Citations

Abstract Medical imaging is undergoing a transformation driven by the advent of new, highly effective, machine learning techniques paired with increases in computational capabilities (Cheng et al. 2021; Gilson et al. 2023; Almeida et al. 2024; Krishna et al. 2024). These advanced algorithms have the potential to improve disease detection, diagnosis, prognosis, and treatment outcomes. However, the complexity of machine learning models, the large amounts of curated and annotated data required by some methods, and the potential for bias and error make it challenging for individuals to safely and effectively leverage these methods (Lin et al. 2024; Guo et al. 2024; Xu et al. 2024; Linguraru et al. 2024; Wood et al. 2019). To address these challenges, the American Association of Physicists in Medicine (AAPM), American College of Radiology (ACR), Radiological Society of North America (RSNA), and Society for Imaging Informatics in Medicine (SIIM) have worked together to develop a syllabus detailing a recommended set of competencies for medical imaging professionals interacting with these systems. This guide is aimed at four different personas: users of AI systems, purchasers of AI systems, individuals who provide clinical expertise during the development of AI systems (“clinical collaborators”), and developers of AI systems.1 This is a syllabus, not a curriculum, and is intentional in this scope. Recognizing that individuals may benefit from different presentations of the same material, this work enumerates a series of relevant competencies but does not prescribe, nor offer, a method of instruction (Schuur, Rezazade Mehrizi, and Ranschaert 2021; Garin et al. 2023). By addressing the task‐specific demands of each role, this guide will enable medical imaging professionals to utilize machine learning systems more safely and effectively, ultimately improving patient care and outcomes.

Introduction: Mitral valve transcatheter edge-to-edge repair (M-TEER) has emerged as a minimally invasive option for high-risk surgical candidates with severe and symptomatic mitral regurgitation (MR), but post-procedure residual mitral valve (MV) dysfunction remains a significant concern. This study evaluates the clinical utility of combining artificial intelligence applied to electrocardiograms (ECG-AI) for diastolic dysfunction (DD) grading and the echocardiography-derived velocity time integral of the MV and left ventricular outflow tract ratio (VTIMV/LVOT) in predicting prognosis in patients post-M-TEER. Methods: A retrospective analysis of patients who underwent M-TEER between 2014 and 2021 was conducted. Patients were categorized based on VTIMV/LVOT and ECG-AI scores into three groups: both normal parameters, either abnormal parameter, or both abnormal parameters to compare outcomes (mortality, major adverse cardiovascular events [MACE], and the need for subsequent MV reintervention) using Kaplan–Meier analysis, multivariable Cox regression models, and net reclassification improvement. Results: Overall, 250 patients were included; the median age was 79.5 (IQR: 73.1, 84.6) and 66.4% were male. The combined abnormal VTIMV/LVOT (≥2.5) and ECG-AI score for DD (>1) was associated with higher risk of one-year mortality (adjusted HR: 4.56 [1.04–19.89], p = 0.044) and MACE (adjusted HR: 3.72 [1.09–12.72], p = 0.037) compared to patients with both normal parameters. Conclusions: This study highlights the potential additive value of integrating VTIMV/LVOT and ECG-AI scores as a prognostic tool for a personalized approach to the post-operative evaluation and risk stratification in M-TEER patients.

Abstract Introduction Cancer therapy-related cardiac dysfunction (CTRCD) after anthracycline-based therapy is a dreaded complication due to its significant morbidity and mortality. Sodium-glucose cotransporters-2 inhibitors (SGLT2i) have been shown to improve cardiovascular outcomes in multiple scenarios. However, its potential benefits in patients who develop CTRCD due to anthracycline-based chemotherapy are not well established. Purpose To investigate the benefits of SGLT2i in cancer patients who develop CTRCD secondary to anthracycline-based chemotherapy. Methods All patients who underwent anthracycline therapy between 2002 and 2022 across three tertiary centers and had a diagnosis of moderate or severe CTRCD according to 2022 European Society of Cardiology (ESC) guidelines were evaluated. Baseline characteristics, echocardiograms pre and post chemotherapy, and mortality were reviewed. Kaplan Meier analysis was conducted to compare all-cause and cardiovascular mortality between patients treated with SGLT2i (both patients on chronic SGLT2i who continued their therapy following CTRCD and those who commenced the treatment after CTRCD diagnosis) and those not receiving this therapy. Results In total, 398 patients diagnosed with moderate or severe CTRCD were included; median age was 66.82 (58.07, 74.46) years and 59.29% were males. Among them, 39 (9.80%) received SGLT2i. Mortality rates at 1- and 5-years were significantly lower among patients who were on SGLT2i treatment compared to patients who were not (8.40% vs 46.30%, p= 0.0001 and 17.30% vs 65%, p= 0.0001, respectively) (Figure1). Furthermore, cardiovascular mortality rate at 5 years was significantly lower in patients receiving SGLT2i compared to patients not receiving this therapy (0% vs 11%, p= 0.046). Conclusions SGLT2i may have survival benefit in cancer patients who develop CTRCD secondary to anthracycline-based chemotherapy and might be considered as an adjunctive treatment to improve survival outcomes in this population.Figure 1.Kaplan-Meier Curves

Advances in plaque imaging have transformed cardiovascular diagnostics through detailed characterization of atherosclerotic plaques beyond traditional stenosis assessment. This review outlines the clinical applications of varying modalities, including dual-layer spectral CT, photon-counting CT, dual-energy CT, and CT-derived fractional flow reserve (CT-FFR). These technologies offer improved spatial resolution, tissue differentiation, and functional assessment of coronary lesions. Additionally, artificial intelligence has emerged as a powerful tool to automate plaque detection, quantify burden, and refine risk prediction. Collectively, these innovations provide a more comprehensive approach to coronary artery disease evaluation and support personalized management strategies.

Importance Pectus arcuatum is a rare anterior chest wall deformity that is often confused with excavatum, carinatum, or a mixed deformity. A complete understanding of its clinical and physiological basis will improve diagnostic accuracy and allow for standardized management. Objectives To gain a comprehensive understanding of pectus arcuatum, focusing on its nomenclatures, epidemiology, classification, pathophysiology, preoperative presentation and assessments, management options, and surgical outcomes. Evidence Review PubMed, Google Scholar, and subsequent reference searches were used to extract original studies addressing pectus arcuatum fully or partially. The searches were performed on February 2, 2025. Two independent reviewers screened articles based on preestablished inclusion and exclusion criteria. Quality assessment was performed, but given the rarity of arcuatum and the limited, heterogeneous nature of available literature, none of the studies were excluded based on the level of evidence or quality assessments. Using a standardized data extraction form, results were synthesized and presented as a review with recommendations to guide clinical decision-making. Findings A total of 65 studies were included in the final review. Of those, 37 (56.9%) were cohort studies, 18 (27.7%) were case reports, 8 (12.3%) were case series, and 2 (3.1%) were technical reports. A total of 455 cases of pectus arcuatum were represented. Heterogeneity was found in nomenclature, epidemiology, associated conditions, assessments, management, and outcomes. An open surgical approach and, more recently, hybrid open and minimally invasive technique are reported for surgical repair. Postoperative outcomes were good in most surgical series, with no significant difference when compared with the repair of other pectus deformities. Conclusions and Relevance Results of this systematic review reveal that pectus arcuatum is a rare variant of pectus deformities that is distinct from carinatum and excavatum. Unified terminology and standardized diagnostic criteria are important to facilitate proper management. Minimally invasive hybrid approaches continue to refine outcomes, balancing invasiveness with efficacy.

Aortic stenosis (AS), the most common valvular heart disease, is traditionally graded based on several echocardiographic quantitative parameters, such as aortic valve area (AVA), mean pressure gradient (MPG), and peak jet velocity (Vmax). This systematic review evaluates the clinical significance and prognostic implications of discordant high-gradient AS (DHG-AS), a distinct hemodynamic phenotype characterized by elevated MPG despite a preserved AVA (>1.0 cm2). Although often overlooked, DHG-AS presents unique diagnostic and therapeutic challenges, as high gradients remain a strong predictor of adverse outcomes despite moderately reduced AVA. Sixty-three studies were included following rigorous selection and quality assessment of the key studies. Prognostic outcomes across five key studies were discrepant: some showed better survival in DHG-AS compared to concordant high-gradient AS (CHG-AS), while others reported similar or worse outcomes. For instance, a retrospective observational study including 3209 patients with AS found higher mortality in CHG-AS (unadjusted HR: 1.4; 95% CI: 1.1 to 1.7), whereas another retrospective multicenter study including 2724 patients with AS observed worse outcomes in DHG-AS (adjusted HR: 1.59; 95% CI: 1.04 to 2.56). These discrepancies may stem from delays in intervention or heterogeneity in study populations. Despite the diagnostic ambiguity, the presence of high gradients warrants careful evaluation, aggressive risk stratification, and timely management. Current guidelines recommend a multimodal approach combining echocardiography, computed tomography (CT) calcium scoring, transesophageal echocardiography (TEE) planimetry, and, when needed, catheterization. Anatomic AVA assessment by TEE, CT, and cardiac magnetic resonance imaging (CMR) can improve diagnostic accuracy by directly visualizing valve morphology and planimetry-based AVA, helping to clarify the true severity in discordant cases. However, these modalities are limited by factors such as image quality (especially with TEE), radiation exposure and contrast use (in CT), and availability or contraindications (in CMR). Management remains largely based on CHG-AS protocols, with intervention primarily guided by transvalvular gradient and symptom burden. The variability among the different guidelines in defining severity and therapeutic thresholds highlights the need for tailored approaches in DHG-AS. DHG-AS is clinically relevant and associated with substantial prognostic uncertainty. Timely recognition and individualized treatment could improve outcomes in this complex subgroup.