Does simultaneous antegrade/retrograde cardioplegia improve myocardial perfusion in the areas at risk? A magnetic resonance perfusion imaging study in isolated pig hearts.

OBJECTIVE: This study was designed to determine whether simultaneous antegrade/retrograde cardioplegia improves myocardial perfusion in areas supplied by occluded vessels. METHODS: Isolated pig hearts placed in a Langendorff preparation were divided into two groups. The left anterior descending coronary artery was occluded at its origin. In group 1 (n = 7), simultaneous antegrade/retrograde cardioplegia was conducted with use of a single perfusion unit with tubing in a Y-shaped configuration at the end, joined to the aorta and the coronary sinus. In group 2 (n = 8) simultaneous antegrade/retrograde cardioplegia was performed with two separate units, one for antegrade delivery of cardioplegic solution and the other for retrograde cardioplegic solution delivery. Myocardial perfusion in the region supplied by the left anterior descending artery and the region not supplied by this artery was assessed by magnetic resonance imaging, with use of a magnetic resonance contrast agent. The contrast agent was introduced into the common perfusion line in group 1 and into the aortic line only in group 2. RESULTS: Magnetic resonance images showed that the myocardium in the region supported by the left anterior descending artery could not be perfused with antegrade cardioplegic solution because of occlusion of the artery. During simultaneous antegrade/retrograde cardioplegia, however, the myocardium in the left anterior descending region was perfused by approximately 40% to 50% (group 1) or 20% to 30% (group 2) of the degree of perfusion in the region not perfused by the left anterior descending artery (100%). Almost no cardioplegic solution was delivered to the heart through the coronary sinus route during simultaneous antegrade/retrograde cardioplegia in both groups of hearts. Myocardial perfusion in the region supported by the left anterior descending artery was heterogeneous during simultaneous antegrade/retrograde cardioplegia. CONCLUSIONS: Simultaneous antegrade/retrograde cardioplegia significantly improved myocardial perfusion in jeopardized areas of the myocardium. The jeopardized myocardium was mainly perfused by the solution drained from the adjacent normal tissue. Elevated pressure at the coronary sinus during simultaneous antegrade/retrograde cardioplegia is responsible for the redistribution of antegradely delivered cardioplegic solution.

Fuzzy clustering of gradient-echo functional MRI in the human visual cortex. Part I: reproducibility.

Reproducibility of human functional MRI (fMRI) studies is essential for clinical and neuroresearch applications of this new human brain mapping method. Based on a recently presented study on reproducibility of gradient-echo fMRI in the human visual cortex (Moser et al. Magn Reson Imaging 1996; 14:567-579), comparing the performance of three different threshold strategies for correlation analysis, we demonstrate that (a) fuzzy clustering is a robust, model-independent method to extract functional information in time and space; (b) intertrial reproducibility of cortical activation is significantly improved by the capability of fuzzy clustering to separate signal contributions from larger vessels, running perpendicular to the slice orientation, from activation apparently close to the primary visual cortex; and (c) for repeated single subject studies, SDs of <20% for signal enhancement in approximately 80% of the studies and SDs of <30% for activated area size in approximately 65% of the studies are obtained. This, however, depends also on signal-to-noise ratio, (motion) artifacts, and subject cooperation.

Cerebral hypoxia during cardiopulmonary bypass: a magnetic resonance imaging study.

BACKGROUND: Neurocognitive deficits after open heart operations have been correlated to jugular venous oxygen desaturation on rewarming from hypothermic cardiopulmonary bypass (CPB). Using a porcine model, we looked for evidence of cerebral hypoxia by magnetic resonance imaging during CPB. Brain oxygenation was assessed by T2*-weighted imaging, based on the blood oxygenation level-dependent effect (decreased T2*-weighted signal intensity with increased tissue concentrations of deoxyhemoglobin). METHODS: Pigs were placed on normothermic CPB, then cooled to 28 degrees C for 2 hours of hypothermic CPB, then rewarmed to baseline temperature. T2*-weighted, imaging was undertaken before CPB, during normothermic CPB, at 30-minute intervals during hypothermic CPB, after rewarming, and then 15 minutes after death. Imaging was with a Bruker 7.0 Tesla, 40-cm bore magnetic resonance scanner with actively shielded gradient coils. Regions of interest from the magnetic resonance images were analyzed to identify parenchymal hypoxia and correlated with jugular venous oxygen saturation. Post-hoc fuzzy clustering analysis was used to examine spatially distributed regions of interest whose pixels followed similar time courses. Attention was paid to pixels showing decreased T2* signal intensity over time. RESULTS: T2* signal intensity decreased with rewarming and in five of seven experiments correlated with the decrease in jugular venous oxygen saturation. T2* imaging with fuzzy clustering analysis revealed two diffusely distributed pixel groups during CPB. One large group of pixels (50% +/- 13% of total pixel count) showed increased T2* signal intensity (well-oxygenated tissue) during hypothermia, with decreased intensity on rewarming. Changes in a second group of pixels (34% +/- 8% of total pixel count) showed a progressive decrease in T2* signal intensity, independent of temperature, suggestive of increased brain hypoxia during CPB. CONCLUSIONS: Decreased T2* signal intensity in a diffuse spatial distribution indicates that a large proportion of cerebral parenchyma is hypoxic (evidenced by an increased proportion of tissue deoxyhemoglobin) during CPB in this porcine model. Neuronal damage secondary to parenchymal hypoxia may explain the postoperative neuropsychological dysfunction after cardiac operations.

An improved robust hierarchical registration algorithm.

This note describes an improvement to an accurate, robust, and fast registration algorithm (Alexander, M.E. and Somorjai, R.L., Mag. Reson. Imaging, 14:453-468, 1996). A computationally inexpensive preregistration method is proposed, consisting of simply aligning the image centroids, from which estimates of the translation shifts are derived. The method has low sensitivity to noise, and provides starting values of sufficient accuracy for the iterative registration algorithm to allow accurate registration of images that have significant levels of noise and/or large misalignments. Also, it requires a smaller computational effort than the Fourier Phase Matching (FPM) preregistration method used previously. The FPM method provides accurate preregistration for low-noise images, but fails when significant noise is present. For testing the various methods, a 256 x 256 pixel T2*-weighted image was translated, rotated, and scaled to produce large misalignments and occlusion at the image boundaries. The two situations of no noise being present in the images and in which Gaussian noise is added, were tested. After preregistration, the images were registered by applying one or several passes of the iterative algorithm at different levels of preblurring of the input images. Results of using the old and new preregistration methods, as well as no preregistration, are compared for the final accuracy of recovery of registration parameters. In addition, the performances of three robust estimators: Least Median of Squares, Least Trimmed Squares, and Least Winsorized Mean, are compared with those of the nonrobust Least Squares and Woods' methods, and found to converge to correct solutions in cases where the nonrobust methods do not.

Fuzzy C-means clustering and principal component analysis of time series from near-infrared imaging of forearm ischemia.

Fuzzy C-means clustering and principal components analysis were used to analyze a temporal series of near-IR images taken of a human forearm during periods of venous outflow restriction and complete forearm ischemia. The principal component eigen-time course analysis provided no useful information and the principal component eigen-image analysis gave results that correlated poorly with anatomical features. The fuzzy C-means clustering analysis, on the other hand, showed distinct regional differences in the hemodynamic response and scattering properties of the tissue, which correlated well with the anatomical features of the forearm.

Classification of 1H MR spectra of human brain neoplasms: the influence of preprocessing and computerized consensus diagnosis on classification accuracy.

We study how classification accuracy can be improved when both different data preprocessing methods and computerized consensus diagnosis (CCD) are applied to 1H magnetic resonance (MR) spectra of astrocytomas, meningiomas, and epileptic brain tissue. The MR spectra (360 MHz, 37 degrees C) of tissue specimens (biopsies) from subjects with meningiomas (95; 26 cases), astrocytomas (74; 26 cases), and epilepsy (37; 8 cases) were preprocessed by several methods. Each data set was partitioned into training and validation sets. Robust classification was carried out via linear discriminant analysis (LDA), artificial neural nets (NN), and CCD, and the results were compared with histopathological diagnosis of the MR specimens. Normalization of the relevant spectral regions affects classification accuracy significantly. The spectra-based average three-class classification accuracies of LDA and NN increased from 81.7% (unnormalized data sets) to 89.9% (normalized). CCD increased the classification accuracy of the normalized sets to an average of 91.8%. CCD invariably decreases the fraction of unclassifiable spectra. The same trends prevail, with improved results, for case-based classification. Preprocessing the 1H MR spectra is essential for accurate and reliable classification of astrocytomas, meningiomas, and nontumorous epileptic brain tissue. CCD improves classification accuracy, with an attendant decrease in the fraction of unclassifiable spectra or cases.

Computerized consensus diagnosis: a classification strategy for the robust analysis of MR spectra. I. Application to 1H spectra of thyroid neoplasms.

We introduce and apply a new classification strategy we call computerized consensus diagnosis (CCD). Its purpose is to provide robust, reliable classification of biomedical data. The strategy involves the cross-validated training of several classifiers of diverse conceptual and methodological origin on the same data, and appropriately combining their outcomes. The strategy is tested on proton magnetic resonance spectra of human thyroid biopsies, which are successfully allocated to normal or carcinoma classes. We used Linear Discriminant Analysis, a Neural Net-based method, and Genetic Programming as independent classifiers on two spectral regions, and chose the median of the six classification outcomes as the consensus. This procedure yielded 100% specificity and 100% sensitivity on the training sets, and 100% specificity and 98% sensitivity on samples of known malignancy in the test sets. We discuss the necessary steps any classification approach must take to guarantee reliability, and stress the importance of fuzziness and undecidability in robust classification.