Pulmonary artery and right ventricle assessment in pulmonary hypertension: correlation between functional parameters of ECG-gated CT and right-side heart catheterization.

BACKGROUND: Right ventricular function predicts outcome in patients with pulmonary hypertension (PH). Therefore accurate assessment of right ventricular function is essential to graduate severity, assess follow-up, and response to therapy. PURPOSE: To evaluate whether PH severity could be assessed using electrocardiography-gated CT (ECG-gated CT) functional parameters. A further objective was to evaluate cardiac output (CO) using two ECG-gated CT methods: the reference Simpson technique and the fully automatic technique generated by commercially available cardiac software. MATERIAL AND METHODS: Our institutional review board approved this study; patient consent was not required. Twenty-seven patients who had undergone ECG-gated CT and right heart catheterization (RHC) were included. Two independent observers measured pulmonary artery (PA) diameter, PA distensibility, aorta diameter, right ventricular cardiac output (CT-RVCO) and right ventricular ejection fraction (CT-RVEF) with automatic and Simpson techniques on ECG-gated CT. RHC-CO and mean pulmonary arterial pressure (mPAP) were measured on RHC. Relationship between ECG-gated CT and RHC measurements was tested with linear regression analysis. RESULTS: Inter-observer agreement was good for all measurements (r > 0.7) except for CT-RVCO calculated with Simpson's technique (r = 0.63). Pulmonary artery (PA) distensibility was significantly correlated to mPAP (r = -0.426, P = 0.027). CT-RVEF was correlated with mPAP only when issued from Simpson technique (r = -0.417, P = 0.034). CT-RVEF was not significantly correlated to RHC-CO (P > 0.2). CT-RVCO measured with Simpson technique (r = 0.487, P = 0.010) and automatic segmentation (r = 0.549, P = 0.005) correlated equally with RHC-CO. CONCLUSION: CT-RVEF and CT-RVCO measured on ECG-gated CT are significantly correlated, respectively, to mPAP and RHC-CO in this population with severe reduction of the right ventricular ejection fraction and could be useful for evaluating and following patients with PH.

Development of a decision support system for diagnosis and grading of brain tumours using in vivo magnetic resonance single voxel spectra.

A computer-based decision support system to assist radiologists in diagnosing and grading brain tumours has been developed by the multi-centre INTERPRET project. Spectra from a database of 1H single-voxel spectra of different types of brain tumours, acquired in vivo from 334 patients at four different centres, are clustered according to their pathology, using automated pattern recognition techniques and the results are presented as a two-dimensional scatterplot using an intuitive graphical user interface (GUI). Formal quality control procedures were performed to standardize the performance of the instruments and check each spectrum, and teams of expert neuroradiologists, neurosurgeons, neurologists and neuropathologists clinically validated each case. The prototype decision support system (DSS) successfully classified 89% of the cases in an independent test set of 91 cases of the most frequent tumour types (meningiomas, low-grade gliomas and high-grade malignant tumours--glioblastomas and metastases). It also helps to resolve diagnostic difficulty in borderline cases. When the prototype was tested by radiologists and other clinicians it was favourably received. Results of the preliminary clinical analysis of the added value of using the DSS for brain tumour diagnosis with MRS showed a small but significant improvement over MRI used alone. In the comparison of individual pathologies, PNETs were significantly better diagnosed with the DSS than with MRI alone.