How Cloud PACS & AI Are Redefining Echocardiogram Interpretation

Echocardiography is a crucial diagnostic tool in cardiology that involves capturing images of the heart’s structure and function using ultrasound waves. Approximately 7.1 million echocardiograms are performed annually¹ in the United States alone, and 20% of Medicare members receive at least one echocardiogram each year. With scans taking up to an hour, physicians compiling echocardiogram images may take anywhere from one to two weeks to analyze these images and present results to their patients.

Cloud-PACS (Picture Archiving, and Communication System) technology are rapidly changing how physicians and medical professionals access and analyze diagnostic medical images for patients. With Cloud PACS, physicians now can view patient images in near-real time, compare these images to previous scans, and collaborate with other physicians has enabled medical professionals and patients to unlock a new standard of healthcare. In addition to increased access to echocardiogram images, the integration of AI (Artificial Intelligence)² can significantly enhances the efficiency, accuracy, and speed in interpreting these echocardiogram images, improving early disease detection and delivering better outcomes for cardiology patients.

Efficiency and Speed Redefined

One of the primary benefits of AI in echocardiogram interpretation lies in its ability to expedite the analysis process. Traditional manual interpretation can be time-consuming, especially in complex cases, often leading to patient diagnosis and treatment delays. AI models, equipped with advanced image recognition and pattern analysis, can rapidly analyze vast comparative datasets within seconds, reducing the time from diagnosis and treatment. AI-based image processing combined with cloud-based PACS provides a seamless workflow, enabling cardiologists and sonographers access to images and detailed reports from any location, spend less time manually reviewing imaging data, and focus more on patient diagnosis and treatment.

Accuracy and Precision Amplified

AI-driven algorithms have demonstrated remarkable accuracy in identifying subtle abnormalities in echocardiogram images. With the incorporation of machine learning models, these tools can continuously improve their accuracy by learning from a vast array of standard and complex imaging data. AI tools excel in recognizing intricate cardiac structures, such as ejection fraction, aortic diameters, and myocardial abnormalities. A recently published paper, Artificial Intelligence in Cardiovascular Imaging, noted that due to AI’s increased capacity to consume large data sets, the technology is on the path to reducing or eliminating human error that could impact patient diagnosis and care. In addition to the immediate benefit of patient diagnosis and analysis presently, the paper also alludes to the future benefits of using AI for cardiac imaging. It is well known that cardiovascular disease continues to be the most common cause of death globally, and with AI’s ability to combine imaging data, clinical information from electronic health records and mobile health devices, and clinical study results into detailed reporting has the potential to exponentially advance cardiovascular imaging and treatment.

Sonographer Development and Support

The integration of AI into echocardiogram interpretation is an asset, particularly for newly qualified sonographers or those undergoing training, and it helps accelerate the learning curve in cardiac imaging.

“The role of sonographers within the echo lab is absolutely fundamental; they are the ones capturing and measuring the very images cardiologists rely on to make their interpretations,” states Dr. Gabriel Shaya, MD, MPH, a leading cardiologist in the field of AI integration practices. “The ripple effects of their work are significant, and here is where artificial intelligence can offer substantial support.”

One of the many issues sonographers face today is staffing and training. In the United States alone, there are around 65,000 sonographers, which may seem like a healthy number of professionals, but with the aging general population and many tenured sonographers retiring, there is an increasing gap in the market. It is widely believed that AI might be an incredible tool for accuracy and in training the next generation of sonographers by helping them interpret images more accurately and with fewer workflow constraints.

“We must acknowledge that the quality of the images is paramount; without high-quality images, accurate measurements and interpretations are unattainable. There’s a fundamental limit to what can be achieved with poor-quality images”, says Dr. Shaya. “Echocardiography is inherently an operator-dependent modality, distinct from CT scans or MRIs. Therefore, developing sonography skills in a manner that adheres to guidelines is not just beneficial, it is critical for the integrity of our practice.”

The ability of AI to continuously learn from deep and diverse datasets means that sonographers entering the medical field can benefit from a wealth of collective knowledge, refining their skills and enhancing their ability to interpret critical cardio images.

The era of AI in echocardiogram image interpretation³ presents a new standard in delivering cardiac care. With its potential to enhance efficiency, accuracy, and speed, AI is poised to become an indispensable ally for cardiologists, sonographers, and newly qualified cardiac clinicians. However, a cautious approach is essential as healthcare providers consider integrating AI tools into echocardiogram interpretation. Despite the remarkable capabilities of these algorithms, experienced clinical oversight remains crucial. Cardiologists and sonographers should maintain an active role in validating AI-generated findings, cross-referencing them with their clinical expertise to ensure the highest standards of accuracy.

In conclusion, the partnering of Cloud PACS and AI-generated echocardiogram image interpretation marks a transformative step forward in delivering cardiovascular care and treatment. The synergistic combination of cloud-based platforms and artificial intelligence promises to redefine the standards of efficiency, accuracy, and speed in the intricate realm of cardiac imaging, ultimately benefiting both healthcare providers and their patients.

UltraLinQ, a leading Cloud PACS provider, and iCardio.ai, a company that develops machine learning and deep learning algorithms for analyzing ultrasound applications, have recently joined forces to provide a ground-breaking service to healthcare providers.

iCardio.ai’s mission to support ultrasound imaging businesses with AI technology has been the cornerstone of their business foundation for over six years. iCardio.ai’s technology provides feedback and image quality scores for each viewport within the image. This level of detail and AI-powered analysis automate essential echo measurements, including LVEF, and just received breakthrough designation for Aortic Stenosis Detection within a single study.

For more information, visit:
https://ultralinq.com/medical-pacs-image-viewer/#cardiology

References

1 Nolan MT, Thavendiranathan P. Automated quantification in echocardiography. JACC Cardiovasc Imaging. (2019)
2 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10308270/
3 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9053659/

Stepping into the cardiac monitoring technology market, UltraLinQ introduces a Holter service that symbolizes a leap in innovation and practicality aimed at optimizing cardiac health management. With this addition to an already comprehensive cardiology suite, UltraLinQ prioritizes the industry’s needs by delivering significant advantages to clinicians and patients. It also accelerates its steadfast mission to lead advancements in heart health for the broader healthcare community.