Validation of FDG-PET datasets of normal controls for the extraction of SPM-based brain metabolism maps(92 views) Caminiti SP, Sala A, Presotto L, Chincarini A, Sestini S, Perani D, Schillaci O, Berti V, Calcagni ML, Cistaro A, Morbelli S, Nobili F, Pappata S, Volterrani D, Gobbo CL
Vita-Salute San Raffaele University, Milan, Italy., In vivo human molecular and structural neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy., Nuclear Medicine Unit, San Raffaele Hospital, Via Olgettina 60, 20132, Milan, Italy., Istituto Nazionale di Fisica Nucleare, Genoa, Italy., Ospedale di Prato (NOP) S. Stefano, Prato, Italy., Vita-Salute San Raffaele University, Milan, Italy. perani.daniela@hsr.it., In vivo human molecular and structural neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy. perani.daniela@hsr.it., Nuclear Medicine Unit, San Raffaele Hospital, Via Olgettina 60, 20132, Milan, Italy. perani.daniela@hsr.it.,
References: Not available.
Validation of FDG-PET datasets of normal controls for the extraction of SPM-based brain metabolism maps
PURPOSE: An appropriate healthy control dataset is mandatory to achieve good performance in voxel-wise analyses. We aimed at evaluating [18F]FDG PET brain datasets of healthy controls (HC), based on publicly available data, for the extraction of voxel-based brain metabolism maps at the single-subject level. METHODS: Selection of HC images was based on visual rating, after Cook's distance and jack-knife analyses, to exclude artefacts and/or outliers. The performance of these HC datasets (ADNI-HC and AIMN-HC) to extract hypometabolism patterns in single patients was tested in comparison with the standard reference HC dataset (HSR-HC) by means of Dice score analysis. We evaluated the performance and comparability of the different HC datasets in the assessment of single-subject SPM-based hypometabolism in three independent cohorts of patients, namely, ADD, bvFTD and DLB. RESULTS: Two-step Cook's distance analysis and the subsequent jack-knife analysis resulted in the selection of n = 125 subjects from the AIMN-HC dataset and n = 75 subjects from the ADNI-HC dataset. The average concordance between SPM hypometabolism t-maps in the three patient cohorts, as obtained with the new datasets and compared to the HSR-HC standard reference dataset, was 0.87 for the AIMN-HC dataset and 0.83 for the ADNI-HC dataset. Pattern expression analysis revealed high overall accuracy (> 80%) of the SPM t-map classification according to different statistical thresholds and sample sizes. CONCLUSIONS: The applied procedures ensure validity of these HC datasets for the single-subject estimation of brain metabolism using voxel-wise comparisons. These well-selected HC datasets are ready-to-use in research and clinical settings.
Validation of FDG-PET datasets of normal controls for the extraction of SPM-based brain metabolism maps
No results.
Validation of FDG-PET datasets of normal controls for the extraction of SPM-based brain metabolism maps
Bruni AC, Bernardi L, Colao R, Rubino E, Smirne N, Frangipane F, Terni B, Curcio SA, Mirabelli M, Clodomiro A, Di Lorenzo R, Maletta R, Anfossi M, Gallo M, Geracitano S, Tomaino C, Muraca MG, Leotta A, Lio SG, Pinessi L, Rainero I, Sorbi S, Nee L, Milan G, Pappata S, Postiglione A, Abbamondi N, Forloni G, St George Hyslop P, Rogaeva E, Bugiani O, Giaccone G, Foncin JF, Spillantini MG, Puccio G * Worldwide distribution of PSEN1 Met146Leu mutation: A large variability for a founder mutation(1433 views) Neurology (ISSN: 0028-3878, 1526-632x, 1526-632xelectronic), 2010 Mar 9; 74(10): 798-806. Impact Factor:8.017 ViewExport to BibTeXExport to EndNote
Hesse B, Tagil K, Cuocolo A, Anagnostopoulos C, Bardies M, Bax J, Bengel F, Busemann Sokole E, Davies G, Dondi M, Edenbrandt L, Franken P, Kjaer A, Knuuti J, Lassmann M, Ljungberg M, Marcassa C, Marie PY, Mckiddie F, O'connor M, Prvuolovich E, Underwood R * 3. 0 T perfusion MR imaging(896 views) Rivista Di Neuroradiologia (ISSN: 1120-9976), 2004; 17(6): 807-812. Impact Factor:0.023 ViewExport to BibTeXExport to EndNote