Effects of sacubitril-valsartan on remodelling, fibrosis and mitochondria in a murine model of isoproterenol-induced left ventricular dysfunction.

BACKGROUND: Sacubitril/valsartan has been demonstrated to promote left ventricular (LV) reverse remodelling and improve outcomes in patients with heart failure (HF) with reduced ejection fraction (EF). Its molecular and tissue effects have not been fully elucidated yet, due to the paucity of preclinical studies, mostly based on ischaemic models. We aimed to evaluate the effects of sacubitril/valsartan on LV remodelling, myocardial fibrosis and mitochondrial biology in a murine model of non-ischaemic LV dysfunction. METHODS: Adult transgenic male mice with cardiac-specific hyperaldosteronism (AS mice) received subcutaneous isoproterenol injections to induce LV systolic dysfunction. After 7 days, mice were randomized to a 2-week treatment with saline (ISO-AS n = 15), valsartan (ISO + V n = 12) or sacubitril/valsartan (ISO + S/V n = 12). Echocardiography was performed at baseline, at day 7, and after each of the 2 weeks of treatment. After sacrifice at day 21, histological and immunochemical assays were performed. A control group of AS mice was also obtained (Ctrl-AS n = 8). RESULTS: Treatment with sacubitril/valsartan, but not with valsartan, induced a significant improvement in LVEF (p = 0.009 vs ISO-AS) and fractional shortening (p = 0.032 vs ISO-AS) after 2- week treatment. In both ISO + V and ISO + S/V groups, a trend toward reduction of the cardiac collagen 1/3 expression ratio was detected. ISO + V and ISO + S/V groups showed a significant recovery of mitochondrial morphology and inner membrane function meant for oxidative phosphorylation. CONCLUSION: In a murine model of non-ischaemic HF, sacubitril/valsartan proved to have beneficial effects on LV systolic function, and on cardiac energetics, by improving mitochondrial activity.

Lacking P2X7-receptors protects substantia nigra dopaminergic neurons and hippocampal-related cognitive performance from the deleterious effects of high-fat diet exposure in adult male mice.

Background: Dietary fat consumption, involved in the pathogenesis of insulin resistance and impaired glucose metabolism, is linked with decline in cognitive functions, dementia, and development of Parkinson's disease and Alzheimer's disease. Mature IL-1ß, requiring the activation of the P2X7 receptor (P2X7R)-inflammasome complex, is an important mediator of neuroinflammation. The aim of the study was to test whether P2X7R activation might interfere with systemic and cerebral metabolic homeostasis. Methods: We treated WT and P2X7R KO mice with a high-fat diet (HFD) for 16 weeks, evaluating the effects on the Substantia Nigra and Hippocampus, target areas of damage in several forms of cognitive impairment. Results: HFD-treated WT and P2X7R KO mice showed a different brain mRNA profile of Insulin and Igf-1, with these genes and relative receptors, more expressed in KO mice. Unlike P2X7R KO mice, WT mice treated with HFD displayed a diameter reduction in dopaminergic neurons in the Substantia Nigra, accompanied by an increased IBA1 expression in this area; they also showed poor performances during Y-Maze and Morris Water Maze, tasks involving Hippocampus activity. Conversely, Parkin, whose reduction might promote neuronal cell death, was increased in the brain of P2X7R KO animals. Conclusion: We report for the first time that HFD induces damage in dopaminergic neurons of the Substantia Nigra and a Hippocampus-related worse cognitive performance, both attenuated in the absence of P2X7R. The involved mechanisms might differ in the two brain areas, with a predominant role of inflammation in the Substantia Nigra and a metabolic derangement in the Hippocampus.

Gut-derived metabolites mediating cognitive development in 5-year-old children: Early-life transplant in mice has lasting effects throughout adulthood.

The gut microbiota has been causally linked to cognitive development. We aimed to identify metabolites mediating its effect on cognitive development, and foods or nutrients related to most promising metabolites. Faeces from 5-year-old children (DORIAN-PISAC cohort, including 90 general population families with infants, 42/48 females/males, born in 2011-2014) were transplanted (FMT) into C57BL/6 germ-free mice. Children and recipient mice were stratified by cognitive phenotype, or based on protective metabolites. Food frequency questionnaires were obtained in children. Cognitive measurements in mice included five Y-maze tests until 23 weeks post-FMT, and (at 23 weeks) PET-CT for brain metabolism and radiodensity, and ultrasound-based carotid vascular indices. Children (faeces, urine) and mice (faeces, plasma) metabolome was measured by 1H NMR spectroscopy, and the faecal microbiota was profiled in mice by 16S rRNA amplicon sequencing. Cognitive scores of children and recipient mice were correlated. FMT-dependent modifications of brain metabolism were observed. Mice receiving FMT from high-cognitive or protective metabolite-enriched children developed superior cognitive-behavioural performance. A panel of metabolites, namely xanthine, hypoxanthine, formate, mannose, tyrosine, phenylalanine, glutamine, was found to mediate the gut-cognitive axis in donor children and recipient mice. Vascular indices partially explained the metabolite-to-phenotype relationships. Children's consumption of legumes, whole-milk yogurt and eggs, and intake of iron, zinc and vitamin D appeared to support protective gut metabolites. Overall, metabolites involved in inflammation, purine metabolism and neurotransmitter synthesis mediate the gut-cognitive axis, and holds promise for screening. The related dietary and nutritional findings offer leads to microbiota-targeted interventions for cognitive protection, with long-lasting effects.

Applications of Deep Learning Algorithms to Ultrasound Imaging Analysis in Preclinical Studies on In Vivo Animals.

BACKGROUND AND AIM: Ultrasound (US) imaging is increasingly preferred over other more invasive modalities in preclinical studies using animal models. However, this technique has some limitations, mainly related to operator dependence. To overcome some of the current drawbacks, sophisticated data processing models are proposed, in particular artificial intelligence models based on deep learning (DL) networks. This systematic review aims to overview the application of DL algorithms in assisting US analysis of images acquired in in vivo preclinical studies on animal models. METHODS: A literature search was conducted using the Scopus and PubMed databases. Studies published from January 2012 to November 2022 that developed DL models on US images acquired in preclinical/animal experimental scenarios were eligible for inclusion. This review was conducted according to PRISMA guidelines. RESULTS: Fifty-six studies were enrolled and classified into five groups based on the anatomical district in which the DL models were used. Sixteen studies focused on the cardiovascular system and fourteen on the abdominal organs. Five studies applied DL networks to images of the musculoskeletal system and eight investigations involved the brain. Thirteen papers, grouped under a miscellaneous category, proposed heterogeneous applications adopting DL systems. Our analysis also highlighted that murine models were the most common animals used in in vivo studies applying DL to US imaging. CONCLUSION: DL techniques show great potential in terms of US images acquired in preclinical studies using animal models. However, in this scenario, these techniques are still in their early stages, and there is room for improvement, such as sample sizes, data preprocessing, and model interpretability.

Cardiomyocyte-targeting exosomes from sulforaphane-treated fibroblasts affords cardioprotection in infarcted rats.

BACKGROUND: Exosomes (EXOs), tiny extracellular vesicles that facilitate cell-cell communication, are being explored as a heart failure treatment, although the features of the cell source restrict their efficacy. Fibroblasts the most prevalent non-myocyte heart cells, release poor cardioprotective EXOs. A noninvasive method for manufacturing fibroblast-derived exosomes (F-EXOs) that target cardiomyocytes and slow cardiac remodeling is expected. As a cardioprotective isothiocyanate, sulforaphane (SFN)-induced F-EXOs (SFN-F-EXOs) should recapitulate its anti-remodeling properties. METHODS: Exosomes from low-dose SFN (3 µM/7 days)-treated NIH/3T3 murine cells were examined for number, size, and protein composition. Fluorescence microscopy, RT-qPCR, and western blot assessed cell size, oxidative stress, AcH4 levels, hypertrophic gene expression, and caspase-3 activation in angiotensin II (AngII)-stressed HL-1 murine cardiomyocytes 12 h-treated with various EXOs. The uptake of fluorescently-labeled EXOs was also measured in cardiomyocytes. The cardiac function of infarcted male Wistar rats intramyocardially injected with different EXOs (1·1012) was examined by echocardiography. Left ventricular infarct size, hypertrophy, and capillary density were measured. RESULTS: Sustained treatment of NIH/3T3 with non-toxic SFN concentration significantly enhances the release of CD81 + EXOs rich in TSG101 (Tumor susceptibility gene 101) and Hsp70 (Heat Shock Protein 70), and containing maspin, an endogenous histone deacetylase 1 inhibitor. SFN-F-EXOs counteract angiotensin II (AngII)-induced hypertrophy and apoptosis in murine HL-1 cardiomyocytes enhancing SERCA2a (sarcoplasmic/endoplasmic reticulum Ca2+ ATPase 2a) levels more effectively than F-EXOs. In stressed cardiomyocytes, SFN-F-EXOs boost AcH4 levels by 30% (p < 0.05) and significantly reduce oxidative stress more than F-EXOs. Fluorescence microscopy showed that mouse cardiomyocytes take in SFN-F-EXOs ~ threefold more than F-EXOs. Compared to vehicle-injected infarcted hearts, SFN-F-EXOs reduce hypertrophy, scar size, and improve contractility. CONCLUSIONS: Long-term low-dose SFN treatment of fibroblasts enhances the release of anti-remodeling cardiomyocyte-targeted F-EXOs, which effectively prevent the onset of HF. The proposed method opens a new avenue for large-scale production of cardioprotective exosomes for clinical application using allogeneic fibroblasts.

Relationships Between Intestinal Ultrasound Parameters and Histopathologic Findings in a Prospective Cohort of Patients With Crohn's Disease Undergoing Surgery.

OBJECTIVES: Recognition of intestinal lesions with substantial fibrosis is strategic for optimal management of patients with Crohn's disease (CD). We aimed to assess the relationships between intestinal ultrasound parameters and histopathologic findings in a prospective cohort of patients with CD undergoing surgery. METHODS: Seventeen consecutive adult CD patients with involvement of the terminal ileum or the sigmoid colon who underwent bowel resective surgeries were enrolled and performed intestinal ultrasound (IUS) within 30 days prior to surgery. Uni- and multivariable analyses were used to assess the relationships between IUS parameters and histopathological elements of lesions. RESULTS: Sensitivity, specificity, accuracy, PPV and NPV (95% CI) of IUS in detecting stricturing and penetrating complications (surgical specimen as reference standard) were 93% (68-100), 86% (42-100), 91% (71-99), 93% (68-100) and 86% (42-100), and 78% (40-97), 92% (64-100), 86% (65-97), 88% (47-100) and 86% (57-98), respectively. Only the presence of hyperechogenic spiculates was statistically significantly associated with collagen content (b = 7.29, 95% CI = 1.88/12.69, P = .012), while only the presence of vascular signals at color Doppler (Limberg score 3 or 4) was significantly associated with active inflammation (OR = 10.0, 95% CI = 0.9/108.6, P = .037). There was a strong correlation between IUS and histological measurements of the wall thickness (r = 0.67, P = .01). CONCLUSIONS: The presence of hyperechogenic spiculates was associated with the presence of fibrosis, while the presence of marked vascular signals was associated with the presence of inflammation. Wall thickness measured by IUS was reliable and reproducible in comparison with histological measurement.

Ultra-High Frequency Ultrasound in Melanoma Management: A New Combined Ultrasonographic-Histopathological Approach.

OBJECTIVES: The main aim of this study is to evaluate the correspondence between the ultrasonographic thickness and the Breslow thickness in melanoma using ultra-high frequency ultrasound and the intra- and inter-operator repeatability in the ultrasonographic measurements of melanoma depth. Moreover, we propose a new protocol based on a combined ultrasonographic-histopathological approach. METHODS: We analyzed 27 melanomas in a population consisted of 27 patients (mean age 57.6 years, 51.8% males), who came at the Department of Dermatology (University of Pisa, Pisa, Italy) from April 2016 to March 2018 and had an ultrasonographic examination of a suspected lesion before the surgical removal using ultra-high frequency ultrasound (Vevo®MD, Fujifilm, Visualsonics, Toronto, Canada; 70 MHz probe). B-mode images were analyzed by two skilled and blinded operators, and the maximum depth of the lesions was measured using a dedicated graphical user interface developed in Matlab R2016b (MathWorks Inc., Natick, MA), to obtain repetitive measurements. RESULTS: All melanomas appeared as band-like or oval/fusiform shaped hypoechoic inhomogeneous lesions. We observed an excellent agreement between the Breslow thickness of melanomas and the ultrasonographic thickness, as well as a reduced intra- and inter-operator variability in the ultrasonographic measurements of melanoma depth. CONCLUSIONS: We propose a ultrasonographic-histopathological protocol which may help clinicians to reduce the diagnostic delay, improve prognosis and survival rates, perform a surgical excision with negative margins, and reduce the variability in the assessment of Breslow thickness.

Carboxymethyl Cellulose-Based Hydrogel Film Combined with Umbilical Cord Blood Platelet gel as an Innovative Tool for Chronic Wound Management: A Pilot Clinical Study.

Treatment of chronic leg ulcers remains a major challenge and it is a substantial financial burden on individuals, families, caregivers, and health care system. There is increasing evidence on using of autologous Platelet-rich-plasma in wound repair but limited clinical data are available on the efficacy and safety of the use of umbilical cord blood platelet gel (CBPG). In our pilot study, for the first time, we aimed to evaluated the safety and efficacy of the use of umbilical CBPG combined with a hydrogel dressing in 10 patients with chronic venous ulcers (VU). The protocol consisted of application of umbilical cord blood platelet-rich plasma (PRP) combined with a Carboxymethyl cellulose (CMC)-based hydrogel dressing once a week for 4 weeks. The 80% of patients after 4 weeks of treatment had a significantly decrease in wound size. Moreover, we obtained an improvement in terms of mean Wound Bed Score (WBS), numeric rating scale (NRS) value and the EQ-5D index score. This pilot study showed that the topically therapeutic administration of umbilical CBPG associated with a CMC-based hydrogel dressing has the potential to accelerate the healing of chronic lesions without adverse reaction. However, additional studies with larger sample size and longer follow-up periods are required to confirm our findings.

Ventricular-Arterial Coupling Derived From Proximal Aortic Stiffness and Aerobic Capacity Across the Heart Failure Spectrum.

BACKGROUND: Ventricular-arterial coupling (VAC) can be evaluated as the ratio between arterial stiffness (pulsed wave velocity [PWV]) and myocardial deformation (global longitudinal strain [GLS]). OBJECTIVES: This study aimed to evaluate VAC across the spectrum of heart failure (HF). METHODS: The authors introduced a Doppler-derived, single-beat technique to estimate aortic arch PWV (aa-PWV) in addition to tonometry-derived carotid-femoral PWV (cf-PWV). They measured PWVs and GLS in 155 healthy controls, 75 subjects at risk of developing HF (American College of Cardiology/American Heart Association stage A-B) and 236 patients in stage C heart failure with preserved ejection fraction (HFpEF) (n = 104) or heart failure with reduced ejection fraction (HFrEF) (n = 132). They evaluated peak oxygen consumption and peripheral extraction using combined cardiopulmonary-echocardiography exercise stress. RESULTS: aa-PWV was obtainable in all subjects and significantly lower than cf-PWV in all subgroups (P < 0.01). PWVs were directly related and increased with age (all P < 0.0001). cf-PWV/GLS was similarly compromised in HFrEF (1.09 ± 0.35) and HFpEF (1.05 ± 0.21), whereas aa-PWV/GLS was more impaired in HFpEF (0.70 ± 0.10) than HFrEF (0.61 ± 0.14; P < 0.01). Stage A-B had values of cf-PWV/GLS and aa-PWV/GLS (0.67 ± 0.27 and 0.48 ± 0.14, respectively) higher than controls (0.46 ± 0.11 and 0.39 ± 0.10, respectively) but lower than stage C (all P < 0.01). Peak arteriovenous oxygen difference (AVO2diff) was inversely related with cf-PWV/GLS and aa-PWV/GLS (all P < 0.01). Although cf-PWV/GLS and aa-PWV/GLS independently predicted peak VO2 in the overall population (adjusted R2 = 0.33 and R2= 0.36; all P < 0.0001), only aa-PWV/GLS was independently associated with flow reserve during exercise (R2 = 0.52; P < 0.0001). CONCLUSIONS: Abnormal VAC is directly correlated with greater severity of HF and worse functional capacity. HFpEF shows a worse VAC than HFrEF when expressed by aa-PWV/GLS.

State of the Art in Lung Ultrasound, Shifting from Qualitative to Quantitative Analyses.

Lung ultrasound (LUS) has been increasingly expanding since the 1990s, when the clinical relevance of vertical artifacts was first reported. However, the massive spread of LUS is only recent and is associated with the coronavirus disease 2019 (COVID-19) pandemic, during which semi-quantitative computer-aided techniques were proposed to automatically classify LUS data. In this review, we discuss the state of the art in LUS, from semi-quantitative image analysis approaches to quantitative techniques involving the analysis of radiofrequency data. We also discuss recent in vitro and in silico studies, as well as research on LUS safety. Finally, conclusions are drawn highlighting the potential future of LUS.

Ultrasound Elastography in Inflammatory Bowel Diseases: A Systematic Review of Accuracy Compared with Histopathological Assessment.

BACKGROUND AND AIMS: Ultrasound elastography [USE] is an innovative, non-invasive, promptly available, ancillary technique that has been proposed in the evaluation of intestinal fibrosis as a monitorable biomarker, in terms of stiffness. The non-invasive estimate of fibrosis by USE appears appealing for dedicated physicians, in order to optimise the treatments for inflammatory bowel disease [IBD] patients [surgical vs non-surgical]. We aimed to systematically review literature evidence on ultrasound elastography in IBD patients. METHODS: For this qualitative systematic review, we searched PubMed, EMBASE, and Scopus to identify all studies, published until October 2021, investigating the application of USE in IBD patients compared with histopathological assessment. RESULTS: Overall, 12 papers published between 2011 and 2019 were included. A total of 275 IBD patients were included: 272 Crohn's disease [CD] [98.9%] and three ulcerative colitis [UC] [1.1%]. Seven [58.3%] and four [41.6%] studies investigated strain elastography [SE] and shear wave elastography [SWE], respectively; in one study [0.1%] both techniques were addressed. The histological evaluation was largely conducted on surgical specimens and in two studies endoscopic biopsies were also included. The histological assessment was semi-quantitative in all the included studies, except for two where the fibrosis was evaluated only qualitatively. In 10/12 publications USE could accurately distinguish inflammation from fibrosis in the examined bowel tracts. CONCLUSIONS: From the preliminary available data, an overall moderate-to-good accuracy of USE in detecting histological fibrosis [10/12 studies] was found. Point-shear wave elastography has been shown to perform superiorly. Further studies are needed to confirm these evidences.

A New SteatoScore in the Evaluation of Non-Alcoholic Liver Disease in Oncologic Patients.

Purpose: The aims of this study were to evaluate the reproducibility of a new multi-parametric steatoscore (new SteatoScore) in oncologic patients with non-alcoholic fatty liver disease (NAFLD) and to compare it with computed tomography (CT). Materials and Methods: Fifty-one (31 men, 20 women) oncologic patients, with a mean age and weight of 63.9 years and 78.33 kg, respectively, were retrospectively enrolled in the study. Patients underwent ultrasound (US) and computed tomography (CT) examinations as part of their oncologic follow-up protocol. US examinations were performed by using a 3.5-MHz convex probe. During the US examination, three standardized clips were obtained in each patient. Two operators performed all measurements, one of whom repeated the processing twice in 1 year. Hepatic/renal ratio (HR), attenuation rate (AR), diaphragm visualization (DV), hepatic/portal vein ratio (HPV), and portal vein wall visualization (PVW) were acquired and calculated by using Matlab and inserted in a multi-parametric algorithm called new SteatoScore. On unenhanced CT scan, hepatic attenuation (HA), liver-spleen difference (L-S), and liver/spleen ratio (L/S) were measured by placement of a region of interest (ROI) within liver and spleen parenchyma, avoiding areas with vessels and biliary ducts. Results: The intra-observer variability was greater than the inter-observer one, with intraclass correlation coefficient (ICC) values of 0.94 and 0.97, respectively. Correlation between single US and CT parameters provided an agreement in no case exceeding 50%. New SteatoScore showed high reproducibility, and high coefficient of correlation with L-S (R = -0.64; p < 0.0001) and L/S (R = -0.62; p < 0.0001) at CT. Conclusion: New SteatoScore has a high reproducibility and shows a good correlation with unenhanced CT in evaluation of oncologic patients with NAFLD.

A causal learning framework for the analysis and interpretation of COVID-19 clinical data.

We present a workflow for clinical data analysis that relies on Bayesian Structure Learning (BSL), an unsupervised learning approach, robust to noise and biases, that allows to incorporate prior medical knowledge into the learning process and that provides explainable results in the form of a graph showing the causal connections among the analyzed features. The workflow consists in a multi-step approach that goes from identifying the main causes of patient's outcome through BSL, to the realization of a tool suitable for clinical practice, based on a Binary Decision Tree (BDT), to recognize patients at high-risk with information available already at hospital admission time. We evaluate our approach on a feature-rich dataset of Coronavirus disease (COVID-19), showing that the proposed framework provides a schematic overview of the multi-factorial processes that jointly contribute to the outcome. We compare our findings with current literature on COVID-19, showing that this approach allows to re-discover established cause-effect relationships about the disease. Further, our approach yields to a highly interpretable tool correctly predicting the outcome of 85% of subjects based exclusively on 3 features: age, a previous history of chronic obstructive pulmonary disease and the PaO2/FiO2 ratio at the time of arrival to the hospital. The inclusion of additional information from 4 routine blood tests (Creatinine, Glucose, pO2 and Sodium) increases predictive accuracy to 94.5%.

P2X7 Receptor and Heart Function in a Mouse Model of Systemic Inflammation Due to High Fat Diet.

Purpose: Low-grade inflammation contributes to heart failure in obesity or type 2 diabetes mellitus. The P2X7 receptor (P2X7R) is a key regulator of several pro-inflammatory responses in multiple tissues and organs; however, its involvement in the onset of heart dysfunction remains unclear. The study evaluated the role of P2X7R as a cardiac function regulator in C57BL/6J wild-type (WT) and P2X7R knockout (KO) mice by inducing systemic inflammation with high fat diet (HFD). Methods: Specific parameters of systolic and diastolic function and heart morphology were measured in vivo before animal sacrifice by high-frequency ultrasonographic analysis. Gene and protein expression of cardiac biomarkers associated with inflammatory-oxidative pathways were evaluated by real-time PCR and Western Blotting. Results: P2X7R-mediated up-regulation of the NLRP3-caspase-1 complex, increased expression of key oxidative stress (NOS-2, TNFα), and chemotactic (MCP-1) mediators were revealed in WT-HFD animals. In KO-HFD mice, such inflammatory-oxidative pathway was silent. Nevertheless, HFD induced in vivo a clear alteration of diastolic pattern (E/A: p < 0.03 vs WT-HFD) and a cardiac morphologic remodelling (left ventricular mass: p < 0.05 vs WT-HFD) only in P2X7R KO animals. Surprisingly, the transcriptional and protein expression of IL-1ß and IL-6, usually regulated through P2X7R activation, were significantly higher in KO-HFD than in WT-HFD mice (both p < 0.05). Furthermore, an up-regulation of miR-214 and a down-regulation of miR-126 in heart of HFD-KO mice were observed, suggesting a link between such epigenetic dysregulation and cytokine overexpression as a potential pathophysiologic mechanism concurring to the progressive cardiac dysfunction. Conclusion: These findings seem to suggest a cardioprotective role of P2X7R toward this tissue-specific inflammatory damage, likely through tissue homeostasis and organ functionality preservation.

Carotid Ultrasound Boundary Study (CUBS): Technical considerations on an open multi-center analysis of computerized measurement systems for intima-media thickness measurement on common carotid artery longitudinal B-mode ultrasound scans.

After publishing an in-depth study that analyzed the ability of computerized methods to assist or replace human experts in obtaining carotid intima-media thickness (CIMT) measurements leading to correct therapeutic decisions, here the same consortium joined to present technical outlooks on computerized CIMT measurement systems and provide considerations for the community regarding the development and comparison of these methods, including considerations to encourage the standardization of computerized CIMT measurements and results presentation. A multi-center database of 500 images was collected, upon which three manual segmentations and seven computerized methods were employed to measure the CIMT, including traditional methods based on dynamic programming, deformable models, the first order absolute moment, anisotropic Gaussian derivative filters and deep learning-based image processing approaches based on U-Net convolutional neural networks. An inter- and intra-analyst variability analysis was conducted and segmentation results were analyzed by dividing the database based on carotid morphology, image signal-to-noise ratio, and research center. The computerized methods obtained CIMT absolute bias results that were comparable with studies in literature and they generally were similar and often better than the observed inter- and intra-analyst variability. Several computerized methods showed promising segmentation results, including one deep learning method (CIMT absolute bias = 106 ± 89 µm vs. 160 ± 140 µm intra-analyst variability) and three other traditional image processing methods (CIMT absolute bias = 139 ± 119 µm, 143 ± 118 µm and 139 ± 136 µm). The entire database used has been made publicly available for the community to facilitate future studies and to encourage an open comparison and technical analysis (https://doi.org/10.17632/m7ndn58sv6.1).

Effects of Different Scan Projections on the Quantitative Ultrasound-Based Evaluation of Hepatic Steatosis.

Non-alcoholic fatty liver disease (NAFLD) is becoming a global public health issue and the identification of the steatosis severity is very important for the patients' health. Ultrasound (US) images of 214 patients were acquired in two different scan views (subcostal and intercostal). A classification of the level of steatosis was made by a qualitative evaluation of the liver ultrasound images. Furthermore, an US image processing algorithm provided quantitative parameters (hepatic-renal ratio (HR) and Steato-score) designed to quantifying the fatty liver content. The aim of the study is to evaluate the differences in the assessment of hepatic steatosis acquiring and processing different US scan views. No significant differences were obtained calculating the HR and the Steato-score parameters, not even with the classification of patients on the basis of body mass index (BMI) and of different classes of steatosis severity. Significant differences between the two parameters were found only for patients with absence or mild level of steatosis. These results show that the two different scan projections do not greatly affect HR and the Steato-score assessment. Accordingly, the US-based steatosis assessment is independent from the view of the acquisitions, thus making the subcostal and intercostal scans interchangeable, especially for patients with moderate and severe steatosis.

Validation and Feasibility of an Automated System for the Assessment of Vascular Structure and Mechanical Properties in the Digital Arteries: An Ultrahigh-Frequency Ultrasound Study.

Ultrahigh-frequency ultrasound (UHFUS) allows sharp visualization of human small muscular arteries. This may help in elucidating some aspects of the pathophysiology of arterial aging, such as the stiffness gradient between large and small conduit arteries and its consequences on the microcirculation, as well as vascular diseases affecting medium-sized arteries. However, UHFUS use is still limited, partly because of the lack of validated tools to quantify vascular structure and mechanical properties of small muscular arteries. In this validation study, scans of digital arteries were obtained with UHFUS (VevoMD, Visualsonics-Fujifilm, Toronto, ON, Canada), analyzed using Carotid Studio software (Quipu, Pisa, Italy) and compared with the manual measurement. Agreement between the two techniques on measures of diameter, distension and intima-media thickness (IMT) was evaluated using Bland-Altman analyses; inter- and intra-operator reproducibility was evaluated using coefficients of variation (CVs). Overall, no trend or significant bias was observed between Carotid Studio and manual analysis. All limits of agreement were acceptable. The intra-observer CV of diastolic diameter and IMT were 4.1% and 4.2%, respectively. The inter-observer CV for diastolic diameter and IMT were 7.3% and 5.4%, respectively. Intra- and inter-observer CVs for distension were higher (25.7% and 26.7%, respectively). These results suggest that the Carotid Studio software is a valid and reproducible tool to study UHFUS scans of digital arteries, with potential utility both in rare vascular diseases of medium-sized arteries and in the study of the pathophysiology of arterial aging in general.

Ultra-high-frequency ultrasound and machine learning approaches for the differential diagnosis of melanocytic lesions.

Malignant melanoma (MM) is one of the most dangerous skin cancers. The aim of this study was to present a potential new method for the differential diagnosis of MM from melanocytic naevi (MN). We examined 20 MM and 19 MN with a new ultra-high-frequency ultrasound (UHFUS) equipped with a 70 MHz linear probe. Ultrasonographic images were processed for calculating 8 morphological parameters (area, perimeter, circularity, area ratio, standard deviation of normalized radial range, roughness index, overlap ratio and normalized residual mean square value) and 122 texture parameters. Colour Doppler images were used to evaluate the vascularization. Features reduction was implemented by means of principal component analysis (PCA), and 23 classification algorithms were tested on the reduced features using histological response as ground-truth. Best results were obtained using only the first component of the PCA and the weighted k-nearest neighbour classifier; this combination led to an accuracy of 76.9%, area under the ROC curve of 83%, sensitivity of 84% and specificity of 70%. The histological analysis still remains the gold-standard, but the UHFUS images processing using a machine learning approach could represent a new non-invasive approach.

Early outcome detection for COVID-19 patients.

With the outbreak of COVID-19 exerting a strong pressure on hospitals and health facilities, clinical decision support systems based on predictive models can help to effectively improve the management of the pandemic. We present a method for predicting mortality for COVID-19 patients. Starting from a large number of clinical variables, we select six of them with largest predictive power, using a feature selection method based on genetic algorithms and starting from a set of COVID-19 patients from the first wave. The algorithm is designed to reduce the impact of missing values in the set of variables measured, and consider only variables that show good accuracy on validation data. The final predictive model provides accuracy larger than 85% on test data, including a new patient cohort from the second COVID-19 wave, and on patients with imputed missing values. The selected clinical variables are confirmed to be relevant by recent literature on COVID-19.

Analysis of Lymph Node Volume by Ultra-High-Frequency Ultrasound Imaging in the Braf/Pten Genetically Engineered Mouse Model of Melanoma.

Tyr::CreER+,BrafCA/+,Ptenlox/lox genetically engineered mice (Braf/Pten mice) are widely used as an in vivo model of metastatic melanoma. Once a primary tumor has been induced by tamoxifen treatment, an increase in metastatic burden is observed within 4-6 weeks after induction. This paper shows how Ultra-High-Frequency UltraSound (UHFUS) imaging can be exploited to monitor the increase in metastatic involvement of the inguinal lymph nodes by measuring the increase in their volume. The UHFUS system is used to scan anesthetized mice with a UHFUS linear probe (22-55 MHz, axial resolution 40 µm). B-mode images from the inguinal lymph nodes (both left and right sides) are acquired in a short-axis view, positioning the animals in dorsal recumbency. Ultrasound records are acquired using a 44 µm step size on a motorized mechanical arm. Afterward, two-dimensional (2D) B-mode acquisitions are imported into the software platform for ultrasound image post-processing, and inguinal lymph nodes are identified and segmented semi-automatically in the acquired cross-sectional 2D images. Finally, a total reconstruction of the three-dimensional (3D) volume is automatically obtained along with the rendering of the lymph node volume, which is also expressed as an absolute measurement. This non-invasive in vivo technique is very well tolerated and allows the scheduling of multiple imaging sessions on the same experimental animal over 2 weeks. It is, therefore, ideal to assess the impact of pharmacological treatment on metastatic disease.