Coverage unlocks reimbursable AI plaque quantification, advancing coronary risk assessment in everyday cardiology practice. Highlights New permanent Category I CPT code 75577 for AI-enabled coronary plaque analysis took effect January 1, 2026 Major payers, including Aetna, alongside UnitedHealthcare, Cigna, Humana, and others, now cover AI-enabled coronary plaque analysis, extending access to tens of millions of commercially insured patients Circle’s FDA-cleared, on-premise cvi 42 |Plaque solution integrates directly into CCTA workflows, giving physicians hands-on control of AI plaque analysis and retains more of the plaque analysis reimbursement Calgary, Alberta – Circle Cardiovascular Imaging Inc. (Circle CVI), the market leader in cardiovascular imaging postprocessing, announced that clinical practices using its FDA 510(k)-cleared cvi 42 with AI-enabled plaque analysis solution are well positioned to benefit from newly activated reimbursement for AI-enabled coronary plaque analysis under permanent Category I CPT code 75577, effective January 1, 2026. Major insurance companies have also announced that they are also reimbursing the costs of this analysis. New Category I CPT Codes Now in Effect Beginning January 1, 2026, AIdriven quantification and characterization of coronary atherosclerotic plaque derived from coronary CT angiography (CCTA) is reimbursed under a permanent Category I CPT code, 75577, replacing prior Category III codes. This transition enables nationally valued payment for quantitative plaque assessment across hospital outpatient departments, imaging centers, and physician offices. Growing Payer Support for AI Plaque Analysis Major commercial payers, including Aetna, UnitedHealthcare, Cigna, Humana, and others, now cover AI-based quantitative coronary plaque analysis , extending access to tens of millions of commercially insured patients and building on prior Medicare coverage decisions. This expanding reimbursement is expected to accelerate adoption of CCTA-based plaque assessment. AMA/ACC Guidance on When to Use Plaque Analysis In December 2025, a major scientific statement published in the Journal of the American College of Cardiology : Cardiovascular Imaging provided consensus recommendations on how and when to use quantitative coronary plaque analysis (QCPA) in practice. Their recommendations stated that among patients who have visual evidence of plaque on coronary CTA, adding QCPA may be useful for enhancing risk assessment and guiding the initiation or intensification of preventive therapies. CCTA’s Emerging Role as a Primary CAD Modality Recent analyses from cardiovascular imaging experts highlight how CCTA, augmented by AI-enabled plaque analysis, is poised to become the foundational imaging modality for the diagnosis and management of coronary artery disease. As reimbursement stabilizes and technology matures, CCTA is increasingly viewed as the frontline test that can characterize both stenosis and atherosclerotic burden, informing preventive strategies long before invasive procedures are required. cvi42|Plaque: FDA-cleared, On-premise AI for Coronary Plaque cvi 42 |Plaque, cleared by the U.S. FDA in late 2025, is an on-premise, AI-enabled coronary plaque analysis module that integrates directly into existing cvi 42 and CCTA workflows. The software automatically segments the coronary lumen and vessel wall, quantifies plaque burden and composition, and generates structured lesion- and vessel-level metrics to support risk stratification, preventive therapy decisions, and revascularization planning. Because the solution runs locally, image data, AI processing, and reporting remain within the institution’s environment, giving physicians interactive control over contouring and final interpretation while allowing programs to retain a larger share of reimbursement compared with outsourced, cloud only services. Localized AI and Circle’s Elevate Pricing Advantage “With the new Category I CPT code for coronary plaque analysis now in effect, and the major insurance players reimbursing plaque analysis, the economics and clinical evidence are finally aligned,” said Chris Bazinet, Chief Commercial Officer at Circle CVI. “cvi 42 |Plaque gives practices an on-premise, FDA-cleared AI solution that fits directly into their existing CCTA workflows, enabling guideline consistent plaque reporting, improved risk stratification, and better capture of the reimbursement now available for quantitative coronary plaque analysis.” cvi 42 |Plaque is available as part of the broader cvi 42 platform for cardiac CT and MR. Clinical sites interested in implementing AI-enabled coronary plaque analysis can contact Circle to assess readiness, workflow integration, and revenue potential. - ENDS - About Circle Cardiovascular Imaging Circle Cardiovascular Imaging Inc. (Circle CVI) is a Canadian-based company founded in 2007 with a mission to develop innovative software solutions that enhance cardiovascular and cerebrovascular imaging analysis and ultimately improve patient care. Circle’s flagship platform, cvi 42 , delivers best-in-class image reading and reporting tools for quantitative and qualitative assessment of cardiac MR, cardiac CT, vascular CT, and neuro CT. At the core of Circle’s work is a relentless commitment to empowering healthcare providers with advanced, intuitive tools that lead to better healthcare outcomes. This passion for innovation, rooted in both medicine and technology, drives Circle’s global impact and fuels a culture of excellence. Today, millions of medical imaging exams each year—across 1,700+ hospitals in over 90 countries—are interpreted using Circle’s cvi 42 platform.​ For media inquiries, please contact: marketing@circlecvi.com

Highlights  The latest release of cvi42v6.4 focuses on workflow efficiency and leveraging artificial intelligence In-house post-processing speeds reporting time and captures more reimbursement Circle’s vascular capabilities expand with the addition of cvi42 | Vascular CT New business models increase the flexibility and accessibility for reporting physicians Calgary, AB – Circle Cardiovascular Imaging (Circle CVI) , the market leader in cardiovascular imaging post-processing will unveil its latest release at the Radiological Society of North America (RSNA) Annual General Meeting being held November 30 – December 4 in Chicago, IL. Circle CVI will demonstrate its newest release, cvi42v6.4. Radiology leaders know that efficiency, accuracy, and practice growth are non-negotiable. At RSNA 2025, Circle Cardiovascular Imaging invites you to experience the new cvi42 release - a solution engineered to grow your CCT and CMR business. What cvi42 can do for your practice: Reduce Reporting Times: Native integration with PowerScribeautomates transcription, minimizing error risk and freeing clinical teams to focus on interpretation rather than manual data entry. Accelerate Patient Care: In-house plaque analysis with cvi42 enables faster turnaround times, supporting timely diagnosis and allowing you to deliver a higher standard of care. Drive Confidence and Adoption: cvi42 | Vascular CT follows best practices with automated contouring, lowering barriers to using advanced CT vascular analysis - so teams adopt new capabilities faster. Increase Revenue Capture: With cvi42 | Plaque you pay for what you process at a fraction of the price of outsourcing and increase your throughput with a streamlined workflow. Elevate Value and Flexibility: Our new subscription model provides scalable access to CMR and CCT functionalities ensuring your team has unlimited access to work from anywhere. “With our latest cvi42 release, we’re helping practices unlock greater efficiency, deliver faster patient care, and build a scalable foundation for the future of cardiovascular imaging while supporting business growth” said Chris Bazinet, Chief Revenue Officer of Circle CVI. “We are excited to see how our customers respond to the latest innovations and hear from them how we are solving their challenges” Benefits for Radiology Leaders and Decision Makers: Minimized risk of errorin reporting Improved workflow efficiency, leading to reduced burnout Faster reporting speeds, translating to greater practice performance Flexibility to scale and capture new revenue streams Technology that aligns with evolving best practices and reimbursement guidelines Join Us at RSNA 2025 - Shape the Future of Cardiovascular Imaging Nov. 30 – Dec. 3 | Booth #7961, North Hall Secure your demo now - see how cvi42 can help you lead with confidence and results.

Decoding the Coronaries CAD-RADS, or the Coronary Artery Disease Reporting and Data System, is a standardized reporting system designed to enhance the communication of coronary artery disease (CAD) findings from imaging studies. CAD-RADS represents a significant step towards a more systematic and evidence-based approach to the management of CAD. By standardizing reporting, guiding clinical decisions, facilitating research, and improving risk stratification, CAD-RADS not only holds the potential to improve the clarity of communication between the diagnostician and the downstream physician, but at a larger scale, it could contribute significantly to better cardiovascular health outcomes across populations. Why CAD-RADS? CAD-RADS was developed to establish a clear and consistent framework for reporting coronary artery disease findings from coronary computed tomography angiography (CCTA). Prior to CAD-RADS, the reporting of coronary computed tomography angiography (CCTA) findings often lacked uniformity. This variability made it challenging for referring physicians to interpret results consistently and make informed decisions about patient care. CAD-RADS was initially created in 2016 , as a result of a collaboration between the Society for Cardiovascular Computed Tomography (SCCT) , the American College of Radiology (ACR) , and the North American Society for Cardiovascular Imaging (NASCI) . Subsequently it was also endorsed by the American College of Cardiology (ACC) . CAD-RADS introduced a standardized classification system, providing a common language for radiologists, cardiologists and referring physicians, facilitating a more consistent understanding of CCTA results across different institutions and regions. The system was then updated to CAD-RADS 2.0 in 2022 to incorporate several methods for the categorization including descriptors of overall coronary plaque burden, with additional options to include CT-FFR (CT fractional flow reserve) or myocardial CT perfusion results for the assessment of lesion-specific ischemia if obtained. It also now includes the description of non-atherosclerotic coronary abnormalities as a separate modifier “E” for exceptions. CAD-RADS reporting ensures that all imaging studies are reported in a uniform manner, making it easier for referring physicians to interpret results. The use of clear categories (ranging from CAD-RADS 0 to CAD-RADS 5) allows for quick assessment of the severity of coronary artery disease. The incorporation of P1 to P4 descriptors into the CAD-RADS framework serves to provide a more nuanced understanding of plaque burden. Each descriptor corresponds to a specific level of plaque accumulation, allowing for a more detailed assessment of a patient's coronary artery health. Since the original CAD-RADS have been developed in 2016, many technological advancements to CCT have been incorporated into routine practice and correspondingly, CAD-RADS guidelines have also been updated. The latest updates to CAD-RADS 2.0 have focused on improving the specificity of reports and providing clear recommendations for patient management. As the framework gets more comprehensive, it is unavoidable that it becomes more complex and therefore more time-consuming as well. Nevertheless, by incorporating CAD-RADS into risk assessment, clinicians can better identify individuals at higher risk who may benefit from more intensive preventive therapies or closer monitoring, potentially improving long-term population health outcomes. The integration of AI with CAD-RADS represents a significant advancement in cardiac imaging. AI can assist in automating the categorization of findings according to CAD-RADS criteria, reducing the potential for human error and ensuring consistency in reporting. Furthermore, AI-driven analytics can provide additional insights into patient data, enabling more personalized treatment plans and improving patient outcomes. At the same time, the stratification of CAD-RADS can aid the training of AI models that might lead to a better validated approach to cardiovascular risk prediction beyond traditional expert consensus approaches. Beyond Stenosis: Understanding the CAD-RADS Categories CAD-RADS isn't solely about quantifying luminal narrowing. It's a comprehensive system that categorizes CCTA findings based on the likelihood of causing myocardial ischemia. This risk stratification allows for more tailored management strategies. The updated CAD-RADS 2.0 classifications follow a now well-established framework, while adding more detailed descriptors and modifiers to augment each CAD-RADS category. This added context improves clarity, helps referring physicians understand the implications of the findings. The system labels findings into distinct levels, ranging from CAD-RADS 0 to CAD-RADS 5 as core categories, allowing healthcare providers to quickly assess the severity of coronary artery disease and make informed decisions regarding patient management. CAD-RADS 0: No evidence of coronary artery disease. This category indicates that the coronary arteries are normal, and there are no significant findings on the imaging study. CAD-RADS 1: Minimal non-obstructive CAD (1-24% stenosis).This category suggests the presence of coronary artery disease without significant stenosis, meaning that there are no blockages that would impede blood flow. Typically managed with lifestyle modifications and risk factor optimization. CAD-RADS 2: Mildly obstructive coronary artery disease (25-49% stenosis). This indicates that there is a presence of stenosis (narrowing of the arteries), which may require monitoring but typically does not necessitate immediate intervention. Clinical context becomes crucial here. Further non-invasive testing may be considered based on symptoms and risk profile. CAD-RADS 3: Moderately obstructive coronary artery disease (50-69% stenosis). This category suggests a higher risk for adverse cardiac events and often leads to further evaluation or intervention. Stress testing is generally recommended to assess functional significance. CAD-RADS 4A: High-grade stenosis (≥70% stenosis) in ≤2 proximal segments. Functional assessment or invasive coronary angiography (ICA) is usually indicated. CAD-RADS 4B: Moderate-to-severe stenosis (≥50% stenosis) in the left main artery, or 3-vessel disease with severe stenosis (≥70% stenosis). ICA is strongly recommended. CAD-RADS 5: Total occlusion. Coronary artery disease with high-risk features. This category includes findings that suggest a high likelihood of significant coronary artery disease, such as extensive calcification or high-risk plaque characteristics. Requires further evaluation, often with ICA, to determine viability and potential for revascularization. CAD-RADS N: Non-diagnostic study. This highlights technical limitations of the study whereby obstructive CAD cannot be excluded, necessitating repeat imaging or alternative modalities. Plaque Amount Assessment While the primary CAD-RADS category provides a strong foundation, the system's true strength lies in its descriptors and modifiers. The recent incorporation of P1 to P4 descriptors into the CAD-RADS 2.0 framework serves to provide a more nuanced understanding of the overall plaque burden. A unique quality of cardiac CT when compared with other non-invasive tests, is its ability to not only detect the presence but also allow for the measurement of the amount of plaque present. It is now well established that beyond the existence or absence of anatomical stenosis, the overall amount of coronary plaque has a strong association with the incidents of coronary heart disease events and therefore the inclusion of P descriptors may, indeed, offer stronger prognostic value. P1 Descriptor Definition : Mild plaque burden. Implication : Indicates the presence of non-obstructive plaque, suggesting a lower risk of significant coronary artery disease. P2 Descriptor Definition : Moderate plaque burden. Implication : Reflects the presence of some plaque that may warrant monitoring but is not yet obstructive. P3 Descriptor Definition : Severe plaque burden. Implication : Suggests a higher risk of coronary artery disease, with potential for obstructive lesions that may require intervention. P4 Descriptor Definition : Extensive plaque burden. Implication : Indicates significant plaque accumulation with a high likelihood of obstructive disease, necessitating immediate clinical attention. The addition of P1 to P4 descriptors to the CAD-RADS categories enhances the ability to assess and communicate the severity of plaque burden in patients. This improvement not only aids in the diagnosis and management of coronary artery disease but also supports more personalized patient care strategies. Understanding these descriptors is crucial for healthcare professionals involved in cardiovascular imaging and treatment. The Power of Modifiers: Adding Clinical Context Modifiers provide additional context for the findings, going beyond just the severity of stenosis and the overall amount of plaque, to include other relevant factors. In addition to a specific level of plaque accumulation, allowing for a more detailed assessment of a patient's coronary artery health, these crucial modifiers incorporate additional information that may significantly impact clinical decision-making: N (Non-diagnostic): Indicates that the study is not fully evaluable or non-diagnostic, which may be due to motion artifacts or other technical issues. HRP (High-Risk Plaque): In CAD-RADS 2.0, HRP replaces the previous "Vulnerable Plaque" designation from the original CAD-RADS and indicates the presence of specific plaque features that may be more likely to cause plaque rupture and subsequent events. The presence of such presentations as positive remodeling, low attenuation plaque, napkin-ring sign, and spotty calcification elevates risk and may warrant more aggressive management even in non-obstructive lesions. I (Ischemia): indicates that either a CT-FFR or CTP was performed. The “I” modifier has three options: "I+" = Ischemia present "I-" = No ischemia detected "I+/-" = Ischemia results indeterminate S (Stent): Indicates the presence of stents in the coronary arteries. G (Graft): Indicates the presence of coronary artery bypass grafts. E (Exceptions): Denotes potential coronary abnormalities not due to atherosclerotic plaque buildup, such as compression or stenosis caused by other factors like anomalous coronary arteries or dissection. By consistently utilizing these modifiers, CAD-RADS classification moves beyond simply reporting stenosis percentages and paints a more complete picture of the patient's atherosclerosis and the overall coronary burden and risk. The information provided by modifiers can help guide patient management decisions, such as the need for invasive angiography or revascularization. As CAD-RADS continues to evolve, there is a high likelihood of more specific modifiers being incorporated in the future as well. Importance of CAD-RADS in Clinical Practice The true value of CAD-RADS lies in its seamless integration into daily clinical practice. Consider these practical implications: Standardization: By providing a uniform reporting system , CAD-RADS enhances communication among healthcare providers, ensuring that everyone involved in a patient's care understands the severity of their condition. Multidisciplinary Collaboration: Discussion of complex CAD-RADS findings should be a routine part of cross-specialty team meetings to leverage the expertise of interventional cardiologists, cardiac surgeons, and imaging specialists. CAD-RADS can serve as a quantified “lingua franca” in these team discussions. CAD-RADS should be a critical pillar of peer-review, quality assurance and continuing education in CAD diagnosis and therapy planning. Guided Management: The clear categorization of findings helps clinicians determine the appropriate management strategies for patients, from medication, lifestyle modifications to invasive procedures. Risk Stratification: Utilizing CAD-RADS categories and modifiers in conjunction with clinical presentation, risk factors, and other diagnostic tools can guide further testing and treatment strategies. Patient Communication: CAD-RADS provides a framework for explaining CCTA findings to patients in a clear and understandable manner, fostering shared decision-making. Using the power of “an image worth a thousand words” combined with quantified measurements, can facilitate an understanding of the severity of the clinical condition and the importance of adhering to the prescribed management routine. Improved Patient Outcomes at Scale: Standardized diagnostic reporting can facilitate following CAD at the population health level. By assisting with timely and accurate diagnosis and treatment, CAD-RADS can contribute to better patient outcomes and reduced morbidity associated with coronary artery disease. In essence, CAD-RADS represents a significant step towards a more systematic and evidence-based approach to the management of CAD. By standardizing reporting, guiding clinical decisions, facilitating research, and improving risk stratification, CAD-RADS has the potential to contribute to better cardiovascular health outcomes across populations. The ongoing updates to CAD-RADS, such as the introduction of CAD-RADS 2.0 incorporating plaque burden assessment and high-risk plaque features, further underscore its evolving role in optimizing patient care and population health. CAD-RADS is a vital tool in the assessment and management of coronary artery disease. By standardizing the reporting of imaging findings, it enhances communication among healthcare providers and guides clinical decision-making. Looking Ahead: As the understanding of coronary artery disease continues to evolve, CAD-RADS will remain an essential component in the care of patients at risk for cardiovascular events. The recent developments incorporated into CAD-RADS 2.0 have already significantly enhanced the communication of test results between radiologists and referring physicians. By providing standardized, clear, and actionable reports, CAD-RADS facilitates better patient management and outcomes. As these advancements continue to evolve, they promise to further improve the quality of care for patients with coronary artery disease. To learn more about CAD-RADS and how to incorporate them into your practice, visit https://www.circlecvi.com/cardiac-ct#reporting Despite the promising developments in CAD-RADS and AI-based post-processing systems , several challenges remain. These include the need for robust validation of AI algorithms, ensuring interoperability and standardization between different systems, in addition to the ever-present concerns related to data privacy and security. Future research should focus on overcoming these obstacles while continuing to refine CAD-RADS and exploring the role of new AI applications in cardiac imaging. As CCTA technology advances, so too will CAD-RADS. We can anticipate further refinement of the categories and modifiers, potentially incorporating artificial intelligence and machine learning to enhance risk prediction and personalized management. For any healthcare professionals, familiarizing themselves with CAD-RADS, embracing its comprehensive framework and utilizing its modifiers thoughtfully, can unlock its full potential and help navigate the complexities of coronary imaging with greater confidence and precision.

Taking a tour of even some of the historical branches of coronary artery disease (CAD) research, should make any healthcare professional excited in anticipation of the synthesizing effect of emerging technologies, such as AI, in CAD diagnosis, treatment and prevention. History of Coronary Artery Disease Research and Diagnosis seems to predict a great leap forward  Coronary artery disease (CAD) is a leading cause of morbidity and mortality worldwide. While often thought of as a “modern disease”, Coronary Artery Disease is probably as old as humanity. In evolutionary terms, the complex effects of prolonged lack of oxygen to myocardial tissue - as a result of the reduced blood flow via the arteries that supply the heart itself - are likely as old as the structure and function of any hominid heart. Long before the terms "atherosclerosis" or "ischemia" were coined, humanity had already begun encountering the symptoms of coronary artery disease. Ancient Egyptian mummies have shown evidence of arterial calcification, suggesting that atherosclerosis – the buildup of atheroma within blood vessels – has existed for millennia. These calcified plaques, visible through modern imaging like CT and MR contrast-enhanced scans, tell a story of a disease that spans human history. The history of diagnosing and treatment of CAD is a fascinating journey reflecting advancements in medical understanding and technology. As is often the case, the various innovations serving as milestones on this journey say as much about the age in which they were introduced as they do about the disease they are attempting to diagnose or treat. For most of humanity's evolution and more recent sentient, recorded history, just from symptoms observed, the morbidity related to the functional “design” of our heart’s own plumbing must have been a terrifying (and perceived mostly as mind-bogglingly random) way to go. “If only we could recognize the signs earlier, predict the “attack” from early occurring symptoms” ...maybe then, we could prevent the seemingly random, sudden deaths resulting. This became the mantra, even the obsession of physicians and researchers focused on solving this puzzle. Starting from very caring, but only anecdotal observation, the inquisitive, but slow pattern-searching followed. Different branches of research began to take shape. Then, as in every other area of medical research, art gave way to science and through experimentation and innovation we started to make progress in researching the heart and the role of the coronary vessels as well. However, while each branch built on the conclusions of previous studies, the different areas of research have remained largely independent in approach and as a result, often stayed isolated in their progress as well. From Early Clinical Observations to Linking Symptoms to the Heart - The age of enlightenment and the honing of the scientific process: Historical medical texts, including those from ancient Greek and Chinese medicine, documented symptoms like chest pain, shortness of breath, and fainting – signs now often associated with CAD. While these early observations were often interpreted through mystical or humoral lenses, they laid the foundation for the clinical curiosity that would fuel centuries of cardiovascular research. Before any specific diagnostic tools existed, CAD was primarily recognized through its symptoms, most notably as chest pain. During the renaissance, anatomical discoveries through autopsies started to uncover the links between the structure of the heart and blood supply but the cause of angina remained too complex for the models of the age. William Heberden provided a detailed clinical description of angina pectoris in the late 18th century, linking it to exertion and emotional stress – further complicating the observed model. However, the underlying cause of narrowed coronary arteries wasn't fully understood. The Dawn of Objective Diagnosis (Early 20th Century): Early 1900s: Electrocardiogram (ECG):The excitement of the age about all things electric, predictably, was applied to cardiac research as well. The early 20th century introduced a transformative leap in cardiac diagnosis with the invention of the electrocardiogram by Willem Einthoven . This groundbreaking device allowed doctors to record the heart’s electrical activity - a revolutionary method that marked the first truly objective diagnostic cardiac exam. ECG allowed physicians to record the electrical activity of the heart and identify patterns indicative of myocardial ischemia and infarction. It also signaled the shift from just understanding to actually trying to do something about cardiac diseases. Visualizing the Arteries - Catheterization and Coronary Angiography: The magic of looking inside the human body without having to take it apart, through Wilhelm Roentgen’s X-rays, was obviously going to be aimed at the heart as well. The moment the technology moved from the hands of WWI military field-medics to routine practice in hospitals, the first cardiac fluoroscopy studies were also performed. The bizarre, self-experimentation story of first the cardiac catheterization was practically inevitable and also reflected the weirdness of the age between the world-wars. But, as Forssmann walked the stairs from the OR to the x-ray room a floor below with a catheter he inserted into his own right ventricle via his antecubital vein in 1929, (just wow!!) the practice of cardiology changed forever– the stunt proved that internal cardiac access was possible. The development of coronary angiography by Mason Sones by the late 1950s logically followed and, indeed, marked another significant leap in our understanding. The concept of injecting a contrast dye into the coronary arteries and taking X-ray images, allowed direct visualization of arterial blockages in real time and in-situ mapping of coronary arteries and their stenosis. Angiography quickly became the "gold standard" for definitively diagnosing the presence and extent of CAD, further improving our model of not only how a normal human heart tissue is structured and supplied with oxygen, but also showing how narrowing's and blockages in “this plumbing” result in the disease that can lead to potentially fatal clinical consequences. While our functional modeling and understanding of the disease took millennia, it took Dr. Sones less than a decade to move from the first coronary angiogram to the first coronary artery bypass graft (CABG) procedure. Expanding Diagnostic Capabilities in the late 20th and early 21st Centuries: Now that we had a clear model of CAD with a viable “fix”, the search was on to recognize it earlier, with decreasingly invasive procedures. The objective became to make the diagnosis more definitive and more predictive, while also reducing the risk from the diagnostic procedures themselves. At the same time, finding new patterns now visible from the combination of deploying the different diagnostic modalities that became available increased our understanding of the cause and the clinical risk from the extent and location of the stenosis. Stress Testing: Exercise electrocardiography (stress testing) gained prominence as a non-invasive way to provoke symptoms and ECG changes suggestive of CAD during physical exertion, combining clear anatomical understanding of heart function with the patterns of electrical activity. Prominence of Imaging: One unexpectedly positive legacy of the “nuclear age” – the medical use of isotopes for functional imaging was predictably applied to CAD diagnosis as well. Nuclear Cardiology techniques like myocardial perfusion imaging using radioactive tracers emerged to assess blood flow to the heart muscle under rest and stress conditions. The recognition of the negative effects of radiation necessitated the innovation of imaging while minimizing ionizing radiation. Ultrasound imaging of the heart became a valuable tool to assess heart function and sometimes visualize signs of ischemia. Combining ECG with ultrasound, stress echocardiography further enhanced CAD diagnostic capability. Computed Tomography Angiography (CTA) : As the age of analog instrumentation gave way to the age of digital signal processing and computers, CT imaging was born. In Cardiology, non-invasive, Computed Tomography Angiography(CTA) logically followed . In more recent decades, even though it is using x-rays, non-invasive CT angiography has become increasingly sophisticated, providing detailed 3D images of the coronary arteries without the need for catheterization in many cases. The near-ubiquitous access to CT scanners made cardiac CT (CCT) studies very common. The acquisition protocols have also evolved to better visualize lipid and calcium deposits, while quantitative analysis and standardized reporting of CAD continues to hold further great potential. Cardiac Magnetic Resonance Imaging (CMR ): Along with CCT, Cardiac MRI offers detailed information about heart structure and function and can be used to detect myocardial scar tissue and assess blood flow. Being a non-invasive, radiation-free imaging modality, CMR imaging is useful for the management of patients with CAD. Various MR acquisition techniques and protocols have been developed over the last three decades to evaluate cardiac function and detect defects in myocardial perfusion. Specifically, late gadolinium enhancement (LGE) imaging, a well-established technique that uses contrast to highlight scar tissue, can identify the presence and extent of scar tissue in the heart, which is a common finding in CAD. While CMR has a high degree of accuracy and reliability in detecting and characterizing CAD, the modality also allows accurate risk stratification of patients with established CAD. Post-processing and Reporting : While the amount of imaging studies and the corresponding imaging data has increased exponentially, the need for post-processing has also sky-rocketed, making automation necessary. Machine-learning techniques make it increasingly possible to minimize the manual effort required to not only accurately map the cardiac structure, function and blood-flow but to also to quantitatively analyze cardiovascular diseases, including CAD. Structured reporting’s adoption in cardiology is significantly ahead of other disciplines. Yet, only in the last decade have we started routinely categorizing and stratifying CAD , based on the extent of stenosis and overall plaque burden. Needless to say, quantified analysis and standardized reporting represent both a great downstream clinical value and a gold-mine of data for population-level analysis. Biomarkers for CAD : Another great branch of CAD research has been producing deeper understanding by identifying and utilizing various proteins, peptides and enzymes that are involved in CAD. Troponins, BNP, CRP, MPO, Lp(a) and IL-6– to name a few - each play a unique role in the diagnosis, risk assessment, and management of CAD. Troponins are considered the gold standard for diagnosing myocardial infarction (MI) and are highly sensitive and specific for cardiac injury. Elevated troponin levels can indicate ongoing ischemia and are used to assess the severity of CAD, often guiding decisions in emergency settings, triaging patients for further imaging or intervention. As research continues to evolve, these and other biomarkers may offer new insights into the pathophysiology of CAD. Labs now use highly sensitive assays to detect even minute changes, and AI-powered platforms hold the potential to synthesize this multifactor, often unstructured data into actionable clinical insights. Genetics and epigenetics - Unlocking Hereditary Risk : Recent studies have identified numerous genetic variants associated with CAD . Genome-wide association studies (GWAS) have pinpointed specific genes linked to lipid metabolism, inflammation, and vascular function. Some of these notable genetic markers associated with CAD have been studied extensively, including: PCSK9 : Variants in this gene can lead to elevated cholesterol levels, increasing CAD risk. LDLR : Mutations in the LDL receptor gene are linked to familial hypercholesterolemia, a condition that significantly raises the risk of CAD. APOE : The APOE gene is involved in lipid metabolism, and certain alleles are associated with increased CAD risk. Ongoing studies aim to discover more genetic variants and their functional implications . Additionally, advancements in gene editing technologies, such as CRISPR, hold promise for developing novel therapies that target the genetic basis of CAD. By leveraging genetic insights, healthcare providers will be empowered to routinely offer personalized care that addresses the unique risk factors of each patient. Present-Day Landscape: Merging Traditional and Tech-Driven Tools By now, in the early 21st century, we understand that Coronary Artery Disease occurs when the coronary arteries become narrowed or blocked, often due to atherosclerosis. Statistically, we have identified known risk factors, that include high cholesterol, hypertension, smoking, and diabetes. Nevertheless, CAD is a complex disease that varies in presentation and its exact progression in an individual remains difficult to predict. The biological mechanisms that lead to lipid deposits and calcification leading to the progression of the disease are relatively well understood. The less deterministic impact of family history, genetics and epigenetics is much less understood. Today, the diagnosis of CAD often involves a combination of the previously mentioned methods, tailored to the individual patient's symptoms, risk factors, and clinical presentation. Simple, diagnostic stress-ECG tests are most often used for initial evaluation followed often by modern, non-invasive imaging studies, such as an echo and cross-sectional imaging studies (CCTA or CMR), with coronary angiography reserved for cases requiring more definitive diagnosis or intervention. The field continues to evolve with ongoing research into new imaging and other diagnostic techniques, with each test carrying different advantages and disadvantages. Progress needs AI: The Case for Integration Overcoming Fragmentation in Research and Practice Progress is never a linear progression. Just like in other areas of cardiac research, and indeed all of medicine, of course, promising work is being done continuously in independent, but often diverging, sometimes even isolated areas of research. The practice of medicine organized into compartmentalized healthcare departments brings focus to sub-specialties, but, combined with the funding structure through grants, the deep and narrow areas of research often continue in silos without the benefit of broader perspectives. This fragmentation not only creates frustrating confusion for patients, it also limits healthcare’s ability to generate holistic, personalized care plans. It is high time to bring our historical learnings together – converging them, breaching conventional boundaries to improve cardiac research and care. Just like in other areas of life, we need to work to figure out how to bring AI to play a key role in integrating huge volumes of data and synthesize the information within various adjacent but seemingly independent scientific domains. AI doesn’t just process data- by analyzing diverse and large datasets, AI could potentially help predict coronary artery disease risk, develop personalized interventions for individual patients, effectively synthesizing knowledge from various biological, diagnostic and medical disciplines. AI also holds the potential to assist researchers by generating novel research hypotheses, detailed overviews, and experimental protocols based on a specified research goal for CAD research. AI could and should be harnessed to improve clinical practice diagnosis and subsequent management. Conclusion From the earliest symptom observations to today’s cutting-edge diagnostics, each era has added layers to our understanding of CAD. Can't wait to see what yet unpredictable benefits the age of AI will bring to the deepening of our understanding, assessment ultimately to the treatment of this pervasive condition. It is exciting to imagine what the ever-expanding pattern-search, pattern recognition, and modeling capabilities of even narrow-AI algorithms will bring to the table in terms of personalized risk assessment from multifactor quantified analysis, early screening, based on genetic and epigenetic risk factors, incidental findings from non-cardiac intended chest studies, and more. Maybe, just maybe,…we are on the cusp of bringing many possible angles of research, population health and diagnostic techniques together to make them quantified enough to bring these new, learning, modeling, intelligent tools to bear early enough for tackling CAD prevention- not just for an individual patient but for an at-risk population segment. To learn more about how AI-based CCTA post-processing can be part of your practice, visit www.circlecvi.com/cardiac-ct . As research continues to evolve, the integration of the many different “branches of research” into clinical practice supercharged by AI, will undoubtedly enhance our ability to prevent, diagnose and treat CAD, ultimately improving patient outcomes and reducing the burden of this prevalent disease. Frequently Asked Questions (FAQs) Q1. What are the most frequently used tests for diagnosing coronary artery disease? A combination of stress testing, cardiac CT angiography (CCTA), cardiac MRI, and biomarkers like troponin offers the highest diagnostic accuracy. Each test has unique advantages depending on patient risk profile. Q2. How can artificial intelligence improve CAD diagnosis? AI has the potential to improve CAD diagnosis by analyzing imaging, ECG, and lab datasets faster and with higher accuracy and consistency. It can help detect patterns in multi-modality datasets in the longitudinal health record of an individual patient, or can be an invaluable tool for analyzing large, multi-factor datasets across many patient groups. Q3. What role do genetics play in CAD? Genetics significantly affect CAD risk. Variants in genes like PCSK9, LDLR, and APOE can influence cholesterol metabolism, inflammation, and vascular function. Epigenetics further modify gene expression in the risk of CAD for a given patient. Q4. Can CAD be detected early without invasive procedures? Yes. Non-invasive imaging techniques like CT angiography, cardiac MRI, and stress testing, combined with biomarker analysis, can detect early signs of CAD without invasive catheterization. Given the general pervasiveness of CT for many different type of trauma or other clinical reasons for abdominal/chest CT acute studies, including additional quantitative analysis of CAD risk might carry significant value in the long run. Q5. What’s next for CAD diagnostics? Future diagnostics will rely heavily on AI, predictive modeling, and integration of multi-modal data including genomics, imaging, and lifestyle tracking. These advancements aim to enable early detection and prevention.

A cardiac computerized tomography (CT) scan – which can also be referred to as a coronary CT angiography or CT angiogram – is an imaging test to view the heart and blood vessels. It is a test that carries few risks and is less invasive than alternative procedures such as an angiogram. In this article, we are going to compare an angiogram with a cardiac CT scan ; a more modern version of the traditional angiogram. What is an angiogram? An angiogram uses X-rays to produce images of the heart’s blood vessels. It is done to check for any restrictions of the blood flow to the heart. An angiogram is also able to diagnose and treat conditions relating to the heart and blood vessels. An angiogram works by guiding a catheter into the artery near the wrist or groin so the contrast dye can be injected to highlight blood vessels within the targeted area. An incision must be made in order to insert the catheter, and this is performed under a local anaesthetic. As the contrast agent flows through the blood vessels, X-rays of the head and chest will be taken from various angles. This is to diagnose or detect any issues affecting a patient’s blood vessels, such as atherosclerosis . What is a CT angiogram? A cardiac CT angiogram is a less invasive version of the traditional angiogram. Utilising state of the art computer tomography scanners, it checks the arteries supplying blood to the heart, and can be used to diagnose conditions such as coronary artery disease (CAD). Using detailed images of the heart and blood vessels, a CT angiogram can accurately highlight any narrowed or congested blood vessels. CT angiography vs angiogram CT angiography is a less invasive version of the traditional angiogram. The main difference between the two procedures is that while a standard angiogram involves a catheter being inserted into the artery and to the area being studied, a CT angiogram does not require the insertion of a catheter. A significant advantage of a CT angiogram over a traditional angiogram is that a CT angiogram is non-invasive. However, for cases of abnormal CT angiogram results - such as one or several blood vessels being blocked or narrowed - a standard angiogram may be required as a follow-up. This is typical when surgery to treat the blockage or narrowing is being considered. Therefore, in some cases, a traditional angiogram can be more beneficial than a CT angiogram, as the doctor can perform an angioplasty right away. How accurate is a CT angiogram compared to a traditional angiogram? Studies have assessed the accuracy of a CT angiogram in comparison to an invasive coronary angiography. A study of CT coronary angiography vs invasive coronary angiography in coronary heart disease (CHD) looked at data from 44 diagnostic studies using invasive coronary angiography as the reference standard and two diagnostic studies using intracoronary pressure measurement as the reference standard. It was found that compared to invasive coronary angiography, CT coronary angiography had a sensitivity of 80% versus 67%, and a specificity of 67% versus 75%. It is advised that CT coronary angiography should be the method of choice for ruling out obstructive coronary stenoses (OCS) to avoid patients having to experience an invasive angiogram. However, this should only be advised for patients with a pretest probability for CHD of 50% or lower. Another study into the accuracy of CT angiography looked at 291 patients with symptoms of coronary artery disease (CAD) who were examined using a 64-slice CT scanner. It was found that CT angiogram identified 85% of patients with significant stenoses and 90% of patients with CAD accurately. The authors concluded that while CT angiography was not ready to replace conventional angiograms entirely, the more modern procedure was nearly as accurate as the traditional angiogram. Cardiac CT Angiograms possess a high amount of accuracy for detecting CHD in patients when compared to a traditional angiogram. Nevertheless, diagnostic accuracy is decreased in diagnosing coronary stents due and severe coronary artery calcification due to its subordinate spatial resolution when compared to invasive angiograms. However, a recent discovery has found an ultrahigh-resolution CT scanner that could be capable of overcoming the limitation of conventional CTA in the environment of severe stents or coronary artery calcification , thus surpassing it’s invasive counterpart. The ultrahigh-resolution CT scanner (UHR-CT) is equipped with 0.25 mm detector rows, half the width than what’s currently on the market (0.5 mm), which will result in twice the spatial resolution. Angiogram risks As with any procedure that involves X-rays, an angiogram exposes you to radiation. Complications from an angiogram are rare. However, potential risks include: Injury to the catheterized artery An allergic reaction to the medication or contrast agent Arrhythmias Bleeding Infection Stroke Heart attack CT angiogram risks Like an angiogram, the X-rays that are involved in a CT angiogram will expose you to radiation. The level of exposure will depend on the machine type that is used. There is some degree of risk related to radiation exposure - such as the potential to harm living tissue and cause cancer - although this risk is small. You are not suitable for a CT angiogram if you are pregnant, as there is the potential it might harm your unborn baby. Other potential complications from a CT angiogram, which are rare, include an allergic reaction to the contrast agent, which could cause symptoms such as: Redness Itching Hives Breathing difficulty Nausea Conclusion A CT angiogram and a traditional angiogram are both effective imaging tests in diagnosing conditions relating to the heart and blood vessels. However, many will favor the non-invasive option of a CT angiogram, which is fast, convenient and relatively painless. A CT angiogram is very accurate in detecting CHD in patients and almost as accurate as a traditional angiogram, allowing doctors to make decisions such as ruling out CAD in patients with a low-to-medium risk of disease. CT scans are already the preferred method of choice for patients with a pretest probability for CHD of 50% or lower. And with the recent introduction of ultrahigh-resolution CT scanners, it could only be a matter of time until conventional invasive angiograms are slowly filtered out and replaced entirely by CT scanners; due to their accuracy, convenience and development in spatial resolution. Try cvi42 for CT scanners  Our fully embedded AI medical imaging software tool cvi 42 , provides unique tools for the evaluations of CAD using cardiac CT . These include: Calcium scoring Coronary arteries Plaque assessment Simplified reporting You can learn more about the capabilities of our leading CT imaging software by downloading a free 42 day trial of cvi 42 . Experience the difference in AI reporting today. For more information or to speak to our customer support team, please contact us. Sources : https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3334923/ https://www.nejm.org/doi/full/10.1056/nejmoa0806576 https://www.docpanel.com/blog/post/significance-coronary-artery-calcification-ct-scan https://www.nhs.uk/conditions/coronary-angioplasty/ https://www.mayoclinic.org/diseases-conditions/arteriosclerosis-atherosclerosis/symptoms-causes/syc-20350569#:~:text=Atherosclerosis%20is%20the%20buildup%20of,leading%20to%20a%20blood%20clot . https://www.nhsinform.scot/tests-and-treatments/scans-and-x-rays/angiography#:~:text=An%20angiogram%20is%20a%20type,as%20it%20moves%20through%20them .

Can quantitative assessment of coronary artery disease (CAD) open the door to greater reproducibility and diagnostic accuracy than qualitative methods? I n a recent review , researchers from the Cardiovascular Imaging Department at the Monzino Cardiology Centre in Milan, Italy, set out to explore the conduction of quantitative assessment of CAD, and its advantages over traditional, qualitative methods. The drawbacks of qualitative techniques were highlighted as limited sensitivity, low reproducibility, and the use of a binary approach to ischemia. The review provided an overview of how myocardial perfusion can be used to assess CAD, as well as indications, challenges, and opportunities to improve patient management. Superior performance of CMR? The review highlighted the three “robust techniques” used for myocardial perfusion in clinical practice as single-photon emission CT (SPECT), positron emission tomography (PET), and cardiovascular magnetic resonance (CMR) . Of the three techniques, CMR and PET had demonstrated superior diagnostic accuracy in most meta-analyses . A fourth method, CT perfusion, has emerged more recently, but the review pointed out that there is less literature containing evidence of this technique’s effectiveness than the first three methods. The limitations of a qualitative approach A comparison of CMR and SPECT in women with suspected CAD from the Clinical Evaluation of Magnetic Resonance Imaging in Coronary Heart Disease (CE-MARC) Trial found that qualitative assessment of ischemia with CMR had greater sensitivity than SPECT in both males and females. However, another study showed that adding semi-quantitative CMR to qualitative stress magnetic resonance myocardial perfusion could produce higher sensitivity, especially in left circumflex lesions detection. There is more evidence to suggest that qualitative perfusion may be insufficient for future clinical practice. The Dan-NICAD study compared the diagnostic accuracy of myocardial perfusion (with visually-assessed SPECT and CMR) against invasive coronary angiography (ICA) with fractional flow reserve (FFR) in patients with suspected CAD by coronary computed tomography angiography (CCTA). It was found that the sensitivity of both CMR and SPECT, which were visually assessed, was low compared with FFR, questioning whether the diagnostic accuracy of qualitative perfusion is sufficient for future clinical needs. Advantages of absolute quantification The review identified the main advantages of the three quantification techniques – which are the dual-bolus protocol, pre-bolus technique, and single bolus with a dual sequence – as being “improved reproducibility and diagnostic accuracy”. It highlighted the findings of a study by researchers from King’s College London which demonstrated that, compared with visual assessment, quantitative perfusion analysis techniques had a higher accuracy for correctly identifying the presence of coronary microvascular dysfunction. Research demonstrating that the capacity to detect functionally significant coronary stenosis is incrementally improved by the successive addition of coronary flow reserve, stress myocardial blood flow (MBF), and relative flow reserve to relative perfusion defect assessments was also presented, along with the CE-MARC trial’s establishment of CMR’s superior diagnostic accuracy over SPECT in CAD. An insufficient level of training has been picked out as the main determinant of the diagnostic accuracy of visual assessment. Using myocardial perfusion to assess CAD The review’s authors stated that in their own experience, as a first-line test in symptomatic patients with a previous history of revascularisation, CMR offered higher cost-effectiveness compared to anatomical assessment with CCTA . The Dan-NICAD study has identified a “huge need” for quantitative perfusion in the setting of obstructive CAD, as the sensitivity of qualitative perfusion alone is not sufficient. Based on this finding and to increase diagnostic accuracy, the authors of the review have begun clinical examinations with quantitative perfusion on top of anatomical assessment with CT and will start assessments using quantitative perfusion with CMR. Improving CAD patient management with absolute quantification Absolute quantification with CMR improves the management of patients with CAD, the review explained. It does this by delineating different levels of ischemia, rather than producing the binary result of qualitative techniques; i.e. a result that is either positive or negative for ischemia. This allows clinicians to differentiate between patients with a mild, moderate, or severe reduction of stress myocardial blood flow (MBF), and also to distinguish between patients with a lower or higher volume of myocardial mass. It is hoped that in the future, quantitative perfusion will be able to identify “an optimal threshold that can be used in clinical practice to distinguish between patients with CAD who require medical therapy and the minority of patients with CAD who require revascularisation”. In terms of diagnosis, the review highlighted research that showed automatically generated, fully quantitative CMR MBF pixel maps to have high diagnostic performance for detecting significant CAD. A study of patients with known or suspected CAD revealed that a strong, independent predictor of adverse cardiovascular outcomes was provided by the automatic measurement of reduced MBF and myocardial perfusion reserve using artificial intelligence quantification of CMR perfusion mapping. Indications for quantitative assessment The authors believe that the first indication for quantitative assessment in patients with a positive CT , and the second indication in patients with complex coronary artery anatomy, “for whom CT is not a useful examination” - is recommended that functional testing with stress CMR is used for these patients. Quantitative assessment is also used by the authors for the prognostic stratification of patients with heart muscle diseases. Challenges and conclusion Among the challenges cited by the review were “a lack of reference values” with “many confounders that can influence MBF thresholds, such as cardiovascular risk factors”. The “cost and lack of availability of perfusion CMR in all centers” were also highlighted. It is concluded that data suggests “quantitative perfusion could be a solution” to the “puzzle” of CAD diagnosis. The authors propose that now “quantitative perfusion has started to be used in a large number of patients, their data must be entered into large registries that track outcomes,” before artificial intelligence is used to establish “robust MBF thresholds that are related to patient outcomes”. To learn more about quantitive perfusion and the many benefits it possesses, from high diagnostic accuracy to fast and automatic analysis, why not try it out for 42 days? Download a free cvi42 trial to discover the many capabilities and benefits of a powerful multi-modality imaging software. Sources: https://www.emjreviews.com/cardiology/article/clinical-efficiency-of-absolute-quantitative-cardiovascular-magnetic-resonance-myocardial-perfusion-for-coronary-artery-disease-s020321/ https://www.researchgate.net/publication/339462630_Clinical_quantitative_cardiac_imaging_for_the_assessment_of_myocardial_ischaemia https://pubmed.ncbi.nlm.nih.gov/24357404/ https://pubmed.ncbi.nlm.nih.gov/26642757/ https://jcmr-online.biomedcentral.com/articles/10.1186/s12968-018-0493-4#:~:text=Our%20study%20demonstrates%20that%20the,in%20the%20identification%20of%20CAD.&text=Rest%20images%20did%20not%20significantly,similarly%20to%20level%2D3%20operators https://pubmed.ncbi.nlm.nih.gov/27894070 https://pubmed.ncbi.nlm.nih.gov/29454767/ https://www.researchgate.net/publication/339273369_The_Prognostic_Significance_of_Quantitative_Myocardial_Perfusion_An_Artificial_Intelligence_Based_Approach_Using_Perfusion_Mapping