Background Gadolinium-perfusion magnetic resonance (MR) identifies gray matter abnormalities in early multiple sclerosis (MS), even in the absence of structural differences. These perfusion changes could be related to the cognitive disability of these patients, especially in the working memory. Arterial spin labeling (ASL) is a relatively recent perfusion technique that does not require intravenous contrast, making the technique especially attractive for clinical research. Purpose To verify the perfusion alterations in early MS, even in the absence of cerebral volume changes. To introduce the ASL sequence as a suitable non-invasive method in the monitoring of these patients. Material and Methods Nineteen healthy controls and 28 patients were included. The neuropsychological test EDSS and SDMT were evaluated. Cerebral blood flow and bolus arrival time were collected from the ASL study. Cerebral volume and cortical thickness were obtained from the volumetric T1 sequence. Spearman’s correlation analyzed the correlation between EDSS and SDMT tests and perfusion data. Differences were considered significant at a level of P < 0.05. Results Reduction of the cerebral blood flow and an increase in the bolus arrival time were found in patients compared to controls. A negative correlation between EDSS and thalamus transit time, and between EDSS and cerebral blood flow in the frontal cortex, was found. Conclusion ASL perfusion might detect changes in MS patients even in absent structural volumetric changes. More longitudinal studies are needed, but perfusion parameters could be biomarkers for monitoring these patients.

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Abstruct -Cluster division is a crucial problem in Analytical Image Based Cytology. Existing algorithms often make use either of the image content or its geometric characterization. Both sources of information are needed for a correct segmentation of difficult clusters. Morphological algorithms naturally deal with the object oriented criteria such as shape, size, contrast, connectivity, etc.In this paper, we prescnt and evaluate a morphological watershed based algorithm applied to fluorescence stained clustered nuclei division. Results are shown for two different types of samples namely bone marrow and peripheral blood specimens. These results are better than those obtained for other published algorithms. This algorithm can also be easily adapted to different types of specimens.

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