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The purpose of this study is to develop a software tool for the extraction of the hippocampus and surrounding medial temporal lobe region in Nuclear Magnetic Resonance images, in order to set up suitable algorithms able to help an early diagnosis of the Alzheimer disease.

A fully automated and three-dimensional (3D) segmentation method for the identification of the pulmonary parenchyma in thorax X-ray computed tomography (CT) datasets is proposed. It is meant to be used as preprocessing step in the computer-assisted detection (CAD) system for malignant lung nodule detection that is being developed by the Medical Applications in a Grid Infrastructure Connection (MAGIC-5) Project. In this new approach the segmentation of the external airways (trachea and bronchi), is obtained by 3D region growing with wavefront simulation and suitable stop conditions, thus allowing an accurate handling of the hilar region, notoriously difficult to be segmented. Particular attention was also devoted to checking and solving the problem of the apparent ‘fusion’ between the lungs, caused by partialvolume effects, while 3D morphology operations ensure the accurate inclusion of all the nodules (internal, pleural, and vascular) in the segmented volume. The newalgorithm was initially developed and tested on a dataset of 130 CT scans fromthe Italung-CT trial, andwas then applied to the ANODE09-competition images (55 scans) and to the LIDC database (84 scans), giving very satisfactory results. In particular, the lung contour was adequately located in 96% of the CT scans, with incorrect segmentation of the external airways in the remaining cases. Segmentation metrics were calculated that quantitatively express the consistency between automatic and manual segmentations: themean overlap degree of the segmentationmasks is 0.96±0.02, and the mean and the maximum distance between the mask borders (averaged on the whole dataset) are 0.74±0.05 and 4.5±1.5, respectively, which confirms that the automatic segmentations quite correctly reproduce the borders traced by the radiologist. Moreover, no tissue containing internal and pleural nodules was removed in the segmentation process, so that this method proved to be fit for the use in the framework of a CAD system. Finally, in the comparison with a two-dimensional segmentation procedure, inter-slice smoothness was calculated, showing that the masks created by the 3D algorithm are significantly smoother than those calculated by the 2D-only procedure.

The Development of Screening Guidelines and Clinical Criteria of Predementia Alzheimer's Disease (DESCRIPA) multicenter study enrolled patients with MCI or subjective cognitive complaints (SUBJ), a part of whom underwent optional brain perfusion SPECT. These patients were classified as SUBJ (n = 23), nonamnestic MCI (naMCI; n = 17) and amnestic MCI (aMCI; n = 40) based on neuropsychology. Twenty healthy subjects formed the control (CTR) group. Volumetric regions of interest (VROI) analysis was performed in six associative cortical areas in each hemisphere. ANOVA for repeated measures, corrected for age and center, showed significant differences between groups (p = 0.01) and VROI (p < 0.0001) with a significant group-region interaction (p = 0.029). In the post hoc comparison, SUBJ did not differ from CTR. aMCI disclosed reduced uptake in the left hippocampus and bilateral temporal cortex (compared with CTR) or in the left hippocampus and bilateral parietal cortex (compared with SUBJ). In the naMCI group, reduced VROI values were found in the bilateral temporal cortex and right frontal cortex. In the comparison between aMCI and naMCI, the former had lower values in the left parietal cortex and precuneus. Discriminant analysis between SUBJ/CTR versus all MCI patients allowed correct allocations in 73 % of cases. Mean VROI values were highly correlated (p < 0.0001) with the learning measure of a verbal memory test, especially in the bilateral precunei and parietal cortex and in the left hippocampus. In a subset of 70 patients, mean VROI values showed a significant correlation (p < 0.05) with the white matter hyperintensities score on MRI. In conclusion, MCI subtypes have different perfusion patterns. The aMCI group exhibited a pattern that is typical of early Alzheimer's disease, while the naMCI group showed a more anterior pattern of hypoperfusion. Instead, a homogeneous group effect was lacking in SUBJ.