1. Much of the early conversation about AI in cardiac imaging focused on producing sharper images. Where do you see AI’s role going from here?
Sharper images still matter, but the bigger shift is in what clinicians can do with them. AI-based imaging is helping cardiology practices move away from identifying isolated blockages and toward a more comprehensive, AI-assisted view of heart health. AI can also automate some of the more complex measurements in cardiac imaging, helping clinicians assess scans more consistently across practices.
The goal isn’t to take clinical judgement out of the equation, but to give physicians better tools and more information to work with. I think of AI as a sidekick: it standardizes expert-level precision and handles more of the analytical work, allowing the physician to focus on interpreting results and deciding what to do next. That combination is what allows advanced diagnostics to move closer to the patient and turns local clinics into capable cardiovascular hubs.
2. Cardiac CT has traditionally answered a narrow question: Is there a blockage or not? How is AI changing what clinicians can learn from a scan?
Determining whether a patient is at risk for a cardiac event takes more than knowing whether a blockage has begun to develop. While traditional cardiac CT has focused on identifying blockages, the addition of AI now gives clinicians a window into a patient’s overall cardiovascular health, including the degree of luminal narrowing, the composition of plaque, the presence of inflammation, and the functional health of the heart muscle itself.
These changes are also reflected in clinical guidelines. The 2021 ACC/AHA Chest Pain Guidelines granted cardiac CT a Class I, Level A recommendation, establishing it as a frontline strategy for diagnosing coronary artery disease. This reflects the growing recognition that effective cardiovascular care requires a more complete picture of both anatomy and function. Instead of reacting to established obstructions, clinicians can characterize plaque stability and evaluate total vascular burden, helping inform earlier interventions before a patient experiences an acute event.
3. AI is also changing the scan itself. What does that mean for patient safety?
AI is altering the physics of the scan itself to enhance patient safety and image fidelity. The industry has been working toward lower radiation dose for a long time, and AI-driven deep learning reconstruction is helping achieve that goal. By identifying significant diagnostic data, these algorithms allow scanners to produce ultra-high-resolution images while using a fraction of the radiation traditionally required. This means that even in high-volume clinics where throughput is a priority, patients receive a safer, lower-dose experience without compromising image quality.
4. Staffing shortages are affecting imaging departments at every level. How does AI help a practice that can’t easily hire experienced technologists?
A growing number of hospitals and clinics face staffing shortages at all experience levels, which is one area where AI is making a practical difference. Building cardiac imaging standards into the equipment helps technologists follow consistent scan protocols, even when their teams are stretched thin.
For example, AI helps before the scan begins by automating patient positioning and tailoring scan parameters in real time. That level of precision helps technologists of all experience levels capture a high-quality image on the first attempt and reduces the need for repeat scans. Built-in guidance supports technologists as they adapt the scan to each patient and helps them capture the images cardiologists need to make care decisions. Having more of these standards built into the technology also allows technologists to focus on the patient-facing aspects of the scan, like providing breathing instructions, helping patients stay calm and making adjustments based on each patient’s individual needs.
5. There’s a growing ecosystem of AI tools for coronary analysis. Where does a scanner manufacturer like Arineta fit?
Our approach is to build AI into the scanner itself and stay vendor agnostic on the analysis side. Arineta’s deep learning image reconstruction reduces image noise while preserving the detail clinicians need for a confident read. Image quality is important because it provides the foundation for the additional analysis that can happen after the scan.
There are several companies developing AI tools for coronary plaque analysis, blood flow assessment and other measures of cardiovascular health. We want our scanners to work with the tools cardiologists choose, giving practices flexibility in how they analyze images and make decisions about patient care.
6. Advanced cardiac imaging has historically been concentrated in large academic medical centers. How is technology changing that, and what does it mean for community cardiology practices and their patients?
The biggest opportunity in cardiology is making innovation more accessible, so patients can receive the same quality of care regardless of where they live or where they see their cardiologist. Historically, bringing cardiac CT into a community practice required significant investment in specialized equipment, infrastructure and personnel, putting it out of reach for many smaller practices.
Our technology combines a more compact, accessible imaging platform with AI-driven automation that helps standardize image acquisition and analysis, reducing the operational complexity traditionally associated with cardiac CT. That means community practices can bring these capabilities in-house without needing the same resources as a major academic medical center.
We want to make it easier for patients to get the same level of care as a leading medical institution from everyday clinical practice. Patients shouldn’t have to travel to a major medical center to access advanced cardiac imaging or wait weeks for an assessment they could receive from their own cardiologist. By bringing these capabilities closer to the patient, we’re helping make earlier, more informed cardiac care more accessible.
7. How does AI-assisted imaging change the patient’s experience?
The convergence of AI and advanced imaging is changing how patients move from diagnosis to treatment. Historically, diagnosis has often been triggered by symptoms, followed by referrals and travel to reach specialized imaging. Moving high-precision diagnostics into local clinical settings can help streamline that process and give clinicians actionable information sooner.
Following this new path, patients may no longer need to travel to a major medical center to access advanced imaging. AI-assisted technology helps make more advanced diagnostic capabilities available at the first point of contact, which can shorten the time between the onset of symptoms and the start of a personalized treatment plan. For patients, that means answers sooner and closer to home.
8. Looking ahead, what does AI-enabled cardiac imaging look like, and who benefits most?
In the U.S., heart disease remains the leading cause of death, accounting for about one in five deaths. People in rural areas face a higher risk of dying from heart disease, in part because of delays in diagnosis and limited access to specialized imaging. Advances in scanner technology and AI are helping change that by making cardiac CT easier to perform and more accessible, allowing smaller practices to offer advanced imaging that has traditionally been concentrated in larger medical centers.
Looking ahead, the goal is to get more information from every scan. Rather than simply identifying blockages, advanced cardiac CT scanners and AI can help clinicians better understand the extent and characteristics of coronary disease and make more informed treatment decisions. These advances mean more patients, particularly those in rural and underserved communities, can benefit from more comprehensive cardiac imaging.
Bio:
Einav Ehre is a global MedTech executive with more than 30 years of experience in financial and operational leadership. Prior to becoming CEO of Arineta, he served as the company’s CFO and COO, leading finance, operations, investor relations, and strategic planning across Israel, the U.S., and China. During his tenure, he helped raise more than $150 million and expand Arineta’s international operations. Earlier in his career, Ehre held senior finance roles in Israel and Nigeria, including serving as CFO of Etco and Company Secretary at CMT Medical Technologies. He holds a BA in Economics from Ben-Gurion University of the Negev and a BA in Accounting from Bar-Ilan University.
About Arineta:
Arineta, based in Israel, specializes in developing innovative cardiovascular imaging solutions. The company is committed to advancing cardiac CT as the front-line non-invasive method for diagnosing, planning therapy, and monitoring cardiovascular disease, the leading cause of death and healthcare costs worldwide. Arineta’s flagship product, the SpotLight™ Duo, based on the company’s proprietary Stereo CT technology, is the world’s first dedicated single-heartbeat, whole-heart cardiovascular and thoracic CT scanner. Building on its history of medical imaging innovation that began in Israel in the 1970s, Arineta’s team includes the inventors of multi-slice spiral CT technology, still the cornerstone of CT imaging, and several other key technologies.
