Cardiovascular magnetic resonance measurements identified a hemodynamic pattern associated with death or heart-transplant referral or listing in people with Fontan circulation, according to a retrospective study of 182 patients followed at a moderate-altitude center. Patients who later experienced the composite outcome had a lower superior vena cava flow index than those who did not. In time-to-event analysis, each 0.1-liter-per-minute-per-square-meter increase in the indexed flow was associated with a 30% lower hazard of the outcome.

The association remained in an exploratory model that also included ventricular ejection fraction, but the researchers said the estimate requires prospective, multicenter validation before clinical application. The cohort comprised people who had undergone Fontan palliation between 1999 and 2021 at a tertiary institution approximately 5,118 feet above sea level. Fontan circulation passively directs systemic venous blood into the pulmonary arteries without the support of a sub-pulmonary ventricle.

Eligible participants had a clinically indicated CMR examination at least five years after Fontan completion, a threshold selected to match the center’s routine surveillance practice. For patients with multiple examinations, investigators used the last CMR obtained before an outcome or censoring. Most participants, 173 of 182, or 95%, had an extracardiac conduit Fontan circulation, and 76, or 42%, underwent a Damus–Kaye–Stansel anastomosis.

At CMR, the median body surface area was 1.43 square meters, with an interquartile range of 1.16 to 1.69 square meters. The median age at Fontan completion was 3.2 years, and the median interval between surgery and imaging was 10.9 years. Median follow-up after CMR was 4.7 years, while participants’ median home elevation was 5,221 feet above sea level.

Hypoplastic left heart syndrome was the most common underlying diagnosis, accounting for 35% of the cohort, followed by tricuspid atresia at 30%. The systemic ventricle was left-dominant in 53% and right-dominant in 47%. Magnetic resonance examinations were performed on 1.5- or 3.0-tesla scanners, with cine imaging used to assess ventricular function and phase-contrast sequences used to measure blood flow.

The primary endpoint combined death with referral or listing for heart transplantation. Fourteen patients, or 7.7% of the cohort, met that endpoint during follow-up: two died and 12 were referred or listed for transplantation. Among patients who experienced the outcome, the median time from CMR to the first qualifying event was 1.2 years, with an interquartile range of 0.5 to 2.5 years.

The median superior vena cava flow index was 0.54 liters per minute per square meter among patients with the primary outcome, compared with 0.82 liters per minute per square meter among those without it; the difference was statistically significant, with a p-value of 0.011. The superior vena cava-to-ascending-aorta flow ratio was also lower in the event group, with medians of 0.22 and 0.30, respectively. Several other CMR flow measures did not differ significantly between patients with and without the primary outcome.

These included flow indices in the ascending aorta, right pulmonary artery, left pulmonary artery and inferior vena cava, as well as calculated systemic-to-pulmonary collateral flow. Receiver operating characteristic analysis indicated that superior vena cava flow index discriminated between patients who met the endpoint and those who did not with an area under the curve of 0.74 and a 95% confidence interval of 0.56 to 0.92. A data-derived threshold of 0.66 liters per minute per square meter, selected using the Youden index, yielded 70% sensitivity and 75% specificity.

Kaplan–Meier curves showed significantly poorer event-free survival among patients below that threshold. Because the threshold and discrimination measures came from the same cohort, they are exploratory rather than externally validated clinical cutoffs. Univariable Cox proportional hazards regression found a hazard ratio of 0.70 for each 0.1-liter-per-minute-per-square-meter increase in superior vena cava flow index, with a 95% confidence interval of 0.50 to 0.92 and a p-value of 0.008.

Right-dominant ventricular morphology was also associated with a higher hazard than left-ventricular dominance, with a hazard ratio of 3.21, a 95% confidence interval of 1.00 to 10.29 and a p-value of 0.049. The investigators constructed a two-variable Cox model containing superior vena cava flow index and ejection fraction. Each one-percentage-point increase in ejection fraction was associated with an adjusted hazard ratio of 0.92, with a 95% confidence interval of 0.86 to 0.97.

Because only 14 primary events occurred, the multivariable analysis was deliberately restricted and was intended to test whether the flow association persisted beyond ventricular function rather than develop a full prediction model. Internal bootstrap analysis using 2,500 resamples produced a median hazard ratio of 0.71 for superior vena cava flow index and 0.92 for ejection fraction, close to the original adjusted estimates. Collinearity between the two variables was negligible, with a Spearman absolute correlation below 0.1, an R-squared value of 0.008 and a variance inflation factor of 1.01.

Tests did not indicate violation of the proportional-hazards assumption. Ventricular measures also differed according to morphology: in the right-dominant subgroup, patients with events had larger indexed ventricular volumes and lower ejection fraction than those without events, whereas comparable differences were not statistically significant in the smaller left-dominant event subgroup. The study does not establish why lower superior vena cava flow was associated with poorer outcomes.

One proposed explanation is that chronic hypobaric exposure at moderate altitude promotes pulmonary vasoconstriction and raises pulmonary vascular resistance, potentially restricting passive flow through the Fontan pathway. However, pulmonary vascular resistance was not directly measured, and the cohort included no sea-level comparator, so the study cannot determine whether altitude caused the observed hemodynamic pattern. Other possible contributors include anatomical differences in the superior vena cava, systemic venovenous collateral vessels that divert blood around the pulmonary vascular bed, and differences in preload or single-ventricle filling.

The findings therefore associate reduced indexed flow with an unfavorable hemodynamic state rather than demonstrate a specific underlying mechanism. Important limitations constrain the results. The retrospective, single-center design creates the possibility of selection bias, and clinically performed CMR examinations were not acquired at standardized surveillance intervals.

Selecting the last scan before an outcome or censoring may introduce reverse-causation bias because patients approaching clinical deterioration could have been imaged nearer the event. Clinically relevant potential confounders—including functional class, cardiopulmonary exercise capacity, resting oxygen saturation, natriuretic peptide levels, catheterization-derived Fontan pressure and pulmonary vascular resistance, pulmonary vasodilator therapy, arrhythmia burden and the severity of liver disease—were unavailable or not incorporated. The small number of events also leaves the multivariable estimates vulnerable to overfitting despite the deliberately parsimonious model and bootstrap resampling.

Furthermore, the predominance of fenestrated extracardiac conduit Fontan circulation limits generalizability to other surgical configurations. The results position superior vena cava flow index as a candidate prognostic marker that may complement ventricular size and ejection fraction in longitudinal assessment of Fontan circulation, but they do not establish a clinical measurement rule or treatment strategy. Prospective, multicenter studies comparing cohorts across elevations would be needed to test the temporal relationship, determine whether altitude modifies the association, and establish external validity.

The authors also identified four-dimensional flow CMR as a possible tool for characterizing three-dimensional flow patterns and energy loss within the Fontan pathway. Further work could compare imaging signatures with exercise physiology, biomarkers of end-organ dysfunction and pulmonary vascular imaging. Until those studies are completed, the association between reduced superior vena cava flow and adverse outcomes should be regarded as an exploratory finding that requires independent validation.

Subject of Research: Association between CMR-derived blood flow and adverse outcomes in people with Fontan circulation

Article Title: Cardiovascular magnetic resonance–derived hemodynamics predict adverse outcomes after Fontan palliation

Article References: Platnick, C., Frank, B., Romanowicz, J., Gonzalez De Alba, C., Chase, M., Umer, A., Chaudhuri, N. R., Awori, J., Chauhan, D., Mascio, C. E., Udassi, J. P., & Hedjazi Moghari, M. (2026). Cardiovascular magnetic resonance–derived hemodynamics predict adverse outcomes after Fontan palliation. Frontiers in Cardiovascular Medicine, 13, Article 1937933. https://doi.org/10.3389/fcvm.2026.1937933

Image Credits: AI Generated

DOI: 10.3389/fcvm.2026.1937933

Keywords: Fontan circulation, cardiovascular magnetic resonance, superior vena cava flow, heart transplantation, congenital heart disease, risk stratification, ventricular function, moderate altitude, flow quantification, retrospective cohort, Cardiovascular, magnetic

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Editor’s Note: Astrobites is a graduate-student-run organization that digests astrophysical literature for undergraduate students. As part of the partnership between the AAS and astrobites, we occasionally repost astrobites content here at AAS Nova. We hope you enjoy this post from astrobites; the original can be viewed at astrobites.org.

Title: Probing the IMF in the Early Universe — Direct Measurements in the Boötes I UFD with JWST/NIRCam
Authors: Keyi Ding et al.
First Author’s Institution: University of Maryland
Status: Published in ApJ

The Stellar Initial Mass Function

A fundamental concept in astronomy is the stellar initial mass function (IMF). The IMF describes the number of stars of each mass that form from a single birth cloud. If the IMF has a negative slope, it means most stars are low in mass; if it has a positive slope, it means most stars are high in mass. Figure 1 shows some examples of commonly used IMFs, all of which have a negative slope, since we see far more low-mass stars than high-mass stars in the Milky Way. You may notice that several models deviate from a straight line at about 0.5 solar mass. This point, known as the turnover or critical mass, is crucial in determining the exact shape of the IMF.

For a relatively simple concept, the IMF is shaped by incredibly complicated underlying physical mechanisms. Things like turbulence, magnetic fields, and chemical enrichment all play a role in shaping the observed IMF. Additionally, the IMF is a pretty fundamental quantity. An enormous amount of astronomy research relies on assumptions made about the IMF. For example, since most stars are low in mass, and low-mass stars are dimmer, astronomers use the IMF to convert the amount of light in a galaxy to the number of stars; if there are more or fewer low-mass stars than we expect, our measurements will be wrong.

A big question surrounding the IMF is whether or not it’s universal. In the Milky Way, astronomers have been able to measure the IMF accurately, and they have found that it seems to be the same regardless of which bunch of stars we use to measure it.¹ However, we know that galaxies in the early universe were very different compared to today. Things get tricky when you acknowledge that most measurements made of early-universe galaxies rely on modeling tools that are entirely reliant on assuming an IMF. This gnarly little detail makes measuring the IMF in the early universe especially valuable to astronomers.

What Makes Ultra-Faint Dwarfs So Special?

Today’s authors attempt to measure the early-universe IMF using a local relic, an ultra-faint dwarf galaxy (UFD). You might describe UFDs as “incredibly funky little galaxies.” They’re much less massive than the Milky Way, with about 10,000 times less stellar mass. What stars they do have tend to be very old and metal poor. The nature of UFDs has led many astronomers to think of them as fossils: relatively untouched galaxies formed in the early universe. Since we think UFDs are fossils of earlier galaxies, measuring the IMF in a UFD tells us whether the IMF was the same in the early universe as it is today. The authors focus on Boötes I, a relatively luminous UFD orbiting the Milky Way. Figure 2 shows Boötes I as seen by the Sloan Digital Sky Survey.

The IMF in Boötes I

Measuring the IMF can get tricky — it’s typically pretty difficult to measure the mass of each individual star in a galaxy. Thankfully, Boötes I is close enough that we can do exactly that! Using JWST’s NIRCam instrument, today’s authors obtain imaging of Boötes I that is sensitive enough to extract roughly 10,000 stars belonging to the galaxy.

To measure the IMF from the observed population of stars, the authors use a modified version of Starwave, a Bayesian inference tool. In short, the tool takes in some assumptions about the population of stars in the galaxy, then generates many potential color–magnitude diagrams for various parameter selections. You can then assess how well each simulated color–magnitude diagram fits the observed data, thus determining likely parameters for the stellar population. The authors apply their tool for three different IMF models, testing how close the IMF in Boötes I is to that of the Milky Way. This allows them to determine how well the IMF compares to that of the Milky Way, which is typically thought of as a broken power law or log-normal distribution. If the IMF in Boötes I aligns with the Milky Way’s IMF, we’ll have a solid piece of evidence for a truly invariant IMF across cosmic time, allowing astronomers to rest easy knowing our modeling efforts haven’t been bunk this whole time.

So… What Did We Learn?

The authors find that a single power law can be ruled out to a good degree of confidence. This is good, as Milky Way studies show undeniable evidence of a turnover in the distribution. The broken power law and log-normal models both fit the observed data relatively well, aligning well with Milky Way–derived IMFs. All in all, they find solid evidence for an invariant IMF in the early universe.

However, they are unable to say with absolute certainty that the IMF is invariant. Given that their data are nearly perfect (that is, it’s pretty much impossible to get better data for Boötes I), the authors emphasize that a larger sample of UFD IMFs is needed to truly rule out an invariant IMF, but we’re certainly taking steps in the right direction! As the age-old saying goes, “more data are needed!”

Original astrobite edited by Maggie Verrico.

1. Editor’s Note: The Milky Way IMF may vary from star cluster to star cluster; as described in this AAS Nova highlight from 8 July 2026, recent research using data from the Gaia spacecraft has found evidence for IMF variation in our galaxy. ︎

About the author, Drew Lapeer:

Drew is a first-year PhD student at the University of Massachusetts Amherst. They are broadly interested in the evolution of galaxies, with a focus on the impact of cosmic feedback on the galactic ecosystem. In their free time, they enjoy reading, rock climbing, hiking, and baking!

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