Risk score model to automatically detect prostate cancer patients by integrating diagnostic parameters.

Introduction: Prostate cancer (PCa) is one of the prevailing forms of cancer among men. At present, multiparametric MRI is the imaging method for localizing tumors and staging cancer. Radiomics plays a key role and hold potential for PCa detection, reducing the need for unnecessary biopsies, characterizing tumor aggression, and overseeing PCa recurrence post-treatment. Methods: Furthermore, the integration of radiomics data with clinical and histopathological data can further enhance the understanding and management of PCa and decrease unnecessary transfers to specialized care for expensive and intrusive biopsies. Therefore, the aim of this study is to develop a risk model score to automatically detect PCa patients by integrating non-invasive diagnostic parameters (radiomics and Prostate-Specific Antigen levels) along with patient's age. Results: The proposed approach was evaluated using a dataset of 189 PCa patients who underwent bi-parametric MRI from two centers. Elastic-Net Regularized Generalized Linear Model achieved 91% AUC to automatically detect PCa patients. The model risk score was also used to assess doubt cases of PCa at biopsy and then compared to bi-parametric PI-RADS v2. Discussion: This study explored the relative utility of a well-developed risk model by combining radiomics, Prostate-Specific Antigen levels and age for objective and accurate PCa risk stratification and supporting the process of making clinical decisions during follow up.

Are the variations in ECG morphology associated to different blood glucose levels? implications for non-invasive glucose monitoring for T1D paediatric patients.

AIMS: Recent clinical trials and real-world studies highlighted those variations in ECG waveforms and HRV recurrently occurred during hypoglycemic and hyperglycemic events in patients with diabetes. However, while several studies have been carried out for adult age, there is lack of evidence for paediatric patients. The main aim of the study is to identify the correlations of variations in ECG Morphology waveforms with blood glucose levels in a paediatric population. METHODS: T1D paediatric patients who use CGM were enrolled. They wear an additional non-invasive wearable device for recording physiological data and respiratory rate. Glucose metrics, ECG parameters and HRV features were collected, and Wilcoxon rank-sum test and Spearman's correlation analysis were used to explore if different levels of blood glucose were associated to ECG morphological changes. RESULTS: Results showed that hypoglycaemic events in paediatric patients with T1D are strongly associated with variations in ECG morphology and HRV. CONCLUSIONS: Results showed the opportunity of using the ECG as a non-invasive adding instrument to monitor the hypoglycaemic events through the integration of the ECG continuous information with CGM data. This innovative approach represents a promising step forward in diabetes management, offering a more comprehensive and effective means of detecting and responding to critical changes in glucose levels.

Health-related quality of life in patients with aortic dissection: An unmet need.

Knowledge about the Health-related Quality of Life (HR-QoL) after Type A (TA-AAD) and Type B acute aortic dissection (TB-AAD) is still insufficient. Through this systematic review, including 22 studies (16 for TA-AAD and 6 TB-AAD -1998-2023), the entire literature on HR-QoL after surgical and/or endovascular and/or medical interventions has been investigated. In TA-AAD patients, despite overall SF-36 score was similar to the standard population, with > 80 years patients displaying a better emotional domain, the SF-12 was significant lower to controls in physical and mental well-being domains. Exercise-based cardiac rehabilitation improved HR-QoL. In TB-AAD, vitality and mental health SF-36 scores improved after thoracic endovascular aortic repair (TEVAR); long-term QoL was similar in the open surgery group compared to TEVAR. Overall, HR-QoL after AAD seems adequate irrespective of age or sex, except for some specific domains. Physical exercise and cardiac rehabilitation may improve HR-QoL in these patients. PROSPERO registry ID: CRD42023421130.

Exercise Stress Echocardiography of the Right Ventricle and Pulmonary Circulation.

BACKGROUND: Exercise echocardiography is used for assessment of pulmonary circulation and right ventricular function, but limits of normal and disease-specific changes remain insufficiently established. OBJECTIVES: The objective of this study was to explore the physiological vs pathologic response of the right ventricle and pulmonary circulation to exercise. METHODS: A total of 2,228 subjects were enrolled: 375 healthy controls, 40 athletes, 516 patients with cardiovascular risk factors, 17 with pulmonary arterial hypertension, 872 with connective tissue diseases without overt pulmonary hypertension, 113 with left-sided heart disease, 30 with lung disease, and 265 with chronic exposure to high altitude. All subjects underwent resting and exercise echocardiography on a semirecumbent cycle ergometer. All-cause mortality was recorded at follow-up. RESULTS: The 5th and 95th percentile of the mean pulmonary artery pressure-cardiac output relationships were 0.2 to 3.5 mm Hg.min/L in healthy subjects without cardiovascular risk factors, and were increased in all patient categories and in high altitude residents. The 5th and 95th percentile of the tricuspid annular plane systolic excursion to systolic pulmonary artery pressure ratio at rest were 0.7 to 2.0 mm/mm Hg at rest and 0.5 to 1.5 mm/mm Hg at peak exercise, and were decreased at rest and exercise in all disease categories and in high-altitude residents. An increased all-cause mortality was predicted by a resting tricuspid annular plane systolic excursion to systolic pulmonary artery pressure <0.7 mm/mm Hg and mean pulmonary artery pressure-cardiac output >5 mm Hg.min/L. CONCLUSIONS: Exercise echocardiography of the pulmonary circulation and the right ventricle discloses prognostically relevant differences between healthy subjects, athletes, high-altitude residents, and patients with various cardio-respiratory conditions. (Right Heart International NETwork During Exercise in Different Clinical Conditions; NCT03041337).

Cardiovascular Side Effects of Anthracyclines and HER2 Inhibitors among Patients with Breast Cancer: A Multidisciplinary Stepwise Approach for Prevention, Early Detection, and Treatment.

Cardiovascular (CV) diseases (CVD) are a major cause of long-term morbidity and mortality affecting life expectancy amongst cancer survivors. In recent years, because of the possibility of early diagnosis and the increased efficacy of neo-adjuvant and adjuvant systemic treatments (targeting specific molecular pathways), the high percentage of survival from breast cancer led CVD to become the first cause of death among survivors. Therefore, it is mandatory to adopt cardioprotective strategies to minimize CV side effects and CVD in general in breast cancer patients. Cancer therapeutics-related cardiac dysfunction (CTRCD) is a common group of side effects of chemotherapeutics widely employed in breast cancer (e.g., anthracycline and human epidermal growth factor receptor 2 inhibitors). The aim of the present manuscript is to propose a pragmatic multidisciplinary stepwise approach for prevention, early detection, and treatment of cardiotoxicity in patients with breast cancer.

Exploring the Cardiotoxicity Spectrum of Anti-Cancer Treatments: Definition, Classification, and Diagnostic Pathways.

Early detection and treatment of cancer have led to a noticeable reduction in both mortality and morbidity. However, chemotherapy and radiotherapy could exert cardiovascular (CV) side effects, impacting survival and quality of life, independent of the oncologic prognosis. In this regard, a high clinical index of suspicion is required by the multidisciplinary care team in order to trigger specific laboratory tests (namely natriuretic peptides and high-sensitivity cardiac troponin) and appropriate imaging techniques (transthoracic echocardiography along with cardiac magnetic resonance, cardiac computed tomography, and nuclear testing (if clinically indicated)), leading to timely diagnosis. In the near future, we do expect a more tailored approach to patient care within the respective community along with the widespread implementation of digital health tools.

Acute Heart Failure: Diagnostic-Therapeutic Pathways and Preventive Strategies-A Real-World Clinician's Guide.

Acute heart failure (AHF) is the most frequent cause of unplanned hospital admission in patients of >65 years of age and it is associated with significantly increased morbidity, mortality, and healthcare costs. Different AHF classification criteria have been proposed, mainly reflecting the clinical heterogeneity of the syndrome. Regardless of the underlying mechanism, peripheral and/or pulmonary congestion is present in the vast majority of cases. Furthermore, a marked reduction in cardiac output with peripheral hypoperfusion may occur in most severe cases. Diagnosis is made on the basis of signs and symptoms, laboratory, and non-invasive tests. After exclusion of reversible causes, AHF therapeutic interventions mainly consist of intravenous (IV) diuretics and/or vasodilators, tailored according to the initial hemodynamic status with the addition of inotropes/vasopressors and mechanical circulatory support if needed. The aim of this review is to discuss current concepts on the diagnosis and management of AHF in order to guide daily clinical practice and to underline the unmet needs. Preventive strategies are also discussed.

Sex differences in type A acute aortic dissection: a systematic review and meta-analysis.

BACKGROUND: In acute aortic dissection (AAD) sex heterogeneity reports are not exhaustive and in part even conflicting. AIMS: To explore sex differences in clinical features, management, and outcomes among patients with type A AAD. METHODS AND RESULTS: A systematic review and meta-analysis of the literature were conducted for studies (2004-2022) reporting type A AAD sex differences. Among the 1938 studies retrieved, 16 (16 069 patients, 7142 women, and 8927 men) fulfilled all eligibility criteria. Data were aggregated used the random-effects model as pooled risk ratio and mean difference. Due to information reported by considered manuscripts, analysis were performed only among surgically treated type A AAD patients. At the time of hospital presentation type A AAD women were older than men but had lower body mass index (BMI), body surface area (BSA), and creatinine plasma levels. Active smoking, bicuspid aortic valve, and previous cardiac surgery were less common in women while diabetes mellitus was more frequent. Furthermore, women experienced more frequently pericardial effusion/cardiac tamponade than men. Interestingly, in-hospital surgical mortality did not differ between sexes [risk ratio (RR), 1.02; 95% confidence interval (CI), 0.53-1.99; P = 0.95], whereas 5 (RR 0.94; 95% CI: 0.92-0.97; P < 0.001) and 10-year survival (RR 0.82; 95% CI: 0.74-0.92; P = 0.004) was higher among men. A descriptive analysis of in-hospital outcomes among medically treated type A AAD patients confirmed prohibitive high mortality for both sexes (men 58.6% vs. women 53.8%, P = 0.59). CONCLUSIONS: A female sex phenotype appears to be evident in type A AAD implying the need for a personalized management patient approach along with tailored preventive strategies. PROSPERO REGISTRY ID: CRD42022359072.

Reports regarding sex heterogenicity in acute aortic dissection (AAD) are not exhaustive and in part even conflicting. Sex differences in clinical features, management, and outcomes were investigated among patients with type A AAD through a systematic review and meta-analysis of literature. A female sex phenotype appears to be evident in type A AAD implying the need for a personalized management patient approach along with tailored preventive strategies. Interestingly, while in-hospital surgical mortality did not differ between sexes, 5- and 10-year survival was higher among men. In the near future, definitive sex-specific data from international clinical registries and trials are expected.

Influence of Delamination Size and Depth on the Compression Fatigue Behaviour of a Stiffened Aerospace Composite Panel.

Delamination in reinforced panels is one of the primary challenges facing the safety and reliability of aerospace structures. This article presents a sensitivity analysis of the fatigue behaviour during the compression of a composite aeronautical stiffened panel experiencing delamination. The main objective is to assess the impact of delamination size and depth on the lifecycle and structural integrity of the panel. Different dimensions and positions of delamination are considered to cover a comprehensive range of damage scenarios. The key feature of this sensitivity analysis is the adoption of a numerical procedure that is mesh- and load-step-independent, ensuring reliable results and providing valuable insight into the criticality of delamination and its impact on the fatigue behaviour during the compression of reinforced aeronautical panels. Sensitivity analyses are essential for enhancing the design process of aerospace structures, thereby contributing to the increased safety and reliability of structural components. In this regard, the use of robust and effective numerical procedures is of crucial significance. This may be seen as the real added value of this paper.

Physiologic Range of Myocardial Mechano-Energetic Efficiency among Healthy Subjects: Impact of Gender and Age.

BACKGROUND: Myocardial mechano-energetic efficiency (MEE) is the capability of the left ventricle (LV) to convert the chemical energy obtained from the cardiac oxidative metabolism into mechanical work. The aim of present study was to establish normal non-invasive MEE and MEEi reference values. METHODS: In total, 1168 healthy subjects underwent physical examinations, clinical assessment, and standardized transthoracic echocardiographic (TTE) examination. MEE was obtained by TTE as the ratio between stroke volume (SV) and heart rate (HR): MEE = SV/HR [HR expressed in seconds (HR/60)]. Because MEE is highly related to left ventricular mass (LVM), MEE was then divided by LVM with the purpose of obtaining an estimate of energetic expenditure per unit of myocardial mass (i.e., indexed MEE, MEEi, mL/s/g). RESULTS: The mean values of MEE and MEEi in the overall population were 61.09 ± 18.19 mL/s; 0.45 ± 0.14, respectively. In a multivariable analysis, gender, body surface area (BSA), diastolic blood pressure, left atrial volume indexed to BSA, E/e' and tricuspid annular plane systolic excursion (TAPSE) were the independent variables associated with MEE, while age, gender, BSA and TAPSE were the independent variables associated with MEEi. CONCLUSIONS: The knowledge of age- and gender-based MEE and MEEi normal values may improve the global assessment of LV cardiac mechanics and serve as a reference to identify phenotypes at high risk of cardiovascular events.

A Complex Radiomic Signature in Luminal Breast Cancer from a Weighted Statistical Framework: A Pilot Study.

Radiomics is rapidly advancing in precision diagnostics and cancer treatment. However, there are several challenges that need to be addressed before translation to clinical use. This study presents an ad-hoc weighted statistical framework to explore radiomic biomarkers for a better characterization of the radiogenomic phenotypes in breast cancer. Thirty-six female patients with breast cancer were enrolled in this study. Radiomic features were extracted from MRI and PET imaging techniques for malignant and healthy lesions in each patient. To reduce within-subject bias, the ratio of radiomic features extracted from both lesions was calculated for each patient. Radiomic features were further normalized, comparing the z-score, quantile, and whitening normalization methods to reduce between-subjects bias. After feature reduction by Spearman's correlation, a methodological approach based on a principal component analysis (PCA) was applied. The results were compared and validated on twenty-seven patients to investigate the tumor grade, Ki-67 index, and molecular cancer subtypes using classification methods (LogitBoost, random forest, and linear discriminant analysis). The classification techniques achieved high area-under-the-curve values with one PC that was calculated by normalizing the radiomic features via the quantile method. This pilot study helped us to establish a robust framework of analysis to generate a combined radiomic signature, which may lead to more precise breast cancer prognosis.

On the Effects of Core Microstructure on Energy Absorbing Capabilities of Sandwich Panels Intended for Additive Manufacturing.

Increasing transportation safety can be observed as one of the biggest engineering challenges. This challenge often needs to be combined with the need to deliver engineering solutions that are able to lower the environmental impact of transportation, by reducing fuel consumption. Consequentially, these topics have attracted considerable research efforts. The present work aims to address the previously cited challenges by maximizing the energy absorption capabilities of hybrid aluminum/composite shock absorbers with minimal thickness and mass. This engineering solution makes it possible to lighten vehicles and reduce fuel consumption, without compromising safety, in terms of crashworthiness capabilities. A numerical sensitivity study is presented, where the absorbed energy/mass (AE/m) and the absorbed energy/total panel thickness (AE/Htot) ratios, as a consequence of low-velocity impact simulations performed on six different shock absorbers, are compared. These hybrid shock absorbers have been numerically designed by modifying the core thickness of two basic absorbers' configurations, characterized, respectively, by a metallic lattice core, intended to be produced through additive manufacturing, and a standard metallic honeycomb core. This work provides interesting information for the development of shock absorbers, which should be further developed with an experimental approach. Indeed, it demonstrates that, by integrating composite skins with a very light core producible, by means of additive manufacturing capabilities, it is possible to design shock absorbers with excellent performance, even for very thin configurations with 6 mm thickness, and to provide a significant increase in AE/m ratios when compared to the respective equal volume standard honeycomb core configurations. This difference between the AE/m ratios of configurations with different core designs increases with the growth in volume. In detail, for configurations with a total thickness of 6 mm, the AE/m increases in additive manufacturing configurations by approximately 93%; for those with a total thickness of 10 mm, the increase is 175%, and, finally, for those with a total thickness of 14 mm, the increase is 220%.

DNA Methylation Profile of the SREBF2 Gene in Human Fetal Aortas.

Increasing evidence suggests that maternal cholesterol represents an important risk factor for atherosclerotic disease in offspring already during pregnancy, although the underlying mechanisms have not yet been elucidated. Eighteen human fetal aorta samples were collected from the spontaneously aborted fetuses of normal cholesterolemic and hypercholesterolemic mothers. Maternal total cholesterol levels were assessed during hospitalization. DNA methylation profiling of the whole SREBF2 gene CpG island was performed (p value <0.05). The Mann-Whitney U test was used for comparison between the 2 groups. For the first time, our study revealed that in fetal aortas obtained from hypercholesterolemic mothers, the SREBF2 gene shows 4 significant differentially hypermethylated sites in the 5'UTR-CpG island. This finding indicates that more effective long-term primary cardiovascular prevention programs need to be designed for the offspring of mothers with hypercholesterolemia. Further studies should be conducted to clarify the epigenetic mechanisms underlying the association between early atherogenesis and maternal hypercholesterolemia during pregnancy.

A Framework of Analysis to Facilitate the Harmonization of Multicenter Radiomic Features in Prostate Cancer.

Pooling radiomic features coming from different centers in a statistical framework is challenging due to the variability in scanner models, acquisition protocols, and reconstruction settings. To remove technical variability, commonly called batch effects, different statistical harmonization strategies have been widely used in genomics but less considered in radiomics. The aim of this work was to develop a framework of analysis to facilitate the harmonization of multicenter radiomic features extracted from prostate T2-weighted magnetic resonance imaging (MRI) and to improve the power of radiomics for prostate cancer (PCa) management in order to develop robust non-invasive biomarkers translating into clinical practice. To remove technical variability and correct for batch effects, we investigated four different statistical methods (ComBat, SVA, Arsynseq, and mixed effect). The proposed approaches were evaluated using a dataset of 210 prostate cancer (PCa) patients from two centers. The impacts of the different statistical approaches were evaluated by principal component analysis and classification methods (LogitBoost, random forest, K-nearest neighbors, and decision tree). The ComBat method outperformed all other methods by achieving 70% accuracy and 78% AUC with the random forest method to automatically classify patients affected by PCa. The proposed statistical framework enabled us to define and develop a standardized pipeline of analysis to harmonize multicenter T2W radiomic features, yielding great promise to support PCa clinical practice.

Impact of Breast Tumor Onset on Blood Count, Carcinoembryonic Antigen, Cancer Antigen 15-3 and Lymphoid Subpopulations Supported by Automatic Classification Approach: A Pilot Study.

BACKGROUND: Recent observations showed that systemic immune changes are detectable in case of breast cancer (BC). In this preliminary study, we investigated routinely measured peripheral blood (PB) parameters for malignant BC cases in comparison to benign breast conditions. Complete blood count, circulating lymphoid subpopulation, and serological carcinoembryonic antigen (CEA) and cancer antigen 15-3 (CA15-3) levels were considered. METHODS: A total of 127 female patients affected by malignant (n = 77, mean age = 63 years, min = 36, max = 90) BC at diagnosis (naïve patients) or benign breast conditions (n = 50, mean age = 33 years, min = 18, max = 60) were included in this study. For each patient, complete blood count and lymphoid subpopulations (T-helper, T-cytotoxic, B-, NK-, and NKT-cells) analysis on PB samples were performed. Hormonal receptor status, Ki-67 expression, and serological CEA and CA15-3 levels were assessed in the case of patients with malignant BC via statistical analysis. RESULTS: Women with malignant BC disclosed increased circulating T-helper lymphocytes and CD4/CD8 ratio in PB when compared to those affected by benign breast conditions (2.345 vs 1.894, P < .05 Wilcoxon rank-sum test). In the case of malignant BC patients, additive logistic regression method was able to identify malignant BC cases with increased CA15-3 levels (CA15-3 >25 UI/mL) via the hematocrit and neutrophils/lymphocytes ratio values. Moreover, in the case of women with aggressive malignant BC featured by high levels of Ki-67 proliferation marker, an increasing number of correlations were found among blood count parameters and lymphocytes subpopulations by performing a Spearman's correlation analysis. CONCLUSIONS: This preliminary study confirms the ability of malignant BC to determine systemic modifications. The stratification of malignant BC cases according to the Ki-67 proliferation marker highlighted increasing detectable alterations in the periphery of women with aggressive BC. The advent of novel and more sensitive biomarkers, as well as deep immunophenotyping technologies, will provide additional insights for describing the relationship between tumor onset and peripheral alterations.

A framework for designing medical devices resilient to low-resource settings.

BACKGROUND: To date (April 2021), medical device (MD) design approaches have failed to consider the contexts where MDs can be operationalised. Although most of the global population lives and is treated in Low- and Middle-Income Countries (LMCIs), over 80% of the MD market share is in high-resource settings, which set de facto standards that cannot be taken for granted in lower resource settings. Using a MD designed for high-resource settings in LMICs may hinder its safe and efficient operationalisation. In the literature, many criteria for frameworks to support resilient MD design were presented. However, since the available criteria (as of 2021) are far from being consensual and comprehensive, the aim of this study is to raise awareness about such challenges and to scope experts' consensus regarding the essentiality of MD design criteria. RESULTS: This paper presents a novel application of Delphi study and Multiple Criteria Decision Analysis (MCDA) to develop a framework comprising 26 essential criteria, which were evaluated and chosen by international experts coming from different parts of the world. This framework was validated by analysing some MDs presented in the WHO Compendium of innovative health technologies for low-resource settings. CONCLUSIONS: This novel holistic framework takes into account some domains that are usually underestimated by MDs designers. For this reason, it can be used by experts designing MDs resilient to low-resource settings and it can also assist policymakers and non-governmental organisations in shaping the future of global healthcare.

Radiomic and Genomic Machine Learning Method Performance for Prostate Cancer Diagnosis: Systematic Literature Review.

BACKGROUND: Machine learning algorithms have been drawing attention at the joining of pathology and radiology in prostate cancer research. However, due to their algorithmic learning complexity and the variability of their architecture, there is an ongoing need to analyze their performance. OBJECTIVE: This study assesses the source of heterogeneity and the performance of machine learning applied to radiomic, genomic, and clinical biomarkers for the diagnosis of prostate cancer. One research focus of this study was on clearly identifying problems and issues related to the implementation of machine learning in clinical studies. METHODS: Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) protocol, 816 titles were identified from the PubMed, Scopus, and OvidSP databases. Studies that used machine learning to detect prostate cancer and provided performance measures were included in our analysis. The quality of the eligible studies was assessed using the QUADAS-2 (quality assessment of diagnostic accuracy studies-version 2) tool. The hierarchical multivariate model was applied to the pooled data in a meta-analysis. To investigate the heterogeneity among studies, I2 statistics were performed along with visual evaluation of coupled forest plots. Due to the internal heterogeneity among machine learning algorithms, subgroup analysis was carried out to investigate the diagnostic capability of machine learning systems in clinical practice. RESULTS: In the final analysis, 37 studies were included, of which 29 entered the meta-analysis pooling. The analysis of machine learning methods to detect prostate cancer reveals the limited usage of the methods and the lack of standards that hinder the implementation of machine learning in clinical applications. CONCLUSIONS: The performance of machine learning for diagnosis of prostate cancer was considered satisfactory for several studies investigating the multiparametric magnetic resonance imaging and urine biomarkers; however, given the limitations indicated in our study, further studies are warranted to extend the potential use of machine learning to clinical settings. Recommendations on the use of machine learning techniques were also provided to help researchers to design robust studies to facilitate evidence generation from the use of radiomic and genomic biomarkers.

MuSA: a graphical user interface for multi-OMICs data integration in radiogenomic studies.

Analysis of large-scale omics data along with biomedical images has gaining a huge interest in predicting phenotypic conditions towards personalized medicine. Multiple layers of investigations such as genomics, transcriptomics and proteomics, have led to high dimensionality and heterogeneity of data. Multi-omics data integration can provide meaningful contribution to early diagnosis and an accurate estimate of prognosis and treatment in cancer. Some multi-layer data structures have been developed to integrate multi-omics biological information, but none of these has been developed and evaluated to include radiomic data. We proposed to use MultiAssayExperiment (MAE) as an integrated data structure to combine multi-omics data facilitating the exploration of heterogeneous data. We improved the usability of the MAE, developing a Multi-omics Statistical Approaches (MuSA) tool that uses a Shiny graphical user interface, able to simplify the management and the analysis of radiogenomic datasets. The capabilities of MuSA were shown using public breast cancer datasets from TCGA-TCIA databases. MuSA architecture is modular and can be divided in Pre-processing and Downstream analysis. The pre-processing section allows data filtering and normalization. The downstream analysis section contains modules for data science such as correlation, clustering (i.e., heatmap) and feature selection methods. The results are dynamically shown in MuSA. MuSA tool provides an easy-to-use way to create, manage and analyze radiogenomic data. The application is specifically designed to guide no-programmer researchers through different computational steps. Integration analysis is implemented in a modular structure, making MuSA an easily expansible open-source software.

Integrated analysis of DNA methylation profile of HLA-G gene and imaging in coronary heart disease: Pilot study.

AIMS: Immune endothelial inflammation, underlying coronary heart disease (CHD) related phenotypes, could provide new insight into the pathobiology of the disease. We investigated DNA methylation level of the unique CpG island of HLA-G gene in CHD patients and evaluated the correlation with cardiac computed tomography angiography (CCTA) features. METHODS: Thirty-two patients that underwent CCTA for suspected CHD were enrolled for this study. Obstructive CHD group included fourteen patients, in which there was a stenosis greater than or equal to 50% in one or more of the major coronary arteries detected; whereas subjects with Calcium (Ca) Score = 0, uninjured coronaries and with no obstructive CHD (no critical stenosis, NCS) were considered as control subjects (n = 18). For both groups, DNA methylation profile of the whole 5'UTR-CpG island of HLA-G was measured. The plasma soluble HLA-G (sHLA-G) levels were detected in all subjects by specific ELISA assay. Statistical analysis was performed using R software. RESULTS: For the first time, our study reported that 1) a significant hypomethylation characterized three specific fragments (B, C and F) of the 5'UTR-CpG island (p = 0.05) of HLA-G gene in CHD patients compared to control group; 2) the hypomethylation level of one specific fragment of 161bp (+616/+777) positively correlated with coronary Ca score, a relevant parameter of CCTA (p<0.05) between two groups evaluated and was predictive for disease severity. CONCLUSIONS: Reduced levels of circulating HLA-G molecules could derive from epigenetic marks. Epigenetics phenomena induce hypomethylation of specific regions into 5'UTR-CpG island of HLA-G gene in CHD patients with obstructive non critical stenosis vs coronary stenosis individuals.