Quantitative Assessment Research Articles

Modeling the health impact of wastewater contamination events in drinking water networks

Pathogen intrusion in drinking water systems can pose severe health risks. To better prepare in planning and responding to such events, computational models that capture the intrusion and health impact dynamics are needed. This study presents a novel benchmark testbed that integrates current knowledge on pathogen transport and fate in chlorinated systems and can assess infection risk from contamination events. The model considers organic matter degradation, chlorine decay mechanisms, pathogen inactivation kinetics, as well as stochastic water demands.We studied modeling of wastewater intrusion events that can occur anywhere within a chlorinated and non-chlorinated network. We applied the Quantitative Microbial Risk Assessment framework focusing on three pathogens: enterovirus, Campylobacter, and Cryptosporidium, and their respective dose-response models. Synthetic household-level water demand time series were used to model the individual water consumption timing and calculate the infection risk (exposure via ingestion).Model outcomes indicate that while chlorination aids mitigation, larger contaminations can still lead to infections due to chlorine resistance (for Cryptosporidium) and chlorine depletion at the contamination point. In our example scenarios, chlorine-susceptible pathogens infected of the downstream population, while chlorine-resistant ones infected the entire downstream population. Enterovirus infection risk is higher, despite the concentrations in the contamination source being lower, due to the lower susceptibility to chlorine than Campylobacter. In non-chlorinated networks, the modeled wastewater contamination events led to infection risk in the total population, depending on the contamination location. Hydraulic uncertainty had a limited influence on infection risk. Furthermore, Campylobacter’s infection risk is more sensitive to the initial concentration in the contamination source whereas enterovirus infection risk to the inactivation rate. The model further indicates that the time window for effective mitigation of the magnitude of a waterborne outbreak is short (within hours).

Preliminary investigation of the effects of high-temperature thermal activation on the activity of graphite tailings and the mechanical properties of graphite tailings mortar

The disposal of graphite tailings, a byproduct of graphite mining, poses significant recycling challenges. This study explores eco-friendly cement mortar by partially replacing sand with activated graphite tailings, focusing on waste utilization. Activating the pozzolanic properties of graphite tailings at various thermal activation temperatures converts them into high-quality binder materials. Quantitative assessments of graphite tailings' activity, conducted through ion leaching tests and raw material diffraction analysis, produce an activity index Ka, evaluating their performance under different thermal activation temperatures. Variable testing of substitution rates and activation temperatures examines changes in mechanical properties, microstructure, and pore distribution of the graphite tailings mortar. Optimum results reveal a 30 % substitution rate and a 750°C activation temperature. Graphite tailings, as pozzolanic binder materials, enhance mortar strength by improving particle size distribution, reducing "micro-area bleeding" and "boundary effects". After thermal activation, reactive minerals on the tailings' surface undergo secondary hydration reactions with cementitious products, modifying chemical structures and micro-morphology at the interface. Semi-quantitative XRD analysis and FT-IR spectroscopy characterize the ensuing chemical reactions, unveiling molecular bond and functional group changes. The superior performance of thermally activated graphite tailings primarily stems from increased active SiO2 and Al2O3 post-activation. The active SiO2 and Al2O3 reacts with cementitious products to form C-(A)-S-H gels, filling micro-pores at the tailings-mortar interface, which is the key characteristic that enables graphite tailings to serve as high-quality pozzolanic binder aggregates. A predictive model for compressive strength, utilizing reference models from solid waste mortar concrete, quantifies the positive impact of chemical activation. The theoretical results obtained from this predictive model closely align with the experimental findings.

A novel approach for microbial activity assessment in bioleaching. Towards to a standardised fast starting up protocol

Biohydrometallurgy is a proven industrial method for extracting base metals from sulfidic ores with low-grade content and as a pre-treatment of Au ores. The lack of study of biological aspects related with microbial activity assessment makes it difficult to control and monitor these processes; and the multitude of experimental procedures described in the literature hinders cross-study comparisons among researchers. Experimental tools that allow a quick and reliable quantitative assessment of the iron oxidising capacity of the cells during the bioleaching process are needed. This work proposes monitoring microbial activity through a simple and reliable method based on the offline measurement of the Oxygen Uptake Rate (OUR). The methodology allows to quantify the microbial activity evolution of a growing culture under no-limiting conditions. By this methodology, the maximum potential bioleaching rate of the culture at any time is determined, assessing the occurrence of a biological or chemical limitation. The results obtained reveals that whether due to Fe2+ or O2 depletion, substrate availability significantly limits microbial activity. This aspect is key to assess a culture suitability for bioleaching bioreactor inoculation, preventing long lag phases. Furthermore, the methodology allows for quick disturbances correction, avoiding process shutdowns and enhances technological reliability of continuous bioleaching.

Qualitative and quantitative assessment of apple quality using bulk optical properties in combination with machine learning and chemometrics techniques

This study aimed to understand the quantitative relationship between the bulk optical properties (BOP), soluble solids content (SSC), and fruit firmness (FF) of apples, along with the qualitative discrimination of apple cultivar and shelf-life. The absorption coefficient (μa) and reduced scattering coefficient (μs′) of 200 apples from four cultivars during 36-days shelf-life were determined using the single integrating sphere technique in 500-1000 nm. Partial least squares regression (PLSR) and random forest (RF) algorithms were used to establish quantitative prediction models for SSC and FF based on the BOP of apples. The results indicated that the PLSR models based on μɑ and μs′ were optimal for quantitative prediction of SSC (R2p=0.749, RMSEP=0.507) and FF (R2p=0.745, RMSEP=0.571), respectively. RF and linear discriminant analysis (LDA) were used to establish qualitative models for discriminating apple cultivar and shelf-life, demonstrating that the RF model based on μɑ and μɑ+ μs′ had the highest accuracy for the determination of apple cultivar and shelf-life, respectively, with the prediction set reaching 93.2 % and 85.7 %. Overall, RF was better than LDA for qualitative discrimination; however, it was less effective than PLSR for quantitative modeling.

Recruitment of pial collaterals and carotid occlusive disease in large-vessel occlusion ischemic stroke

Background and purposeDespite the fundamental role of pial collateral vessels in limiting the progression of ischemic tissue injury in acute stroke with large vessel occlusion (LVO), in addition to the fact that collateral vessel abundance varies naturally from person to person for genetic reasons, there is limited knowledge regarding potential factors contributing to inherent interindividual variation in pial collateral supply. As it has been repeatedly hypothesized that chronic carotid occlusive disease may favor pial collateralization, we aimed to investigate the association between quantitatively assessed leptomeningeal collateral supply and pre-existing carotid stenosis in patients with acute stroke due to LVO.Materials and methodsPatients with proximal middle cerebral artery (MCA) occlusion with or without additional internal carotid artery (ICA) occlusion were included. The degree of collateral supply was quantitatively assessed based on signal variance in T2*-weighted time series in perfusion-weighted magnetic resonance imaging (PWI). Patients were stratified into two groups according to quantitative collateral status (poor and fair to good collateral supply). The prevalence of high-grade ICA stenosis (≥70%) was evaluated in both groups.ResultsA total of 98 patients (mean age 68.8 ± 16.1 years, n = 52 (53.1%) of whom were female individuals) with MCA and/or ICA occlusion were included in the final analysis. Out of these patients, 42 had poor collateral supply, while 56 exhibited fair to good collateral supply. Additionally, 18 patients showed ipsilateral high-grade ICA stenosis. After classifying the entire cohort based on their collateral status (poor vs. fair to good collateral supply), there was no significant difference in the proportion of the patients with ipsilateral high-grade ICA stenosis between the two groups. Specifically, 6 (14.3%) patients had poor collateral supply, and 12 (21.1%) patients had fair to good collateral supply. The odds ratio (OR) was 1.58, with a 95% confidence interval (CI) of 0.490–5.685 and the p-value of 0.440. In the entire patient cohort, signal variance-based collateral supply was significantly correlated with initial stroke severity (r = −0.360, p < 0.001), baseline ischemic core volume (r = −0.362, p < 0.001), and functional outcomes (score on the modified Rankin Scale) at discharge (r = −0.367, p < 0.01).ConclusionIn this study, we performed a quantitative and observer-independent MRI-based collateral assessment in patients with LVO. We found no significant difference in the prevalence of pre-existing high-grade ICA stenosis between patients with fair to good collateral supply and those with poor collateral supply. The potential influence of demographic and clinical variables on pial collateral supply in patients with acute stroke warrants further exploration in future studies. MRI-based collateral supply is significantly related to initial stroke severity, ischemic core volume, and early functional outcomes.

Macrophyte Diversity and Ecosystem Services in Wetlands of Eastern Ranchi: A Multi-site Analysis of Abundance, Frequency, and Importance Value Index Patterns

Macrophytes, visible aquatic and semi-aquatic plants, are integral components of wetland ecosystems, playing crucial roles in maintaining biodiversity, providing ecosystem services, and ensuring ecological stability. This research examines the distribution, abundance, frequency, diversity, and ecosystem services of macrophytes in several wetlands (W1-W7) located in the eastern part of Ranchi district, Jharkhand, India. The study sites include Bundu Lake, Hindalco Pond, Choga Bada Talab, Raja Bandh, Kita Uparbandh, Tamar Bada Talab, and Rukka Dam. A quantitative assessment using quadrat sampling and phytosociological methods was conducted from September 2022 to March 2023 to ensure accurate data collection and analysis. The study documented 78 macrophyte species belonging to 33 families and 58 genera. Emergent macrophytes were found to be the dominant life form, constituting 69% of the recorded species. Several species demonstrated high frequency and abundance across multiple study sites, including Pontederia crassipes Mart., Alternanthera philoxeroides (Mart) Griseb., Hydrilla verticillata (L.f.) Royle, Ipomoea aquaticaForssk., and Nymphoides hydrophyllum (Lour.) kuntze. To assess the diversity and ecological characteristics of the macrophyte communities, various diversity indices were calculated. These included the Shannon-Wiener index, Simpson's index, Margalef index, and Pielou's Evenness index. The results of these analyses revealed high levels of macrophyte diversity and evenness within the studied wetlands. Twenty-one macrophytes were identified as key species and nine species as rare species based on their IVI (Importance Value Index) scores. The key species were found to provide essential ecosystem services, including erosion control, water quality improvement, nutrient cycling, carbon sequestration, and habitat provision for other organisms. This research contributes significantly to our understanding of macrophyte diversity patterns and traits-based ecosystem services in wetland ecosystems. The findings of this study have important implications for the development and implementation of effective conservation strategies for these vital wetland ecosystems in the eastern Ranchi (W1- W7).

Association of polarimetric signatures with coronary plaque composition in patients with acute and chronic coronary syndrome: an intravascular polarization-sensitive optical coherence tomography study

Abstract Background Intravascular polarimetry with polarization-sensitive (PS-) optical coherence tomography (OCT) measures polarization properties, birefringence and depolarization, in parallel with structural features available with conventional OCT (Figure 1). Birefringence is elevated in collagen and collagen-synthesizing smooth muscle cells, which imparts mechanical integrity to fibrous caps. Depolarization is elevated in the presence of macrophages and lipid/necrotic core. Purpose This study aimed to investigate polarimetric signatures of coronary lesions in patients with acute coronary syndrome (ACS) and chronic coronary syndrome (CCS). Furthermore, we aimed to investigate diagnostic value for birefringence and depolarization of ACS culprit lesions discriminating from CCS target lesions. Methods This was the first-in-human study of intracoronary PS-OCT in Japan, consisting of 17 patients with ACS (n = 5) or CCS (n = 12) who underwent intravascular PS-OCT. ACS culprit lesions (ACS-lesions) and CCS target lesions (CCS-lesions) were included in the analysis, resulting in a total of 862 cross-sections. In the cross-sectional images, lumen segmentation and guidewire artifact were automatically segmented. The median value of birefringence and depolarization were automatically analyzed using depolarization cut-off value (cross-sectional level). Birefringence and depolarization of ACS- and CCS-lesions were compared by using a generalized estimating equation model. Receiver operating characteristic (ROC) analysis was used to investigate diagnostic performance of polarimetric signatures for the identification of ACS-lesions. Results Compared to CCS-lesions, ACS-lesions featured higher lipid-burden index and maximum lipid arc (both p < 0.05). Compared to the CCS-lesions, ACS-lesions exhibited significantly lower birefringence (p < 0.05) and higher depolarization (p < 0.05) (Figure 2). In the ROC analysis for differentiating ACS-lesions from CCS-lesions, area under the curves (AUC) for birefringence and depolarization were 0.712 and 0.672, respectively. In the multivariable ROC analysis in diagnosing ACS lesions, combination of birefringence with depolarization improved the AUC to 0.755 (p ＝ 0.025). Conclusions Intravascular PS-OCT provides quantitative compositional assessment of coronary lesions. Decreased birefringence and pronounced depolarization within the ACS-lesions indicate increased collagenolytic activity and the presence of macrophage infiltration, respectively. These results suggest that polarization properties may serve as quantitative imaging markers for assessing natural history of coronary atherosclerosis.

Plug-and-play segment anything model improves nnUNet performance.

The automatic segmentation of medical images has widespread applications in modern clinical workflows. The Segment Anything Model (SAM), a recent development of foundational models in computer vision, has become a universal tool for image segmentation without the need for specific domain training. However, SAM's reliance on prompts necessitates human-computer interaction during the inference process. Its performance on specific domains can also be limited without additional adaptation. In contrast, traditional models like nnUNet are designed to perform segmentation tasks automatically during inference and can work well for each specific domain, but they require extensive training on domain-specificdatasets. To leverage the advantages of both foundational and domain-specific models and achieve fully automated segmentation with limited training samples, we propose nnSAM, which combines the robust feature extraction capabilities of SAM with the automatic configuration abilities of nnUNet to enhance the accuracy and robustness of medical image segmentation on smalldatasets. We propose the nnSAM model for small sample medical image segmentation. We made optimizations for this goal via two main approaches: first, we integrated the feature extraction capabilities of SAM with the automatic configuration advantages of nnUNet, which enables robust feature extraction and domain-specific adaptation on small datasets. Second, during the training process, we designed a boundary shape supervision loss based on level set functions and curvature calculations, enabling the model to learn anatomical shape priors from limited annotationdata. We conducted quantitative and qualitative assessments on the performance of our proposed method on four segmentation tasks: brain white matter, liver, lung, and heart segmentation. Our method achieved the best performance across all tasks. Specifically, in brain white matter segmentation using 20 training samples, nnSAM achieved the highest DICE score of 82.77 ( 10.12) % and the lowest average surface distance (ASD) of 1.14 ( 1.03) mm, compared to nnUNet, which had a DICE score of 79.25 ( 17.24) % and an ASD of 1.36 ( 1.63) mm. A sample size study shows that the advantage of nnSAM becomes more prominent under fewer trainingsamples. A comprehensive evaluation of multiple small-sample segmentation tasks demonstrates significant improvements in segmentation performance by nnSAM, highlighting the vast potential of small-samplelearning.

Segmental post-PCI physiological gradients using ultrasonic or optical flow ratio

Abstract Background Segmental pressure gradients post percutaneous coronary intervention (PCI) may detect residual disease and potential targets for optimization. Ultrasonic flow ratio (UFR) or optical flow ratio (OFR) provide simultaneous physiological and morphological data using a single imaging catheter. Notably, both have been validated against wire based FFR Objectives To evaluate the utility of UFR and OFR to identify residual disease post-PCI. Methods The present study is a sub analysis of the ASET (Acetyl Salicylic Elimination Trial) JAPAN pilot study Phase I which showed the feasibility and safety of low dose prasugrel monotherapy following PCI in Japanese patients presenting with chronic coronary syndrome and an anatomical SYNTAX score <23. Patients with complete intra-vascular imaging pullback data were included with UFR/OFR acquired in all patients post-PCI. Quantitative and qualitative assessment of IVUS or OCT pullbacks was performed by automatically delineating vessel, lumen, and stent contours every 0.5 mm using QCU-CMS (version 4.69, Division of Image Processing, Leiden University Medical Centre). UFR or OFR was calculated using the respective IvusPlus or OctPlus software, Pulse Medical, Shanghai, China.(13)(15) All UFR and OFR tracings, and IVUS and OCT pullbacks were analyzed at the CORRIB Core lab, Galway, Ireland by two analysts blinded to clinical and procedural data. Anatomically focal lesions distal and proximal to the stent were evaluated in segments ≥5mm long. UFR/OFR virtual pullback curves were used to calculate intra-stent pressure gradients and physiologically define lesions as focal or diffuse by segmental pressure drops ≥0.05 over lengths <10mm or ≥10mm, respectively. Results The median post-PCI UFR/OFR was 0.93 (0.88-0.96) with 69/195 vessels (35.4%) having a UFR/OFR≤0.90. There were significantly more focal anatomical and physiological lesions proximal and distal to the stent in vessels with a UFR/OFR≤0.90 versus >0.90. In vessels with a UFR/OFR≤0.90 there was moderate agreement (weighted kappa=0.553, p<0.001) between anatomical and physiological focal lesions proximal to the stent, whilst it was fair (weighted kappa=0.219, p=0.002) distally. In-stent gradient had poor discriminative ability to detect significant stent under-expansion. The performance of a proximal or distal virtual FFR gradient to detect proximal or distal anatomically focal disease was good (AUC–0.835 and 0.877, respectively) Conclusions UFR/OFR enables suboptimal vessel physiology post-PCI to be detected and helps identify the precise anatomical location with corroboration from intra-vascular imaging. Adequately powered physiology optimization trials using UFR/OFR will determine the role of combined morphology and physiological evaluation post PCI in improving clinical outcomes.

A Conceptual Model for Health Impact Assessment of Personalized Prevention Policies

Abstract Background Personalized prevention and pharmacogenomics are emerging fields in global health, promoting tailored approaches to disease prevention and individualized drug therapy, based on the individuals’ genetic profile. However, adoption of these technologies in public health is challenged by the possibility of health disparities. Health Impact Assessment (HIA) is a useful tool to address this issue, by examining how policies differentially impact population groups, guiding stakeholders to more equitable and inclusive outcomes. Solid frameworks for assessing health impacts are needed to avoid heterogeneity when accounting for equity outcomes in HIA. This study tested a conceptual model for HIA in personalized medicine, using a case study in pharmacogenetics to map potential impacts and outcomes, with a focus on health equity. Methods A conceptual model for a HIA was developed to map expected impacts and outcomes of a health policy, aimed at enforcing DPYD genotype-guided dosing to prevent fluoropyrimidine toxicity in colorectal cancer patients. The conceptual model was developed based on literature reviews and consultation with stakeholders. Identification of relevant impacts guided selection of indicators and quantitative impact assessment using a Markov chain model. Results Impact pathways were identified using a three-tiered reference framework encompassing individual and population perspectives, organizational factors, and overarching health system considerations. The final diagram outlined key outcomes in four categories: health, organizational, economic and equity. HIA projections using this model were obtained for the DPYD testing policy. Conclusions In the rise of personalized medicine and pharmacogenomics, health inequalities challenges need to be addressed before implementation in healthcare. This study provided a novel HIA conceptual model for personalized prevention policies based on genomic information, with an emphasis on equity. Key messages • HIA is an adequate tool to evaluate potential health inequalities resulting from personalized medicine policies in healthcare. • This study provides a validated framework for HIA of personalized prevention policies grounded in genomic data.

Learning through playing in public health: a card game’s evaluation

Abstract Background In medical education and particularly in public health, the shift toward active learning addresses the limitations of traditional lecture-based methods. Game-based learning, such as serious games, showed potential to overcome these limitations. “Accidémie” is a card game designed to improve medical students’ knowledge of home accidents and their competencies in public health through an interactive format. This study aims to evaluate the effectiveness of “Accidémie”. Methods We conducted a quantitative pre-post assessment study among sixth-year medical students of the University of Versailles. Data were collected through a 20-item true/false repeated questionnaire before and after. In addition, the post-intervention questionnaire included questions on students’ satisfaction and an open-ended question. Responses to the questionnaires were converted into scores. The main outcome measured was the change in the scores. The scores before and after the intervention are presented with their mean and standard deviation. They were compared using a paired t-test. Student satisfaction is presented in terms of frequency and includes verbatim responses from the students. Results Thirty-eight students participated, with pre-test scores averaging 13.13 (SD = 1.98) and post-test scores averaging 14.89 (SD = 1.94). A paired t-test provided statistical evidence of the difference between the pre- and post-test scores (p < 0.001). Students provided positive feedback: 81.6% of the students were very satisfied with the game; 42.1% considered it extremely useful. They also underlined that ‘Accidémie’ is an enjoyable learning tool, praising its innovative approach. Conclusions “Accidémie” improved students’ knowledge of home accidents and their engagement. It supports the use of serious games in medical education complementary to traditional methods. Applying the concept of “Accidémie” across various subjects and among diverse groups of health students offers promising prospects. Key messages • ‘Accidémie’ significantly improves students’ knowledge of home accidents, a public health topic. • “Accidémie” allows medical students to learn while playing, boosting satisfaction and engagement.

Climate change and health vulnerability assessments to increase regional climate resilience

Abstract Background The impacts of climate change on health and healthcare systems exhibit complex interrelationships, varying across time and space. Population groups already disadvantaged due to their demographics, health, socioeconomic status, or geographical location tend to be particularly vulnerable to climate-related health risks. Our work aims to develop a method for a systematic quantitative vulnerability assessment to make regional vulnerabilities comparatively measurable. Methods Building on the WHO framework on Climate Change and Health Vulnerability and Adaptation Assessment (2021) a data mapping process was carried out to identify and validate vulnerability factors and quantitative indicators on a small-scale spatial resolution for the five dimensions: demographic, socioeconomic, biological/health, sociopolitical, and geographic/climate. Regional vulnerability scores for each indicator were calculated and visualized as geographic maps and circular barplots to allow for easily understandable interpretation. Results A set of 25 quantitative vulnerability indicators from a multitude of data sources - combining register data, survey data, and geospatial data - was compiled. Main challenges were the identification of sociopolitical vulnerability factors suitable for Austria and data availability on a small-scale level. The indicator set was used to identify regions that are particularly vulnerable due to their population composition, disease burden, and geographical location (e.g. regions in Eastern Austria with high shares of persons < 65 years of age, unemployment, and heat days). Conclusions Systematically assessing vulnerabilities in key dimensions is central to identifying regionally specific pressure points, allowing for a quantitative baseline to derive adequate and tailored climate change adaptation measures to sustain future health. Systematic assessment provides essential insights for policymakers, public health officials, and disaster management agencies.

Influence of Sporulation Temperature on Germination and Growth of B. weihenstephanensis Strains in Specific Nutrients and in an Extended Shelf-Life Refrigerated Matrix Under Commercial Pasteurization and Storage Conditions

Extended shelf-life (ESL) refrigerated ready-to-eat foods are thermally pasteurized to ensure food safety and stability. However, surviving psychrotrophic Bacillus cereus spores can still pose a challenge. Studies predicting their behavior often overlook sporulation conditions. This study investigated the effect of sporulation temperature on germination of three Bacillus weihenstephanensis strains in specific nutrients (inosine and/or amino acids) with or without prior heat activation (80 °C, 10 min). Sporulation temperature variably affected germination, with stronger effects in moderately responsive strains and nutrients. Heat activation strongly stimulated germination, particularly in nutrients with poorer responses, mitigating differences induced by sporulation temperature. The influence of sporulation temperature on germination and growth in an ESL matrix at refrigeration temperatures (4 °C or 8 °C) in vacuum packaging after heat activation or commercial pasteurization (90 °C, 10 min) was also studied. The latter treatment increased germination rates of surviving spores; however, some strains suffered damage and lost viability upon germination at 4 °C but recovered and grew at 8 °C. These findings highlight the need to account for variability in spore recovery and outgrowth during quantitative risk assessments for psychrotrophic B. cereus in ESL foods.

Extracellular vesicles characterization in patients with hypertrophic cardiomyopathy

Abstract Background Hypertrophic cardiomyopathy (HCM) is a genetic disorder, diagnosed according to the presence of phenotypical traits of the myocardium. A specific biomarker which can associate with the severity of HCM is lacking. Extracellular Vesicles (EVs), nanoparticles released by cells into biological fluids, hold promise as accessible diagnostic tools, as their abundance and molecular composition can reflect the severity of cardiac diseases (Rizzuto 2024). We aim at characterising plasma-derived EVs isolated from 28 HCM patients and 18 healthy volunteers (CTR). Methods The whole cohort underwent transthoracic echocardiography, whereas magnetic resonance and exome sequencing was performed on HCM patients. EVs were isolated via ultracentrifugation from plasma of both groups. Quantitative and qualitative assessments of EVs were performed by nanoparticle tracking analysis, transmission electron microscopy, Western blot, targeted (Olink) and untargeted (nLC-MS/MS) proteomics and FACS analysis. Plasma-derived EV subpopulations were characterised according to their cellular origin. Data are expressed as median and interquartile range (25th, 75th). Results Most patients were male (68% HCM and 66% CTR) with a median age of 58 (49-69) years (HCM) and 47 (44-52) (CTR). Among HCM patients, missense mutations in the MYH7 gene were the most identified. The median maximum wall thickness (WTMax) in HCM was 16 mm (15-19) vs 8 mm (7-9) in CTR. The isolated EVs expressed tetraspanins (CD9, CD63 and CD81), Alix and β-integrin and showed an intact phospholipid bilayer of 100 nm in size. EV concentration was reduced in HCM vs CTRL, respectively 2.8*109 EV/ml/cell count (2*109-4*109) and 4.6*10⁹ EV/ml/cell count (3*109-6*109). Among 15 plasma-derived EV subpopulations studied, those released from platelets (CD41a) and activated platelets (CD62P and CD40L) were increased in HCM patients vs CTR by 1.7 fold. Negative associations were found between E/e’, parameter of diastolic function, and cardiomyocyte-derived EVs (r= -0.2658), and between left ventricle ejection fraction and platelet-derived EVs (r=-0.2189); a positive correlation was found between WTMax and EVs derived from activated endothelial cells (r=0.2330). The proteomic analysis of EVs shows an enrichment in proteins related to platelets adhesion and inflammation in HCM patients. Conclusions HCM patients present a peculiar phenotypic pattern of EVs that may associate with diagnostic clinical features of HCM.

Validation of quantitative aortic valve calcification assessment by photon-counting computed tomography from contrast-enhanced data sets using virtual non-contrast reconstructions

Abstract Background The spectral information of photon-counting computed tomography (PCCT) permits the reconstruction of energy-selective images. Purpose We evaluated two methods for the reconstruction of virtual non-contrast-enhanced images from contrast-enhanced CT angiographic data sets regarding their ability to quantify aortic valve calcification. Results were validated by comparison to non-enhanced computed tomography. Methods A total of 100 subjects with severe aortic valve stenosis who underwent ECG-synchronized cardiac photon-counting CT for diagnostic workup prior to transcatheter aortic valve implantation (TAVI) were included in the current analysis. A standard true non-contrast acquisition was performed for aortic valve calcium quantification in each subject. In addition, two virtual non-enhanced data sets were reconstructed from contrast-enhanced CT angiographic data: a calcium-specific image ("pure calcium scan", PCS) and a virtual non-contrast (VNC) scan by subtraction of iodine. The PCS algorithm separates calcium and iodine in spectral PCCT images, creating a non-calcium mask for denoised spectral input and preserving calcium contrast in final material decomposition. Iodine extraction is achieved by measurement of the iodine content and its differentiation from native soft tissue attenuation. The Agatston Score was assessed in each of the three image data sets using semi-automated software. Results The mean age of the subjects was 78 ± 7 years, 66% were male. Mean EUROSCORE II was 4 ± 4%, mean STS Score for morbidity and mortality was 16 ± 11%. In the true non-contrast scan used for validation, the mean Agatston Score was 3028 ± 1820. The mean Agatston Score obtained from the PCS data set was 3004 ± 2042 and did not differ significantly from true non—contrast image sets (p=0.716). In the VNC data sets, the mean Agatston score was 1726 ± 1288, significantly lower than in the true non-contrast and the PCS data sets (both <0.001). Both, PCS and VNC data showed a significant correlation with true non-contrast scans (correlation coefficient PCS: 0.978, VNC scan: 0.975, both p<0.001). Conclusion In conclusion, the current results show the possibility to reliably quantify the Agatston Score of larger cardiac calcifications in virtual non-contrast data sets – however, there is substantial influence of the algorithm that is used so that validation of new techniques is of key importance.

Invasive quantitative assessment of coronary microvascular dysfunction in patients with hypertrophic cardiomyopathy

Abstract Background Patients (P) with hypertrophic cardiomyopathy (HCM) commonly suffer from coronary microvascular dysfunction (CMD) - the affection of function/structure of the coronary microvasculature. Invasive assessment of CMD through thermodilution methods allows for the calculation of coronary flow reserve (CFR) and index of microvascular resistance (IMR). These methods, while extensively studied in the context of non-obstructive coronary artery disease and myocardial infarction, have not been thoroughly validated in HCM P. Objectives To invasively assess the presence of CMD in P with HCM and to determine clinical predictors of invasively assessed CMD. Methods In a prospective single-centre study, we opportunistically recruited consecutive adult P with an established diagnosis of HCM with or without LVOTO that had an indication to pursue elective coronarography – such as pre-procedural evaluation for alcoholic septal ablation (ASA) or exclusion of epicardial coronary artery disease. P characteristics and coronary hemodynamic invasive assessment data were extracted. CFR was calculated as the ratio between resting and hyperemia mean transit times (TmnRest;TmnHyper). IMR was calculated as the ratio between distal coronary pressure (Pd) and the inverse of TmnHyper (IMR=Pd/TmnHyper-1). A cutoff of ≤22.0 in IMR, an ≥d 2 in CFR was used. We excluded P with end-stage HCM (LV EF <50% and/or or left ventricular wall thinning), or with epicardial coronary artery disease. Continuous variables were reported as mean ± SD or median and IQR depending on data distribution pattern and categorical data as frequencies and percentages. A linear regression model was used to test predictors of IMR and CFR involvement. Results 25 HCM P with a mean age of 63±10 years were included, 14 (56%) were female. In 20 (80%) of the P the cause for coronary angiography was ASA. All P referred for ASA had LVOTO and were on beta-blocker therapy (Table 1.). Median CFR was 2.5 [1.5-3] and median IMR was 19 [14-22], both within normal range. A total of 13 (44%) P had a reduced CFR and 5 (20%) of P had an increased IMR. 14 P (56%) had an altered CFR or IMR value, with the presence of a functional CMD phenotype in 10 P (40%) (Table 2). Angina was associated with a higher IMR (5.3, 95% CI - 0.05-10, p=0.053) and for each +1 increase in CCS a larger increase in the likelihood of a higher IMR was observed (CCS 1, +7 (95%CI 0.68 – 14); CCS 2, +9 (95%CI 4 – 14); CCS 3, 10 (95%CI 2 – 18)). A similar but non significant trend was observed for higher CCS correlating with lower CFR (Table 3). Conclusion In a prospective cohort of HCM P submited to invasive angiographic evaluation 56% had at least one invasive measure compatible with CMD. Angina, and a higher degree of anginal symptoms correlated positively with the presence of higher IMR and therefore with a higher level of CMD. In the future, we intend to correlate these findings with multimodality imaging/clinical outcomes.Patient characteristics and LR results

Identification of drug use degree by integrating multi-modal features with dual-input deep learning method.

Most of studies on drug use degree are based on subjective judgments without objective quantitative assessment, in this paper, a dual-input bimodal fusion algorithm is proposed to study drug use degree by using electroencephalogram (EEG) and near-infrared spectroscopy (NIRS). Firstly, this paper uses the optimized dual-input multi-modal TiCBnet for extracting the deep encoding features of the bimodal signal, then fuses and screens the features using different methods, and finally fused deep encoding features are classified. The classification accuracy of bimodal is found to be higher than that of single modal, and the classification accuracy is up to 89.9%.

Decreased left atrial volume and preserved left atrial function in children with congenital Zika syndrome

Abstract Introduction The infection caused by Zika virus during pregnancy leads to congenital Zika syndrome (CZS). In a previous study of our group, we found that the heart is smaller in children with CZS, with few functional alterations. Left atrial strain imaging enables quantitative assessment of left atrial function, and recently its application has also shown promise in the pediatric population. Purpose To evaluate left atrial function in children affected by CZS, using echocardiogram and speckle tracking imaging technique. Methods This observational study was conducted with children with CZS using a two-dimensional speckle tracking technique to measure left atrial reservoir strain (LAS-r), conduit strain (LAS-cd), and contraction strain (LAS-ct). Also, to investigate the relationship between LAS-r and systolic excursion of the septum and lateral mitral annular plane (MAPSE), left atrial volume index and E/e’ ratio. Results A total of 52 patients were included, the median age of the studied population was 5 years (3 to 6), 59.6% male, and the body surface area was 0.66 [0.51, 0.90]. In the echocardiographic evaluation the left atrium volume index (ml/m²) was 13.15 [6.80, 18.00], considered smaller by the reference value. Also, the LAS-r (%) was 40.99 [24-70.5], LAS-cd (%) was 30,94 [32.5-52.5], LAS-cd (%) was 10,91 [5.2-24], values considered normal by the literature. Lateral MAPSE (cm) was 1.25 [0.81, 1.86] and septal MAPSE (cm) was 0.98 [0.78, 1.66] and E/e' ratio was 7.52 [4.57, 10.78]. A positive linear correlation was found between LAS-r and lateral MAPSE (r = 0.51, P = 0.019). Conclusion This original study with children with CZS shows that despite reduced atrial volume, the left atrial function remains normal, and correlates with left ventricular function evaluated by MAPSE. Further studies are needed to prospectively analyze the follow-up of left atrial morphology and function in this population.

Normal values and reference ranges for quantitative assessment of myocardial first-pass perfusion by spectral computed tomography. From the Cadami-Spectral study

Abstract Background Spectral computed tomography (SCT) can generate iodine concentration maps according to the tissue iodine uptake, serving as a surrogate marker of organ perfusion. Thus, assessment of the iodine distribution maps derived from SCT allows to detect deviations in normal myocardial perfusion. As of present, reference ranges for the iodine concentration in each myocardial segment of the left ventricle (LV) derived from the first-pass perfusion have not been published. Purpose To provide normal values of first pass perfusion in individuals without coronary artery disease (CAD). Additionally, we explored whether these values could vary according to gender, contrast dosing or the cardiac cycle phase assessed. Methods From October 2021 to January 2024, we retrospectively identified patients who underwent a CT Cardiac Angiography (CTCA) and had no evidence of CAD or structural heart disease. Subjects were scanned using a dual-layer SCT, following a standard local protocol which included a weight-based contrast medium dosing of 0.8 mL/Kg. Iodine density maps were reconstructed using the MCA filter at a phase of 78%. An additional sample of 18 subjects who received a dosing of contrast of 1 mL/Kg and 16 cases scanned using a systolic acquisition and reconstructed at phase of 35% were also included. Spectral reconstructions were combined with tissue segmentation to obtain the spatial distribution of iodine along the myocardium. Mean, median and standard deviations values of density of iodine (mg/ml) were quantified for each segment following the AHA-17 segment model. Results Perfusion data from 80 woman (median age: 60 [IQR: 54-65.6] years) and 47 males (median age: 47 [IQR: 43 – 54] years) were analysed. Despite receiving higher dose of contrast (67.9 vs 59.8 mL; p < 0.05), male subjects exhibited lower iodine density values in the myocardium compared to females (median concentration per segment 1.58 vs 2.01 mg/dL, p<0.001; figure 1). Notably, the volume of the LV myocardium was higher in male than in women (143 mL vs 92 mL, p<0.001). These differences could be partially explained in a mixed model considering the ratio contrast dose/myocardium volume (b = 1.500, p < 0.001). Higher contrast dosing (1 mL/Kg vs 0.8 mL/kg) correlated with higher iodine density values in the myocardium (2.03 vs 1.83 mg/dL, respectively; p = 0.023). No differences were noted when comparing reconstructions at systole vs diastole (1.86 vs 1.80 mg/dL, respectively; p = 0.484). Reference range values of each myocardial segment are listed in table 1. Conclusions Significant gender discrepancies are detected in the analysis of first-pass myocardial perfusion. These variations can be partially explained by differences in the LV myocardium volume. Our findings provide applicable reference ranges of the iodine concentration in myocardium at first pass perfusion in controls without coronary or structural heart disease.

Feasibility of quantitative evaluation of hemodynamics using SPECT/CT in patients with chronic thromboembolic pulmonary hypertension

Abstract Background A ventilation/perfusion (V/Q) lung scan is recommended in the diagnostic work-up of patients with newly diagnosed pulmonary hypertension to rule out chronic thromboembolic pulmonary hypertension (CTEPH). V/Q single-photon emission computed tomography (SPECT) is considered the method of choice for diagnosis in CTEPH because it allows more precise evaluation than planar imaging. However, the evaluation of lung perfusion using V/Q SPECT imaging remains mainly a qualitative evaluation, and no quantitative method has been established. We hypothesized that the standardized uptake value (SUV) technique in Positron Emission Tomography (PET)-CT, a nuclear imaging technique well suited for quantitative of tumor biology, could be applied to quantitative assessment of lung perfusion. Purpose The purpose of this study was to evaluate the correlation between pulmonary perfusion distribution and hemodynamic data in Tc-labeled large-assembly albumin (99mTc-MAA) SPECT images in order to determine the feasibility of SPECT/CT for quantitative assessment of lung perfusion. Methods Twenty-five patients with CTEPH who underwent BPA and received SPECT-CT were included. Since the injected 99mTc-MAA selectively accumulates only in the lungs, SUV normalization was conducted using each patient’s lung volume, calculated by SPECT/CT and defined as SUV lung volume (LV) . The percentage of lung volume below each SUVLV value in total lung volume on SPECT/CT was examined before BPA, after two procedures of BPA, and six months after a series of BPA, and the correlations with hemodynamic parameters on right heart catheterization at each time point were evaluated. Results The Percent lung volume below SUVLV of 0.7 in total lung volume before BPA, after two procedures of BPA, and six months after a series of BPA had the strongest correlation with mean pulmonary artery pressure (mPAP) (rs; 0.727, p<0.001, Figure 1). The percent lung volume below SUVLV of 0.7 decreased with the BPA procedure in each patient with CTEPH (Figure 2). Furthermore, receiver operating characteristic analysis revealed that a threshold for the percent lung volume below SUVLV of 0.7 of 50.3% or greater could identify mPAP greater than 21 mmHg for right heart catheterization (area under the curve = 0.86, 95% CI 0.78-0.94, p<0.001). Conclusion Percent lung volume below SUVLV of 0.7 in total lung volume using SPECT/CT might reflect the severity of hemodynamics in patients with CTEPH. This method would be feasible for quantitative assessment of lung perfusion, even inter-patient and intra-patient.Figure 1Figure 2