Bruno Alfano

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UNLABELLED We present software for integrated analysis of brain PET studies and coregistered segmented MRI that couples a module for automated placement of regions of interest (ROI) with 4 alternative methods for partial-volume-effect correction (PVEc). The accuracy and precision of these methods have been measured using 4 simulated (18)F-FDG PET studies(More)
Global grey matter (GM) loss has been reported in multiple sclerosis (MS). We addressed the question of if and where GM loss is localized by means of optimized voxel-based morphometry, applied to MRI studies of 51 patients with clinically defined relapsing-remitting MS and 34 age-matched normal subjects, segmented into normal and abnormal brain tissues(More)
OBJECTIVE To measure white matter (WM) and gray matter (GM) atrophy and lesion load in a large population of patients with multiple sclerosis (MS) using a fully automated, operator-independent, multiparametric segmentation method. METHODS The study population consisted of 597 patients with MS and 104 control subjects. The MRI parameters were abnormal WM(More)
Segmentation (tissue classification) of medical images obtained from a magnetic resonance (MR) system is a primary step in most applications of medical image post-processing. This paper describes nonparametric discriminant analysis methods to segment multispectral MR images of the brain. Starting from routinely available spin-lattice relaxation time,(More)
BACKGROUND Fatigue is a major problem in multiple sclerosis (MS), and its association with MRI features is debated. OBJECTIVE To study the correlation between fatigue and lesion load, white matter (WM), and grey matter (GM), in MS patients independent of disability. METHODS We studied 222 relapsing remitting MS patients with low disability (scores <or=2(More)
A fully automated magnetic resonance (MR) segmentation method for identification and volume measurement of demyelinated white matter has been developed. Spin-echo MR brain scans were performed in 38 patients with multiple sclerosis (MS) and in 46 healthy subjects. Segmentation of normal tissues and white matter lesions (WML) was obtained, based on their(More)
A method for postprocessing of segmented routine brain MRI studies providing automated definition of major structures (frontal, parietal, occipital, and temporal lobes; cerebellar hemispheres; and lateral ventricles) according to the Talairach atlas is presented. The method was applied to MRI studies from 25 normal subjects (NV), 14 patients with deficit(More)
OBJECTIVE The aim of this study was to differentiate benign from malignant adrenal tumors using positron emission tomography (PET) with 18F-fluorodeoxyglucose (FDG) in patients with unilateral adrenal masses originally detected by CT or MR imaging. CONCLUSION PET imaging with FDG can metabolically characterize adrenal masses. Abnormally increased FDG(More)
The purpose of this study was the development and testing of a method for unsupervised, automated brain segmentation. Two spin-echo sequences were used to obtain relaxation rates and proton-density maps from 1.5 T MR studies, with two axial data sets including the entire brain. Fifty normal subjects (age range, 16 to 76 years) were studied. A(More)
Characteristic patterns of regional cerebral blood flow (rCBF) reduction, as detected by technetium-99m hexamethylpropylene amine oxime (99mTc-HMPAO) single-photon emission tomography (SPET), may help clinicians in differentiating patients with frontotemporal dementia (FTD) from those with Alzheimer's disease (AD). However, in some cases these patients may(More)