Biomedical Optics Express

ABSTRACT Background: Metallic implants such as orthopedic screws, prostheses, and dental hardware produce beam-hardening, photon-starvation, and streak artifacts that degrade computed tomography (CT) image quality, and the metal artifact reduction (MAR) methods developed to mitigate them require objective, reproducible benchmarking. Purpose: Objective evaluation of MAR algorithms in CT is hindered by the absence of phantoms that simultaneously provide anatomically realistic backgrounds, embedded implants of known geometry, and controllable, ground-truth--referenced artifact intensity. We present a dual-filament, voxel-level three-dimensional (3D) printing method that fulfills these requirements and demonstrate its capabilities on a clinically representative cervical spine case with embedded orthopedic spinal screws. Methods: The proposed method extends the PixelPrint framework, a fused-deposition-modeling (FDM) workflow that converts clinical Digital Imaging and Communications in Medicine (DICOM) data directly into 3D-printer Geometric code (G-code) without intermediate segmentation or surface meshing, to interleaved, voxel-level deposition of two filaments: a calcium-doped polylactic acid (PLA) for soft tissue and bone, and a higher-attenuation metal-doped PLA for metallic implants. For demonstration, anonymized DICOM data of a healthy cervical spine were used to design and fabricate three matched phantoms, each with six embedded spinal screws at C4--C6: a 0% metal-infill ground-truth phantom, a 50% medium-metal-infill phantom, and an 85% high-metal-infill phantom. All phantoms were scanned on a clinical spectral CT system at 120 kVp and 1000 mAs, reconstructed at 0.67 mm slice thickness with virtual monoenergetic imaging (VMI) across 50--190 keV. Method performance was characterized by region of interest (ROI)-based Hounsfield Unit (HU) agreement with the source patient data and by the noise-independent Gumbel-distribution p-index metric. Results: The dual-filament method reproduced patient anatomy, soft-tissue contrast, and screw geometry with high fidelity. ROI HU values agreed with patient data within {+/-}25 HU for soft tissue and trabecular bone; cortical regions were underestimated owing to the current ceiling of the calcium-doped PLA used in this study. The tunable-artifact behavior was quantified as follows: the Gumbel location parameter scaled monotonically from 46.7 HU (no-metal background) to 57.1 HU (50% infill) to 90.5 HU (85% infill) for the VMI 70 keV with standard filter. High-keV VMI reconstructions substantially reduced streak and beam-hardening artifacts while preserving anatomic detail. Conclusions: The proposed dual-filament, voxel-level PixelPrint method enables the fabrication of patient-specific, multi-material CT phantoms with embedded metallic implants and controllable, ground-truth--referenced artifact intensity. Although demonstrated here in a single cervical-spine case, the workflow is anatomy- and implant-agnostic by construction and could in principle be adapted to other musculoskeletal sites (e.g., knee, hip, dental) and implant materials, providing a reproducible methodological foundation for benchmarking MAR algorithms, characterizing spectral CT performance, and validating emerging photon-counting detector systems. Keywords: 3D printing methodology; fused deposition modeling; voxel-level multi-material printing; spectral computed tomography; metal artifact reduction; phantom design; orthopedic implants; dual filament; PixelPrint.

Minimally invasive endovascular procedures offer reduced surgical trauma, shorter recovery times, and improved outcomes, but rely on 2D fluoroscopic X-ray imaging, which provides limited depth perception and exposes patients and clinicians to ionizing radiation. Here we present an augmented reality (AR) system that fuses intravascular ultrasound (IVUS) and electromagnetic (EM) position tracking with preoperative computed tomography (CT) to produce an anatomically accurate, deformation-corrected navigational reference. A robotic device performs ECG-gated pullback of the IVUS probe, capturing 4D aortic motion across the cardiac cycle. We introduce a deep learning architecture for extracting vascular lumen boundaries and side-branch orifices from artifact-prone IVUS streams, and a semantically driven non-rigid CT-IVUS fusion pipeline robust to false positive landmarks. We evaluate the platform with trained surgeons in benchtop phantom studies and in-vivo ovine models, and demonstrate its application to fenestrated endovascular aneurysm repair (FEVAR). Compared to fluoroscopy alone, AR guidance significantly reduces cannulation time, radiation exposure, and cognitive workload, while improving procedural efficiency and safety. Our IVUS-EM and CT aortic datasets are released open source.

Abstract Background. Quantitative optical coherence tomography (OCT) measurements are essential for retinal disease monitoring, yet leading vendors store acquisition data in undocumented proprietary formats or encode measurements exclusively in private DICOM tags inaccessible to open systems. Methods. We present Transducin, an open-source Python library that reverse-engineers the undocumented Optopol Revo FC130 and Revo 60 .OPT binary format and extracts quantitative measurements from Zeiss Cirrus HDOCT private DICOM tags, generating TID 1500 Structured Reports with SNOMEDCT coded findings for both platforms. A novel finding, that OCTPARAMS tag 23 encodes ocular laterality through the arithmetic sign of the foveal horizontal position, enables geometry based laterality inference requiring no operator data entry, validated across 18 files from two device models and four software versions with 100% accuracy. Results. The primary corpus of 452 Optopol .OPT files (73 patients, 7 acquisition types) was parsed with 100% success. Cross-version compatibility was confirmed across SOCT versions 11.5.0 through 21.5.0, spanning approximately eight years of software development. The Zeiss Cirrus pipeline generated TID 1500 SRs for all 41 applicable studies (100%), yielding CMT 203to 630um and RNFL 53 to123 um across a clinically representative range. Conclusions. Transducin provides the first publicly documented specification of the Optopol .OPT format and the first open-source multivendor pipeline generating SNOMEDCT coded DICOM Structured Reports from both Optopol Revo and Zeiss Cirrus devices, closing a gap explicitly confirmed by both manufacturers' own documentation. The code is available at https://github.com/oftalmos-org/transducin (Apache License 2.0).

As machine learning and artificial intelligence systems are increasingly used in healthcare, rigorous evaluation of their classification performance has become critical. The F1 and F{beta} scores are widely adopted metrics for assessing performance in imbalanced biomedical data. Recently, we introduced psF1, a unified statistical framework for inference and study design for single and comparative F1 and F{beta} scores under the assumption of independent classifiers. In practice, however, benchmarking two classifiers on the same dataset creates a correlated paired setting. Ignoring this intrinsic dependency leads to overestimation of the standard error and a substantial loss of statistical power. To address this, we develop psF1pair, an advanced framework for statistical inference and power analysis that explicitly accounts for correlations between classifier pairs. Extensive simulation studies demonstrate the performance of psF1pair, and its utility is further illustrated through application to a real-world imaging classification system. As expected, higher correlation between classifiers yields narrower confidence intervals and enhanced statistical power. A freely available R package is provided to facilitate implementation, supporting accurate evaluation and study design for predictive and classification models in biomedical research.

Background: Cardiovascular disease remains the leading cause of death in the United States, and marked geographic disparities in cardiovascular mortality persist. However, the community-level socioeconomic indicators most strongly associated with these disparities remain unclear. Community-level measures capture the social and economic conditions that influence cardiovascular health across populations and may help identify communities at greatest risk. We used the Area Health Resources File (AHRF) to identify socioeconomic measures most strongly associated with county-level cardiovascular mortality. Methods: We performed a national cross-sectional ecological analysis using the 2024-2025 Area Health Resources File (AHRF), including counties in the 50 U.S. states and the District of Columbia. The primary outcome was an AHRF-defined cardiovascular mortality composite derived from 2021-2023 National Center for Health Statistics (NCHS) mortality data. Community-level socioeconomic measures included 2023 overall, pediatric, and family childhood poverty and 2019-2023 overall, female, and White unemployment. County-level associations were evaluated using Spearman rank correlation and regional differences using the Kruskal-Wallis test. Sensitivity analyses used a partial mortality composite and Kendall {tau} correlation. Results: Among 1,982 counties, cardiovascular mortality varied significantly across U.S. Census divisions (P<0.001), with the highest population-weighted rate in the East South Central division (348.5 deaths/100,000) and the lowest in the Mountain division (233.9 deaths/100,000). Pediatric poverty demonstrated the strongest association with cardiovascular mortality ({rho}=0.612), followed by family childhood poverty ({rho}=0.603) and overall poverty ({rho}=0.524, all P<0.001). In contrast, unemployment measures were more weakly associated (overall {rho}=0.209, White {rho}=0.176, female {rho}=0.141, all P<0.001). Results were consistent in sensitivity analyses. Conclusions: County-level poverty, particularly pediatric poverty, was more strongly associated with cardiovascular mortality than unemployment across U.S. counties. These findings suggest pediatric poverty may serve as a useful community-level indicator for identifying populations at increased cardiovascular risk and prioritizing future public health interventions.

White matter lesion (WML) identification, assessment, and characterization using magnetic resonance imaging (MRI) are fundamental for diagnosis and monitoring of multiple sclerosis (MS). Portable ultra-low field (pULF) MRI at 64 millitesla (mT) has been shown to visualize WML with at least one dimension greater than 4 mm. An automated WML segmentation tool catered to pULF-MRI can provide standardized and accurate quantitative measurements of WML volume. In this study, we sought to investigate and compare the accuracy of machine-learning (ML) and deep-learning (DL) pULF MRI segmentation tools. Same-day paired pULF (64mT) and high-field (HF, 3T) MRI scans from 84 adults with MS or suspected-MS (mean age {+/-} SD: 48 {+/-} 13, 62 females) included T2-FLAIR and T1w images. Reference WML segmentations were manually annotated on pULF T2-FLAIR for all scans, with WML confirmed with registered HF T2-FLAIR. HF reference WML segmentations were created. Four automated segmentation methods were applied to pULF scans: Method for Inter-Modal Segmentation Analysis (MIMoSA), an ML algorithm trained on HF WML masks; WMH-SynthSeg, a convolutional neural network model with flexible segmentation capabilities across field strengths and resolution; nnU-Net, a DL algorithm trained on pULF reference WML masks; and Pseudo-Label Assisted nnU-Net (PLAn), a DL algorithm pre-trained on HF reference WML masks and refined with 64mT reference WML masks. Two models were trained with nnU-Net, one using T2-FLAIR images only (nnU-Net-FL) and one using T1w and T2-FLAIR images (nnU-Net-FL/T1). The same was done with PLAn, creating PLAn-FL and PLAn-FL/T1. The six automated WML segmentation outputs were compared to the manual segmentations to determine Dice Similarity Coefficient (DSC) scores. Associations of WML volume estimates with clinical measures were investigated. DSC scores with pULF reference WML masks from PLAn-FL (DSC mean {+/-} SD: 0.50 {+/-} 0.24) outperformed MIMoSA (0.24 {+/-} 0.20, p < 0.0001), WMH-SynthSeg (0.30 {+/-} 0.18, p < 0.0001), nnU-Net-FL (0.41 {+/-} 0.24, p < 0.0001), and nnU-Net-FL/T1 (0.41 {+/-} 0.26, p = 0.0004). Worse Expanded Disability Status Scale (EDSS) and Scripps Neurologic Rating Scale (SNRS) scores were correlated with higher WML volumes in the pULF and HF reference masks. They were also correlated with WML volumes derived from WHM-SynthSeg, nnU-Net-FL, nnU-Net-FL/T1, PLAn-FL, and PLAn-FL/T1, but not MIMoSA. After adjusting for age, WHM-SynthSeg, nnU-Net FL, nnU-Net-FL/T1, PLAn-FL, and PLAn-FL/T1 had significant associations with EDSS and SNRS scores. nnU-Net and PLAn performed best in segmenting WML on pULF-MRI at 64 mT, providing accurate quantitative estimates of WML burden. Moreover, WML volumes estimated by these algorithms were associated with clinical measures of disability, underscoring their utility for reflecting clinical and radiological disease severity. Given pULF-MRI's mobility and lower cost, these findings highlight its relevance in clinical trials, particularly in involving more participants who face logistical constraints and barriers.

Importance: Neuroinflammation is a key component of the response to injury after concussion, but direct links between diffusion MRI metrics and specific plasma inflammatory pathways in human concussion have not been established. Objective: To examine associations between diffusion MRI metrics and pathway-level inflammatory proteomic signatures in adolescents during the subacute period after concussion. Design, Setting, and Participants: Cross-sectional analysis of data from the CARE4Kids Consortium, a six-site prospective study. Participants were English-speaking adolescents ages 11-17.99 with concussion and symptoms at 7-35 days post-injury. Data were collected between 2022-2024. Of 370 enrolled participants, 122 had both diffusion MRI and plasma proteomics available for analysis. Exposure: Advanced diffusion MRI metrics were converted to z-scores and participants were grouped by the spatial extent of outlier values (potholes and peaks) across 15 white matter regions of interest. Nine non-redundant groupings were selected for primary analysis. Main Outcomes and Measures: Pathway-level inflammatory profiles derived from gene set enrichment analysis (GSEA) of ~5,400 plasma proteins measured by Olink proximity extension assay, targeting nine hallmark inflammatory pathways spanning initiation through resolution. Persistent symptoms were assessed 64-115 days post-injury. Results: Diffusion metrics reflecting tissue disorganization were associated with upregulation of the coagulation pathway, consistent with hemostatic-inflammatory signaling. Metrics reflecting reduced tissue complexity and neurite density were associated with upregulation of interferon- and interferon-{gamma} response pathways, consistent with microstructural remodeling driven by cellular immune activation. Elevated free water content was associated with downregulation of most inflammatory pathways and trend-level transforming growth factor - {beta} upregulation, reflecting inflammatory resolution. Time since injury did not differ between groups based on free water (Kolmogorov-Smirnov p = 0.97), suggesting these differences reflect individual variability in recovery pace. Exploratory analyses showed a trend toward lower odds of persistent symptoms in the group with elevated free water content (odds ratio = 0.51, p = 0.18). Conclusions and Relevance: Multiple diffusion MRI metrics are differentially sensitive to distinct neuroinflammatory states in the subacute period after adolescent concussion. These findings suggest that diffusion imaging could serve as a non-invasive tool for inflammatory phenotyping, with potential implications for identifying patients who may benefit from targeted immunomodulatory intervention.

Objective: Photobiomodulation therapy has emerged as a promising modality to facilitate scar healing and pain management in dermatology and plastic surgery. However, its role in postoperative care following spine surgeries remains understudied. This double-blinded, placebo-controlled study aimed to investigate the effects of photobiomodulation in patients with chronic lower back pain undergoing lumbar decompression, with postoperative wound healing as the primary outcome and pain reduction and functional recovery as secondary outcomes. Methods: Patients were randomized to receive either active photobiomodulation braces (N=13) or placebo braces (N=12). Follow-up assessments were performed at 2, 4, 6, 8, and 12 weeks postoperatively. Outcomes included wound healing (Stony Brook Scar Evaluation Scale), back and leg pain (Visual Analog Scale), quality of life (EuroQol 5D), and functional status (Oswestry Disability Index). Results: Compared to the placebo group, the photobiomodulation treatment group had a 4.12-fold cumulative improvement in final scar scores, with significant between-group differences at postoperative weeks 6, 8, and 12 (p = 0.0062, 0.010, 0.042). Among patients with severe preoperative disability, treatment resulted in a 1.89-fold faster improvement in back pain (p=0.025) and a 1.80-fold faster improvement in ODI scores (p=0.025); and superior treatment effect on wound healing were again observed at weeks 6, 8, and 12. Among patients with poor initial scars, treatment led to a significantly better scar outcome than placebo at week 6 and a 1.94-fold faster EQ5D improvement (p=0.052), with significant gains observed as early as two weeks after surgery. There were no adverse events associated with photobiomodulation treatment. Conclusions: Photobiomodulation significantly promoted postoperative wound healing following lumbar decompression surgery, with therapeutic benefits preserved even in patients with poor baseline scar scores and functional impairment. This indicates that the efficacy of photobiomodulation is not limited by the initial scar condition or disability, supporting its broad clinical applicability. Additionally, patients with severe preoperative disability experienced greater benefits from photobiomodulation than placebo, including faster reduction in back pain and more rapid improvement in functional capacity, highlighting its role in postoperative pain management and rehabilitation. These therapeutic effects are likely mediated by photobiomodulation-induced reduction of inflammation and enhancement of tissue repair. Together, this study suggests that photobiomodulation can be a promising adjunct therapy to facilitate postoperative recovery in patients undergoing spine surgery.

BACKGROUND: Chronic coronary syndromes (CCS) remain under-characterized in Latin America, where clinical profiles may differ from high-income countries. OBJECTIVE: We aim to characterize the clinical presentation, coronary anatomic profile, and pharmacologic treatment patterns of adults living with CCS using data from the Mexican Chronic Coronary Syndrome Registry (RESINCCRO). METHODS: RESINCCRO is an observational, multicenter, cross-sectional registry conducted across ~50 centers in five regions from Mexico. We included adults ([&ge;]18 years) enrolled between September 2024 and March 2025 who met 2019 ESC CCS criteria. Coronary imaging data was collected from medical records into a standardized electronic case report form. RESULTS: We enrolled 3,029 adults (men [72.5%]; mean age 67.2 {+/-} 10.7 years). Cardiometabolic comorbidities were frequent: overweight/obesity (76%), arterial hypertension (69.0%), type 2 diabetes (44.0%), and chronic kidney disease (24.2%). Persistent angina/equivalents occurred in (23.9%), of which most had Canadian Cardiovascular Society class I - II (91.2%). The mean LVEF was of 53.7 {+/-} 12.0. Cardiac rehabilitation participation was (6.2%). Median LDL-C was 70 mg/dL (IQR 51 - 95) and LDL <55 mg/dL was only 26.1%, despite high prescription of lipid-lowering therapies, including statins (93.2%), ezetimibe (24.6%), and PCSK9 inhibitors (2.4%). 60.3% had obstructive epicardial disease. CONCLUSIONS: Mexican adults with CCS exhibit high cardiometabolic burden, frequent symptoms, suboptimal LDL-C goal attainment, low rehabilitation uptake, and a substantial obstructive phenotype. These findings highlight opportunities to intensify secondary prevention, adopt mechanism-directed evaluation and therapy, and expand cardiac rehabilitation to improve CCS care in Mexico.

Cognitive impairment is a prevalent symptom extending from physiological ageing to disease. It commonly manifests itself in initial memory problems, progressing and co-occurring in more severe conditions such as Mild Cognitive Impairment, Alzheimer's Disease and Major Depressive Disorder. However, current non-invasive screening assessments either lack biological information or are invasive and restricted to specialized centers with complex and cost-intensive set-ups. Here, we conducted an initial validation of mobile pupillometry with Virtual Reality (VR) under experimental conditions as a digital biomarker for cognitive impairment by testing required biomarker-specific properties. For this purpose, we first assessed its construct validity by testing healthy participants (n=43) on an n-back task in VR while pupil size was measured. Mixed effects models revealed that similar to lab-based eye-tracking systems, pupil size increased in a sensible and distinguishable fashion as a function of working memory load. Second, to test the signal's reliability, the same participants were tested on the identical set-up two to three months after their first visit. We observed that the pupil response profile was highly stable over this period. Third, for its clinical validity, we examined patients (n=89) from three different cohorts with varying degrees of cognitive impairment and compared them to healthy control participants (n=81). Mixed-effects models indicated that pupil size was reduced as a function of cognitive impairment levels at higher cognitive load and that this effect was stronger pronounced with increasing age. In conclusion, we provide initial evidence for mobile pupillometry being a sensitive, reliable and clinically valid digital biomarker for cognitive functioning and impairment, which offers desirable properties due to its quick, automatized and location-independent set-up. Keywords: digital biomarker, mobile pupillometry, Virtual Reality, cognition, , Major Depressive Disorder, Mild Cognitive Impairment, Alzheimer's Disease

Objective To develop and validate a risk model for predicting postoperative bleeding in patients with thyroid cancer. Methods A total of 2800 consecutive patients diagnosed with thyroid cancer in the Department of Thyroid and Breast Surgery of the Affiliated Hospital of Xuzhou Medical University between January 2020 and December 2023 were retrospectively analyzed. Patients were categorized into two groups based on postoperative bleeding occurrence: bleeding and non-bleeding groups. Univariate and multivariate logistic regression analyses were utilized to screen independent risk factors. Meanwhile, risk prediction models were developed and nomogram . Subgroup analysis was performed to identify independent risk factors. The predictive effects of the models were assessed using the Hosmer-Lemeshow test and receiver operating characteristic (ROC) curves. Results Of the 2800 recruited patients, 50 had postoperative bleeding, with an incidence rate of 1.7%. Multivariate logistic regression analysis showed that age, hypertension, total thyroidectomy, tumor size [&ge;]4 cm, and operation time [&ge;]90 min were the risk factors for postoperative bleeding in thyroid cancer patients (P<0.05). A risk prediction model was established based on the above factors, and the area under the ROC curve was 0.881, with a sensitivity of 94.0%, a specificity of 67.3%, and an accuracy of 74.0%. Decision curve analysis revealed that the model had good predictive ability. Conclusions The constructed risk prediction model has good predictive power and can provide a reference for healthcare professionals to predict the risk of bleeding in patients after thyroid cancer surgery.

Purpose: To develop an accelerated motion-compensated diffusion-weighted pseudo-continuous arterial spin labeling (MCDW-pCASL) method using a spatial subspace low-rank reconstruction method for efficient quantification of blood-brain barrier (BBB) water exchange (kw) and permeability (PSw). Methods: An accelerated multidelay MCDW-pCASL sequence was developed to simultaneously encode intravascular and extravascular diffusion-weighted ASL signals across multiple post-labeling delays (PLDs). A spatial subspace low-rank reconstruction framework was optimized to enable joint estimation of cerebral blood flow (CBF) and BBB water exchange rate and permeability. Fourteen young healthy adults underwent test-retest scans (separated by ~1 week) at 3T with both the accelerated MCDW-pCASL and a conventional diffusion-prepared (DP) pCASL sequence. Whole-brain, gray-matter, and white-matter CBF and kw values were quantified to assess test-retest repeatability and cross-method agreement. An additional cohort of 30 older adults underwent single-session MCDW and DP scans to evaluate age-related perfusion and BBB kw/PSw differences. Intraclass correlation coefficients (ICCs) were used to assess reliability and agreement. Results: Accelerated MCDW-pCASL demonstrated excellent agreement with DP-pCASL for CBF (ICC = 0.89) and fair agreement for kw (ICC = 0.56). Test-retest repeatability of MCDW-pCASL was good for CBF, BBB kw and PSw (ICC {approx} 0.6). Across both sequences, younger subjects exhibited significantly higher CBF and kw compared with older adults. Conclusion: Incorporating a spatial low-rank subspace reconstruction enables accelerated MCDW-pCASL acquisition with reliable simultaneous quantification of CBF, BBB kw and PSw. Clinical applications of this method for assessing perfusion and BBB function are warranted.

Background: Sex differences in cerebrovascular disease are established determinants of outcome in acute stroke care and vascular interventions, but evidence in cerebrovascular bypass surgery remains limited. This study examined whether biological sex was associated with outcome after superficial temporal artery to middle cerebral artery (STA-MCA) bypass in patients with atherosclerotic cerebrovascular disease (ACVD). Methods: We retrospectively screened adults undergoing extracranial-to-intracranial (EC-IC) bypass (2012?2025) and included ACVD patients treated by STA-MCA bypass with available follow-up. The primary outcome was modified Rankin Scale (mRS) at latest follow-up, analyzed using proportional odds regression. Multivariable models adjusted for age, preoperative mRS, and vascular comorbidities. Cerebrovascular reserve capacity (CVRC) was analyzed in a subgroup. Results: A total of 140 patients (30.7% female) were included. Disease morphology varied by sex, with more multivessel (65.1% vs. 47.4%) and stenotic disease (39.5% vs. 20.6%) in females and more isolated internal carotid artery occlusion in males (43.3% vs. 16.3%). The 30-day risk of symptomatic ischemic stroke was higher in females than in males (9.3% vs. 1.0%). A similar pattern was observed at follow-up (median 13.5 months), with ischemic events predominating in females (16.3% vs. 7.2%) and hemorrhagic events occurring exclusively in males (5.2%). Female sex was independently associated with worse functional outcome (OR 2.59, 95% CI 1.28?5.30, p=0.008). Preoperative mRS was the strongest determinant of outcome (OR 4.30, 95% CI 3.07?6.18, p<0.001). Adjusted analysis detected no significant association between CVRC and outcome (OR 0.80, 95% CI 0.24?2.70, p=0.721). Conclusions: Female sex was independently associated with worse functional outcome after STA-MCA bypass, independent of preoperative functional status, hemodynamic impairment and cardiovascular comorbidities. These findings identify sex as a clinically relevant determinant of outcome in cerebrovascular bypass surgery and should be considered in future risk stratification and trial design.

Purpose: To assess the feasibility of quantitative fundus autofluorescence (FAF) measurement in early age-related macular degeneration (AMD) using the freely available ImageJ software, to characterize signal intensity across FAF patterns, and to evaluate interobserver reproducibility in pattern classification. Methods: Single-center, non-blinded, retrospective, consecutive-case analytical study. FAF images acquired with Spectralis OCT+HRA (Heidelberg Engineering) from patients with early dry AMD seen at a tertiary referral center between January 2010 and September 2016 were analyzed. A standardized 300x300-pixel region of interest (ROI) centered on the fovea was evaluated in ImageJ v2.0.0-rc54/1.51h (Fiji distribution). Mean, minimum, and maximum autofluorescence (AF) pixel intensity were recorded. Each image was independently classified according to the Bindewald classification system by two graders; a third senior grader adjudicated discordances. Cohen's kappa (k) was used to assess interobserver agreement. Results: Of 423 patients with available FAF studies, 107 had dry AMD; 45 met quality and diagnostic criteria for early AMD and were included in the quantitative analysis. Mean age was 73.47 +/- 8.1 years; 62.2% were female. Mean FAF intensity was 120.26 (range 74.76-160.79); mean minimum was 32.07 (range 3-63) and mean maximum was 205.80 (range 125-255). Seven of eight Bindewald patterns were identified; the stippled pattern was absent. The most frequent pattern was minimal changes (31.1%), followed by increased focal (24.4%) and patchy (15.6%). Reticular pattern showed the highest mean AF (143.8), while lace pattern showed the lowest (88.4). Interobserver agreement for Bindewald pattern classification was almost perfect (k = 0.969; 95% CI, 0.908-1.000; p < 0.001). Agreement for lesion extent was moderate (k = 0.531) and for foveal involvement was substantial (k = 0.622). Conclusions: Quantitative FAF evaluation of early AMD using ImageJ is feasible and reproducible. ImageJ represents a cost-free alternative for multimodal retinal image analysis, with potential for automated screening applications in resource-limited settings. Keywords: age-related macular degeneration; fundus autofluorescence; ImageJ; quantitative autofluorescence; image analysis; Bindewald classification; interobserver agreement

Background: Rheumatic heart disease (RHD) remains a major cause of premature death in low- and middle-income countries and First Nations communities. Early detection and management can prevent progression, but requires echocardiography, which is limited in high-burden settings. Task-sharing echocardiographic screening is an accessible, evidence-based approach but implementation remains unclear. Methods: We conducted a prospective implementation evaluation of a co-designed task-sharing screening programme across five remote First Nations Australian communities between May 2023 and November 2025. Predominantly community health workers (CHWs), alongside nurses and doctors, were trained to scan using handheld devices with off-site cardiologist interpretation. We assessed implementation outcomes and used a realist evaluation to explore how context shaped CHWs ability to complete training and embed screening into routine work. Data included scanning activity, surveys, costing, interviews, focus groups, and field notes. Findings: We trained 32 staff (21 CHWs, 8 nurses, 3 doctors) to scan across five sites. Scanning frequency was lower and more variable than anticipated: 360 scans (including training and post-certification) of 5 - 20 year olds over 14 months, with site-level coverage of 3 - 85%. Fidelity was limited by device unavailability, charging problems, and delays in uploads and reviews. Set-up and training cost A$51,903 per site, plus A$9,858/year in implementation support. Screening was easier for CHWs to embed when the legitimacy of their role as a scanner was communicated, but harder when invisible work outweighed opportunities to scan. Interpretation: Future implementation will require efforts to legitimise CHWs scanning and support invisible work. Event-based screening offers a promising complementary strategy. Scale-up requires policy support. Funding: This research was funded by the Australian Medical Research Futures Fund Cardiovascular Health Mission (GNT2015869), in addition to philanthropic donations from Medtronic Australasia, Edwards Life Sciences and the Rotary Club of Kiama. Hand-held devices (Philips Lumify, USA) were donated by Humpty Dumpty Foundation and East Timor Hearts Fund.

Background: Apical sparing of left ventricular longitudinal strain (LS) is an echocardiographic clue to cardiac amyloidosis but may also occur in hypertensive heart disease (HHD). Objectives: To determine whether apical sparing in HHD is associated with regional left ventricular wall stress estimated according to Laplace's law. Methods: We retrospectively studied 1,559 patients with HHD, 47 with light-chain cardiac amyloidosis (ALCA), and 409 normotensive controls. Artificial intelligence-assisted echocardiography quantified segmental LS, wall thickness, and cavity radius at the basal, midventricular, and apical levels. Wall stress was estimated as mean blood pressure (MBP) x radius/(2 x wall thickness). Apical sparing was defined as a relative regional strain ratio (RRSR)[&ge;]1.0. Results: Apical sparing was present in 14 patients with HHD (0.9%), 13 with ALCA (27.7%), and no controls. Among HHD patients with apical sparing, RRSR decreased from 1.11{+/-}0.13 to 0.72{+/-}0.10 after antihypertensive treatment (P<0.001), accompanied by reduced wall stress and improved basal and midventricular LS, with resolution of apical sparing in all 14 patients. In the overall HHD cohort, changes in MBP and left ventricular mass index were independently associated with changes in RRSR. In an exploratory analysis of HHD patients with apical sparing, a reduction in basal wall stress was associated with a reduction in RRSR ({beta}=0.267 for {bigtriangleup}RRSRx100, 95% CI 0.023-0.511; P=0.036). In ALCA, favorable hematologic response was the only determinant of RRSR reduction. Conclusions: Apical sparing in HHD was uncommon but reversible and may represent a load-sensitive deformation pattern associated with regional wall stress, consistent with Laplace's law.

Background: The optimal timing of percutaneous coronary intervention (PCI) in patients undergoing transcatheter aortic valve replacement (TAVR) remains unclear, particularly regarding its impact on renal outcomes. Methods: We conducted systematic review and meta-analysis of studies comparing staged versus concomitant PCI in patients with aortic stenosis and coronary artery disease undergoing TAVR. We searched MEDLINE, Embase, and Cochrane databases comprehensively. Using a random-effects model, we calculated odds ratios (OR) with 95% confidence intervals (CI) to assess the incidence of contrast-induced acute coronary injury (CI-AKI) across different stages. Results: The analysis included 11 studies encompassing 7,119 patients. Overall, staged PCI did not significantly differ from concomitant PCI in reducing CI-AKI (OR 1.02; 95% CI 0.53 to 1.98; p = 0.959; Figure 2A). Subgroup analysis revealed no significant differences in stage 1 (OR 1.99; 95% CI 0.38 to 10.47; p = 0.417; Figure 2B) or stage 2 CI-AKI (OR 1.01; 95% CI 0.39 to 2.64; p = 0.978; Figure 2C). However, a statistically significant difference emerged for stage 3/4 CI-AKI, favoring the staged approach (OR 0.48; 95% CI 0.24 to 0.99; p = 0.046; Figure 2D). Conclusion: While staged PCI does not consistently reduce CI-AKI in patients undergoing TAVR, it may offer potential benefits for more severe kidney injury (stages 3/4). Given the observed heterogeneity, large-scale randomized controlled trials are essential to establish the relationship between procedural timing and renal outcomes.

Background: Prior analyses have demonstrated an inverse association between transcatheter aortic valve replacement (TAVR) procedural volume and short-term outcomes. However, less is known regarding the relationship between procedural volume and 1-year outcomes in the contemporary TAVR era. Objectives: To evaluate the association between annual hospital and operator TAVR procedural volumes and 1-year clinical outcomes in a contemporary national cohort. Methods: Clinical records from the Society of Thoracic Surgeons (STS)/American College of Cardiology (ACC) Transcatheter Valve Therapies (TVT) Registry for patients undergoing commercial TAVR between January 2020 and December 2022 were linked to Centers for Medicare & Medicaid Services administrative claims. Annualized hospital and operator TAVR volumes were modeled continuously and categorized into tertiles. Primary outcomes included 1-year all-cause mortality, stroke, the composite of mortality or stroke, and all-cause readmissions. Hierarchical risk-adjusted models accounting for patient clustering within sites were used to evaluate associations between procedural volume and outcomes. Results: Among 215,335 patients undergoing TAVR at 788 hospitals by 3,444 operators between 2020 and 2022, median annual hospital and operator volumes were 74 (IQR: 43-115) and 16 (IQR: 10-32), respectively. Volume was then categorized into tertiles (low, medium and high). Compared with high-volume hospitals ([&ge;]102/year), low-volume hospitals ([&le;]52/year) had higher adjusted rates of 1-year all-cause mortality (Odds Ratio (OR): 1.10 [95% CI: 1.05-1.16]), stroke (OR: 1.10 [95% CI: 1.01-1.19]), mortality or stroke (OR: 1.10 [95% CI: 1.05-1.15]), and all-cause readmissions (OR: 1.05 [95% CI: 1.00-1.09]). Compared with high-volume operators ([&ge;]25/year), low-volume operators ([&le;]11/year) had higher adjusted rates of stroke (OR: 1.16 [95% CI: 1.05-1.28]) and mortality or stroke (OR: 1.09 [95% CI: 1.03-1.15]) but not other endpoints. Conclusions: In a large, contemporary national TAVR registry, lower annual hospital ([&le;] 52/year) and operator ([&le;] 11/year) procedural volumes were independently associated with worse 1-year clinical outcomes. These findings suggest that procedural experience continues to influence outcomes despite maturation of contemporary TAVR practice.

BACKGROUND In line with International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) recommendations for high-sensitivity cardiac troponin assays, analytical validation and reference limit assessments are required to confirm that an assay meets performance criteria. This study evaluated the analytical performance and established the 99th percentile upper reference limit (URL) for the SPINCHIP High-Sensitivity Cardiac Troponin I (SPINCHIP hs-cTnI) point-of-care assay. METHODS Analytical performance characteristics, including the limit of blank (LoB), limit of detection (LoD), and limit of quantification (LoQ), were assessed. Additionally, 1,053 plasma samples and 1,055 whole-blood samples were used to determine the URL. Imprecision around the 99th percentile URL was evaluated as part of the analytical validation. High-sensitivity criteria were assessed by confirming measurable cTnI in [&ge;]50% of healthy individuals (n=432 plasma; n=431 whole blood) and achieving imprecision <10% at the 99th percentile (plasma, n=960; whole blood, n=480). RESULTS SPINCHIP hs-cTnI demonstrated a LoB of 0.3 ng/L; LoDs of 0.8 ng/L (plasma) and 0.9 ng/L (whole blood); and LoQs of 1.1 ng/L (plasma) and 1.4 ng/L (whole blood). The analytical measuring range was 1.1-9,000 ng/L. Imprecision at the common 99th percentile URL (14 ng/L) was 5.8%; for men (URL=16 ng/L) 5.6% and for women (URL=10 ng/L) 6.3%. Greater than 85.2% (94.0% and 76.1% in men and women, respectively) of healthy individuals showed measurable cTnI above the LoD. CONCLUSIONS The SPINCHIP hs-cTnI assay meets the IFCC high-sensitivity requirements, demonstrating <10% imprecision at the 99th percentile, reliable low-concentration precision and cTnI detection in more than half of healthy individuals.

Background: Cardiovascular disease (CVD) is the leading cause of mortality in low- and middle-income countries (LMICs). In Haiti, depression remains an underexplored CVD risk factor. We assessed the association between depressive symptoms (DS) and prevalent CVD in urban Haiti and examined sex differences. Methods: We conducted a cross-sectional analysis of enrollment data from the Haiti Cardiovascular Disease Cohort (adults [&ge;]18 years; March 2019--August 2021). DS were measured using the Patient Health Questionnaire-9 (PHQ-9) and categorized as none--mild (<10) versus moderate--severe ([&ge;]10). Prevalent CVD (angina, myocardial infarction, transient ischemic attack or stroke, heart failure) was adjudicated using epidemiologic definitions aligned with international cohorts. We estimated prevalence ratios (PRs) using generalized estimating equation Poisson models with a log link, adjusting for age, sex, education, income, food insecurity, smoking, alcohol use, physical activity, stress, and BMI. Effect modification by sex was assessed on multiplicative and additive scales. Results: Among 2,995 participants (mean age 41.9 years; 58.0% female), 16.2% (95% CI: 14.8-17.5; n=484) had moderate--severe DS. Prevalence was higher in females (22.0%, 95% CI: 19.8-23.6) than males (8.5%, 95% CI: 7.0-10.1). The prevalence of CVD was higher among participants with moderate--severe DS compared with those with none--mild DS, with similar patterns observed in both sexes (males: 21.5% vs 10.6%; females: 23.3% vs 15.3%). Moderate--severe DS were associated with higher CVD prevalence compared with none--mild DS (adjusted PR [aPR]=1.36; 95% CI: 1.08--1.71). In sex-stratified models, aPRs were 1.38 (95% CI: 1.06--1.78) for females and 1.25 (95% CI: 0.75--1.99) for males. Evidence for interaction by sex on the additive scale was limited (RERI=0.07, 95% CI: -0.74 to 0.88). Conclusion: Moderate--severe DS were independently associated with a higher prevalence of CVD in urban Haiti. Associations were consistently stronger among women, although evidence for effect modification by sex was limited. Integrating depression screening and management into CVD prevention efforts may help address the growing burden of both conditions in resource-limited settings. Prospective studies are warranted to better understand the underlying mechanisms and causal pathways.