Qualitative (Q) and semiquantitative (SQ) brain 18FFDG PET analyses in primary progressive aphasia (PPA) variants

PO027 Qualitative (Q) and semiquantitative (SQ) brain 18FFDG PET analyses in primary progressive aphasia (PPA) variants S. Nuvoli2, M.R. Piras1, S. Contu2, B.L.J. Pung2, G. Tanda2, A. Marongiu2, A. Spanu2, G. Madeddu2 1Unit of Neurology, Department of Medical, Surgical and Experimental Sciences, University of Sassari, Sassari, Italy. 2Unit of Nuclear Medicine. DPT of Medical, Surgical and Experimental Sciences. University of Sassari, Sassari, Italy Background-aim: The differential diagnosis of PPA variants represents a critical problem since logopenic aphasia (LPA) might progress to Alzheimer disease (AD) and progressive non-fluent aphasia (PNFA) and semantic variant (SVA) to fronto-temporal dementia (FTD). We evaluated the usefulness of both Q and SQ analyses of 18F-FDG PET images in the differentiation of PPA variants. Methods: We retrospectively enrolled 35 consecutive patients, 18 with clinical symptoms of aphasia but with normal MMSE and with unclear classification of PPA variants (Group A); 17 patients with clinical and MMSE signs attributable to PPA and with mixed symptoms for early AD and FTD (Group B). All patients underwent brain 18F-FDG PET/CT analyzing the images by both Q and QL methods, the latter using an automated analysis program that produces brain metabolic z score region map, and comparing each patient with age matched control group. Results: Q analysis visualized hypometabolism areas of different degree, irregularly widespread or localized in different cortical regions, in most cases bilaterally and in prevalence in the left hemisphere. SQ analysis evidenced z score highest value in different areas permitting to identify those with the major pathological involvement. In particular, in Group A patients, Q and QL analyses were concordant to achieve a correct diagnosis in 8/18 (44.4%) cases as 4 LPA and 4 PNFA. In the other 10/18 (55.6%) patients, only SQ analysis could be useful for the most appropriate diagnosis as LPA in 5 cases and as PNFA in the remaining five cases, one of the latter wrongly classified as LPA at Q analysis. In Group B patients, both analyses were concordant in 9 (52.9%) patients classifying 5/17 cases as PNFA and 4/17 cases as LPA. In other 4/17 patients with difficulties in discriminating LPA from PNFA at Q analysis, a correct classification of PNFA could be permitted only by SQ analysis. Moreover, in 1 of 17 cases, SQ was able to change the classification from LPA to PNFA as well as it could permit to classify as SVA a further 1 of 17 cases not clarified by Q analysis. Furthermore, only SQ could suggest the diagnosis of PNFA in the remaining 2/17 cases. Finally, in the patients classified as PNFA or SVA, also based on clinical and MMSE signs, a progression to FTD could be hypothesized, while in those patients classified as LPA a relation to AD could be suggested. Conclusions: This study seems to confirm the usefulness of FDGPET in diagnosing PPA variants already in an early stage as well as in suggesting the development in FTD or AD in uncertain cases. SQ analysis proved to give a significantly increment of Q analysis performance in our cases, permitting to achieve the most appropriate disease classification, thus suggesting that the combined use of the two procedures of analysis represents the most valid tool for the best interpretation of FDG-PET images in PPA patients. A larger series of cases monitored in a long clinical and instrumental follow up are necessary to confirm these data.