Resumen:
Purpose We aim to present and critically evaluate the use of FDG-PET in the differential diagnosis between dementing conditions including Alzheimer disease (AD), frontotemporal dementia (FTD) and its variants, vascular dementia (VaD) and pseudodepressive dementia. Methods This review is based on the available consensus recommendations for the use of FDG-PET and current clinical diagnostic criteria. In addition, we updated these reviews with relevant publications in the field after conducting a literature search during the last 5 years through predefined keyword strings relating to the specific terms related to the diseases covered in this review and a common part ('FDG-PET'). Results Neurodegenerative disease are complex groups of several forms of dementia and their clinical diagnostic criteria are progressively incorporating imaging biomarkers as a supporting tool. The role of FDG-PET is currently increasing as part of the clinical practice supporting the clinical diagnosis of AD (at both mild cognitive impairment-MCI-and early dementia stages), FTD and its variants, as well as VaD and pseudodepressive dementia. The pattern of AD is well defined and its negative predicted value may help the differential diagnosis when comorbidities like vascular disease or depression are present. However, the formal evidence supporting the use of FDG-PET is reasonable for MCI due to AD, and the differential diagnosis between FTD and AD, but lacking for the remaining clinical uses. Interestingly, the evidence provided during the last years reinforces these recommendations and gives additional clues about the usefulness of semiquantitative methods in addition to visual reading. Conclusion The large experience accumulated using FDG-PET for the differential diagnosis of the main conditions with dementia has been translated into more formal evidence to support its clinical use. Although FDG-PET form currently part of the clinical practice in many countries, there is still a lack of studies using standardized analysis that confirm specific patterns at individual level.
