NMR in Biomedicine

Background and Aims: Steatotic liver disease (SLD) has high clinical and public health relevance. Robust population estimates of SLD and its subcategories are challenging due to the limitations of ultrasound measurements or non-invasive scores, particularly for low-grade steatosis. We aimed to quantify SLD prevalence using magnetic resonance imaging (MRI) in the population-based German National Cohort (NAKO). Methods: Hepatic multi-echo Dixon MRI was performed at 5 dedicated study sites with identical setup across Germany. Liver fat (proton density fat fraction, PDFF), R2* as proxy for liver iron, and liver volume were assessed. The resulting data of N = 29'842 individuals (age range 20-72 years) were weighted by survey weights for regional representativeness, resulting in a sample of 50% women and a mean age of 45.6 years. SLD was defined as PDFF [&ge;] 5.75%, and sex-specific prevalence according to age, BMI, socioeconomic status and geographic region was calculated. Results: Overall, SLD prevalence was 21.3% in women and 35.7% in men, and the majority were metabolic dysfunction-associated (MASLD, 89.3% of all SLD cases). Prevalence increased with age in a sex-specific pattern, suggesting potential menopausal effects in women. There was a relevant prevalence of SLD in individuals with normal weight (5.3% in women, 13.2% in men) and the age group <25 years (7.5% in women, 11.9% in women). Differences in prevalence between low and high socioeconomic status were more pronounced in women (37% vs 15.8%) compared to men (45.5% vs 30.3%). Conclusions: Data underscore the high public health relevance of SLD and its subcategory MASLD. The considerable prevalence in groups historically considered low-risk, such as younger or lean individuals, emphasizes the need for raising awareness early.

Background: Cardiovascular magnetic resonance (CMR) quantification of the left ventricular (LV) volumes and ejection fraction (EF) typically involves manual segmentation of many short axis (SAx) and long axis (LAx) slices of the left ventricle. The scan time and the number of breath holds is proportional to the number of slices. We aimed to evaluate a geometric model of the left ventricle that could enable planimetry from a reduced number of slices. We sought to determine whether acceptable accuracy was retained for evaluating the End Diastolic Volume (EDV), End Systolic Volume (ESV), Stroke Volume (SV), and EF to provide a rapid and reliable clinical alternative. Methods: A cohort of 342 patients, median age: 54 (40 - 65) years, with full-stack CMR examinations was used. Nine geometrical combinations were evaluated: 3, 4 or 5 short axis slices and one of three LAx orientations (2-chamber, 3-chamber or 4-chamber) by retrospectively decimating the full-stack acquisition. LV volumes were calculated as a sum of trapezoidal approximations for apical and mid-cavity slices and a generalized prismoidal model at the base. The accuracy of the volume calculations was quantified against the full-stack reference for the EDV, ESV, SV, and EF using concordance correlation coefficient (CCC), two-way repeated measures ANOVA, pairwise tests, and Bayes factor log10(BF10) analysis. Results: The choice of the long axis (LAx) view was the most influential driver of accuracy (g2 = 0.104, for EDV), approximately 50 times more impactful than the number of SAx slices (g2 = 0.002, for EDV). Volumes calculated using the combination of 2-chamber LAx view and 5 SAx slices had the highest concordance with the full stack (CCC>0.90). While the estimated absolute volumes displayed a systematic negative bias, EF and SV remained highly robust due to bias cancellation. For a 2ch + 5 SAx protocol, EF bias was just 0.83% (LoA: -6.18 to 7.84%), with a minimum detectable change (MDC) of 7.01%, compared to 8.7% reported for expert human readers, suggesting strong concordance. Bayesian paired-samples t-tests yielded log10(BF10) = 6.42 in favor of 5 SAx over 3 SAx, constituting decisive evidence on the Jeffreys scale. The bias and limits of agreement (LoA) for stroke volume and ejection fraction were found to be lower than scan-rescan reproducibility in literature. Conclusion: This reduced-slice geometric model allows for reduced number of breath holds compared to a conventional full-stack CMR acquisition and provides an acceptable accuracy with bias less than scan-rescan variability.

Hypoxia-targeted BOLD MRI is a novel technique, which probes oxygenation physiology in response to a controlled transient hypoxia stimulus. In glioblastoma, the signal response is spatially and temporally heterogeneous. We developed a voxel-wise temporal decomposition framework for hypoxia-targeted BOLD MRI that separates the arrival of responses, transition phases, and steady state during controlled isocapnic hypoxia. Twenty healthy controls underwent 3-T BOLD MRI during a double hypoxic step challenge to establish a normative reference. Three patients with newly diagnosed glioblastoma were included as proof-of-concept cases. For each voxel, we estimated response arrival delay (Delaycorr), delay to plateau, delay to return and an O2-normalized steady-state response (HypoxiaSS). Healthy-control maps were used to construct a voxel-wise normative atlas and, for HypoxiaSS, a global-response-adjusted model for patient deviation mapping. In healthy controls, HypoxiaSS showed lower supratentorial between-subject variabilitythan both whole-stimulus comparators (coefficient of variation: 1.77 versus 2.36 for Hypoxiaavg) and higher voxel-level step-to-step agreement (ICC(2,1): median 0.951 versus 0.792 for Hypoxiaavg). Whole-stimulus averaging exhibited a systematic step-2 signal amplification present in 19 of 20 subjects, which was absent from HypoxiaSS. Asingle global response scalar explained a median 72.5% of voxel-wise between-subject variance in HypoxiaSS. In proof-of-concept patient analyses, G-adjusted HypoxiaSS deviation maps and timing maps identified spatially coherentabnormalities that were partly complementary and extended beyond conventional MRI-defined lesion margins.Temporal decomposition improves the stability and interpretability of hypoxia-targeted BOLD MRI and provides a practical framework for population-referenced physiological mapping and atlas-based deviation mapping in glioblastoma.

Purpose. The choroid plexus (ChP) is the primary source of cerebrospinal fluid and an emerging marker of cerebral health, with enlargement and hypoperfusion reported in aging and neurodegeneration. However, frequent ChP calcifications can confound volumetric and perfusion measures. Although computed tomography (CT) is the gold standard for detecting calcification, it is rarely available in research MRI. Quantitative susceptibility mapping (QSM) offers an alternative sensitive to diamagnetic mineralization but lacks validated susceptibility thresholds. Method. Participants underwent CT and MRI within four weeks, including 3D T1-weighted and a multi-echo gradient echo QSM MRI. ChP calcifications were identified on CT using standard diagnostic criteria. Using the Bayes decision boundary framework, we identified optimal susceptibility thresholds for detecting diamagnetic signals consistent with calcification and compared these thresholds with multiple density levels measured on gold standard CT images. Results. Across all participants (n=20; age=62.2+-12.0 yrs), the optimal susceptibility threshold separating background ChP signal from calcifications was -0.10 ppm at 60 HU (low-density) and -0.15 ppm at 100 HU (high-density). Susceptibility values within calcified tissue exhibited a linear relationship with CT-derived tissue density. A significant positive association was observed between ChP volume and calcification volume among participants with detectable calcification (beta=2.26, p=0.047). Conclusion. This work should provide a practical framework for quantifying ChP calcifications routinely from MRI. The observed relationship between ChP volume and calcification volume highlights the importance of accounting for calcified tissue, particularly when calcification burden is substantial, when investigating ChP abnormalities in aging and neurodegenerative disease.

Background: Quantitative lipid assessment is central to identifying rupture-prone coronary plaques and represents a therapeutic target for lipid-lowering therapy. Near-infrared spectroscopy (NIRS)-derived lipid core burden index (LCBI) is well validated and widely used for detecting lipid-rich lesions. Optical frequency domain imaging (OFDI) is increasingly adopted for guiding percutaneous coronary intervention (PCI) due to its high-resolution structural imaging capabilities. Depolarization-sensitive OFDI (depOFDI) provides intrinsic lipid contrast and may enable combined structural and compositional plaque characterization within a single OFDI-based platform. Objective: To define an OFDI-derived lipid metric and evaluate its agreement with NIRS-derived LCBI. Methods: Thirty-three patients underwent both polarization-sensitive OFDI and NIRS-intravascular ultrasound imaging during PCI. After exclusion of 4 datasets, 29 co-registered pullbacks were analyzed. A signal-to-noise-corrected depolarization metric was used to identify lipid-rich regions and generate depOFDI chemograms. maxLCBI4mm value and location, as well as total LCBI, were computed and compared with NIRS. Results: depOFDI demonstrated strong agreement with NIRS, showing high correlation for maxLCBI4mm (r^2 = 0.862) and total LCBI (r^2 = 0.867), along with strong spatial concordance for the location of the maxLCBI4mm (r^2 = 0.900). Bland-Altman analysis of LCBI4mm showed minimal bias (10.7) with 95% limits of agreement of [81.4 to 102.8]. Conclusions: depOFDI enables accurate quantification of lipid burden alongside the high-resolution structural information inherently provided by OFDI. Because depolarization metrics can be derived from polarization-diverse detection available in many commercial OFDI systems, this approach provides a practical pathway toward comprehensive plaque characterization within existing PCI workflows, without the need for additional imaging modalities.

Background: Autosomal recessive spastic ataxia of Charlevoix-Saguenay (ARSACS) is a genetic disease characterized by spasticity and ataxia which reflects involvement of the corticospinal tracts (CST) and cerebellum. The primary involvement of the middle cerebellar peduncles (MCP) and transverse pontine fibers (TPF) at the crossing with the CST, and their role in the pathophysiology of the disease, is currently debated. Objectives: Advanced MRI techniques capable of isolating sub-voxel microstructural parameters can test the hypothesis that the MCP and TPF are abnormally large, compressing the CST at their crossing, and potentially impairing CST development. Methods: Tract macro- and micro-structural properties, including axon and tract caliber, axon density and geometry, and myelin content were estimated from diffusion-relaxometry and magnetization transfer imaging. These features were analyzed along segments of the CST, MCP, and TPF of 9 patients and 9 age-matched controls. Results: While the CST showed significant decreases in tract size, axon caliber, and myelination throughout its length compared to controls (p<0.01), the MCP and TPF were relatively unaffected. In our group, neither the MCP nor the pons were enlarged. The proximal MCP showed an increase in axon caliber. Conclusions: The increase in fractional anisotropy and axon density towards the center of the TPF could be driven by geometric confounds related to differences in the relative sizes of the CST and TPF compared to controls. This highlights the importance of investigating tract-specific microstructural profiles, particularly in regions of geometric complexity. The findings confirm the involvement of the CST, with a relatively limited involvement of the MCP and TPF.

Our study evaluated whether a deep learning auto segmentation model combined with machine learning triage can streamline radiotherapy clinical trial quality assurance (QA). We analyzed 107 stereotactic ablative radiotherapy (SABR) cases from a multi-institutional phase II clinical trial of neurovascular sparing prostate SABR, focusing on physician contours of the internal pudendal artery (IPA) as a novel organ-at-risk with substantial interobserver variability. Contours were scored by the trial principal investigator as Per-Protocol or Minor Deviation/Unacceptable. We applied a deep learning model for IPA auto-segmentation. Agreement between human and AI contours was then quantified using 14 overlap, distance, and surface metrics, and a supervised classifier was trained on these metrics to flag clinical trial protocol deviations. While AI segmentation achieved only modest geometric accuracy with mean Dice similarity coefficient of 0.446 and 95th percentile Hausdorff distance of 14.23, when incorporating all 14 metrics, a machine learning classifier yielded AUROC of 0.836, flagging all Minor Deviation/Unacceptable cases with 100% sensitivity on the 27 case hold-out set with 6 false positives and no false negatives. AI segmentation combined with metrics-based machine learning can triage protocol deviations within a multi-institution radiotherapy clinical trial, supporting prospective evaluation of AI-assisted trial QA.

Background: Prostate-specific membrane antigen (PSMA) PET/CT is central to prostate cancer staging and theranostic workflows. To our knowledge, no direct within-patient comparison of [18F]FC303 ([18F]Florastamin) and [68Ga]Ga-PSMA-11 has been reported. We performed a preliminary paired method-comparison study under non-harmonized acquisition protocols. Patients and Methods: Twenty patients with histologically confirmed prostate cancer underwent [68Ga]Ga-PSMA-11 PET/CT (185 +/- 37 MBq, 60 +/- 10 min) followed by [18F]FC303 PET/CT (370 +/- 37 MBq, 105 +/- 15 min) on the same PET/CT system within each patient (median interval, 29.5 days). Index targets were anatomically matched to the biopsied or surgically sampled lesion or target region. The primary malignant set included 18 histologically malignant targets; two histology-negative or indeterminate targets were included only in sensitivity analysis. Fixed [68Ga]Ga-PSMA-11-first scan order and the 45-min uptake-time difference were central interpretive constraints. Results: Across five predefined reference organs, [18F]FC303 showed lower SUVmean than [68Ga]Ga-PSMA-11 (all Benjamini-Hochberg-adjusted p < 0.001; [68Ga]/[18F]FC303 geometric mean ratio [GMR], 1.29-3.89). In the primary malignant set, [18F]FC303 lesion SUVmax was lower than [68Ga]Ga-PSMA-11 (median, 11.3 vs 18.1; paired median difference, -5.50; 95% CI, -6.85 to -2.90; Wilcoxon p = 8.4 x 10-4), with strong rank correlation (Spearman {rho} = 0.90). Passing-Bablok regression yielded {beta} = 1.13 (95% CI, 1.04-1.45), and log-Bland-Altman GMR (FC303/[68Ga]) was 0.75, consistent with proportional non-interchangeability. Tumor-to-liver and tumor-to-mediastinum ratios did not differ significantly (GMR, 1.17 [95% CI, 0.94-1.45] and 0.96 [0.80-1.15], respectively); the study was not powered for equivalence. The n = 20 sensitivity analysis showed consistent directionality. Conclusions: Under non-harmonized acquisition conditions, [18F]FC303 showed lower physiologic reference-organ SUVmean and malignant target-region SUVmax than [68Ga]Ga-PSMA-11, whereas tumor-to-liver and tumor-to-mediastinum ratios were not significantly different. Absolute SUVs were not interchangeable; [68Ga]Ga-PSMA-11-derived SUV thresholds should not be directly transferred to [18F]FC303 without tracer-specific calibration.

Hypokalemia is a common and potentially life-threatening electrolyte abnormality in emergency care, yet rapid noninvasive screening remains difficult in time-critical triage settings. We developed PocketED-K, a single-lead AI-ECG prescreening model initialized from ECGFounder, and evaluated it in retrospective multicenter cohorts and a prospective handheld pilot. Retrospective development and validation included 37,115 patients from MC-MED and MIMIC-ED, and the pilot enrolled 18 patients at Peking University First Hospital. Hypokalemia was defined as venous serum potassium < 3.5 mmol/L. PocketED-K achieved AUROCs of 0.8189 (95% CI 0.8172--0.8207) in internal testing, 0.8104 (95% CI 0.8092--0.8115) in temporal validation, and 0.7889 (95% CI 0.7692--0.8074) in independent external validation; external negative predictive value was 0.9911 (95% CI 0.9895--0.9925). Higher predicted risk was associated with ST-segment depression, T-wave flattening or inversion, and relative U-wave prominence. The prospective handheld pilot provided an initial signal of workflow feasibility in real-world acquisition. These findings support single-lead AI-ECG as a low-burden prescreening tool to prioritize potassium testing in emergency care.

Pediatric patients with cardiac implantable electronic devices (CIEDs) face limited MRI access due to RF-induced heating, and computational modeling is increasingly used to characterize this risk. The validity of these simulations, however, depends on pairing body models with clinically realistic lead configurations, guidance that is currently lacking. We retrospectively analyzed 302 CIED surgeries in 281 pediatric patients to derive weight-based constraints for simulation design. Weight alone discriminated epicardial from endocardial lead implantation with AUC = 0.90, and adding age and height yielded no improvement, supporting weight as a sufficient single-parameter selection metric. The probabilistic crossover between approaches occurred at 44~kg, substantially higher than the 10 to 15~kg threshold commonly cited in the literature, with a broad transition zone of 21 to 66~kg in which both lead types were routinely used. Lead length was likewise weight-constrained: only 25~cm leads were observed in patients below 6~kg, and leads of 45~cm or longer were uncommon below 50~kg. These findings yield a three-tier framework, with epicardial-only configurations below 21~kg, dual configurations within 21 to 66~kg, and weight-thresholded lead lengths throughout, enabling MRI safety simulations to focus on clinically realizable anatomy and device combinations.

Abstract Purpose: MyotonPRO (MTP) and time-harmonic elastography (THE) are increasingly used to assess muscle mechanical properties, yet they operate on fundamentally different physical principles. MTP measures composite MTP stiffness (N/m) through surface oscillations, while THE quantifies intrinsic shear modulus (THE stiffness, kPa) via propagating shear waves. This study aimed at systematically compare MTP and THE measurements in the vastus lateralis muscle across different contraction intensities and examine how the skin layer and subcutaneous fat (SLSF) thickness influence their relationship. Methods: Twenty-six healthy adults (15 males, 11 females; age 25 [SD 4] years) underwent MTP and THE measurements of the vastus lateralis at rest and during isometric contractions at 15% and 30% maximal voluntary contraction (MVC). Effects of contraction intensities on tissue properties were assessed using univariate analyses of variance with repeated measures. Associations between the different outcomes of THE and MTP technologies were explored using Pearson's correlations and partial correlation coefficients separately for each contraction intensity with adjustment of the SLSF thickness of participants. Results: Both technologies detected contraction intensity-dependent stiffening across all outcomes (p < 0.001). THE stiffness increased from 5.3 [1.2] kPa at rest to 15.6 [6.1] kPa at 30% MVC; THE wave attenuation increased from 0.83 [0.19] to 1.42 [0.36] s/m while MTP stiffness increased from 337.3 [49.3] N/m at rest to 529.4 [160.7] N/m at 30% MVC. Correlations between modalities were weak and condition-dependent. THE wave attenuation did not significantly correlate with any MTP outcome across conditions. Conclusion: MTP and THE detect contraction-induced stiffening through fundamentally different physical mechanisms and should not be regarded as interchangeable. Their correlation is modest at rest and breaks down (or reverses) during active contraction, with subcutaneous fat as a key modifying factor. Clinical trial number: Not applicable.

Background: Coronary artery bypass grafting (CABG) remains the standard of care for complex multivessel and left main coronary artery disease. However, current preoperative planning remains largely subjective, relying on qualitative interpretation of coronary CT angiography (CCTA), operator-dependent stenosis grading, and fragmented multi-software workflows. Invasive fractional flow reserve (FFR), the reference standard for physiologic lesion assessment, is infrequently acquired preoperatively, leaving distal anastomosis planning without an objective hemodynamic basis. Methods: We developed a fully automated, AI-powered platform that converts routine CCTA into a patient-specific CABG planning workflow through five integrated modules: nnU-Net based segmentation of coronary lumen and calcification; quantitative morphological and topological characterization generating more than thirty descriptors; automated stenosis detection using a local reference-radius formulation; a nine-point composite scoring framework for distal anastomosis site selection incorporating luminal caliber, landing-zone length, calcification burden, distal perfusion reserve, and bifurcation proximity; and interactive virtual graft construction coupled to a distributed reduced-order solver for pre- and post-bypass FFR estimation. Results: Lumen segmentation achieved a mean Dice similarity coefficient of 0.96 {+/-} 0.01, whereas calcium segmentation achieved 0.73 {+/-} 0.15 on the held-out cohort. Platform-derived FFR demonstrated strong agreement with invasively measured FFR (r=0.96, mean absolute relative difference 1.73 {+/-}1.42%) across the evaluated lesions, supporting the physiologic validity of the reduced-order hemodynamic solver. End-to-end analysis from raw CCTA to hemodynamic assessment and virtual graft planning was completed in approximately seven minutes per case on a standard workstation, representing a substantial reduction in processing time compared with conventional multi-tool and CFD-based workflows. Conclusions: The proposed platform demonstrates the feasibility of rapid, reproducible, and physiology-informed CABG planning using routine CCTA. By integrating anatomical characterization, automated target-site analysis, virtual graft construction, and reduced-order hemodynamic assessment into a single workflow, the framework provides objective, quantitative surgical decision support compatible with routine clinical workflows. Keywords: Coronary artery bypass grafting (CABG); Fractional flow reserve (FFR); Coronary CT angiography (CCTA); Surgical planning

One of the prominent methods in neuroimaging data processing is SSM-PCA, which is based on principal component analysis and allows for the identification of diagnostically significant patterns in the form of statistical maps. We developed software, PIE Toolbox, employs SSM-PCA and classification based on the obtained diagnostic patterns revealed from functional and structural tomographic brain imaging. The program supports the entire analysis pipeline including preprocessing of brain images, diagnostic patterns extraction, building classification models, and prediction based on them. The resulting diagnostic patterns are weighted principal components obtained through SSM-PCA, or their linear combinations. PIE Toolbox allows selection of relevant structural and functional brain patterns, computation of their expression values in regions of interest, classification using support vector machines, and evaluation of model performance via cross-validation. This approach enables the use of patterns as features of intergroup differences for individual diagnosis. The software has been validated on both simulated and ADNI datasets.

We present a compact pump-and-probe mid-infrared Optothermal Spectrometer (OTHES) equipped with Spatial Probing and Autocorrection (SPAC) optimized for robust intravital application in humans. SPAC-OTHES facilitates alignment stability and spectral comparability across different measurement sessions involving different skin types. Contrary to state-of-the-art, SPAC-OTHES uses camera-based beam detection and an auto-calibration mechanism that enables ca. 73% better spectral reproducibility in intravital measurements in human volunteers than non-calibrated readouts. Moreover, SPAC-OTHES has the potential to lower the glucose quantification error, as demonstrated here in artificial skin phantoms, where an improvement of 52% compared to conventional diode-based detection was observed. The compactness of OTHES, combined with reliable SPAC-readout, has the potential to accelerate commercialization and broad application of biosensors based on mid-infrared spectroscopy.

INTRODUCTION: Cognitive trajectories may clarify how type 2 diabetes (T2D) and impaired fasting glucose (IFG) relate to dementia risk, but longitudinal associations remain unclear, particularly in the context of stroke. METHODS: Data from 5,631 dementia- and stroke-free older adults (mean age 75 years) from 7 international population-based cohorts were analyzed. Linear mixed-effects models estimated cognitive trajectories during stroke-free and post-stroke follow-up. Glucose status was defined by fasting glucose and prior T2D diagnosis. RESULTS: Over 6.6 years of follow-up (4.5% with incident stroke), T2D was associated with lower baseline cognitive performance compared with normal fasting glucose (-0.14 SD, 95% CI -0.21 to -0.07), but not with faster cognitive decline during stroke-free or post-stroke follow-up. IFG was not associated with lower cognitive performance or faster decline. DISCUSSION: In older adults, T2D was associated with persistently lower cognitive performance but not faster decline, suggesting adverse cognitive effects may be established before late life.

Objective Memory impairment is a frequent comorbidity of focal epilepsy, incompletely explained by seizure frequency or structural pathology. Ictal and postictal hippocampal dysfunction disrupt memory processes, but their cumulative impact remains poorly quantified. This study introduces cumulative hippocampal seizure-related burden metrics and examines their association with long-term memory consolidation. Methods Twenty consecutive patients undergoing stereo-EEG in Marseille (2016-2018) were prospectively included. Continuous stereo-EEG recordings between two memory assessments (30 minutes and one week post-encoding) were analysed. Hippocampal ictal involvement and durations were assessed using epileptogenicity markers and visual stereo-EEG analysis. The postictal period was quantified using permutation entropy. Cumulative hippocampal seizure-related burden metrics (ictal, postictal and combined: c-HipSZB) were computed across hippocampus-involving ictal events. Verbal and visual memory were assessed using standardized recall and recognition tasks. Associations were examined using univariate and multivariate analyses. Results Higher dominant-hemisphere hippocampal burden was associated with poorer one-week verbal memory (performance and retention), independently of most covariates. Higher c-HipSZB was associated with lower total recall performance (RT; free + cued) and RT retention ({beta} = -25.04 and -23.88; R2 = 0.57 and 0.53; p < 0.05) and accounted for the greatest variance in both outcomes (adjusted R2= 0.59 and 0.53; {beta} = -25.45 and -24.27; p < 0.01), particularly when adjusting for epilepsy duration. No robust associations were observed between non-dominant-hemisphere hippocampal seizure-related burden metrics and visual memory. Effects predominantly involved recall. Interpretation Cumulative ictal-postictal hippocampal dysfunction is a major determinant of impaired long-term verbal memory consolidation in focal epilepsy.

While SARS-CoV-2 and influenza continue to place a significant burden on population health, within-household differences in decisions towards vaccination and seeking care across these two pathogens, and across sociodemographic groups, remain largely unexplored. By conducting a household-level survey in Illinois, we found that many individuals made inconsistent decisions about vaccination: among all adults, 29% were vaccinated for only one of COVID-19 or influenza, and among those with children in the home, 39% lived with a child whose influenza or COVID-19 vaccination status differed from their own. A higher proportion of adults were vaccinated against COVID-19 compared to influenza, while the opposite was true for those younger than 18 years old. These differences hold even when accounting for disparities in coverage by age, race/ethnicity, political affiliation, and socioeconomic status. While vaccinated individuals consistently reported wanting to protect themselves or others, those who declined vaccination reported highly heterogeneous reasons ranging from resource constraints to distrust or misconceptions about vaccination. These differences are even more pronounced for COVID-19, with larger partisan gaps and higher refusal driven by safety concerns, lack of trust, or religious reasons than those who decide not to get the influenza vaccine. In contrast to vaccination, the decision to seek medical care when sick showed opposite sociodemographic trends, that are likely attributable to illness severity. Our findings highlight that closing gaps in COVID-19 and influenza vaccination coverage will require an integrative strategy that accounts for diverse motivations, fears, and barriers to access, while addressing social inequalities common to both diseases.

Background: Antenatal care (ANC) utilization is critical for improving maternal and neonatal health outcomes. Despite the World Health Organization recommendation of at least eight ANC contacts during pregnancy and the implementation of free maternal healthcare policies in Ghana, significant geographic and socioeconomic disparities in ANC utilization persist. This study therefore assessed the spatial distribution and geographically varying determinants of ANC utilization among women in Ghana. Methods: A cross sectional analytical study was conducted using women data from the 2022 Ghana Demographic and Health Survey. The analysis included women aged 15 to 49 years with an index child younger than five years preceding the survey. Descriptive statistics were computed using Stata version 18, while spatial analyses were conducted in QGIS version 3.44. Global Morans I was used to assess spatial autocorrelation, whereas Local Morans I and Getis Ord Gi analyses identified spatial clusters, hotspots, and coldspots of ANC utilization. Ordinary Least Squares (OLS) regression and Geographically Weighted Regression (GWR) models were fitted to assess global and local determinants of ANC utilization. Results: Overall, only 26.0% of women achieved adequate ANC utilization, while 74.0% reported inadequate ANC attendance. Adequate ANC utilization was higher among women with higher education (42.0%) and those from the richest households (41.3%) compared with women without formal education (19.1%) and those from the poorest households (17.6%). Regional disparities were observed, with Western (48.8%), Eastern (48.0%), and Greater Accra (47.3%) regions recording the highest ANC utilization, whereas Savannah (24.7%), Northern (25.8%), and North East (26.8%) regions recorded the lowest utilization levels. Global Morans I demonstrated significant positive spatial autocorrelation (Morans I = 0.457, p = 0.044), indicating geographic clustering of ANC utilization across Ghana. Getis Ord Gi analysis identified significant coldspots within Northern, Savannah, and North East regions, while Central Region demonstrated significant hotspot clustering. OLS regression showed that maternal education (B = 0.284, p = 0.003) and household wealth (B = 0.191, p = 0.011) positively influenced ANC utilization, whereas distance to health facility negatively influenced utilization (B = -0.156, p = 0.019). The GWR model demonstrated improved explanatory performance (Adjusted R-squared = 0.71), confirming substantial spatial heterogeneity in ANC determinants across Ghana. Conclusion: Adequate ANC utilization in Ghana remains low and geographically unequal. Maternal education, household wealth, and geographic accessibility significantly influence ANC utilization, with pronounced disparities concentrated within Northern Ghana. Spatially targeted maternal health interventions aimed at improving education, reducing socioeconomic inequalities, and enhancing healthcare accessibility are required to improve equitable ANC utilization across Ghana.

Wearable digital health technologies may complement traditional gait assessments in amyotrophic lateral sclerosis (ALS) by sensitively capturing real-world mobility changes. In this study, we validated six digital gait metrics derived from ankle-worn sensors in a natural history cohort of 182 individuals with ALS. Investigated metrics correspond to various aspects of gait, including volume, speed, intensity, similarity, variability, and fragmentation. Longitudinal analyses showed significant declines in step count, peak cadence, stride intensity, and stride similarity, with increasing stride duration variability and walking fragmentation over 52 weeks. Many participants exhibited greater relative change in the gait metrics than the self-reported ALS Functional Rating Scale-Revised (ALSFRS-RSE). Stratified analyses revealed that digital metrics captured significant functional decline even in participants with stable walking scores on the ALSFRS-RSE. These findings support the potential utility of these metrics for disease monitoring in ALS clinical care and trials.

Background: The rising prices of cancer medicines have intensified concerns about treatment access and health system sustainability particularly in low- and middle-income settings. Systematic facility level evidence on what medicines is actually available, at what prices, and at what cost to patients remains scarce, constraining evidence-based policy reform. Methods: Using adapted WHO/Health action international methodology, we conducted a cross-sectional survey of 52 cancer medicines across five therapeutic classes at five health facilities in Kisumu County, Kenya. Availability was measured as the proportion of facilities stocking each medicine. Affordability was assessed using days' wages required for the lowest-paid government worker to purchase standard treatment regimens, calculated per one chemotherapy cycle and maximum possible cycles. Results: Overall medicine availability was 48.1%, with marked inter-facility variation. Affordability analysis revealed severe financial barriers. The breast cancer AC regimen required 19.6-47.4 days' wages per full course; cervical cancer cisplatin, 19.8-49.2 days' wages; colorectal FOLFOX, 80.0-303.6 days' wages; and prostate docetaxel reached 437 days' wages at the highest-cost facility. The Social Health Authority's (SHA) KES 550,000 annual ceiling adequately covered cytotoxic regimens for common cancers at competitive prices but was exceeded by 24-116% for HER2-positive breast cancer requiring trastuzumab, with further strain for recurrent cervical and metastatic prostate cancers. Conclusions: Cancer medicines in Kisumu County are inconsistently available and highly variable in price resulting in inequitable access. We call for urgent retail price markup regulation, expanded pooled procurement through KEMSA, inclusion of priority targeted therapies on the Kenya Essential Medicines List, and SHA benefit packages redesigned around full-course regimen costs.