This week's episode features special Guest Host Victoria Delgado, as she interviews author Qiang Zhang and Greg (who was the editorialist and handling editor) as they discuss the article "Towards Replacing Late Gadolinium Enhancement with Artificial Intelligence Virtual Native Enhancement for Gadolinium-Free Cardiovascular Magnetic Resonance Tissue Characterization in Hypertrophic Cardiomyopathy." Dr. Carolyn Lam: Welcome to Circulation on the Run, your weekly podcast summary and backstage pass to the Journal and its editors. We're your cohost. I'm Dr. Carolyn Lam, associate editor from the National Heart Center and Duke National University of Singapore. Dr. Greg Hundley: And I'm Dr. Greg Hundley, director of the Pauley Heart Center at VCU Health in Richmond, Virginia. And Carolyn, this week's feature actually is a magnetic resonance imaging paper, which you know, of course, I'm very fond of. And these authors have come up with a new methodology to get information equivalent to a late gadolinium-enhanced exam without administering gadolinium. But before we get to that feature discussion, how about we start in with some of the other articles in this issue? Dr. Carolyn Lam: Yep. Dr. Greg Hundley: Well, how about if I go first? So Carolyn, the first paper I'm going to discuss is from Dr. Paul Welsh from the University of Glasgow, and it pertains to abdominal aortic aneurysms, which you know can occur in patients who are ineligible for routine ultrasound screening. A simple abdominal aortic aneurysm risk score was derived and compared to current guidelines used for ultrasound screening of abdominal aortic aneurysms. Dr. Greg Hundley: And so, this study comes to us from the UK Biobank, and they examined participants without previous, and let's just abbreviate this as AAA or AAA. So without previous AAA, we're split into a derivation cohort of 401,820 individuals, and a validation cohort of 83,000 individuals. An incident AAA was defined as a first hospital, inpatient diagnosis of AAA, death from AAA, or a AAA-related surgical procedure. And, of course, they used multivariable Cox models to develop the derivation cohort, and then apply that to the validation cohort. Dr. Carolyn Lam: Wow, Greg, that is a large number of people, the power of the UK Biobank, huh? So, what did they find? Dr. Greg Hundley: Right. So, Carolyn, components of the AAA risk score were age, stratified by smoking status, weight, stratified by smoking status, any hypertensive and cholesterol-lowering medication use, height, diastolic blood pressure, baseline cardiovascular disease, and then diabetes. Dr. Greg Hundley: So, Carolyn, in the validation cohort, over 10 years of follow-up, the C index, for the model for the USPSTF guidelines, was 0.705, whereas, the C index of the risk score as a continuous variable was 0.856. And in the validation cohort, the USPSTF model yielded a sensitivity of 63%, and a specificity of 71%. Dr. Carolyn Lam: Okay, Greg, but what's a take-home message? Dr. Greg Hundley: Right, Carolyn. So the take-home message is that in an asymptomatic general population, a risk score based on patient age, height, weight, and a medical history may improve identification of asymptomatic patients at risk for clinical events from AAA. And also, these results highlight that further development and validation of risk scores to detect asymptomatic AAA are needed. Dr. Carolyn Lam: Wow, and that was a great summary with a lot more data in the article, huh? Let's refer the readers to it. But for my paper, it highlights the key role of histidine triad nucleotide-binding protein 1, or HINT 1, in the pathogenesis of cardiac hypertrophy. Dr. Greg Hundley: Wow. Carolyn, so tell me a little bit more about HINT 1. Dr. Carolyn Lam: I thought you may ask. HINT 1 is a highly-conserved 14 kilodalton protein that belongs to the histidine triad super family. It was previously shown to play a role in diverse neuropsychiatric diseases. Loss of HINT 1 increased susceptibil