The Journal of Heart and Lung Transplantation

Aims: Myocardial strain enables sensitive assessment of cardiac function, but its clinical application has largely focused on individual chambers or selected patient populations. We evaluated the feasibility and clinical relevance of fully automated multi-chamber strain assessment in consecutive patients undergoing routine transthoracic echocardiography (TTE). Methods and results: This retrospective study included 8,350 consecutive adults undergoing TTE. A hospital-wide artificial intelligence (AI)-based system automatically measured left ventricular (LV) global longitudinal strain (LVGLS), left atrial (LA) reservoir strain (LASr), and right ventricular (RV) free-wall strain (RVFWS). AI-derived LVGLS was available from at least one apical view in 97.1% of patients and from all three views in 94.8%; LASr and RVFWS were available in 94.1% and 94.5%, respectively, resulting in complete multi-chamber strain assessment in 90.3%. Strain measures showed modest correlations with conventional chamber-specific echocardiographic parameters and differential associations with clinical outcomes. Gaussian mixture modeling identified three distinct clusters characterized by preserved multi-chamber function, RV-dominant dysfunction, and pan-chamber dysfunction. Compared with the preserved cluster, pan-chamber dysfunction was associated with the highest risk of all-cause death or heart failure hospitalization (adjusted hazard ratio, 3.44; 95% CI, 2.43-4.88; P<0.001). Prognostic associations remained evident in patients with LV ejection fraction (LVEF) [&ge;]50%, and cluster assignment provided incremental prognostic information beyond clinical factors, LVEF, and RV fractional area change. Conclusions: Fully automated multi-chamber strain assessment was feasible in a large consecutive TTE cohort. Integrating strain across cardiac chambers may provide complementary functional characterization and identify clinically relevant clusters with prognostic information beyond conventional assessment.

Background: The systemic immune-inflammation index (SII) is a routinely available blood-derived marker with potential prognostic relevance after coronary artery bypass grafting (CABG). We evaluated associations between preoperative SII and postoperative outcomes. Methods: PubMed, Embase, Scopus and Web of Science were searched to 1 October 2026, with supplementary searches through 14 October 2026. Peer-reviewed observational studies evaluating preoperative SII in adults undergoing CABG were eligible. Methodological quality was assessed using the Newcastle-Ottawa Scale. Compatible categorical associations and exploratory adjusted continuous mortality effects were pooled separately using restricted maximum-likelihood random-effects models; other findings were summarized descriptively. Results: Thirty-one reports were included, with an aggregate sample of 30,976 and possible cohort overlap; five contributed to meta-analysis. Two off-pump cohorts comprising 1,378 patients and 180 atrial-fibrillation events yielded an imprecise crude association with postoperative atrial fibrillation (OR 1.60, 95%CI 0.53-4.82; I2=68%). An exploratory crude synthesis indicated greater intra-aortic balloon pump use with higher SII (OR 2.45, 95%CI 1.16-5.18; I2=51%). Two cohorts with differing follow-up yielded an exploratory adjusted mortality HR of 1.11 (95% Wald CI 1.05-1.18) per study-specific SD increase in log-SII. In one 624-patient cohort, high SII was associated with postoperative acute kidney injury after adjustment (OR 3.35, 95% CI 2.25-4.97).Apparent atrial-fibrillation discrimination varied (AUC 0.587-0.946). Conclusions: Preoperative SII showed associations with selected adverse outcomes after CABG, supporting further evaluation as an accessible prognostic marker. Its incremental value beyond established clinical risk models requires validation. Keywords: Systemic immune-inflammation index; Coronary artery bypass grafting; Atrial fibrillation; Prognosis; Systematic review

Background: Transthoracic echocardiography (TTE) remains the gold standard for assessing left ventricular (LV) diastolic dysfunction (DD), but noninvasive alternatives are needed to overcome geometric and acoustic limitations. 4D-Flow MRI enables comprehensive assessment of intraventricular pressure differences (IVPDs) and flow propagation velocity (VP). We aimed to evaluate 4D-Flow-derived IVPDs and VP in patients with hypertrophic cardiomyopathy (HCM). Methods: Thirty-eight HCM patients and 38 age- and sex-matched healthy controls underwent TTE and 4D-Flow MRI. Spatiotemporal maps of velocity and IVPDs, decomposed into inertial and convective components, were derived along the main inflow streamline from the mitral valve to the apex. Peak early filling rate (PEFR) was used to normalize IVPDs and VP. Results: While absolute peak flow rates were comparable, HCM patients exhibited significantly faster VP (100.4 vs. 60.2 cm/s, p < 0.01) and higher positive early E IVPD (1.40 vs. 0.92 mmHg, p < 0.01) compared to controls. Normalizing IVPDs by PEFR amplified group differences, revealing a markedly increased flow-normalized E-IVPD (5.13 vs. 2.94 x 103 mmHg.ml1.s, p < 0.001) and deeper reverse ER IVPD (-6.06 vs. -4.61 x 103 mmHg.ml1.s, p < 0.01) in HCM. These differences were primarily driven by the inertial components. Multivariable analysis demonstrated that ER IVPD is independently determined by PEFR and the TTE E/E' ratio (r = 0.65, p < 0.001). Conclusions: 4D-Flow MRI-derived, flow-normalized IVPDs and propagation velocity provide robust, noninvasive markers of altered LV chamber stiffness and impaired diastolic filling in HCM, offering deeper 3D hemodynamic insights into diastolic dysfunction.

Background. Fluid collections are common after kidney transplantation, but their prevalence at scheduled imaging and their management are inconsistent from canter to canter. We describe the cross sectional prevalence and management of perigraft collections, including an exploratory deepdrain subgroup. Methods. In this retrospective single center cohort, 146 consecutive adult kidney transplant recipients (Cleveland Clinic Weston Hospital, July 2024 to June 2025) were imaged on postoperative day 0/1 and at approximately 1 and 3 months. Routine deep drainage was avoided (n=124), 22 clinically selected recipients with perioperative anticoagulation received a deep drain. The primary outcome was cross sectional prevalence of a perigraft collection at each visit. Secondary outcomes were management among patients with a collection. Drain group comparisons were exploratory. Results. Collections were present in 29 of 146 recipients at postoperative day 0/1 (19.9%; 95% CI, 14.2 to 27.1), 71 of 146 at 1 month (48.6%; 95% CI, 40.7 to 56.7), and 34 of 146 at 3 months (23.3%; 95% CI, 17.2 to 30.8). Prevalence in the no drain group was 21.0%, 50.0%, and 23.4%, respectively; corresponding prevalence in the deep drain group was 13.6%, 40.9%, and 22.7%. Between group prevalence comparisons were not statistically significant at any time point. BMI was higher in the deep-drain group than in the no-drain group (30.04 vs 27.1 kg/m2; P=0.01). Among patients with a 1-month collection, management did not differ significantly between groups (any invasive management, 11.1% vs 16.1%; P=1.00). Among patients with a 3month collection, invasive management was more common in the deep drain group than in the no drain group (80.0% vs 13.8%; P=0.007). This comparison included only five deep-drain recipients and was confounded by clinical selection, perioperative anticoagulation, and BMI imbalance. Conclusions. Perigraft collection prevalence was highest at 1 month and lower at 3 months in this predominantly no drain cohort. Most collections were managed conservatively, and invasive treatment was uncommon in the no-drain group. The deep drain subgroup provides clinically relevant information about high risk recipients selected for drainage but cannot support causal conclusions regarding drain benefit or harm. Patient level linkage is required to distinguish persistence, resolution, and new collection formation.

Rural patients with heart failure (HF) have poor access to care, worse outcomes, and may benefit from at-home monitoring. We evaluated whether foot temperature measured using a thermographic floor mat was associated with invasively measured cardiac output and whether longitudinal temperature changes preceded HF events. We conducted a two-part prospective, observational single-center study using the SmartMat (Podimetrics, Somerville, MA), which acquires plantar thermograms and ambient temperature. In the acute study, patients undergoing clinically indicated right heart catheterization completed 4 scans on the same day. In the chronic study, patients with a HF hospitalization in the past year and New York Heart Association Class II-III symptoms were instructed to use the device and a scale daily for 6 months. A HF event was defined as receiving at least one dose of intravenous or subcutaneous diuretic. Thirty patients were enrolled in the acute study. Mean right hallux temperature positively correlated with thermodilution cardiac output (r=0.63, p<0.001). 42 patients were enrolled in the chronic study. Among patients experiencing an HF event, ambient-adjusted hallux temperature declined in the 15 days immediately preceding the event compared with days 15-30 before the event. Plantar thermograms are associated with invasively measured cardiac output and may detect subclinical worsening before HF events. Foot temperature may provide complementary information regarding HF decompensation, supporting further evaluation of plantar thermography for remote HF monitoring.

Background: Anatomic isthmus 3 (AI 3) is defined as the myocardium between the pulmonary valve annulus and the ventricular septal defect patch that persists after tetralogy of Fallot (ToF) repair. Ventricular tachycardia (VT) propagated through slow conducting AI 3 (SCAI 3) represents a significant cause of morbidity in ToF. There is an unmet need for non-invasive identification of SCAI 3 in patients with ToF. Objectives: To assess whether the anatomic features of AI 3 as derived from cardiac computed tomography (CT) can predict slow conduction velocity during EP study. Methods: This retrospective single-center study included patients with ToF who underwent an electrophysiologic study and had AI 3 width measured from the pre-procedure cardiac CT. All patients underwent programmed ventricular stimulation, and electroanatomic. Logistic regression was performed to assess the relationship between AI 3 width and the presence of SCAI 3. Results: Of 27 consecutive patients with ToF, twelve patients were found to have SCAI 3, and ten patients were found to have SCAI 3 mediated VT. The AI 3 was significantly narrower in patients with SCAI 3 compared to those with normal AI 3 conduction (18.4 +/- 6.6 mm vs. 29.2 +/- 9.0 mm; p = 0.001). An AI 3 width above 21.5 mm carried a negative predictive value of 80.0%. Conclusion: In adults with repaired ToF referred for electrophysiology study, a narrower CT-derived AI 3 width was associated with SCAI 3 identification. AI 3 width measured on a CT obtained before PV replacement could help guide invasive risk stratification.

Background: Cardiovascular (CV) screening is critical for personnel deploying to Antarctica, where geographic isolation and limited medical care make the management of acute cardiovascular events challenging. The utility of contemporary risk prediction tools such as the AHA PREVENT equations in this unique population remains uncertain. Methods: We retrospectively analyzed 154 individuals referred for enhanced CV evaluation before deployment to the U.S. Antarctic Program (USAP). Participants were evaluated across three temporal cohorts (2018-2020, 2021-2023, and 2024-2026). Demographics, CV risk factors, cardiac testing, and deployment clearance outcomes were collected. Risk was estimated using the Framingham Risk Score (FRS), AHA/ACC Pooled Cohort Equations (PCE), and AHA PREVENT risk models. Results: The cohort was predominantly male (79.9%; mean age 44.6 {+/-} 14.6 years), and abnormal ECG was the most common referral trigger (70.8%). Median 10-year risk was low by PREVENT and FRS and borderline elevated by PCE (PREVENT 2.7% [IQR 1.1-6.6], FRS 2.3% [IQR 0.5-7.1], and PCE 6.1% [IQR 2.4-9.2]). Among 72 participants with all scores, 51% were classified discordantly; PREVENT ASCVD agreed closely with FRS (=0.77) but poorly with PCE (=0.24-0.35), which consistently estimated higher risk. PCE was calculable in 52.6% versus 70.8% for PREVENT. Overall, 132 participants (85.7%) were cleared for deployment, while 8 (5.2%) were not physically qualified (NPQ); 6 of these NPQs were due to cardiovascular causes. Of 22 cardiac medical evacuations during the study period, 21 involved individuals without prior advanced cardiovascular screening. One screened individual was evacuated for symptoms subsequently found to have no cardiac cause. Conclusions: Risk calculators disagree substantially in the fitness-selected population. We recommend PREVENT as the primary risk-stratification tool as it is the most contemporary derivation, incorporates renal function, is race-agnostic, extends to heart failure, applies from age 30, and agrees closely with FRS, easing transition. Targeted imaging, including coronary artery calcium scoring, may supplement intermediate-risk candidates.

Background Cardiac amyloidosis is an increasingly recognized cause of heart failure in older adults, yet Colombian data, and data from the southwest of the country in particular, remain scarce. We describe the clinical, diagnostic, imaging and outcome profile of patients with cardiac amyloidosis at two high-complexity institutions in Cali. Methods Observational, descriptive, retrospective, two-center study. Patients were identified in the institutional registries of both centers using ICD-10 codes for amyloidosis, and clinical data were abstracted manually from medical records. Continuous variables are reported as median (interquartile range) and categorical variables as counts and percentages over the number of patients with available data. Results Thirty-two patients were analyzed (median age 77 years; 68.8% men). Heart failure (90.6%), atrial fibrillation (46.9%) and carpal tunnel syndrome (31.2%) were frequent. The etiological classification depended on the test considered: bone scintigraphy was positive (Perugini 2-3) in 23 of 26 patients studied (88.5%), but a monoclonal protein was screened for in only 22, and the full non-invasive criteria for ATTR were met in 16 of 32 (50.0%). Genetic testing was positive in 9 of 18 tested, and the variant was Val142Ile in all 8 patients in whom it was characterized. The working diagnosis was ATTR in 26 patients (81.2%) and AL in 6 (18.8%). Tafamidis was used in 37.5%. Eleven of the 31 patients with known vital status died (35.5%), and NT-proBNP was markedly higher among those who died (6640 vs 1186 pg/mL; p=0.003). Conclusions In this southwestern Colombian cohort, cardiac amyloidosis presented as the classic transthyretin phenotype, with the Val142Ile variant in all 8 patients in whom it was characterized. Bone scintigraphy was frequently positive, but screening for a monoclonal protein was often omitted, so only half the cohort met the full non-invasive criteria for ATTR. Mortality was high and closely associated with NT-proBNP.

Background: Artificial intelligence (AI) may improve electrocardiographic differentiation of Takotsubo syndrome from acute anterior ST-segment elevation myocardial infarction (STEMI), but its impact on human diagnostic performance, the added value of visual explanations, and differences by reader background and experience remain uncertain. Methods: Using 12-lead electrocardiogram (ECG) images from two hospitals, we developed and externally validated an ensemble of three deep learning models after self-supervised pretraining and fine-tuning. The diagnostic task used ECGs recorded within 14 days after symptom onset, regardless of reperfusion status. We conducted a four-phase reader study. Phases 1-3 compared unaided interpretation, a reference sheet, and additional AI assistance. In Phase 4, readers evaluated a new ECG set after randomization to reference-sheet support alone, with AI predictions, or with AI predictions plus gradient-weighted class activation mapping (Grad-CAM) heatmaps. Diagnostic correctness was analyzed using generalized linear mixed-effects models. Exploratory analyses examined differences by cardiologist status and experience. Results: Development and external-validation cohorts, including healthy controls, comprised 832 and 95 participants, respectively. For Takotsubo-STEMI discrimination, external-validation accuracy was 0.914, with areas under the receiver operating characteristic and precision-recall curves of 0.970 and 0.984. Seventy healthcare providers completed the reader study. The estimated probability of correct diagnosis increased from 0.632 without assistance to 0.864 with AI assistance (odds ratio [OR], 3.71; P<0.001). In randomized Phase 4, AI assistance improved accuracy vs reference-sheet support alone (OR, 4.28; 95% CI, 3.08-5.95; P<0.001), and Grad-CAM provided additional benefit (OR, 1.53; 95% CI, 1.04-2.25; P=0.033). Exploratory analyses showed greater improvement among less experienced readers; with AI assistance, non-cardiologists outperformed cardiologists. AI-assisted readers remained less accurate overall than the model alone. Conclusions: An ECG image-based ensemble differentiated Takotsubo syndrome from anterior STEMI and improved reader accuracy. Visual explanations provided additional benefit, while experience-related differences highlight the importance of effective human-AI interaction.

Background: Coronary perivascular fat attenuation index score (FAI-Score) on coronary computed tomography angiography (CCTA) quantifies vascular inflammation and predicts cardiac mortality in symptomatic cohorts. However, its prevalence, anatomical distribution, and clinical correlates in asymptomatic primary prevention populations remain uncharacterized. Methods: In an IRB-approved prospective study across two clinical sites, 84 consecutive asymptomatic adults (mean age 53.7 {+/-} 8.6 years; 63.1% men) with no prior coronary artery disease underwent screening CCTA and comprehensive clinical, metabolic, and biomarker profiling. AI-standardized FAI-Score was quantified across three epicardial vessels (LAD, LCx, RCA). High and very high perivascular inflammation were pre-specified as any vessel [&ge;]75th and [&ge;]90th percentiles, respectively. Luminal stenosis and plaque were graded using CAD-RADS 2.0. Results: Elevated FAI-Score ([&ge;]75th percentile) was present in 42.9% of participants (36/84; 95% CI 32.8% - 53.5%), with 17.9% (15/84; 95% CI 11.1% - 27.4%) exhibiting very high inflammation ([&ge;]90th percentile). Multi-vessel inflammation was identified in 17.9% (15/84), with the RCA most frequently involved ([&ge;]90th percentile in 13.1%). Standard circulating biomarkers, including ApoB, non-HDL-C, HbA1c, and PREVENT-ASCVD 10-year risk showed no association with binary inflammation. Systemic hs-CRP (median 0.8 mg/L) exhibited an inverse correlation with maximum vessel FAI-Score (Spearman {rho}=-0.27, p=0.014). Men demonstrated higher rates of elevated FAI-Score than women (52.8% vs. 25.8%, p=0.016; [&ge;]90th percentile: 26.4% vs. 3.2%, p=0.007). Strikingly, 46.2% (30/65) of participants with normal luminal anatomy (CAD-RADS 0) and 47.2% (25/53) with zero plaque burden harbored elevated FAI-Score; all 15 individuals with very high FAI-Score had CAD-RADS 0 (Fisher's exact p=0.018). Body mass index was the sole secondary correlate surviving false discovery rate correction (AUC = 0.71, p=0.001, all-test FDR q=0.028). Regularized multivariable models showed modest out-of-sample discrimination for FAI-Score elevation (cross-validated AUC = 0.71). Conclusions: Coronary perivascular inflammation is common among asymptomatic adults and frequently uncouples from structural plaque and luminal stenosis. Routine circulating biomarkers and clinical risk calculators fail to identify inflamed vessels, highlighting FAI-Score as an independent dimension of primary cardiovascular risk assessment.

Background. Real-world 12-lead electrocardiograms (ECGs) often have missing or corrupted leads. A deep-learning classifier can be prepared for this by random lead masking during training, or by injecting clinical knowledge, for example by pulling its attention towards the leads that guidelines use for each diagnosis. Whether this knowledge adds robustness beyond masking is unknown. Methods. Pre-registered comparison of three arms sharing one network (per-lead 1D-ResNet encoder and per-diagnosis attention over the 12 leads): standard training (M0); random whole-lead masking (M1); masking plus a Kullback-Leibler penalty pulling attention towards a fixed guideline-derived key-lead map (M2, guideline-based attention guidance). Six diagnoses; five seeds per arm. Development on PTB-XL (21,799 ECGs); single sealed evaluation on PTB-XL fold 10 (2,198 ECGs) and on CODE-15% (233,204 exams, external validation). Primary endpoint: AUROC difference M2 - M1, averaged over first-degree AV block, right and left bundle branch block and atrial fibrillation and over 1 to 6 lost (zeroed) leads, with a patient-level paired BCa bootstrap 95% confidence interval. Results. The guidance did not change robustness: {Delta}AUROC -0.0010 (95% CI -0.0033 to +0.0006), an interval entirely within the pre-specified +-0.02 margin; the result was unchanged with another bootstrap seed, other interval methods and leave-one-diagnosis-out analyses. Masking improved AUROC: M1 - M0 = +0.0134 (95% CI +0.0102 to +0.0172) when one key lead was lost, and the number of lost leads tolerated before AUROC fell by more than 0.02 rose from 7 (M0) to 10 (M1). M2 attention matched the map and M2 was non-inferior on intact ECGs, but its calibration slope was lower for all six diagnoses in both datasets. M2 lost slightly more when all key leads were lost together (-0.0067) and gained only when one to three leads remained (exploratory; AUROC 0.9408 vs 0.9210 with 11 leads lost). CODE-15% reproduced every pattern (primary -0.0007, 95% CI -0.0011 to -0.0003). Conclusions. Random lead masking suffices to make an ECG classifier robust to missing leads; adding guideline knowledge aligns attention with clinical criteria but adds no robustness and worsens calibration. Guideline-aligned attention should not be taken as evidence of robustness.

Chronic intermittent hypobaric hypoxia is an occupational exposure experienced by workers who alternate between high-altitude worksites and lower-altitude resting locations. Its effects on cardiac autonomic modulation and electrocardiographic parameters remain insufficiently characterized in Andean workers. This study aimed to compare heart rate variability and electrocardiographic parameters between workers exposed to chronic intermittent hypobaric hypoxia and controls working permanently at lower altitude in Arequipa, Peru. An observational cross-sectional study was conducted in 96 male workers aged 20-60 years. The exposed group included 53 workers performing rotational shifts at altitudes [&ge;]3,000 m above sea level with rest periods at <2,500 m, while the control group included 43 workers working permanently at <2,500 m. Heart rate variability was assessed during the morning rest period in Arequipa, at approximately 2,300 25 m above sea level, using a Polar(R) H10 heart rate sensor after 15 minutes of rest. Participants also underwent standard 12-lead electrocardiography. Vital signs were clinically similar between groups. No statistically significant differences were observed in PR interval, corrected QT interval, time-domain heart rate variability parameters, or frequency-domain heart rate variability parameters. In this sample of apparently healthy male workers evaluated during their rest period at moderate altitude, exposure to chronic intermittent hypobaric hypoxia was not associated with significant differences in resting heart rate variability or standard electrocardiographic parameters.

BACKGROUND: The chromosome 9p21.3 locus is among the strongest genetic risk loci for cardiovascular disease (CVD), yet the regulatory mechanisms underlying this association remain poorly understood. Previous vascular disease studies focused predominantly on the role of this locus in smooth muscle cell (SMC) dysfunction, whereas its potential role in endothelial cells (ECs) remains less well characterized. Here, we sought to identify candidate regulatory variants at 9p21.3, their distal target genes, and effector transcripts that contribute to CVD-related phenotypes in ECs. METHODS: Promoter capture Hi-C was used to map chromatin interactions at 9p21.3 in primary human ascending aortic SMCs (n=6), supplementing the previously obtained ECs (n=16) dataset. To support the regulatory relevance of these interactions, expression quantitative trait locus analysis was performed in 136 vascular biopsies. Variant effects were prioritized in silico using AlphaGenome. The regulatory activity of the prioritized region was validated using CRISPR activation. RESULTS: Chromatin interaction mapping identified a complex regulatory architecture at the 9p21.3 locus involving 19 putative regulatory elements and 15 genes across ECs and SMCs. MIR31HG showed the most recurrent distal promoter connectivity with the 9p21.3 region. Consistent with the chromatin interaction map, expression of MIR31HG transcripts was associated with genetic variation at the 9p21.3 locus. In ECs, the lncRNA MIR31HG, but not miR-31, was responsive to hemodynamic flow. Depletion of MIR31HG in ECs was associated with endothelial activation. Epigenetic tracks and deep learning predictions highlighted an active enhancer element at 9p21.3, which was subsequently validated by CRISPR activation and increased MIR31HG expression, confirming its capacity to regulate MIR31HG over a large genomic distance of approximately 538 kb. CONCLUSIONS: Altogether, these data implicate lncRNA MIR31HG as a likely effector of the 9p21.3 CVD locus, linking the cis-regulatory element and heritable genetic variation in the respective region to endothelial activation through long-range enhancer regulation.

Rationale: Conventional CT-derived pulmonary vascular metrics quantify vascular pruning but do not assess the spatial heterogeneity of vascular architecture. In COPD, peripheral microvascular pruning coexists with compensatory central vessel dilation, paradoxically preserving total vessel volume while reducing effective vascular penetration into lung parenchyma. Objectives: To develop and evaluate Vascular Proximity Coverage (VPC), a distance-based CT biomarker quantifying the spatial efficiency of pulmonary vascular distribution. Methods: This retrospective analysis included 7,881 COPDGene participants [PHASE] with complete vascular segmentations. VPC was estimated by integrating the area under the cumulative lung tissue coverage curve at distances of 0-10 mm from segmented vessel voxels. Multivariable models assessed associations with lung function, six-minute walk distance (6MWD), St. George's Respiratory Questionnaire (SGRQ) score, mMRC dyspnea score, and all-cause mortality over a median follow-up of [10.8] years, adjusting for demographics, smoking, emphysema, scanner type, and BV5. The cohort was stratified at median BV5 and VPC into concordant (high/high, low/low) and discordant (high-BV5/low-VPC, low-BV5/high-VPC) vascular phenotypes. Results: VPC declined across disease severity (5.82 {+/-} 0.50 [UNITS] in non-smokers to 5.21 {+/-} 0.64 in GOLD 4; p < 0.001). Among spirometrically normal smokers, current smokers had lower VPC than former smokers (5.31 vs. 5.68; p < 0.001). Each standard deviation decrease in VPC was independently associated with reduced 6MWD ({beta} = -16.8 m, 95% CI: -19.5 to -14.0), worse SGRQ ({beta} = 1.9, 95% CI: 1.4 to 2.4), and greater dyspnea (RR = 1.05, 95% CI: 1.03 to 1.08; all p < 0.001). The lowest VPC quartile was associated with 38% higher mortality than the reference quartile (HR = 1.38, 95% CI: 1.18 to 1.62; p < 0.001). The high-BV5/low-VPC phenotype showed 24% higher mortality than high-BV5/high-VPC (HR = 1.24, 95% CI: 1.08 to 1.42; p = 0.002) despite preserved vessel volume. Conclusions: VPC captures spatial heterogeneity of vascular architecture independent of vessel volume, is reduced in smokers without airflow obstruction, and identifies excess mortality risk among individuals whose total vessel volume appears preserved.

Background. Immune checkpoint inhibitors (ICIs) can cause immune-related adverse events in almost any organ. While myocarditis has received the most attention, data on pericardial disease with ICI use are limited. We examined pericardial adverse event reporting with nine ICIs using the FDA Adverse Event Reporting System (FAERS). Methods. We combined legacy AERS and current FAERS quarterly files from January 2011 to June 2026 into 18,629,240 unique cases, deduplicated by case number, and removed cases the FDA had listed as deleted. ICI exposure was identified from generic names, brand names, development code names and the active-ingredient field. Pericardial events were defined by seven MedDRA preferred terms. We estimated reporting odds ratios (ROR), proportional reporting ratios (PRR), Bayesian information components (IC) and empirical Bayes geometric means (EBGM). We also examined myocarditis co-reporting, time trends, a comparison with other antineoplastic agents, a MedDRA query-based outcome, and 14 alternative definitions. Results. The analysis included 18,514,045 cases: 277,434 involved an ICI, 34,792 carried a pericardial term, and 1,680 had both. Pericardial events were reported disproportionately with ICIs (ROR 3.35 (95% CI 3.19 to 3.52); PRR 3.34; IC025 1.62). Eight of nine agents had a ROR above 1 (3.32 to 5.63). Among the most frequently reported terms, estimates were highest for cardiac tamponade (5.59 (95% CI 4.98 to 6.28)), followed by pericardial effusion (3.83 (95% CI 3.60 to 4.07)) and pericarditis (2.09 (95% CI 1.89 to 2.31)). After removing cases that also reported myocarditis, the ROR was 3.13 (95% CI 2.98 to 3.30). Most sensitivity analyses gave similar estimates (ROR 3.13 to 3.47); defining exposure by generic drug names alone, which identified only 44% of exposed cases, gave 3.99. Compared with cases naming other L01 antineoplastic agents, the ROR was 1.13 (95% CI 1.08 to 1.19): 1.28 (95% CI 1.20 to 1.36) for ICI-only cases and 0.96 (95% CI 0.89 to 1.04) when another antineoplastic was also named. The ICI-specific reporting odds ratio fell each quarter (odds ratio 0.977 per quarter, 95% CI 0.973 to 0.980). Conclusions. In FAERS, pericardial events were reported more often with ICIs than with other drugs across most agents and terms; however, incidence and causation cannot be determined. The excess over other antineoplastic agents was small, and reporting disproportionality declined over time. These findings support clinical awareness of pericardial disease in patients receiving ICIs and warrant study in data that can measure incidence.

Patients with implantable cardioverter-defibrillators (ICDs) often are excluded from receiving CMR scans at 3.0T due to ICD-induced image artifacts. This work aims to transfer sequence protocols established for CMR imaging in the presence of ICDs at 1.5T to a first human application at 3.0T. All measurements were performed on a clinical 3T MRI scanner. Phantom measurements were used to establish and optimize wideband PSIR LGE imaging at 3.0T. Volunteer measurements with externally placed ICDs were used for optimization of CINE imaging and wideband PSIR imaging. Thirdly, patients with implanted ICD were examined with the optimized protocols. Human measurements showed that SA stacks obtained with spoiled GRE after contrast agent showed a markedly lower artifact burden than the conventional approach. For scar imaging, a wideband PSIR with a bandwidth of 3kHz and a frequency offset of +750Hz allowed a sufficient suppression of relevant artifacts in the majority of scans. No strong correlation between the image quality and the distance between the cardiac silhouette and the device was detected. The presented work shows the feasibility of clinical cardiac MRI at 3.0T including GRE-CINE and wideband PSIR-LGE for patients with ICDs.

Objectives: To determine how strongly clinical referral text, rather than image content, drives the decisions of multimodal large language models (LLMs) differentiating glioma from brain abscess on MRI. Materials and methods: This retrospective single-center study included 60 contrast-enhanced T1-weighted brain MRI examinations (30 gliomas, 30 abscesses; reference-standard diagnosis). One axial slice per case was paired with five referral texts (explicitly inflammatory to explicitly tumor-suggestive) under three prompt instructions and submitted 20 times each to GPT-4o, Claude Sonnet 5, Gemini 3.5 Flash, and Qwen 3.6 (72,000 answers). The primary outcome was the text-driven span (difference in tumor-call frequency between explicit inflammatory and explicit tumor text). Two blinded radiologists classified the images without text; sensitivity, specificity, and accuracy were compared descriptively. Results: Patients (29 women) had a mean age of 55.8 +/- 16.4 years. With neutral text, models answered tumor in 45-67% of queries (specificity, 0.38-0.78), versus 52% and 60% for radiologists (specificity, 0.77 and 0.63). The text-driven span was 0.79-1.00 (p < 0.001 for all models), whereas confirmed gliomas and abscesses differed by only 0.01-0.10 in three models and 0.25 in Gemini 3.5 Flash. Subtle wording produced at least 83% of the span in three models. An instruction to ignore the text reduced the span to 0.48-0.70 in three models and to 0.04 in Gemini 3.5 Flash, partly through reversion to a tumor default. Model accuracy was 0.52-0.73 versus 0.78 and 0.73 for radiologists. Conclusion: Multimodal LLMs deferred to referral text over imaging evidence in differentiating glioma from brain abscess, and prompt instructions did not reliably correct this.

Blood-based neurofilament light (NfL) is associated with all-cause mortality, but whether this reflects neuroaxonal injury or overlaps with cognitive and functional decline remains unclear. We followed 559 individuals aged 92-107 from three oldest-old cohorts for up to 16 years: cognitively healthy Dutch centenarians and two population-based Danish cohorts. Plasma biomarkers (A{beta}42/40, A{beta}40, A{beta}42, pTau-181, pTau-181/A{beta}42, NfL, and GFAP; Dutch cohort; NfL, Danish cohorts), cognition, and activities of daily living (ADL) were evaluated against mortality. NfL was the only biomarker consistently associated with mortality (HR 1.21-1.38), whereas AD-specific biomarkers did not predict mortality despite reflecting post-mortem AD neuropathology. NfL remained associated with mortality independently of cognition and ADL; ADL mediated 13-21% across cohorts and cognition 28%, only where cognitive impairment was widespread. Mortality at extreme age is more closely linked to neuroaxonal injury than to upstream AD pathology, with NfL capturing biological vulnerability beyond cognitive and functional decline.

Lesion network mapping (LNM) has provided a compelling framework in clinical neuroscience, linking focal brain damage at heterogeneous anatomical locations to shared functional networks across behavioural syndromes. Recently, the methodological specificity of LNM has come under discussion following observations that derived network maps tend to converge onto the normative connectome's generic degree distribution. While current efforts largely treat this convergence as a statistical inference challenge addressable via post-hoc spatial null models or individual-level analyses, we identify a foundational upstream measurement artifact operating within individual patients: the lesion "bystander effect". Because pathological lesions follow biological constraints rather than functional brain parcellations, a typical lesion encapsulates both a symptom-driving critical node and surrounding asymptomatic bystander tissue. By averaging connectivity profiles across the entire lesion mask, LNM mechanically dilutes focal clinical signals. Across empirical clinical cohorts, individual-level machine learning classifiers, synthetic within-cohort lesion unions, and whole-brain spherical simulations, we demonstrate that increasing lesion extent deterministically drives network maps toward the connectome degree vector following a mathematical power law. Fulfilling the clinical promise of LNM will therefore require computational strategies that isolate the causal functional core from surrounding bystander tissue prior to network projection.

Chinese is one of the living languages with the highest homophone densities, making homophone processing a critical component of language comprehension and orthographic decoding, as well as an ideal model for examining its cognitive mechanisms. This study assessed mono- and bi-character homophone selection function in 129 Mandarin- and Cantonese-speaking participants, including 66 cognitively healthy individuals, 17 with semantic variant (sv) primary progressive aphasia (PPA), 23 with the nonfluent/agrammatic variant (nfv) PPA, and 23 with the logopenic variant (lv) PPA. All PPA variants showed impairment in homophone selection, with most significant deficits in svPPA and lvPPA. ROC analyses demonstrated its strong diagnostic utility for distinguishing PPA from controls. Voxel-based morphometry revealed that homophone performance correlated with gray-matter volume in left anterior and inferior temporal regions, with variant-specific patterns observed. These findings described the potential role of homophone selection in diagnosing PPA syndrome in Chinese speakers, illuminate crosslinguistic influences on language impairment in PPA, and provide novel insights into the cognitive processing of homophones.