-Shalom and Moshe Shami, partnered with senior physicians from Sheba Medical Center to start AISAP. The team included Prof. Ehud Raanani, Prof. Robert Klempner, Prof. Elad Maor, and Prof. Ehud Schwammenthal.

This advanced AI-powered software integrates with portable ultrasound devices, enabling physicians to perform fast diagnostics directly at the patient’s bedside. The name “AISAP” combines “AI” with “as soon as possible”, reflecting their mission for rapid, efficient healthcare solutions. This cloud-based platform integrates four computer-assisted diagnosis modules for valvular pathologies and eight essential cardiac measurements, allowing clinicians to accurately diagnose up to 90% of common cardiac structural and functional parameters at the bedside within minutes.

Dr. Smadar Kort, a prominent figure in non-invasive cardiac imaging, highlighted the potential impact of AISAP CARDIO in diagnosing structural heart disease and heart failure, which are major causes of hospitalization in the US. Early and accurate diagnosis could lead to better patient outcomes and cost savings.

The software assesses key cardiac parameters, including various valvular pathologies and measurements such as left ventricle ejection fraction and ventricular dimensions. Designed for seamless integration into clinical workflows and existing electronic health record systems, AISAP CARDIO provides quick and reliable assessments, enhancing decision-making for emergency medicine, critical care, and primary care physicians.

The platform, developed by experts in technology and cardiology, aims to improve patient care by making advanced diagnostic tools more accessible. It has been validated through extensive clinical trials at renowned institutions, showing that it enables non-cardiologists to interpret echocardiograms as accurately as expert cardiologists. Data from studies indicated that the AISAP CARDIO device demonstrated a 93% sensitivity and specificity for significant major valve diseases. It has the potential to change care pathways for a significant portion of patients scanned.

The CARDIO platform offers several key features and benefits:

• Comprehensive Cardiac Assessment: It provides accurate evaluations of cardiac conditions, including valvular pathology, left ventricle ejection fraction (LVEF), ventricular dimensions, and more.
• Enhanced Clinician Performance: Studies show CARDIO improves clinician accuracy in interpreting point-of-care echocardiograms.
• Scalability and Integration: As a vendor-agnostic solution, CARDIO integrates smoothly with existing EHR/EMR and PACS systems, making it adaptable to various healthcare environments.
• Improved Patient Care: By delivering timely and precise diagnoses, CARDIO helps clinicians make informed decisions, enhancing patient outcomes.

Generally speaking, AI algorithms are trained using data generated by digital health technologies, which has had a big impact on cardiovascular healthcare. These AI systems may, however, be biased if the training data is uniform or if healthcare procedures are unfair. Inaccurate risk assessments, misclassified diseases, missed diagnoses, and inappropriate treatment recommendations are just a few of the detrimental effects that can arise from bias in the creation, testing, and application of AI algorithms. Frequently, marginalized groups are disproportionately impacted by this bias.

We need to discuss the real-world harms caused by biased algorithms, identify stages where bias can be introduced, and apply AI to cardiovascular care. Equality of benefits for all people at risk of or suffering from cardiovascular disease is ensured by improved methods to lessen bias during AI training, testing, and deployment.

According to my standpoint, AI can produce results that are error-proof and prevent even the smallest risk to the entire population by using a large database to test the algorithms. The limitations of current POCUS AI systems include limited generalizability, insufficient datasets, regional disparities in research, patient noncompliance, ethical issues in remote settings, and a lack of standardized protocols, algorithms, and devices. Despite these challenges, POCUS AI has shown promise in overcoming barriers like scarce resources and a lack of trained personnel in low-resource settings.

Future research should focus on developing cost-effective, resource-efficient AI applications that address these gaps without compromising performance. Additionally, making POCUS AI systems more user-friendly could empower inexperienced users in low-resource settings to perform high-quality point-of-care ultrasound examinations.

It is a great advancement for the healthcare system, diagnosing diseases early and treating the patient with the best available treatment option. To stay up to date and to get the queries cleared at the earliest, the Global Ultrasound Institute (GUSI) has launched Sage AI, an advanced AI tool designed to answer open-ended ultrasound-related questions. Integrated into GUSI’s scan Hub training platform, Sage AI aims to support healthcare practitioners in mastering point-of-care ultrasound (POCUS) across various medical specialties. The tool provides fully referenced answers, is enriched with ultrasound images and video clips from GUSI’s pathology library, and can deliver responses in over 80 languages.

Medical science and technology are advancing rapidly. As a physician, I will judiciously employ proven cutting-edge medical technology to provide the best patient care. This approach will ensure that I leverage advanced tools and techniques while maintaining a focus on evidence-based practice and cost-effectiveness. By carefully selecting and applying the most appropriate technological solutions, I aim to enhance diagnostic accuracy, treatment efficacy, and overall patient satisfaction and outcomes.

References

1. https://pmc.ncbi.nlm.nih.gov/articles/PMC11312308
2. https://www.businesswire.com/news/home/20240822701346/en/AISAP%E2%80%99s-CARDIO-AI-powered-Point-of-Care-Ultrasound-Diagnostic-Assessment-Software-Receives-FDA-Clearance
3. https://www.auntminnie.com/clinical-news/ultrasound/article/15684092/gusi-introduces-sage-ai-tool-for-ultrasound-learners
4. https://hitconsultant.net/2024/08/22/aisaps-ai-powered-cardiac-ultrasound-receives-fda-clearance
5. https://www.thelancet.com/journals/landig/article/PIIS2589-7500%2824%2900155-9/fulltext
6. https://www.haaretz.com/haaretz-labels/2024-10-09/ty-article-labels/striving-to-empower-physicians-as-super-physicians/00000192-7058-d4e7-adb2-f1ff99890000