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Abstract Background 99mTc-labelled cardiac scintigraphy enables noninvasive diagnosis of transthyretin amyloid cardiomyopathy (ATTR-CM). Guidelines recommend using planar semiquantitative (heart to contralateral ratio, H/CL) and single photon emission computed tomography (SPECT) qualitative visual grading for diagnostic interpretation. However, planar imaging has inherent limitations, and visual grading is prone to interobserver variability, underscoring the need for standardized quantitative assessment. We developed a 3D volumetric quantitative score (3D Score) and assessed its diagnostic performance compared to myocardial tissue, the gold standard for ATTR-CM diagnosis. Methods At a single, tertiary referral center, we retrospectively identified consecutive patients from 06/2017 to 06/2024 who underwent 3-hour 99mTc-pyrophosphate or 99mTc-hydroxymethylene diphosphonate planar and SPECT/CT for suspected ATTR-CM and had archived myocardial tissue (biopsy or myectomy). On planar imaging, H/CL was calculated. On SPECT/CT, volumes of interest were drawn around the entire left ventricle (LV), avoiding calcifications, and within the right atrium (RA) blood pool. Mean uptake values were used to calculate the 3D Score (LVmean:RAmean), Fig 1A. Myocardial tissue was stained via sulfated Alcian blue and/or Congo red histochemistry. Once histologically confirmed, amyloid deposits were subtyped by liquid chromatography tandem mass spectrometry. The diagnostic performance of H/CL and 3D Score was assessed using receiver operating characteristic (ROC) curve analysis and predictive characteristics were defined. ROC areas under the curve (AUC) were compared using Delong test. Optimal cutoffs were determined using Youden’s J statistic. Baseline characteristics (demographics, echocardiogram, biomarkers) and H/CL were compared between patients above and below 3D Score cutoff. Results 239 patients were identified (median age 72 [65-78], 78% male, 46% ATTR positive). Median time between cardiac scintigraphy and myocardial tissue collection was 22 (6-65) days. Distribution of the 3D Score stratified by ATTR-CM status is illustrated in Fig 1B-C. The discriminative ability of the 3D Score was excellent (AUC 0.92) and superior to H/CL (0.87, p =0.006, Fig 1D-E). The optimal 3D Score cutoff for identifying ATTR-CM was ≥1.0 with sensitivity of 86%, specificity of 92%, positive predictive value (PPV) 90%, and negative predictive value (NPV) 89%. The optimal H/CL ratio cutoff for identifying ATTR-CM was ≥1.4 with sensitivity of 72%, specificity of 86%, PPV 81%, NPV 78%. Baseline characteristics of the overall cohort stratified by 3D Score are displayed in Table 1. Conclusions The 3D Score demonstrated excellent diagnostic performance for detecting ATTR-CM and was superior to current quantitative metrics. Future studies are needed to externally validate its performance across diverse patient cohorts and imaging centers and to investigate correlation with myocardial amyloid burden. Figure 1

Abstract Background Common genetic variation has been linked to an increased risk of developing dilated cardiomyopathy (DCM) in case-control studies. However, the phenotypic profile and biological mechanisms by which genetic background may predispose individuals to DCM and outcomes in the general population remain unclear. Aim The primary objectives of this study were twofold: (1) to validate a DCM polygenic score (PRS-1) based on a prior meta-analysis of case–control genetic association studies [Tadros R et al. Nat Genet (2021)]; and (2) To apply this PRS, along with two recently developed PRSs for DCM [PRS-2 from Zheng SL et al. Nat Genet (2024) and PRS-3 from Jurgens SJ et al. Nat Genet (2024)] to a general population that underwent comprehensive longitudinal phenotypic assessments and had long-term outcomes available. Methods While the PRS-1 was derived from only 13 SNPs, PRS-2 and PRS-3 were generated from 709,534 and 1,072,247 SNPs, respectively with significant overlap between them. These DCM-PRSs were applied to an unselected community-based cohort (n=1897) aged >45 years, who underwent a physical examination, echocardiogram, and blood sample at baseline. Subsequent clinical outcomes were collected over a median 16 year follow-up (IQR: 15-17). Results No significant differences between the quartiles were present in terms of age, sex (48% male), and cardiovascular risk factors (CV-RF) (such as hypertension, diabetes, and coronary artery disease). However, linear regression models demonstrated a significant correlation between all DCM-PRSs and left ventricular (LV) parameters, including LV ejection fraction, LV end-systolic diameter, and LV end-diastolic diameter (Table). Multivariable regression analysis confirmed that these correlations were independent of age, sex, CV-RF, and population stratification (adjusted for the first 10 principal components [PCs]). During follow-up, 47 individuals developed DCM. A logistic regression analysis, using a 3:1 matched cohort of non-DCM vs. DCM individuals based on age and sex and adjusted for the same 10 PCs, found a significant correlation between DCM development and both PRS-1 [OR=2.27 (1.06–4.85), p=0.03] and PRS-3 [OR=2.63 (1.20–5.75), p=0.02], while PRS-2 did not show a significant association [OR=1.85 (0.84–4.06), p=0.12]. No association was found between the DCM-PRSs and heart failure (HF) biomarkers (aldosterone, natriuretic peptides, ST2, Galectin-3) or HF outcomes (all-cause mortality/HF hospitalization). Conclusion PRS-1 for DCM despite being derived from only 13 risk alleles, performs at least as well as the newer and more extensive PRSs, in its correlation with LV function, dimensions, and DCM development (except for PRS-2) in a general population. The absence of correlation between these DCM-PRSs and the renin-angiotensin-aldosterone system or natriuretic peptides suggests that genetic background influences LV traits through mechanisms independent of these biological pathways.

BACKGROUND: Guidelines recommend 3-hour cardiac amyloid radionuclide imaging (CARI) for transthyretin amyloid cardiomyopathy. Citing rapid blood clearance of 99m Tc-hydroxymethylene-diphosphonate (HMDP) and efficient laboratory throughput, 1-hour imaging is increasingly practiced despite limited supporting evidence. We sought to compare diagnostic performance and interpreter experience of 1-hour versus 3-hour HMDP-CARI. METHODS: Consecutive patients with suspected transthyretin amyloid cardiomyopathy (n=114) underwent both 1-hour and 3-hour HMDP single photon emission computed tomography (CT)/CT. Two cardiologist-radiologist reader teams, blinded to imaging timepoint (1 versus 3 hours), assessed overall interpretation, single photon emission CT–based Perugini grade, interpretation difficulty, interpreter confidence, and need for CT-fused images for anatomic localization. Discordant, equivocal, and difficult cases were arbitrated by a third tie-breaking team. The myocardial-to-blood-pool radiotracer uptake ratio (3-dimensional Score) was measured as a surrogate of contrast resolution. RESULTS: Interinterpreter agreement was high at both time points (κ≥0.81), with more cases requiring arbitration at 3 hours versus 1 hour (22% versus 13%; P =0.049). Overall interpretation and Perugini grades were concordant between time points in 111/114 (97%) and 106/114 (93%) patients, respectively. Three patients (3%) were negative at 1 hour but equivocal at 3 hours, all of which were clinically ruled out for transthyretin amyloid cardiomyopathy. Interpreter confidence was comparable at both timepoints (97% versus 95%; P =0.317). Compared with 3-hour imaging, contrast resolution was inferior (lower 3-dimensional score, P <0.001) and CT fusion was more frequently needed (57% versus 31%, P <0.001) at 1-hour imaging. CONCLUSIONS: In a prospective, blinded comparison of 1-hour versus 3-hour HMDP-CARI, diagnostic performance and interpreter experience were similar, with readers requesting CT fusion more frequently at 1 hour to optimize myocardial-to-blood pool discrimination.

BACKGROUND: Chronic aortic regurgitation (AR) is associated with significant cardiac remodeling, but the prevalence and prognostic impact of extravalvular cardiac damage remain unexplored. METHODS: Adults with moderate or greater chronic AR identified on echocardiogram between January 2008 and July 2024 were included. Exclusion criteria were acute AR, hypertrophic and infiltrative cardiomyopathies, prior cardiac surgery, and valve stenosis. Cardiac damage was classified into hierarchical stages: no cardiac damage (stage 0), left ventricular damage (stage 1), moderate or greater mitral regurgitation or left atrial enlargement or atrial fibrillation (stage 2), pulmonary hypertension or moderate or greater tricuspid regurgitation (stage 3), and significant right ventricular dysfunction (stage 4). The primary outcome was the association between cardiac damage stages and all-cause mortality under medical surveillance. RESULTS: Of 4026 patients (median age, 72 [61–80] years), 78% had moderate AR, 11% had moderate-severe, and 11% had severe AR. Cardiac damage was present in 87% of patients: 14% in stage 1, 53% in stage 2, 18% in stage 3, and 2% in stage 4. In a multivariable model, including age, sex, AR severity, and Charlson Comorbidity Index, cardiac damage stages were associated with mortality. Adjusted hazard ratios were 1.42 (95% CI, 1.04–1.96) for stage 1, 1.58 (95% CI, 1.21–2.06) for stage 2, 2.78 (95% CI, 2.10–3.67) for stage 3, and 5.34 (95% CI, 3.67–7.76) for stage 4. Adding cardiac damage staging to multivariable models improved predictive accuracy for mortality, increasing the concordance statistics from 0.73 (95% CI, 0.71–0.75) to 0.76 (95% CI, 0.74–0.77). CONCLUSIONS: Cardiac damage is present in nearly 90% of patients with moderate or greater AR and is associated with increased mortality, highlighting the need for a more comprehensive evaluation of cardiac structure and function beyond the aortic valve and left ventricle.

Background: Breast cancer polygenic risk scores (PRS) and traditional risk models (e.g., the Gail model [Gail]) are known to contribute largely independent information, but it is unclear how the overlap varies by ancestry, age, disease type (invasive breast cancer, DCIS), and risk threshold. Methods: In a retrospective case–control study, we evaluated risk prediction performance in 180,398 women (161,849 of European ancestry; 18,549 of Asian ancestry). Odds ratios (ORs) from logistic regression models and the area under the receiver operating characteristic curve (AUC) were estimated. Results: PRS for invasive disease showed a stronger association in younger (<50 years) women (OR = 2.51, AUC = 0.622) than in women ≥ 50 years (OR = 2.06, AUC = 0.653) of European ancestry. PRS performance in Asians was lower (OR range = 1.62–1.64, AUC = 0.551–0.600). Gail performance was modest across groups and poor in younger Asian women (OR = 0.94–0.99, AUC = 0.523–0.533). Age interactions were observed for both PRS (p < 0.001) and Gail (p < 0.001) in Europeans, whereas in Asians, age interaction was observed only for Gail (invasive: p < 0.001; DCIS: p = 0.002). PRS identified more high-risk individuals than Gail in Asian populations, especially ≥50 years, while Gail identified more in Europeans. Overlap between PRS, Gail, and family history was limited at higher thresholds. Calibration analysis, comparing empirical and model-based ROC curves, showed divergence for both PRS and Gail (p < 0.001), which indicates miscalibration. In Europeans, family history and prior biopsies drove Gail discrimination. In younger Asians, age at first live birth was influential. Conclusions: PRS adds value to risk stratification beyond traditional tools, especially in younger women and Asian ancestry populations.

Background: Heart failure with preserved ejection fraction (HFpEF) accounts for approximately half of all heart failure hospitalizations; yet, tools for individualized 1-year mortality risk stratification remain limited. We conducted a retrospective study to develop and validate a machine learning model using genetic programming and automated model search to predict 1-year all-cause mortality in HFpEF patients admitted for decompensated HF. Methods: Electronic medical records from Mayo Clinic (2010-2020) were queried to identify 7,840 adult patients hospitalized with HF exacerbation and a left ventricular ejection fraction>50% on echocardiograms performed between six months pre-admission and seven days post-discharge. Demographic, clinical, laboratory, medication, comorbidity, and imaging data available at the time of index hospitalization were extracted. The cohort was split into 80% training (n=6,272) and 20% held-out test (n=1,568) sets. After standard preprocessing, we performed an evolutionary AutoML search. The final pipeline applied a RobustScaler, two sequential feature-union blocks, and an XGBoost classifier. Model performance on the test set was assessed by area under the receiver operating characteristic curve (AUC), Brier score, accuracy, precision, recall, and F1 score, each with bootstrap-derived 95% confidence intervals (CIs). For interpretability, SHAP (SHapley Additive exPlanations) values were computed using the full scaled training set as background. Results: On the held-out test set, the XGBoost-based model achieved an AUC of 0.7595 (95% CI: 0.7307-0.7870) and a Brier score of 0.1764 (95% CI: 0.1652-0.1890). Accuracy was 0.7406 (95% CI: 0.7143-0.7645), precision 0.6349 (95% CI: 0.5759-0.6942), recall 0.4135 (95% CI: 0.3636-0.4609), and F1 score 0.5008 (95% CI: 0.4529-0.5444). The global SHAP summary plot (Figure 1) ranked age, serum albumin, blood urea nitrogen (BUN), presence of renal failure, and NT-proBNP as the top 5 predictors. Conclusions: In this large HFpEF cohort, an AutoML-derived XGBoost pipeline achieved robust discrimination (AUC≈0.76) and calibration (Brier≈0.18) for 1-year mortality prediction. SHAP-based explanations highlighted the importance of age, nutritional status (albumin), renal biomarkers (BUN, renal failure), and natriuretic peptides (NT-proBNP) as principal drivers of risk. These interpretable machine learning findings may guide personalized risk stratification and identify therapeutic targets in HFpEF.

Introduction: Cardiovascular risks following SARS-CoV-2 infection are incompletely defined. We evaluated evolving cardiovascular outcomes across COVID-19 variant eras using a large community-based cohort to inform risk stratification and clinical care. Methods: We conducted a retrospective cohort study of 162,471 adults with COVID-19 between March 2020 and December 2023 using the Rochester Epidemiology Project. Patients were stratified by variant era (Pre-Delta, Delta, and Omicron). Cardiovascular outcomes included major adverse cardiovascular events (MACE: myocardial infarction, stroke, death), ischemic and inflammatory heart disease, thrombotic events, and dysrhythmias. Diagnoses were identified using ICD-10 codes and validated in a subset. Cumulative incidence was estimated using Kaplan-Meier and competing risk models. Cox proportional hazards regression was used to assess differences by era and age. Results: MACE occurred in 4,922 patients, primarily in those ≥80 (2-year incidence: 17%). Event rates peaked within 30 days post-infection, with marked variation by variant. In patients ≥80, 30-day MACE risk was highest in the Pre-Delta (HR 3.85; 95% CI, 3.14–4.71) and Delta (HR 2.72; 95% CI, 2.13–3.47) eras versus Omicron. After 30 days, event rates fell and era differences narrowed. Thrombotic events (n=2,090; 1.4%) decreased across eras. Ischemic and inflammatory heart disease rates were stable. Myocarditis/pericarditis were rare (0.1%) without age trends. Dysrhythmias affected 6,765 patients (2-year incidence: 4.9%) and rose with age (2.0% in <40 vs. 19.9% in ≥80). Within 30 days, risk was higher in the Pre-Delta and Delta eras for age ≥40, especially ≥80 (Delta HR 3.08; 95% CI, 2.08–4.56) and 60–79 (HR 2.23; 95% CI, 1.75–2.85). Among those 40–59, Delta posed the highest risk (HR 2.74; 95% CI, 1.94–3.86 vs. Pre-Delta HR 1.77; 95% CI, 1.26–2.49). No differences were observed in <40. Beyond 30 days, risk converged across variants. Conclusion: Cardiovascular risk after SARS-CoV-2 infection was concentrated in the first 30 days, with attenuation thereafter. While MACE and thrombotic event rates declined over time, early dysrhythmia risk varied by variant and age, especially in older adults. These findings define a time-sensitive, variant-specific risk window and support short-term, risk-stratified post-COVID monitoring. This work informs targeted follow-up protocols by infection era and age, with implications for quality improvement, resource use, and equitable care.

Abstract Background Molecular breast imaging (MBI) has shown utility as a supplement to mammography in women with dense breasts. Background parenchymal uptake (BPU), which describes the level of Tc-99m sestamibi in fibroglandular tissue on MBI, varies among women with similar density. Higher BPU is associated with greater breast cancer risk. The goal of this work is to investigate the histological correlations of BPU that may explain this association with risk. Methods We compared histologic features of prospectively collected benign breast tissue biopsies from healthy women who had a region of dense tissue on mammography exhibiting one of the extreme categories of BPU on MBI: either photopenic or marked. Tissue composition of specimens was assessed by measuring area of epithelium, stroma, and fat and counting lobules. Lobular involution status was assessed by an expert pathologist as either none, partial, or complete. Ki-67 index and estrogen receptor-alpha expression were also assessed. Results Biopsies were performed in 48 women (mean age 54.9 years [SD 11.1 years]), including 20 with marked BPU and 28 with photopenic BPU. Women with marked BPU were younger (mean age 49.9 vs. 58.4 years, p = 0.004), had higher body mass index ( p = 0.01), and were more likely premenopausal ( p = 0.005). Marked BPU specimens had a higher proportion of epithelium (14.5% vs. 2.2%, p < 0.001), lower stromal content (44.8% vs. 84.2%, p = 0.005), similar fat (18.9% vs. 12.9%, p = 0.41), and greater lobule counts (15.5 vs. 6.3, p < 0.001) compared to photopenic specimens. Complete lobular involution was less frequent in marked tissue than in photopenic tissue (10.5% vs. 76%, p < 0.001). Ki-67 index was higher in marked BPU tissues (5.4% vs. 1.6%, p = 0.006), though the difference was attenuated after adjustment for epithelial area (p = 0.26). Estrogen receptor-alpha expression did not differ between marked and photopenic groups (25.6% vs. 28.4%, p = 0.12). Conclusions Marked BPU on MBI is associated with greater epithelial content, less lobular involution, and higher proliferative activity—features characteristic of tissue at elevated risk for malignant transformation. These findings suggest that BPU provides functional information beyond mammographic density, supporting its role as an imaging biomarker for breast cancer risk in women with dense breasts. Trial Registration: NCT01240278 and NCT01588834

Importance Inherited pathogenic variants (PVs) in known predisposition genes can greatly increase breast cancer risk, but the combined impact of PV status, family history, and other factors on breast cancer risk in the general US population has not been well described. Objective To evaluate population-based breast cancer risk estimates for those with established PVs overall and stratified by first-degree family history of breast cancer and other factors. Design, Setting, and Participants This study used pooled data from 13 US-based breast cancer case-control studies participating in the Cancer Risk Estimates Related to Susceptibility (CARRIERS) consortium. Enrollment for individual studies occurred between 1976 and 2013, and results are based on data released March 2023, with analyses conducted from June 2022 to July 2025. Exposures PVs, breast cancer family history, self-reported race and ethnicity, and established risk factors. Main Outcomes and Measures Breast cancer rate ratios for PVs in 7 genes were estimated from the CARRIERS consortium. PV status and incidence and mortality statistics were combined using the Individualized Coherent Absolute Risk Estimation (iCARE) model to estimate conditional cumulative breast cancer risks and 95% CIs, stratified by family history and standardized to the US population. Models that incorporated population-based data and published estimates for established epidemiologic risk factors were also evaluated. Results A total of 67 692 women were studied, including 33 841 who were diagnosed with breast cancer. PVs in ATM , BRCA1 , BRCA2 , CHEK2 , and PALB2 were strongly associated with breast cancer risk, with BRCA1 and PALB2 PVs showing evidence of heterogeneity by family history. In models considering PVs, family history, and established risk factors, the estimated cumulative risks of breast cancer by age 50 years ranged from 2.4% (95% CI, 2.4-2.4) in women with no PVs and no family history to 35.5% (95% CI, 21.6-55.1) in PALB2 PV carriers with a family history. Among women who have not been diagnosed with breast cancer by age 50 years, the cumulative risk of breast cancer by age 80 years ranged from 11.1% (95% CI, 11.0-11.2) in noncarriers with no family history to 70.5% (95% CI, 52.8-83.5) for PALB2 carriers with a family history. PV-specific cumulative risk estimates varied across subgroups defined by race and ethnicity and potentially modifiable epidemiologic risk factors. Conclusions and Relevance In this study, population-based estimates of cumulative breast cancer risk for established PVs, as informed by the CARRIERS case-control sample, varied by family history and potentially modifiable risk factors. These estimates provide guidance for identifying individuals who will most benefit from enhanced screening and prevention strategies.

Background Atrial fibrillation (AF) impacts management decisions in valvular heart disease but its significance in patients with chronic aortic regurgitation (AR) is not well established. Objectives To evaluate the prevalence and prognostic role of AF in patients with chronic, haemodynamically significant AR. Methods Adults with chronic ≥moderate-to-severe AR, from March 2004 to April 2019, were retrospectively identified. Those with acute AR, moderate or worse other valve disease or prior valve surgery were excluded. Patients with AF were identified based on 12-lead ECGs, 1-lead ECGs (showing AF for ≥30 s), or episodes recorded by implanted cardiac devices. Primary outcome was all-cause mortality. Cox regression models were used to assess associations with mortality: model 1 adjusted for age, symptoms (New York Heart Association class II–IV), Charlson Comorbidity Index, left ventricle (LV) end-systolic volume index and AF; model 2 added left atrial volume index and model 3 further added systolic pulmonary artery pressure. Results Of the 1006 included patients (age 59±18 years; 822 (82%) men), 446 (46%) had hypertension and 364 (36%) had a bicuspid aortic valve. AF was present in 161 (16%) patients at the time of ≥moderate-to-severe AR diagnosis. During a median follow-up of 1.6 years (IQR 0.2–6.2), AF was associated with an increased mortality risk in univariate and in all three multivariable models (HR 1.61 (95% CI 1.07 to 2.43), HR 2.21 (95% CI 1.31 to 3.72) and HR 2.06 (95% CI 1.21 to 3.52), respectively), including after propensity matching (HR 1.58 (95% CI 1.01 to 2.48)). Conclusions AF is present in one in six patients with chronic≥moderate-to-severe AR and is associated with an increased risk of mortality even after adjusting for measures of LV systolic and diastolic function. There is a need for future prospective studies to validate these findings and evaluate AF as a potential trigger for early surgery.