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BACKGROUND: In clinical assessment of Pectus Excavatum (PE), the indication to surgery is based not only on symptoms but also on quantitative markers calculated from Computed Tomography (CT) or Magnetic Resonance Imaging (MRI) scans. According to clinical routine, these indexes are measured manually by radiologists with limited computer support. This process is time consuming and potentially subjected to inaccuracy and individual variability in measurements. Moreover, the existing indexes have limitations, since they are based on linear measurements performed on single slices rather than on volumetric data derived from all the thoracic scans. RESULTS: In this paper we present an image processing pipeline aimed at providing radiologists with a computer-aid tool in support of diagnosis of PE patients developed in MATLAB® and conceived for MRI images. This framework has a dual purpose: (i) to automatize computation of clinical indexes with a view to ease and standardize pre-operative evaluation; (ii) to propose a new marker of pathological severity based on volumetric analysis and overcoming the limitations of existing axial slice-based indexes. Final designed framework is semi-automatic, requiring some user interventions at crucial steps: this is realized through a Graphical User Interface (GUI) that simplifies the interaction between the user and the tools. We tested our pipeline on 50 pediatric patients from Gaslini Children's Hospital and performed manual computation of indexes, comparing the results between the proposed tool and gold-standard clinical practice. Automatic indexes provided by our algorithm have shown good agreement with manual measurements by two independent readers. Moreover, the new proposed Volumetric Correction Index (VCI) has exhibited good correlation with standardized markers of pathological severity, proving to be a potential innovative tool for diagnosis, treatment, and follow-up. CONCLUSIONS: Our pipeline represents an innovative image processing in PE evaluation, based on MRI images (radiation-free) and providing the clinician with a quick and accurate tool for automatically calculating the classical PE severity indexes and a new more comprehensive marker: the Volumetric Correction Index.

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BACKGROUND: Diabetes is a common disease in heart failure and its prevalence ranges from 10 to 30%. ST-2 is a novel biomarker of myocardial fibrosis and remodelling in heart failure and may be involved in the inflammatory process of diabetes mellitus. In this study, we sought: to evaluate levels of ST-2 and B-type natriuretic peptide (BNP) in groups with acute heart failure with and without diabetes; to analyse the prognostic impact of ST-2 over a 6-month follow-up period. METHODS: We performed an echocardiographic examination and measured ST-2 and BNP within 24 h of hospital admission. Patients were classified as heart failure with reduced ejection fraction {HFrEF [left ventricular ejection fraction (LVEF) <50%]} or heart failure with preserved ejection fraction (HFpEF, LVEF ≥50%). We defined diastolic function according to recent guidelines, and we calculated left ventricular stiffness was assessed by the ratio between E/e' (index of left ventricular filling pressure) and left ventricular diastolic diameter (LVEDD) (index of left ventricular volume). The sum of death and rehospitalization due to cardiovascular causes was considered in the composite outcome. RESULTS: Of 121 patients enrolled, 58 experienced diabetes and 63 had normal glucose levels. Sixty patients showed HFrEF and 61 HFpEF. Among patients with diabetes, we observed significantly increased levels of serum ST-2 with respect to patients without diabetes [89 (29-147) 72 ±â€Š42 vs. 48 (29-80) 59 ±â€Š33 ng/ml; P = 0.04]. No differences were found between the two groups in terms of BNP levels, risk factors, renal function and echocardiographic measurements. Conversely, BNP was significantly higher in HFrEF with respect to HFpEF [786 (344-1390) vs. 423 (195-796) pg/ml; P = 0.004]. A significant correlation between ST-2 and BNP in diabetic patients (r = 0.50; P < 0.001) compared with nondiabetic patients (r = 0.40; P = 0.001) was found. ST-2 showed a numerically greater correlation with left ventricular stiffness in patients with diabetes (r = 0.56; P < 0.001) than patients without (r = 0.29; P = 0.04). Moreover, in all patients, ST-2 demonstrated a significant correlation with glycated glycosylated haemoglobin HbA1c (r = 0.40; P < 0.001). Univariate analysis demonstrated that both ST-2 more than 54 ng/ml and BNP more than 567 pg/ml were related to adverse events occurrence within 6 months [hazard ratio (HR): 3.64 (1.90-6.94), P < 0.001; HR: 2.21 (1.20-4.07), P = 0.01, respectively]. After adjustment for potential confounding factors, the multivariable analysis showed that only ST-2 levels greater than 54 ng/ml were associated with poor prognosis [HR: 3.56 (1.66-7.62); P = 0.001]. CONCLUSION: ST-2 confirmed its prognostic power independently of diabetes and LVEF. Patients with diabetes showed higher levels of ST-2. However, the mechanism related to ST-2 increase needs to be better understood, although increased left ventricle stiffness and filling pressure seem to be the most important causative factors. CLINICAL TRIAL REGISTRATION: www.clinicaltrial.gov Diur-HF Trial (Trial ID: NCT01441245).

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BACKGROUND: Cardiorenal syndrome (CRS) is associated with increased cardiovascular morbidity and mortality; still, its biomarker pattern has been poorly evaluated so far. The aim of this study was to measure the inflammatory activation, neurohormonal status and kidney and myocardial damage in patients with CRS compared to patients with heart failure (HF) without renal impairment (RI). METHODS: We analyzed 246 patients on the basis of renal function (group 1: 120 HF patients without RI; group 2: 126 CRS patients). In each group, interleukin-6, tumor necrosis factor-α, B-type natriuretic peptide (BNP), neutrophil gelatinase-associated lipocalin (NGAL), troponin T (TnT), osteoprotegerin and blood urea nitrogen (BUN) were measured. The diagnostic power of all laboratory parameters to detect CRS was evaluated by the receiver operating characteristic (ROC) curve and logistic regression analysis. RESULTS: A significant increase in BNP [626.4 pg/ml, confidence interval (CI) 518-749 vs. 487.8 pg/ml, CI 411-578; p < 0.05], NGAL (156 ng/ml, CI 129-186 vs. 89.1 ng/ml, CI 72-109; p < 0.0001), BUN (108.9 mg/dl, CI 98-120 vs. 51 mg/dl, CI 46-55; p < 0,0001) and TnT (0.62 ng/ml, CI 0.51-0.75 vs. 0.21 ng/ml, CI 0.15-0.28; p < 0.001) was seen in CRS patients compared to HF patients without RI. ROC curve analysis showed that only NGAL, BUN, BUN/creatinine ratio and TnT can discriminate patients with CRS from patients without RI. CONCLUSIONS: In CRS patients, renal tubular damage and neurohormonal and cardiac injury activation are increased compared to patients without RI. The current biomarker pattern could be used for an early diagnosis of RI in acute and chronic HF.