Previous studies of our group showed that C₁-C₂ spinal cord stimulation increases carotid and brain blood flow in normal conditions in the goat and dog and it has a beneficial vasomotor effect in a model of vasospasm in the rat. For further clinical application it seemed rational to investigate the possible vascular changes mediated by this technique in experimental brain infarction. To this aim, 45 New Zealand rabbits were used. Brain infarction was produced by bilateral carotid ligation in 15, unilateral microcoagulation of the middle cerebral artery in 15 and by microcoagulation of the vertebral artery at the cranio-cervical junction in the other 15. One week later, following daily clinical scoring and cortical and posterior fossa blood flow readings by laser Doppler, a period of 120 min of right C₁-C₂ spinal cord electric stimulation was performed. A mean of 27% increase in previous blood flow recordings was obtained at the right hemisphere and a mean of 32% in the posterior fossa. This procedure was used in 10 patients presenting with various cerebral low perfusion syndromes. Though not constant, an increase in alertness, retention, speech, emotional lability and performance in skilled acts was achieved. No MR changes were observed, though SPECT readings showed an increase in blood flow in the penumbral perilesional area.

Dynamic-Contrast Enhanced MRI is currently used as a complementary diagnosis tool to assess the malignancy of the liver tumor, called hepatoma or adult primary liver cancer. This paper proposes a set of features and computation methods to extract them in order to design a classifier for automatic diagnosis of the hepatoma.A dynamic discrete linear pharmacokinetic model is used to estimate the perfusion curves from the noisy observations, based on the multi-compartment paradigm. The arterial response to the contrast agent bolus injection, called arterial input function, is also estimated since no arteries are available in the neighborhood of the tumor.The compensation of involuntary movements of the patient, such as the respiratory activity, during the acquisition process is performed using a Mutual Information based registration algorithm with non-rigid transformations. The tumor is isolated in a small region of interest in order to speed up the analysis and the tumor itself is segmented using an active contour algorithm.The classification of the tumor can be based on the mean and variance values of the Maximum, WashIn and WashOut rates of the perfusion curves inside the tumor as it is shown that these rates are adequate discriminative features to automatically classify the tumors with respect to its malignancy.Tests using real data are used to illustrate the ability of using these features to classify the tumor with respect to its malignancy.