Tag: CAC scoring

Next-Generation AI Platform Redefines Radiology Workflow Standards

Posted on by Partner Content

AI is no longer being viewed as a diagnostic aid but as essential medical infrastructure. Nowhere is that more apparent than in lung screening, with Germany and other European Union countries increasingly embedding AI into their lung cancer screening guidelines and pilot programs.

This evolution will be on display at RSNA 2025, where Coreline Soft will introduce its groundbreaking chest AI platform AVIEW 2.0.

  • The solution demonstrates how unified AI automation is fundamentally transforming radiology workflows and elevating diagnostic precision across pulmonary, cardiac, and airway pathologies.

AVIEW 2.0 represents a paradigm shift from task-specific tools to an integrated diagnostic ecosystem. 

  • The platform seamlessly combines lung-cancer screening (LCS), coronary-artery calcium (CAC) scoring, and COPD quantification into a single, continuous analytical pipeline. 

Clinical validation shows radiologists using AVIEW 2.0 achieve 89% increase in case throughput and 60% reduction in interpretation time compared to the previous generation. 

  • This effectively consolidates multi-disease CT assessment into one streamlined, automated workflow.

AVIEW’s clinical foundation extends far beyond pilot studies. The platform has processed over 2.5M cases across 19 countries, establishing itself as a proven solution in diverse healthcare ecosystems. 

  • Most notably, AVIEW has been selected as the AI platform for major government-led lung cancer screening pilots and programs in Germany, France, and Italy.

Beyond Europe, AVIEW solutions are already integrated into major U.S. medical centers, where their clinical reliability has been independently validated in real-world settings…

  • UMass Memorial Medical Center has deployed the system as an integrated platform for LCS, CAC, and COPD diagnosis, supporting full-spectrum thoracic screening in daily radiology operations.
  • Temple Lung Center, 3DR Labs, and ImageCare Radiology have incorporated AVIEW products into their research and diagnostic environments – each adapting AI functions to site-specific workflows and physician preferences.

SOL Radiology, a fast-growing radiologist-owned practice serving communities across California and Illinois, has deployed AVIEW LCS Plus across its outpatient centers and hospital network, leveraging the platform for high-confidence nodule detection, rapid turnaround, and integrated COPD/CAC assessment. 

  • The group reports significant gains in diagnostic efficiency and consistency within one week of implementation, supporting its vision for technology-driven, high-quality community radiology.

With national-scale validation in Europe, clinical adoption across top-tier U.S. institutions, and 2.5M cases processed globally, Coreline Soft is positioning AVIEW 2.0 as the new benchmark for AI-driven thoracic imaging – where efficiency, accuracy, and scalability converge.

The Takeaway

Coreline Soft will conduct an end-to-end AI workflow demonstration in the “Radiology Reimagined” demo zone at RSNA 2025, using real-world clinical scenarios. With AVIEW and HUB, the full pathway – from triage and interpretation to reporting and quality management – will be validated against standards such as IHE and FHIR, allowing attendees to experience integrated flow firsthand. Learn more or book an appointment on Coreline Soft’s website.

Opportunistic Screening Takes Big Step Forward

Posted on by Brian Casey

Opportunistic screening took a big step forward this week with new research in Nature Scientific Reports showing how an AI algorithm from Riverain Technologies was able to calculate coronary artery calcium scores from non-contrast CT scans – with performance close to that of radiologists. 

Opportunistic screening gives radiologists the chance to detect clinical conditions other than those for which the original scan was ordered. 

  • Potential use cases include calculating cardiovascular risk from mammograms or undiagnosed osteoporosis from CT exams.

One of the opportunistic applications with the most potential is CAC scoring from CT scans. 

  • CAC scores are a good marker for future cardiovascular risk. But it can be time-consuming to perform separate cardiac CT scans just to acquire CAC data when thousands of abdominal and thoracic CT studies are conducted every day and could serve just as well.

Riverain’s ClearRead CT CAC algorithm uses AI to analyze non-contrast CT exams and produce Agatston scores, the reference standard for CAC analysis. 

  • Previous research found Agatston scores to be predictive for both cardiovascular and all-cause mortality, but generating the scores requires some manual involvement from clinicians. 

In the new study, Mass General Brigham researchers compared ClearRead CT CAC’s performance to ground-truth calculations from radiologists in 491 patients who got non-contrast CT scans at five U.S. hospitals in 2022 and 2023. Researchers found…

  • CAC score agreement between AI and radiologists was high, with a kappa of 0.959 (1.0 is perfect agreement).
  • The association remained strong regardless of sex, age, race, ethnicity, and CT scanner model, with kappa higher than 0.90 for all groups except “other race.” 
  • The AI model’s CAC scores from non-gated CT scans were similar to those from gated cardiac CT exams (kappa = 0.906), which are generally considered the gold standard for cardiac CT but are more complex to perform.
  • The model’s kappa for gated CT exams compared favorably to recent research conducted with other commercially available algorithms.

The results are a boost for opportunistic screening but in particular for Riverain, which got FDA clearance for ClearRead CT CAC in December 2024 and offers the solution as part of its ClearRead CT suite.

The Takeaway

The new results show that opportunistic screening is moving beyond the research phase and that the opportunity could be now for real-world clinical use. 

CAC Research Leads Imaging at AHA 2025

Posted on by Brian Casey

The 2025 American Heart Association annual conference wraps up today, and cardiac imaging has been a major focus in New Orleans. In particular, research has highlighted imaging’s power to predict future cardiac events – and guide treatment to prevent them. 

Coronary artery calcium scoring with CT is a great example, as CAC scores can predict not only cardiovascular but also all-cause mortality. 

  • Another common theme at AHA 2025 has been opportunistic screening, in which data from imaging exams acquired for other clinical indications can be used to detect osteoporosis, cardiovascular disease, and other issues. 

Check out the items below for some of the hottest imaging topics at AHA 2025, and for a deeper dive into non-imaging news from New Orleans, be sure to visit our Cardiac Wire sister site. 

News from the show’s first three days include…

  • A massive study of 40k people found that those with CT-derived CAC scores greater than 0 were 2X-3X more likely to die from any cause than people without any CAC – and more died of causes other than cardiovascular disease. Also, 8.5% of patients had other significant findings. 
  • Community health personnel on a Native American reservation were trained to perform point-of-care screening echocardiography assisted by Us2.ai’s AI algorithms. 
  • Us2.ai’s algorithm was also used with transthoracic echo in the SCAN-MP study to detect transthyretin amyloid cardiomyopathy, a cause of heart failure. 
  • Treadmill stress tests fell short compared to CCTA in screening older master’s athletes for ischemia that could lead to sudden cardiac death.
  • A program in Brazil that used echocardiography to screen schoolchildren for latent rheumatic heart disease led to lower prevalence rates after 10 years (2.5% vs. 4.5%). 
  • Patients with hypertrophic cardiomyopathy who had higher levels of myocardial fibrosis on cardiac MRI were almost 6X more likely to have adverse events over eight years.
  • HeartLung Technologies’ AI tool predicted CAC presence on CT scans in 2.1k participants in the MESA study with higher AUC than other tools (AUC = 0.73 vs. 0.68).
  • Another study used HeartLung’s AI to analyze CAC scans to detect myosteatosis – a sign of systemic metabolic dysfunction – which predicted atrial fibrillation and heart failure. 
  • A program promoting CAC scoring to an urban population brought in people for screening who might have been missed through physician referral. 

The Takeaway

This week’s news from AHA 2025 shows medical imaging’s contribution to early detection of cardiovascular disease – the leading cause of death worldwide. CT-based CAC scoring has especially promising potential, not only for heart disease but also other conditions through opportunistic screening.

Opportunistic Calcium Scoring Shifts to Abdomen

Posted on by Brian Casey

Most of the recent research on calcium scoring has focused on calcium in the coronary arteries and its link to cardiovascular disease. But a new study in American Heart Journal used abdominal CT scans with AI analysis for opportunistic measurement of abdominal aortic calcium to predict cardiac events – possibly earlier than CAC scores.

CT-derived CAC scores have become a powerful tool for predicting cardiovascular disease, helping physicians determine when to begin preventive therapy with treatments like statins.

  • CAC scores can be generated from dedicated cardiac CT scans, or even lung screening exams as part of a two-for-one test. 

Abdominal CT represents another promising area for calculating calcium. 

  • Previous research has found that atherosclerosis in the abdominal aorta may occur before its development in the coronary arteries, creating the opportunity to detect calcium earlier. 

Researchers from NYU Langone did just that in the new study, performing abdominal and cardiac CT scans in 3.6k patients and using an AI algorithm they developed in partnership with Visage Imaging to calculate AAC. They found that over an average three-year follow-up period … 

  • AI analysis of AAC severity was positively associated with CAC.
  • AAC could be used to rule out the presence of CAC relative to two versions of the PREVENT score (AUC=0.701 and 0.7802). 
  • The presence of AAC was associated with a higher adjusted risk of major adverse cardiovascular events (HR=2.18).
  • A doubling of the AAC score was linked to 11% higher risk of MACE.

The Takeaway

The new results are an exciting demonstration of opportunistic screening’s value, especially given the volume of abdominal CT scans performed annually. AI analysis of routinely acquired abdominal CT could give radiologists a tool for detecting heart disease risk even earlier than what’s possible with CAC scoring.

CAC Scoring Shines at ACC 2025

Posted on by Brian Casey

The American College of Cardiology’s annual meeting is wrapping up today in Chicago, and new research into coronary artery calcium scoring has been one of cardiac imaging’s top trends at McCormick Place.

CAC scoring has been around for ages as a way to detect and quantify calcium buildup in the coronary arteries based on data from non-contrast CT scans. 

  • But it’s only been in recent years that CAC scoring has come into its own as a tool for predicting risk of mortality and major cardiac events – in some cases years before they happen. 

Clinicians are learning that they can use CT-generated CAC scores to estimate future risk and guide interventions to reduce it, such by prescribing statins or behavior modifications. 

Research presented at ACC 2025 underscored CAC scoring’s potential …

  • In the CLARIFY CAC screening program, researchers found a 6.2% rate of thoracic aneurysm, indicating a need for screening and prevention.
  • CAC scores of 0 were more common in women than men (49% vs. 23%), but there was no statistically significant difference in non-calcified plaque rates between genders.
  • Researchers found moderate accuracy (AUC range=0.60-0.73) for a method of generating CAC scores from 12-lead ECG data rather than non-contrast CT scans.
  • Bunkerhill Health’s I-CAC algorithm was used to generate automated CAC scores for 200 patients. After six months, patients with scores >400 had a 17% rate of cardiac events and 11% all-cause mortality. 
  • A commonly used measure for low-value care based on administrative claims classified too many CAC tests as inappropriate, with a positive predictive value of only 43%.
  • A case study focused on the paradox of a 59-year-old healthy triathlete with a CAC score of 780, possibly due to chronic coronary stress from high-endurance exercise. Invasive testing was deferred in favor of medical therapy due to his low cardiac risk.
  • On the other hand, a literature review of 19.4k people found no statistically significant difference in CAC scores between endurance athletes and healthy controls.
  • Non-calcified plaque in patients with CAC scores of 0 was common (26%) in residents of rural Appalachia, indicating high risk of rupture and suggesting the limitation of relying on CAC scores. 
  • A Sunday debate discussed whether CAC scoring should be added to mammography and colon cancer screening, or reserved as a decision aid. 

The Takeaway

The studies from ACC 2025 show that CAC scoring has a bright future – bright enough that it’s generating heightened interest from cardiology. New CAC scoring tools arriving on the market should improve its predictive value even more. 

More Support for Cardiac CT’s Value

Posted on by Brian Casey

A new study in Radiology offers more support for the value of CT-based coronary artery calcium scoring, finding that people with higher CAC scores had worse outcomes, and suggesting that those with scores of 0 could potentially avoid invasive coronary angiography. 

Evidence has been building that by measuring calcium buildup in the heart, CAC scores can predict clinical outcomes, in particular major adverse cardiac events, particularly in patients with stable chest. 

  • Studies ranging from MESA to SCOT-HEART to PROMISE have found that patients with CAC scores of 0 have MACE risk that’s lower than 2% – meaning they could be discharged without further invasive workup. 

The new study is an update to the DISCHARGE trial, which in 2022 published results comparing a CT-first evaluation strategy to one with invasive coronary angiography. The new study investigates the value of CAC scoring by analyzing its prognostic power in patients with stable chest pain who were referred for invasive coronary angiography. 

  • The DISCHARGE study is notable for its diversity – 26 clinical centers in 16 European countries – as well as its use of 13 different models of CT scanners from all four major CT OEMs from 2015 to 2019. 

In all, 1.7k patients were studied, and CAC scores were generated based on CT scans and used to stratify patients into one of three groups; they were then followed for 3.5 years and rates of MACE were correlated to CAC levels, finding … 

  • Patients with CAC scores of 0 had the lowest rates of MACE compared to those with scores of 1-399 and ≥400 (0.5% vs. 1.9% & 6.8%)
  • Rising CAC scores corresponded to higher prevalence of obstructive coronary artery disease (0=4.1% vs. 1-399=29.7% & ≥400=76%)
  • Revascularization rates rose with CAC scores (0=1.7% vs. ≥400=46.2%)

While the authors steered away from commenting on the study’s impact on clinical management, the findings – if confirmed with additional studies – suggest that stable chest pain patients may not need invasive coronary angiography.

  • And in another interesting wrinkle to the study, the researchers pointed out that 57% of the DISCHARGE study’s patient population were women, a fact that addresses sex bias in previous research. 

The Takeaway

The DISCHARGE study’s findings are yet another feather in the cap for cardiac CT, with higher CAC scores indicating the long-term presence of atherosclerosis. Should they be confirmed, individuals with stable chest pain in the future will benefit from less invasive – and less expensive – management.

CT Flexes Muscles in Heart

Posted on by Brian Casey

CT continues to flex its muscles as a tool for predicting heart disease risk, in large measure due to its prowess for coronary artery calcium scoring. In JAMA, a new paper found CT-derived CAC scores to be more effective in predicting coronary heart disease than genetic scores when added to traditional risk scoring. 

Traditional risk scoring – based on factors such as cholesterol levels, blood pressure, and smoking status – has done a good job of directing cholesterol-lowering statin therapy to people at risk of future cardiac events. But these scores still provide an imprecise estimate of coronary heart disease risk. 

Two relatively new tools for improving CHD risk prediction are CAC scoring from CT scans and polygenic risk factors, based on genetic variants that could predispose people toward heart disease. But the impact of either of these tools (or both together) when added to traditional risk scoring hasn’t been investigated. 

To answer this question, researchers analyzed the impact of both types of scoring on participants in the Multi-Ethnic Study of Atherosclerosis (1,991 people) and the Rotterdam Study (1,217 people). CHD risk was predicted based on both CAC and PRS and then compared to actual CHD events over the long term. 

They also tracked how accurate both tools were in reclassifying people into different risk categories (higher than 7.5% risk calls for statins). Findings included: 

  • Both CAC scores and PRS were effective in predicting 10-year risk of CHD in the MESA dataset (HR=2.60 for CAC score, HR=1.43 for PRS). Scores were slightly lower but similar in the Rotterdam Study
  • The C statistic was higher for CAC scoring than PRS (0.76 vs. 0.69; 0.7 indicates a “good” model and 0.8 a “strong” model) 
  • The improved accuracy in reclassifying patient risk was statistically significant when CAC was added to traditional factors (half of study participants moved into the high-risk group), but not when PRS was added  

The Takeaway 

This study adds to the growing body of evidence supporting cardiac CT as a prognostic tool for heart disease, and reinforces CT’s prowess in the heart. The findings also support the growing chorus in favor of using CT as a screening tool in cases of intermediate or uncertain risk for future heart disease.

Chest CT’s Untapped Potential

Posted on by Jake Fishman

A new AJR study out of Toronto General Hospital highlighted the largely-untapped potential of non-gated chest CT CAC scoring, and the significant impact it could have with widespread adoption.

Current guidelines recommend visual CAC evaluations with all non-gated non-contrast chest CTs. However, these guidelines aren’t consistently followed and they exclude contrast-enhanced chest CTs.

The researchers challenged these practices, performing visual CAC assessments on 260 patients’ non-gated chest CT exams (116 contrast-enhanced, 144 non-contrast) and comparing them to the same patients’ cardiac CT CAC scores (performed within 12-months) and ~6-year cardiac event outcomes.

As you might expect, visual contrast-enhanced and non-contrast chest CT CAC scoring:  

  • Detected CAC with high sensitivity (83% & 90%) and specificity (both 100%)
  • Accurately predicted major cardiac events (Hazard ratios: 4.5 & 3.4)
  • Had relatively benign false negatives (0 of 26 had cardiac events)
  • Achieved high inter-observer agreement (κ=0.89 & 0.95)

The Takeaway

Considering that CAC scores were only noted in 37% of the patients’ original non-contrast chest CT reports and 23% of their contrast-enhanced chest CT reports, this study adds solid evidence in favor of more widespread CAC score reporting in non-gated CT exams.

That might also prove to be good news for the folks working on opportunistic CAC AI solutions, noting that AI has (so far) seen the greatest adoption when it supports processes that most radiologists are actually doing.

UCSF Automates CAC Scoring

Posted on by Jake Fishman

UCSF is now using AI to automatically screen all of its routine non-contrast chest CTs for elevated coronary artery calcium scores (CAC scores), representing a major milestone for an AI use case that was previously limited to academic studies and future business strategies.

UCSF’s Deployment – UCSF becomes the first medical center to deploy the end-to-end AI CAC scoring system that it developed with Stanford and Bunkerhill Health earlier this year. The new system automatically identifies elevated CAC scores in non-gated / non-contrast chest CTs, creating an “opportunistic screening pathway” that allows UCSF physicians to identify high-CAC patients and get them into treatment.

Why This is a Big Deal – Over 20m chest CTs are performed in the U.S. annually and each of those scans contains insights into patients’ cardiac health. However, an AI model like this would be required to extract cardiac data from the majority of CT scans (CAC isn’t visible to humans in non-gated CTs) and efficiently interpret them (there’s far too many images). This AI system’s path from academic research to clinical deployment seems like a big deal too.

The Commercial Impact – Most health systems don’t have the AI firepower of Stanford and UCSF, but they certainly produce plenty of chest CTs and should want to identify more high-risk patients while treatable (especially if they’re also risk holders). Meanwhile, there’s growing commercial efforts from companies like Cleerly and Nanox.AI to create opportunistic CAC screening pathways for all these health systems that can’t develop their own CAC AI workflows (or prefer not to).

Silent Atherosclerosis

Posted on by Jake Fishman

A new study in Circulation used coronary CTA scans and CAC scoring to reveal a surprisingly high prevalence of “silent” coronary artery atherosclerosis in the general population, suggesting that this could “lay the foundation” for future CT-based cardiac screening programs.

The Study – The researchers analyzed CCTA and CAC exams from 25k randomly recruited Swedish participants (50-64yrs, none w/ known coronary heart disease) finding that:

  • 42% had CCTA-detected atherosclerosis
  • 8.3% had noncalcified plaques
  • 5.2% had significant stenosis
  • 1.9% had serious coronary artery diseases
  • All participants with >400 CAC scores had atherosclerosis (yes, 100%), and 45.7% had significant stenosis
  • Some participants with 0 CAC scores had atherosclerosis (5.5%) and significant stenosis (0.4%)
  • So, CAC-based screening might still miss some at-risk patients

The Takeaway – 2021 brought a notable surge in academic and business efforts focused on CT-based cardiac screening, and this study’s revelation about “silent” atherosclerosis in the general population suggests that cardiac screening’s momentum will continue.

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