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.