Planken, R. Nils

Background Homozygous familial hypercholesterolemia (HoFH), characterized by extremely elevated low‐density lipoprotein cholesterol (LDL‐C) due to severely impaired LDL‐C clearance from circulation, remains challenging to treat. Here, we investigated clinical benefits of monoclonal antibody, evinacumab, inhibiting angiopoietin‐like 3, recently approved in children with homozygous familial hypercholesterolemia. Methods This retrospective, observational study included 13 children with homozygous familial hypercholesterolemia on oral lipid‐lowering therapy and assessed their attainment of LDL‐C goal, need for lipoprotein apheresis (LA), and cardiac plaque formation at initiation of evinacumab and at follow‐up of 2.0 (1.3–3.0) years. Results Evinacumab, initiated at age 11 (8.5–13.5) years, increased number of patients reaching LDL‐C goal from none before initiation to 9 of 13 (69%; P =0.004) at follow‐up. Mean±SD LDL‐C at follow‐up was 111 (44) mg/dL, compared with 206 (61) mg/dL before evinacumab (mean difference, −95 mg/dL [95% CI, −142 to −47]; P <0.001). Before initiation of evinacumab, 11 of 13 children received LA with average interval of 7.8 days. At follow‐up, LA frequency decreased in 7 of 11 children with average interval of 18.9 days; increase between LA sessions was 11.0 days (3.5–18.5; P =0.008), 42% longer session interval. For 3 (15%) children, due to evinacumab initiation, LA remained dispensable over the course of treatment. Coronary computed tomography angiography showed plaque stabilization (n=5), regression (n=3), and no formation (n=2), in 10 of 13 (77%) children, and plaque progression in 3 (23%) children. Conclusions Add‐on evinacumab increased number of children with homozygous familial hypercholesterolemia reaching and maintaining LDL‐C goal, concomitant reduction in LA frequency, and in most patients, stabilization or improvement in coronary computed tomography angiography findings.

Abstract The persistent global rise in atherosclerotic cardiovascular disease (ASCVD) challenges the effectiveness of current risk factor-based algorithms in primary prevention. Most myocardial infarctions occur in individuals without prior symptoms or recognized standard modifiable risk factors, underscoring the need to improve risk stratification. Coronary CT imaging, including coronary artery calcium scoring (CACS) and coronary computed tomography angiography (CCTA), enables direct non-invasive visualization of coronary atherosclerosis, supporting a shift from population-based prevention towards personalized, disease-based risk assessment and targeted preventive treatment. CCTA provides comprehensive evaluation of plaque burden, composition, stenosis severity, and high-risk plaque (HRP) features, thereby refining risk stratification and guiding personalized treatment decisions. The presence and total burden of coronary atherosclerotic plaque are considered the primary CCTA-derived markers for guiding preventive therapy, while noncalcified plaque burden and HRP features may support treatment intensification. Advances in CT technology, including photon-counting CT, and the application of artificial intelligence-based tools may further refine risk assessment by enabling accurate and reproducible plaque quantification and characterization. Although no randomized trials have yet demonstrated that CCTA-based screening improves clinical outcomes in asymptomatic individuals compared with standard care, the same is true of traditional cardiovascular risk scores. Three large ongoing randomized trials are currently evaluating whether CCTA-guided, personalized prevention strategies can reduce ASCVD events. The results are eagerly awaited and may redefine the role of CCTA in asymptomatic individuals.

BACKGROUND: Cardiac computed tomography (CT) acquired during the acute stroke imaging protocol is an emerging modality to detect cardiac thrombi. We determined its yield in patients with acute ischemic stroke. METHODS: We performed a 1-stage individual patient data meta-analysis of 4 prospective observational cohorts (AIS of HEARTS [Acute Ischemic Stroke of Heart-Related Embolic Sources Detected on Acute Cardiac CT Scans]), including patients with acute ischemic stroke who underwent ECG-gated or non–ECG-gated cardiac CT between May 2018 and June 2024. We excluded patients with transient ischemic attack or stroke mimics. The primary outcome was the proportion of patients with a thrombus on cardiac CT. Secondary outcomes were additional scan time, radiation dose, comparison with echocardiography, and 90-day outcomes. We performed logistic regression analyses to compare 90-day outcomes between patients with and without thrombus, adjusting for age, sex, history of atrial fibrillation, ischemic heart disease, chronic heart failure, stroke or transient ischemic attack, anticoagulant use, prestroke modified Rankin Scale score, National Institutes of Health Stroke Scale score, large vessel occlusions, and intravenous thrombolysis, as appropriate for each outcome. RESULTS: We included 3919 patients (median age, 74 [interquartile range (IQR), 63–82], 58% male, median National Institutes of Health Stroke Scale score 6 [IQR, 3–12]). Cardiac CT detected a thrombus in 243 (6.2%) patients. Among 1323 patients that underwent both cardiac CT and transthoracic echocardiography, cardiac CT had a higher yield than transthoracic echocardiography (odds ratio, 7.4 [95% CI, 4.0–15.1]; P <0.001). Median additional scan time was 6 minutes (IQR, 5–7) for ECG-gated and 13 seconds (IQR, 12–61) for non–ECG-gated cardiac CT. Median additional radiation dose was 2.9 mSv (IQR, 1.6–4.1). Patients with thrombi had higher 90-day mortality (33% versus 15%, adjusted odds ratio, 1.6 [95% CI, 1.1–2.3]) and worse modified Rankin Scale scores (median modified Rankin Scale score 3 versus 2, adjusted odds ratio, 1.6 [95% CI, 1.2–2.0]), but similar recurrent stroke rates (5% versus 4%, adjusted odds ratio, 1.4 [95% CI, 0.7–2.5]). CONCLUSIONS: Implementing cardiac CT into the acute stroke imaging protocol is feasible, detects thrombi in ≈6% of patients, and has a higher yield than transthoracic echocardiography. Cardiac thrombi were associated with higher mortality, but not higher stroke recurrence. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT07165093.

Abstract Background and aims Cardiac CT is increasingly used in the acute diagnostic work-up of acute ischemic stroke (AIS), but commonly used scan protocols do not allow assessment of left ventricular ejection fraction (LVEF), a known predictor of functional outcome. We aimed to develop a prediction model for reduced LVEF using clinical and imaging data. Methods This post-hoc analysis of the Mind the Heart study included AIS patients who underwent acute cardiac CT (acquired during diastole) and routine diagnostic work-up, including transthoracic echocardiography (TTE), which served as the reference standard for LVEF. Multivariable logistic regression models incorporating baseline variables, arterial input function (AIF) derived from CT-perfusion, and left atrial and ventricular cardiac CT volumes were developed using the training set (80%) to predict reduced LVEF (&lt;50%). Performance was evaluated on the testing set (20%) using receiver operating characteristic analysis, reporting the area under the curve (AUC), sensitivity, and specificity. Non-linear associations were modeled using restricted cubic splines, and Least Absolute Shrinkage and Selection Operator regression was used for variable selection. We evaluated whether cardiac CT information improved model fit. Results We included 298 AIS patients (61% male, median age 71 [IQR 61-79] years), of whom 87 (29%) had reduced LVEF. The final model showed moderate discrimination (AUC 0.71), sensitivity (0.67) and specificity (0.70). Including cardiac CT volumes in addition to baseline and AIF variables improved model fit (p=0.04). Conclusions Our model may aid risk stratification for reduced LVEF in AIS patients undergoing acute cardiac CT and could support identification of patients in whom additional TTE is warranted. Conflict of interest MMW received the Arthur Fonville Award for Stroke Research in 2025 for this work. SSN received travel grants from the Cultuurfondsbeurs, Remmert Adriaan Laan Fonds, CONTRAST consortium and Dr. Jan Meerwaldt Stichting outside the submitted work, JMC reports grants from Medtronic, Siemens, AstraZeneca and Bayer outside the submitted work (all paid to institution). JMC is shareholder and co-founder of TrianecT. CBM reports grants from Stryker and Boeringher-Ingelheim outside the submitted work (paid to institution) and is shareholder of Nicolab (minority interest). LAR was supported by a personal Dekker Junior Clinical Scientist Grant from the Dutch Heart Foundation.The other authors have no financial conflicts of interest.

Abstract Aims Lipoprotein(a) [Lp(a)] is a causal risk factor for cardiovascular events. However, the effect of Lp(a) on coronary plaque composition and high-risk plaque features has not been fully characterized. This study aimed to investigate the association between Lp(a) and coronary atherosclerotic plaque phenotype at the plaque level. Methods and results This study included 710 patients who underwent coronary computed tomography angiography (CCTA) and had Lp(a) measured between 2008 and 2024. CCTA scans were analysed with a previously validated artificial intelligence-based algorithm (AI-QCT, Cleerly Inc.). The association of Lp(a) with non-calcified and calcified plaque volumes and HRP features was evaluated at the plaque level using generalized estimating equation models adjusted for traditional cardiovascular risk factors. Among the 710 patients, the mean age was 56 ± 10 years and 379 (53%) were male. In total, 3642 plaques were identified. In the adjusted plaque-level analysis, elevated Lp(a) (≥150 nmol/L) was associated with an increase in non-calcified plaque volume per plaque (P = 0.009), but not with an increase in calcified plaque volume (P = 0.81). Furthermore, elevated Lp(a) (≥150 nmol/L) was strongly associated with the presence of high-risk plaque at the plaque level (adjusted odds ratio: 1.78, 95% CI: 1.25–2.54, P = 0.001), whereas low-density lipoprotein-cholesterol and high-sensitivity C-reactive protein were not (P &gt; 0.05). Conclusion In this plaque-level CCTA study of 3642 individual plaques, elevated Lp(a) levels were independently associated with increased non-calcified plaque volume and with the presence of high-risk plaque, but not with calcified plaque volume. These findings elucidate the impact of Lp(a) on unstable plaque phenotypes, even in patients without prior cardiovascular events.

Abstract Background Computed tomography coronary angiography (CCTA) has emerged as a powerful non-invasive imaging modality for the evaluation of coronary artery disease (CAD), with a global trend towards a "CT-first" strategy in stable patients with suspected CAD. While overall beneficial, this approach requires a shift in resources, straining specific parts of healthcare systems. Pre-test probability (PTP) models stratify risks of obstructive CAD and are intended to result in better utilization of CCTA. However, these models show variability across subpopulations and have modest discriminatory power with low positive predictive values (PPV). Purpose This study aims to leverage explainable artificial intelligence (XAI) for optimization of PTP models. Methods Patients that underwent a CCTA for suspected CAD with a CAD-Reporting and Data System (CAD-RADS) classification and Coronary Artery Calcium Score (CACS) were included. Obstructive CAD was defined as stenosis &gt;50% (CAD-RADS 3 or higher). Missing data was imputed. The Risk Factor Weighted Clinical Likelihood (RF-CL) model based on clinical risk factors (age, sex, type of symptoms, smoking, hypertension, dyslipidemia, diabetes and familial predisposition) was calculated. Two gradient descent-based decision tree models, "AI-ECG" and "AI-CAC" were developed. AI-ECG is built using clinical risk factors and electrocardiogram (ECG) classification. AI-CAC is built using the aforementioned features with addition of CACS. Sensitivity analysis was performed using a 15% threshold, aligning with the threshold for CCTA acquisition. Comparative analysis was performed using Python 3.10.2, with area under the curve (AUC) analysis using the DeLong test and feature importance calculation using shapely values. Preliminary results: We identified 6178 patients with a CCTA between 2022 and 2024 in the Cardiology Centers Netherlands (CCN) and included 2083 patients (mean age 57.4 ± 10.2; 48.1% male). Obstructive CAD was present in 413 (19.8%) patients. The RF-CL model was outperformed by the AI-ECG model (AUC: 0.69 vs 0.80, p&lt;0.001) and the AI-CACS model (AUC: 0.69 vs 0.90, p&lt;0.001). Although sensitivity increased in both the AI-ECG and AI-CACS models from 0.46 to 0.87 and 0.83 respectively, PPV increased only in the AI-CACS model (0.37 to 0.61). Most important features were CACS, age, sex, ECG classification and familial predisposition. Conclusion and Discussion Our study demonstrates that the incorporation of XAI with clinical risk factors, ECG classification and CACS improves the pre-test probability estimation of obstructive CAD. ECG classification appears to be a robust feature. Adopting these models can stratify patients at risk for obstructive CAD, enabling targeted use of CCTA, reducing unnecessary testing, and thus alleviate the burden on healthcare systems. However, further external validation is necessary to assess the model’s performance in prospective real-world settings.Sensitivity analysis feature importance

Abstract Background Increased QRS voltages in athletes’ ECGs are attributed to electrophysiological cellular adaptations, complicating the detection of left ventricular hypertrophy (LVH). Conversely, higher extracellular volume (ECV), indicative of diffuse fibrosis, reduces QRS voltages – so-called ‘relative voltage deficiency’– and can mask true LVH on ECG. Purpose To investigate sex-specific associations between QRS voltages and myocardial ECV and assess the impact of ECV on false-positive and negative ECG-LVH detection in elite athletes. Methods We conducted a cross-sectional, sex-specific, contrast-enhanced CMR study in healthy, elite athletes with normal ECGs and no complete right bundle branch blocks. Myocardial ECV (%) was measured from pre- and post-contrast T1 mapping. LVH on CMR was defined as an indexed LVM &gt;75 g/m² (men) or &gt;59 g/m² (women). Primary analyses evaluated correlations between ECV, LVM, and summed 12-lead ECG voltages (including voltage/LVM to assess independence), as well as Sokolow-Lyon and Cornell voltages. Secondary multivariable logistic regression examined the association of ECV on false-positive and false-negative ECG-LVH rates using Sokolow-Lyon (≥3.5 mV) and sex-specific Cornell (≥2.8 mV in men; ≥2.3 mV in women) criteria for CMR-LVH. Results In 162 elite athletes (median age 25 years, 44% female, 45% endurance, 96% Caucasian), 23% met Sokolow-Lyon criteria, 6% met Cornell criteria, and 17% had LVH on CMR. The median myocardial ECV was 23% (range 19–31%), which was lower in male compared to female athletes (22% [Q1-Q3: 21–23%] vs 25% [23–26%]; p&lt;0.001). In both sexes, summed 12-lead voltages were inversely correlated with ECV (ρ=–0.36 to –0.37; p=0.001), independent of LVM (voltage/LVM: ρ=–0.33; p=0.004). Only in female athletes did 12-lead voltages correlate with LVM (ρ=0.37; p=0.001). Logistic regression confirmed that lower ECV was associated with an increased likelihood of false-positive Sokolow-Lyon (OR: 0.64 per 1% ECV increment; p=0.011), independent of body mass index (OR: 0.77 per kg/m²; p=0.039) male sex (OR: 2.7; p=0.123) and age (OR: 0.93 per year; p=0.075; AUROC 0.82). Higher ECV conferred greater odds of a false-negative (OR 3.98 per %; p=0.041), though this was limited by small LVH-positive sample size. In Cornell-based models, lower ECV was not statistically significantly associated with increased false-positive rate (OR 0.59; p=0.059). Conclusion In elite athletes, lower ECV ("denser" myocardium) is associated with increased QRS voltages and higher false-positive ECG-LVH rate, particularly for Sokolow-Lyon, while higher ECV may dampen voltages and can mask true LVH on the ECG. Although sex-specific criteria partly mitigate ECV-related effects, these findings demonstrate inherent limitations of voltage-based LVH criteria in athletes. Unexpectedly low QRS voltages in athletes with otherwise high LVM may imply increased ECV, though further research is warranted.Figure:Likelihood of False Pos SL rate Table:Population characteristics

Abstract Background Coronary Computed Tomography Angiography (CCTA) is the first-line diagnostic tool for suspected stable Coronary Artery Disease (CAD) to rule out obstructive CAD and is recommended for risk stratification. Both obstructive CAD and total plaque burden on CCTA predict cardiovascular (CV) risk. Prior studies demonstrated that type 2 diabetes (T2D) patients exhibit greater plaque burden and higher CV event risk. Purpose This study evaluates whether T2D patients undergoing CCTA for stable CAD symptoms, when matched for traditional cardiovascular risk factors, have a higher prevalence of CAD and greater atherosclerotic plaque burden. Methods A total of 568 patients were included: 284 T2D patients were 1:1 propensity-matched to 284 non-T2D patients based on age, sex, and CV risk factors. All underwent diagnostic CCTA between January 2022 and November 2023. CCTA parameters included CAD-Reporting and Data System (RADS) classification, segment involvement score (SIS), coronary artery calcium (CAC) score, and plaque composition. SIS was defined as the number of segments with at least mild plaque. Coronary segmentation followed the 16-segment model (SCCT). Plaque burden was classified as P1 (mild), P2 (moderate), P3 (severe), and P4 (extensive) per CAD-RADS 2.0, based on SIS, CAC score, and the number and severity of affected vessels. Results The mean age was 60.8 ± 9.97 years (T2D) vs. 61.2 ± 9.80 years (non-T2D), with similar gender distribution (48.6% vs. 48.9% female). BMI was significantly higher in T2D patients (29.2 vs. 26.5, p &lt; 0.05). Smoking was less frequent in T2D patients (56.0% vs. 60.9%, p = 0.03). Other CV risk factors were similar. T2D patients were more likely to use antiplatelet and lipid-lowering agents. CAD prevalence was higher in T2D patients (83.1% vs. 76.4%, p &lt; 0.05), while obstructive CAD was not significantly higher in T2D (33.5% vs. 27.5%, p = 0.13). No significant differences were observed in 1-, 2-, or 3-vessel disease. The SIS was significantly higher in T2D patients (3.85 vs. 3.37, p = 0.03). CAC scores were higher in T2D patients (median 60 [6–369] vs. 31 [0–224]), though not statistically significant. For plaque burden classification, P2 (moderate plaque burden) was more common in non-T2D patients (23.6% vs. 15.5%, p = 0.02), while P4 (extensive plaque burden) was significantly higher in T2D patients (21.1% vs. 14.1%, p = 0.03). Conclusion When matched for cardiovascular risk factors, T2D patients more frequently exhibited CAD on CCTA, with higher SIS scores and a greater prevalence of extensive plaque burden (P4 classification). Despite greater use of preventive medication and a lower smoking prevalence in the T2D group, plaque burden remained higher in these patients. These findings emphasize the need for improved risk stratification and preventive strategies in individuals with T2D.

Abstract Background Coronary computed tomography angiography (CCTA) and myocardial perfusion imaging (MPI) are guideline-recommended to assist in clinical decision-making in patients with prior coronary artery bypass grafting (CABG). However, the value of combining CCTA and MPI for guiding revascularization decision-making in post-CABG patients with recurrent ischemic symptoms remains unexplored. In this study, we compared Heart Team strategies for revascularization based on CCTA and MPI as standalone and hybrid CCTA/MPI imaging, to strategies guided by invasive coronary angiography (ICA). Methods We included symptomatic patients with prior CABG who underwent CCTA and MPI (single-photon emission computed tomography, positron emission tomography or stress perfusion cardiac magnetic resonance imaging) preceding ICA. Simulated Heart Teams, blinded to other Heart teams and outcomes, performed revascularization decision-making based on conventional CCTA, MPI and a hybrid CCTA/MPI strategy (non-invasive Heart Team) or based on ICA (invasive Heart Team). The primary outcome was the Cohen’s kappa agreement (κ) between non-invasive and invasive Heart Teams. Results A total of 115 patients (mean age 73±7 years; 99 [86%] male) were included. Revascularization was recommended in 96 patients (83.5%) by CCTA, 92 patients (80.0%) by MPI, 80 patients (69.6%) by hybrid CCTA/MPI and 76 patients (66.1%) by ICA. The agreements were significant but low for CCTA (κ: 0.25 [95% confidence interval (CI): 0.07-0.42], P=0.003) and MPI (κ: 0.27 [95% CI: 0.09-0.48], P=0.002) compared to ICA, with only a modest increase when using the hybrid non-invasive imaging strategy (κ: 0.32 [95% CI: 0.14-0.51], P&lt;0.001). Conclusions In patients with recurrent ischemic symptoms after CABG, Heart Team assessment of conventional CCTA and MPI yielded similarly poor agreements with revascularization strategies based on ICA, with only a modest improvement observed when using a hybrid CCTA/MPI approach. Overall, non-invasive imaging alone appears insufficient to accurately guide treatment strategies in patients with prior CABG, and their use as gatekeeping for ICA in these patients should be questioned.