Added value of semiquantitative analysis of brain FDG-PET for the differentiation between MCI-Lewy bodies and MCI due to Alzheimer's disease.

Purpose: FDG-PET is an established supportive biomarker in dementia with Lewy bodies (DLB), but its diagnostic accuracy is unknown at the mild cognitive impairment (MCI-LB) stage when the typical metabolic pattern may be difficultly recognized at the individual level. Semiquantitative analysis of sc...

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Publicado en:European Journal of Nuclear Medicine & Molecular Imaging Vol. 49; no. 4; pp. 1263 - 1275
Autores principales: Massa, Federico, Chincarini, Andrea, Bauckneht, Matteo, Raffa, Stefano, Peira, Enrico, Arnaldi, Dario, Pardini, Matteo, Pagani, Marco, Orso, Beatrice, Donegani, Maria Isabella, Brugnolo, Andrea, Biassoni, Erica, Mattioli, Pietro, Girtler, Nicola, Guerra, Ugo Paolo, Morbelli, Silvia, Nobili, Flavio
Formato: Journal Article
Publicado: Springer Nature Mar2022
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Mar2022
      vid: 49
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s00259-021-05568-w
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        atl: Added value of semiquantitative analysis of brain FDG-PET for the differentiation between MCI-Lewy bodies and MCI due to Alzheimer's disease.
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          Massa, Federico
          Chincarini, Andrea
          Bauckneht, Matteo
          Raffa, Stefano
          Peira, Enrico
          Arnaldi, Dario
          Pardini, Matteo
          Pagani, Marco
          Orso, Beatrice
          Donegani, Maria Isabella
          Brugnolo, Andrea
          Biassoni, Erica
          Mattioli, Pietro
          Girtler, Nicola
          Guerra, Ugo Paolo
          Morbelli, Silvia
          Nobili, Flavio
        affil: Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Largo Daneo 3, 16132, Genoa, Italy
      sug:
      ab: Purpose: FDG-PET is an established supportive biomarker in dementia with Lewy bodies (DLB), but its diagnostic accuracy is unknown at the mild cognitive impairment (MCI-LB) stage when the typical metabolic pattern may be difficultly recognized at the individual level. Semiquantitative analysis of scans could enhance accuracy especially in less skilled readers, but its added role with respect to visual assessment in MCI-LB is still unknown. Methods: We assessed the diagnostic accuracy of visual assessment of FDG-PET by six expert readers, blind to diagnosis, in discriminating two matched groups of patients (40 with prodromal AD (MCI-AD) and 39 with MCI-LB), both confirmed by in vivo biomarkers. Readers were provided in a stepwise fashion with (i) maps obtained by the univariate single-subject voxel-based analysis (VBA) with respect to a control group of 40 age- and sex-matched healthy subjects, and (ii) individual odds ratio (OR) plots obtained by the volumetric regions of interest (VROI) semiquantitative analysis of the two main hypometabolic clusters deriving from the comparison of MCI-AD and MCI-LB groups in the two directions, respectively. Results: Mean diagnostic accuracy of visual assessment was 76.8 ± 5.0% and did not significantly benefit from adding the univariate VBA map reading (77.4 ± 8.3%) whereas VROI-derived OR plot reading significantly increased both accuracy (89.7 ± 2.3%) and inter-rater reliability (ICC 0.97 [0.96–0.98]), regardless of the readers' expertise. Conclusion: Conventional visual reading of FDG-PET is moderately accurate in distinguishing between MCI-LB and MCI-AD, and is not significantly improved by univariate single-subject VBA but by a VROI analysis built on macro-regions, allowing for high accuracy independent of reader skills.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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