Pulmonary hypertension is a common cause of death among patients with sickle cell disease. This study investigates the use of pulmonary vein analysis to assist the diagnosis of pulmonary hypertension non-invasively with CT-Angiography images. The characterization of the pulmonary veins from CT presents two main challenges. Firstly, the number of pulmonary veins is unknown a priori and secondly, the contrast material is degraded when reaching the pulmonary veins, making the edges of these vessels to appear faint. Each image is first denoised and a fast marching approach is used to segment the left atrium and pulmonary veins. Afterward, a geodesic active contour is employed to isolate the left atrium. A thinning technique is then used to extract the skeleton of the atrium and the veins. The locations of the pulmonary veins ostia are determined by the intersection of the skeleton and the contour of the atrium. The diameters of the pulmonary veins are measured in each vein at fixed distances from the corresponding ostium, and for each distance, the sum of the diameters of all the veins is computed. These indicators are shown to be significantly larger in sickle-cell patients with pulmonary hypertension as compared to controls (p-values < 0.01).
Background Serial assessment of right ventricular ejection fraction (RVEF) predicts the clinical outcome of patients with pulmonary hypertension (PH). Cardiac magnetic resonance imaging (CMRI) enables RVEF monitoring, but its applicability is limited in clinical practice. This study aimed to examine the correlation between changes in CMRI-derived RVEF with those in echocardiographic indices in patients with precapillary PH. Methods CMRI and echocardiographic indices of RV systolic function were evaluated at baseline and follow-up in 54 consecutive patients with precapillary PH (pulmonary arterial hypertension (PAH), n = 23; non-PAH, n = 31). During follow-up, medical treatment was optimized according to the guidelines for PH. Using CMRI-derived RVEF as the gold standard, we examined the accuracy of five echocardiographic indices by correlation analysis and receiver operating characteristic (ROC) analysis and by calculating sensitivity, specificity, and positive and negative predictive values. Results After an average period of 9.5 months, CMRI-derived RVEF improved from 30.2% +/- 10.6% at baseline to 41.4% +/- 11.3% at follow-up. These changes significantly correlated with those in the five echocardiographic indices, i.e., % RV fractional shortening (r = 0.27), % RV area change (r = 0.46), tricuspid annular plane systolic excursion (TAPSE) (r = 0.84), RV myocardial performance index (RVMPI) (r = -0.72), and systolic lateral tricuspid annular motion velocity (TVlat) (r = 0.66). Of these indices, % RV area change, TAPSE, and TVlat significantly correlated with those of CMRI-derived RVEF in both PAH and non-PAH subgroups. ROC analysis showed that improvement in echocardiographic indices predicted a prespecified improvement in CMRI-derived RVEF (>2.9%), with TAPSE and TVlat showing better accuracy over the other three indices. Conclusions Echocardiographic indices modestly correlate with the changes in CMRI-derived RVEF in precapillary PH patients. Comparison among the five echocardiographic indices revealed that TAPSE and TVlat provide better accuracy than % RV fractional shortening, % RV area change, and RVMPI.
Purpose To demonstrate feasibility of automated 3D volumetry of central pulmonary arteries based on magnetic resonance angiography (MRA), to assess pulmonary artery volumes in patients with pulmonary hypertension compared to healthy controls, and to investigate the potential of the technique for predicting pulmonary hypertension. Methods MRA of pulmonary arteries was acquired at 1.5T in 20 patients with pulmonary arterial hypertension and 21 healthy normotensive controls. 3D model-based image analysis software was used for automated segmentation of main, right and left pulmonary arteries (MPA, RPA and LPA). Volumes indexed to vessel length and mean, minimum and maximum diameters along the entire vessel course were assessed and corrected for body surface area (BSA). For comparison, diameters were also manually measured on axial reconstructions and double oblique multiplanar reformations. Analyses were performed by two cardiovascular radiologists, and by one radiologist again after 6 months. Results Mean volumes of MPA, RPA and LPA for patients/controls were 5508 +/- 1236/3438 +/- 749, 3522 +/- 934/1664 +/- 468 and 3093 +/- 692/1812 +/- 474 mu l/(cm length x m(2) BSA) (all p<0.001). Mean, minimum and maximum diameters along the entire vessel course were also significantly increased in patients compared to controls (all p<0.001). Intra-and interobserver agreement were excellent for both volume and diameter measurements using 3D segmentation (intraclass correlation coefficients 0.971-0.999, p<0.001). Area under the curve for predicting pulmonary hypertension using volume was 0.998 (95% confidence interval 0.990-1.0, p<0.001), compared to 0.967 using manually measured MPA diameter (95% confidence interval 0.910-1.0, p<0.001). Conclusions Automated MRA-based 3D volumetry of central pulmonary arteries is feasible and demonstrated significantly increased volumes and diameters in patients with pulmonary arterial hypertension compared to healthy controls. Pulmonary artery volume may serve as a superior predictor for pulmonary hypertension compared to manual measurements on axial images but verification in a larger study population is warranted.
This study introduced entropy measures to analyze the heart sound signals of people with and without pulmonary hypertension (PH). The lead II Electrocardiography (ECG) signal and heart sound signal were simultaneously collected from 104 subjects aged between 22 and 89. Fifty of them were PH patients and 54 were healthy. Eleven heart sound features were extracted and three entropy measures, namely sample entropy (SampEn), fuzzy entropy (FuzzyEn) and fuzzy measure entropy (FuzzyMEn) of the feature sequences were calculated. The Mann-Whitney U test was used to study the feature significance between the patient and health group. To reduce the age confounding factor, nine entropy measures were selected based on correlation analysis. Further, the probability density function (pdf) of a single selected entropy measure of both groups was constructed by kernel density estimation, as well as the joint pdf of any two and multiple selected entropy measures. Therefore, a patient or a healthy subject can be classified using his/her entropy measure probability based on Bayes' decision rule. The results showed that the best identification performance by a single selected measure had sensitivity of 0.720 and specificity of 0.648. The identification performance was improved to 0.680, 0.796 by the joint pdf of two measures and 0.740, 0.870 by the joint pdf of multiple measures. This study showed that entropy measures could be a powerful tool for early screening of PH patients.
Abstract This study was designed to assess whether superior vena cava (SVC) Doppler flow velocities are associated with invasive measures of pulmonary arterial pressure. Eighty patients with unrepaired congenital heart disease who underwent cardiac catheterization were included (31 men, 49 women; mean age: 37.3 ± 14.7 y). Compared with the non-pulmonary hypertension group, the moderate and severe pulmonary hypertension groups had decreased SVC ventricular reserve flow velocity and a significantly increased ratio of atrial reverse flow to systolic flow (AR/ S ). AR/ S correlated significantly with invasive pulmonary arterial systolic pressure ( r = 0.426, p < 0.0001). A cutoff of 0.45 had a sensitivity and specificity of 74% and 80%, respectively, for prediction of pulmonary hypertension. Good correlation also existed between SVC AR/ S and pulmonary arterial systolic pressure in cases without tricuspid regurgitation ( r = 0.706, p = 0.034). These results indicate that SVC AR/ S may be an alternative method for assessing pulmonary hypertension.