FDG-PET has proven to be a useful tool in both the clinical arena and in research studies of AD. This methodology holds particular promise as an early marker of functional change, which may have important prognostic value in preclinical disease and for tracking outcomes in therapeutic intervention trials.4
Mounting evidence for the utility of various MRI measures such as structural imaging, white matter hyperintensities, and diffusion tensor imaging has established MRI to be a powerful tool for studying AD,13
but PET remains the gold standard for functional assessments. An MRI-based functional measurement such as ASL could potentially streamline AD studies as it can be easily incorporated into any MRI protocol.
The primary goal of this study was to compare the abilities of ASL-MRI and FDG-PET in detecting functional abnormalities associated with AD. As is evident in , both ASL and FDG-PET identified the typical AD pattern of compromised function in the bilateral parietal lobes and the posterior cingulate.19
Conjunction analysis showed that the overlap between the 2 modalities in these areas was statistically significant. Contrary to several reports of hyperperfusion in the hippocampus for patients with prodromal AD,27–29
we did not find any areas with mismatched CBF and CMRGlc, suggesting that the elevated hippocampal CBF was likely a compensatory mechanism only present in early disease stages. Complementary to the voxel-wise comparison, the ROI results showed significantly lower rCBF and rCMRGlc in the angular and posterior cingulate areas of the patients, while motor, thalamus, and basal ganglia regions were unaffected. ROC analysis on the ROI results demonstrated high disease detection accuracy of >0.9 for both modalities. While promising, this preliminary result requires further validation in a larger scale study. Nonetheless, both ROI and voxel-wise results support the notion that ASL and FDG-PET offer similar functional measures.
The AD-related atrophy pattern was significantly different from the hypoperfusion and hypometabolism patterns (figure e-4). This frequently reported discrepancy30,31
has been suggested to be a result of diaschisis, in which in addition to local neuronal loss, functional deficits can also occur in distant areas as a result of denervation.32
In support of this theory, Villain et al.33
reported a strong correlation between hippocampal atrophy and cingulum bundle disruption, which was in turn correlated to hypometabolism in association cortices. The complementary findings associated with structural and functional measures (CMRGlc and CBF) suggest a value in obtaining both structural and functional data in tracking disease progression, which can be easily achieved with MRI techniques such as ASL and MPRAGE.
The mean GM CBF value in patients was approximately 20% lower than that of the controls in the current study (mean ± SD = 49.9 ± 10.1 mL/100 g/min), in good agreement with previous studies reporting global hypoperfusion in patients with AD.34
Compared to the majority of reproducibility studies on ASL, our wsCV of 16% is slightly higher than the norm of less than 10%.12,35
This is likely due to the fact that most other studies were performed in young, healthy subjects, who typically have higher CBF and also better signal-to-noise ratio in their ASL scans.36
Though no formal assessment of FDG-PET reproducibility in patients with AD exist, CMRGlc measurements in healthy subjects have a reproducibility of 7.1%,37
which is slightly better than the reproducibility of ASL in healthy subjects.
Both ASL and FDG-PET show expected correlations with cognitive task performance, as evidenced by the correlation maps for BNT and DSS in . While not a central goal of this present study, the inferior frontal/temporal correlation with BNT and dorsal frontoparietal correlation with DSS are consistent with known networks supporting naming and control/working memory processes involved in these psychometric measures.38,39
That ASL and FDG-PET were able to detect these distinct networks with good agreement between them is further evidence for the similarity between these 2 methodologies. A major limitation of the present study is the small patient cohort, which precludes assessment of correlations with disease severity. Further research in a larger patient population of more varied disease stages is necessary to determine the utility of ASL in tracking disease severity.
Using voxel-wise comparisons, we have demonstrated that ASL-MRI identifies highly overlapping patterns of hypoperfusion with FDG-PET hypometabolism in patients with AD compared to controls. ROI results revealed that rCBF and rCMRGlc show similar degrees of functional deficits between patients and controls in affected brain regions. The noninvasive nature of ASL makes it well-suited for screening and longitudinal disease tracking. However, its sensitivity in early-stage AD remains to be investigated. In order to facilitate planning of ASL-MRI longitudinal studies, we also present an estimate for ASL-MRI reproducibility in our patient population. Future work in a more varied patient cohort will help realize the full potential of ASL-MRI in AD-related research and clinical care.