Whither the Hippocampus? FDG-PET Hippocampal Hypometabolism in Alzheimer Disease Revisited

Hippocampal Activity Differences Embedded in Jacobian Determinants

The negative findings in previous FDG-PET reports stem from a processing approach adapted from the MRI VBM literature and the nature of the underlying comparisons in the activity being performed. Specifically, much of the activity difference is contained in the Jacobian information from the spatial normalization procedure. While the Jacobian is used for MRI VBM processing (modulated data, or tensor-based morphometry), it has instead been discarded in the PET processing pipeline. Because the warp fields are typically computed between individual subject MR imaging and template MR imaging, and subsequently applied to coregistered PET data, it does not make sense to use this Jacobian information, as it would provide only a measure of MR imaging differences. We have taken the approach of generating a PET-study-specific template for the normalization procedure, rather than relying on coregistration between PET and MR imaging. Thus, the Jacobian information reflects only PET-related differences in populations, with no relationship to the MR imaging normalization procedure. Using this approach, large differences are identified specifically in the hippocampus on both the PET Jacobian maps alone, as well as the modulated PET data. The decreased metabolism on the raw FDG maps is not sufficient to survive multiple comparisons correction for whole-brain voxelwise studies. It only becomes apparent with the use of a hippocampal region of interest, which significantly reduces the multiple comparisons problem, allowing statistical significance to be achieved.

An important question is whether there is decreased activity, as a whole, in the hippocampus, taking into consideration the effects of atrophy. The critical piece of information is contained in the degree of expansion and contraction required to match the template. In the case of AD, there is a massive difference in the activity levels in the hippocampus, as manifested on the modulated maps and in the Jacobian maps alone.

Extrahippocampal Regions

Some additional, interesting observations arise from an analysis of the modulated and Jacobian maps, with reference to areas outside the hippocampus. On the raw FDG maps, there are large activity differences in the parietal lobes bilaterally, as well as in the cingulate gyrus, which have been demonstrated in numerous FDG-PET studies. With modulation, however, the parietal areas disappear and the cingulate gyrus activity differences become markedly reduced, as well as more restricted to the posterior cingulate. On the Jacobian maps alone, there are no differences identified in either of these regions. In the context of the PET-based normalization procedure, this suggests that these areas have some increased spatial extent of FDG uptake in the patients with AD (or a spatial up-regulation) to compensate for the reduced underlying activity (assuming the difference is not attributable to a regional increase in gray matter volume in the subjects with AD).

Study-Specific PET Template

A significant methodologic departure proposed here is the use of a study-specific PET template for the spatial normalization procedure. Many previous studies have used coregistration of PET data to a corresponding MRI in the same subject, and application of the parameters computed from an MRI-to-MRI normalization procedure. The reasoning for this approach is that, due to the inherently higher spatial resolution, the MRI-based normalization is more accurate. This approach assumes that PET activity corresponds to anatomic structure in a consistent manner between disease states and anatomic locations. This assumption is not biologically plausible, as cerebral metabolic activity levels can vary within anatomic structures, based on metabolic demand and underlying pathology. In addition, this approach universally discards information on local expansion and contraction computed from the MRI-based parameters. The use of a PET-study-specific template allows the valid use of all normalization information (including the Jacobian determinants) to identify population differences based only on FDG-PET data. In previous reports, the use of MRI-to-MRI normalizations would invalidate any unique PET information to be gained from the tissue expansion and contraction coded in the MRI-based transformations. The PET data can contain combinations of information that may be lost when standard MRI-to-MRI normalization is transposed to PET, such as metabolic volumetric differences, activity changes restricted to an anatomic structure, activity differential gradients across an anatomic structure, as well as up-regulation of the spatial extent of activity that may encompass more than a particular anatomic boundary.

The use of modulated data and Jacobian information is more than simply academic in importance. A primary goal of AD research is the search for early biomarkers to diagnose and evaluate treatment effects. Imaging has taken an important role in this regard, with numerous efforts aimed at using both MR imaging and PET imaging data for diagnosis and classification of subjects such as those with AD and MCI, or those who are CN. With regard to PET, much of the sensitivity present in the data for identifying AD in the critical hippocampal regions is not currently being utilized. Incorporation of these additional imaging biomarkers (Jacobian and modulated data) may increase the sensitivity of methods for individual subject diagnosis, including those that rely on univariate statistics, z-score population comparisons, and the newer machine learning classification approaches.

The differences in analytic approaches are clearly exemplified by comparing power curves and sample sizes required to identify differences in populations for the hippocampal region (Fig 8). Using the modulated PET approach, a difference in populations can be identified using only 12 subjects per group. This is comparable with the power of using MRI VBM alone (8 subjects per group). In contrast, using the conventional PET approach, a 5- to 6-fold increase in subjects (68 subjects per group) is required to observe comparable differences. In addition to the massive loss in sensitivity for identifying subtle differences, this translates to nearly an order of magnitude increase in imaging costs (in this example, well over $100,000, assuming $1000 per PET scan).

Use of Modulated Data

Unlike the case for structural MR imaging analyses, modulated data are typically not used for imaging studies of brain function. For example, in fMRI studies, most investigators are only interested in comparisons of the average signal within each region. Information on the total amount of signal in fMRI (provided by modulated data) within a region is typically not considered. However, total activity may provide a better model for the underlying processes being studied. In this sense, the use of modulated data with functional brain imaging data (fMRI, PET, arterial spin-labeling, etc) may provide a more appropriate model and better sensitivity, depending on the question being asked.

Reconciling Voxelwise and ROI-Based Studies

We have demonstrated why previous SPM-style voxelwise analyses of AD PET data have not shown strong hippocampal differences. These previous SPM-style analyses are measuring average activity, which is enforced by the spatial normalization process. The average activity within the hippocampi between groups is not greatly different, whereas total activity shows large differences. Activity differences become apparent only with the use of a hippocampal region of interest, which reduces the multiple comparisons problem. ROI methods do not need to correct for multiple comparisons. In this sense, the multiple comparisons correction applied to whole-brain voxelwise studies is potentially the source of differences with ROI-based methods that are also measuring average activity. In addition, some manual and semiautomated ROI-based PET analyses demonstrating hippocampal hypometabolism are probably measuring total activity in the hippocampal region (or mean of total activity between hemispheres). This capability is inherent in the ROI-based approach, regardless of whether each hippocampus is carefully outlined on a corresponding structural image or drawn directly on the PET image itself.

Limitations

There are several potential limitations of our study. For the PET analysis, we used signal-intensity-scaled data from the ADNI data base. There are a variety of signal scaling methods used in PET imaging and continued debate regarding which to use in different circumstances.^30,31 The ADNI preprocessing is essentially a proportional scaling approach, similar to that of SPM. We performed some analyses using additional proportional scaling in the SPM modeling and had similar results to those reported here. In AD, the cerebellum is probably more normal in FDG activity than the remaining brain; thus, using a cerebellar standard would result in lower supratentorial values for AD and would probably increase the observed cingulate and bilateral parietal activity on the raw FDG maps. It is important to note that a cerebellar normalization procedure can have a profound effect on the reverse AD-CN contrast, in which proportional scaling typically demonstrates large bilateral cerebellar activity differences, which disappear with cerebellar normalization.^30,31 Thus, some care must be taken in interpreting differences that relate to the regions used for intensity scaling in the frontotemporal dementias. Partial volume effects can result in an underestimation of the metabolic activity.^32,33 Additional PET analyses performed using a voxelwise gray matter volume regression method³⁴ to correct for these effects demonstrated similar findings. In many SPM VBM studies, a significant degree of spatial smoothing is used. This has the effect of increasing signal-to-noise for identifying subtle differences, as well as making the data more Gaussian for use with SPM Gaussian random field theory corrections. For this study, smoothing was unnecessary, as we had ample SNR for demonstrating activity differences. In addition, we used stringent Bonferroni corrections for whole-brain analyses, which do not rely on Gaussian random field theory.