Tag: heart imaging

Unpacking Heartflow IPO’s Lessons for AI Firms

Posted on by Brian Casey

Cardiac AI specialist Heartflow went public last week, and the IPO was a watershed moment for the imaging AI segment. The question is whether Heartflow is blazing a path to be followed by other AI developers or if the company is a shooting star that’s more likely to be admired from afar than emulated.

First the details: Heartflow went public August 8, raising $317M by issuing 16.7M shares at $19 each – and finishing up 50% for the day. 

  • The IPO beat analyst expectations, which originally estimated gross proceeds of $215M, and put the company’s market capitalization at $2.5B – well within the mid-cap stock category. 

So what’s so special about this IPO? Heartflow’s flagship product is FFRCT Analysis, which uses AI-based software to calculate fractional flow reserve – a measure of heart health – from coronary CT angiography scans. 

  • This eliminates the need for an invasive pressure-wire catheter to be threaded into the heart.

Heartflow got an early start in the FFR-CT segment by nabbing FDA clearance for Heartflow FFRCT Analysis in 2014, and since then has been the single most successful AI company in winning reimbursement from both CMS and private payors.

  • In fact, a 2023 analysis of AI reimbursement found that FFRCT Analysis was the top AI product by number of submitted CPT claims, at 67.3k claims – over 4X more than the next product on the list.

That’s created a revenue stream for Heartflow that clearly bucks the myth that clinicians aren’t getting paid for AI.

  • And in an IPO filing with the SEC, Heartflow revealed how reimbursement is driving revenue growth, which was up 44% in 2024 over 2023 ($125.8M vs. $87.2M, respectively). 

But it’s not all sunshine and rainbows at the Mountain View, California company, which posted significant net losses for both 2024 and 2023 ($96.4M and $95.7M).

  • As a public company, Heartflow may have a shorter leash in getting to profitability had it remained privately held.

But the bigger picture is what Heartflow’s IPO means for the imaging AI segment as a whole. 

  • It’s easily the biggest IPO by a pure-play imaging IT vendor in years, and dispels the conventional wisdom that investors are shying away from the sector.

The Takeaway

Heartflow’s IPO shows that in spite of clinical AI’s shortcomings (slow adoption, sluggish reimbursement, etc.), it’s still generating significant investor interest. The company’s focus on achieving both clinical and financial milestones (i.e. reimbursement) should be an example for other AI developers.

Imaging News from ESC 2024

Posted on by Brian Casey

The European Society of Cardiology annual meeting concluded on September 2 in London, with around 32k clinicians from 171 countries attending some 4.4k presentations. Organizers reported that attendance finally rebounded to pre-COVID numbers. 

While much of ESC 2024 focused on treatments for cardiovascular disease, diagnosis with medical imaging still played a prominent role. 

  • Cardiac CT dominated many ESC sessions, and AI showed it is nearly as hot in cardiology as it is in radiology. 

Major imaging-related ESC presentations included…

  • A track on cardiac CT that underscored CT’s prognostic value:
    • Myocardial revascularization patients who got FFR-CT had lower hazard ratios for MACE and all-cause mortality (HR=0.73 and 0.48).
    • Incidental coronary artery anomalies appeared on 1.45% of CCTA scans for patients with suspected coronary artery disease.
  • AI flexed its muscles in a machine learning track:
    • AI of low-dose CT scans had an AUC of 0.95 for predicting pulmonary congestion, a sign of acute heart failure. 
    • Echocardiography AI identified HFpEF with higher AUC than clinical models (0.75 vs. 0.69).
    • AI of transthoracic echo detected hypertrophic cardiomyopathy with AUC=0.85.

Another ESC hot topic was CT for calculating coronary artery calcium (CAC) scores, a possible predictor of heart disease. Sessions found … 

  • AI-generated volumetry of cardiac chambers based on CAC scans better predicted cardiovascular events than Agatston scores over 15 years of follow-up in an analysis of 5.8k patients from the MESA study. 
  • AI-CAC with CT was comparable to cardiac MRI read by humans for predicting atrial fibrillation (0.802 vs. 0.798) and stroke (0.762 vs. 0.751) over 15 years, which could give an edge to AI-CAC given its automated nature.
  • An AI algorithm enabled opportunistic screening of CAC quantification from non-gated chest CT scans of 631 patients, finding high CAC scores in 13%. Many got statins, while 22 got additional imaging and 2 intervention.
  • AI-generated CAC scores were also highlighted in a Polish study, detecting CAC on contrast CT at a rate comparable to humans on non-contrast CT (77% vs. 79%), possibly eliminating the need for additional non-contrast CT.  

The Takeaway

This week’s ESC 2024 sessions demonstrate the vital role of imaging in diagnosing and treating cardiovascular disease. While radiologists may not control the patients, they can always apply knowledge of advances in other disciplines to their work.

Cardiac Imaging in 2040

Posted on by Brian Casey

What will cardiac imaging look like in 2040? It will be more automated and preventive, and CT will continue to play a major – and growing – role.

That’s according to an April 11 article in Radiology in which Dr. David Bluemke and Dr. João Lima look into the future and offer a top 10 list of major developments in cardiovascular imaging in 2040.

Cardiovascular disease carries a massive medical burden, with over 800,000 myocardial infarctions occurring annually in the US alone. By 2030 almost one-third of deaths worldwide are expected to be due to cardiovascular disease.

Multiple different imaging modalities are adept at identifying both ischemic and nonischemic heart disease, but CT has risen to the top for ischemic imaging, making “quantum” advances in the last decade thanks to its growing prowess in the coronary arteries.

CT’s advances have been so great that the modality occupies seven of the top 10 spots on Bluemke and Lima’s list. In brief, they see: 

  • Coronary CTA becoming totally automated, a development that will no doubt benefit AI developers like HeartFlow (see below).
  • CCTA becoming a preventive tool rather than a gatekeeper to interventional cardiology (also hinted at in a recent study from Denmark). For example, CCTA will be used to track the effectiveness of statin therapy
  • Photon-counting CT flexing its muscles for coronary artery evaluation and routine plaque characterization and quantification
  • Next-generation cardiac CT becoming more like MRI
  • Next-generation cardiac MRI becoming more like CT
Table of Top 10 Cardiovascular Imaging Developments by 2040

They also see a major growing role for software-assisted cardiac CT with AI and other tools. Software-based automation has simplified the “postprocessing nightmares” once common with coronary CT, making it “wonderfully ordinary” to perform. 

The Takeaway

Bluemke and Lima offer a fascinating glimpse of cardiac imaging’s future. But one area they don’t touch on is whether CT’s rising prominence means radiologists will start taking back turf in heart imaging once ceded to cardiologists. Heart specialists haven’t taken over cardiac CT in the same way that they monopolized echocardiography and nuclear cardiology. Could we be seeing a renaissance of radiology in the heart?

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