We have described the imaging features of a relatively large cohort of lvPPA subjects with respect to FDG metabolism and gray matter volume. We found characteristic patterns of left-sided temporoparietal involvement in lvPPA, but also involvement of other regions in the language network, and showed that imaging variables can differentiate lvPPA from DAT.
With regard to the imaging characteristics of lvPPA, our results are consistent with previous findings in that we observed the most striking FDG hypometabolism and gray matter atrophy to be in the left lateral temporoparietal region 
. These regions have been shown to be associated with repetition deficits and phonological errors 
, which are both features of lvPPA. However, we also saw involvement of left lateral and medial frontal lobe, right lateral temporal lobe, and left and right precuneus. These findings show involvement across almost the entire language network 
, suggesting that although pathology may begin in the left lateral temporal lobe, it then spreads throughout this network of regions. It is unsurprising that patterns of FDG-PET hypometabolism were very similar to patterns of atrophy, given that these measures are biologically related. Neuronal loss in the grey matter, measured as atrophy, will alter local neuronal connections and hence influence the synaptic activity measured indirectly by FDG-PET.
We also sought to understand how functional and structural anatomy in lvPPA compares to DAT. The left lateral temporal lobe was the main region where the imaging changes in lvPPA exceed that of DAT. This finding is consistent with the prominence of aphasia in lvPPA patients. It also concurs with the fact that cortical regions are typically more heavily involved on imaging and pathology in atypical AD compared to typical AD 
, and that the distribution of neurofibrillary tangles is typically asymmetric in lvPPA, with greater involvement of the left hemisphere, yet symmetric in DAT 
. Two previous studies similarly found greater left temporal atrophy in lvPPA compared to DAT 
. The FDG-PET analysis also showed greater hypometabolism in left inferior parietal regions in lvPPA than DAT, suggesting that FDG-PET may be more sensitive to differences in parietal regions. On-the-contrary, the main region where DAT showed greater imaging abnormalities than lvPPA was the medial temporal lobe. The medial temporal lobes were indeed relatively spared in the lvPPA subjects, yet are typically the primary focus of atrophy in DAT 
. This finding accounts for the fact that episodic memory impairment is typically more severe in DAT than lvPPA. The FDG-PET analysis also showed greater involvement of a number of parietal and occipital regions in the right hemisphere, particularly the posterior cingulate, in DAT compared to lvPPA, reflecting the fact that the right hemisphere is relatively spared in lvPPA.
Our multivariate logistic regression models were constructed to prevent over fitting and therefore be generalizable. The analysis revealed that both FDG-PET and MRI could differentiate lvPPA from DAT, with comparable accuracy. In both models the right medial temporal lobe (more involvement in DAT than lvPPA) and left lateral temporal regions (more involvement in lvPPA than DAT) were important for optimal discrimination. The right posterior cingulate was also a useful region in the FDG-PET models, while left putamen was useful in the MRI model. Both patterns of atrophy on MRI and hypometabolism on FDG-PET are therefore useful biomarkers to distinguish lvPPA from DAT, and only a few specific regions are necessary to aid diagnosis. Noticeably, in the model that included both modalities, the majority of the variables were FDG-PET variables, showing that FDG-PET is contributing more to optimum differentiation than MRI.
The strengths of our study include the relatively large cohort of lvPPA subjects and the inclusion of more than one imaging modality. Our lvPPA subjects were matched by age to the controls and DAT subjects, although young subjects are underrepresented in our ADRC/ADPR and, hence, there remained some age difference across groups. To address this concern we accounted for age differences in all our analyses. Our findings have important clinical ramifications. Diagnosing lvPPA clinically is a difficult task due to the complexity of the disease and the characteristics it shares with other forms of PPA and DAT. This diagnosis relies on cognitive-linguistic features of patients 
which are variably present, often vary in severity, and sometimes co-exist with other cognitive-linguistic features. As the patterns of brain atrophy and hypometabolism in lvPPA are better characterized, we anticipate that imaging will become an increasingly important validating factor in lvPPA diagnosis. The specific imaging characterization of lvPPA that we have provided will be helpful in this regard. In addition, our results pertaining to the differentiation of lvPPA and DAT provide neuroanatomical explanations for the differing clinical presentations of these syndromes that share molecular pathology, and demonstrate that both MRI and FDG-PET can be useful clinically to help differentiate these syndromes. The differentiation of atypical variants of Alzheimer’s disease, such as lvPPA, from DAT could be very important for future clinical studies and treatment trials that utilize imaging biomarkers. Imaging biomarkers that are relevant as outcome measures in DAT will likely differ from those that are relevant in lvPPA. Identifying these patients before enrolment into a treatment trial will be critical.