Classification of Brain Imaging

In order to test this hypothesis, an imaging technique is needed that fulfills two requirements. First, a technique needs to be sensitive to neuronal function—not just structure. As already mentioned, the early stages of AD are characterized by cell sickness, not cell death. Animal studies have established that insofar as aging causes memory decline, it does so by interrupting neuronal physiology—again, a form of cell sickness—with a notable absence of cell loss (Rapp and Gallagher, 1996). Second, the technique needs to have sufficient spatial resolution to interrogate the hippocampus as a circuit. Because of its circuit organization, a lesion in one hippocampal subregion will secondarily affect the function of other subregions, and will affect the circuit as a whole. Thus, in order to pinpoint the primary subregion targeted by a particular mechanism of dysfunction, a technique needs to assess each hippocampal subregion individually but also simultaneously to account for circuitwide effects.

With these goals in mind, a number of imaging approaches have been developed that have fulfilled both requirements—sensitivity to neuronal function and resolution sufficient to visualize individual hippocampal subregions (Small, 2003). As in any field, a shorthanded terminology is typically used to describe different imaging approaches, and terms are often confusing or even misleading. In this regard, a brief review of the field of functional imaging is worthwhile, pinning down which aspects of the brain are actually being imaged (Figure 12.2).

Figure 12.2. Classification of brain imaging. Brain imaging is dichotomized into structural versus functional imaging. Brain structure is imaged using either magnetic resonance imaging (MRI) or computerized tomography (CT). Functional imaging indirectly assesses regional energy metabolism by relying on the neuronal consumption of two ingredients of ATP production—glucose and oxygen. Glucose consumption is imaged with positron emission tomography (PET). Oxygen consumption is measured by imaging its three correlates—cerebral blood volume (CBV), deoxyhemoglobin content, or cerebral blood flow (CBF). CBV and deoxyhemoglobin content can be imaged with functional magnetic resonance imaging (fMRI), and CBF can imaged with fMRI, PET, or single photon emission tomography (SPECT). Among these, CBV and deoxyhemoglobin content imaged with fMRI are best suited for pinpointing functional defects in individual hippocampal subregions.

Figure 12.2. Classification of brain imaging. Brain imaging is dichotomized into structural versus functional imaging. Brain structure is imaged using either magnetic resonance imaging (MRI) or computerized tomography (CT). Functional imaging indirectly assesses regional energy metabolism by relying on the neuronal consumption of two ingredients of ATP production—glucose and oxygen. Glucose consumption is imaged with positron emission tomography (PET). Oxygen consumption is measured by imaging its three correlates—cerebral blood volume (CBV), deoxyhemoglobin content, or cerebral blood flow (CBF). CBV and deoxyhemoglobin content can be imaged with functional magnetic resonance imaging (fMRI), and CBF can imaged with fMRI, PET, or single photon emission tomography (SPECT). Among these, CBV and deoxyhemoglobin content imaged with fMRI are best suited for pinpointing functional defects in individual hippocampal subregions.

Historically, in vivo imaging has been subdivided into structural imaging, such as magnetic resonance imaging (MRI) or computerized axial tomography (CT) imaging, versus functional imaging—single photon emission tomography (SPECT), positron emission tomography (PET) or functional magnetic resonance imaging (fMRI). Of course, in principle, functional imaging techniques are more likely to be sensitive to cell sickness. What exactly is meant by the "function" in functional imaging? Since the early studies performed by Kety and Schmidt (Small, 2004), functional brain imaging has come to imply a method that detects changes in regional energy metabolism. Energy metabolism is best defined as the rate with which cells produce ATP, which in neurons requires the consumption of oxygen and glucose from the blood stream. Visualizing ATP directly is challenging, but imaging techniques have been developed that can visualize correlates of oxygen and glucose consumption. With the use of radiolabeled glucose, PET can quantify the regional rates of glucose uptake. In contrast, MRI-based techniques have typically relied on the second ingredient of ATP production, oxygen consumption, to visualize correlates of energy metabolism. Because of hemodynamic coupling, oxygen consumption is correlated with cerebral blood flow, cerebral blood volume, and deoxyhemoglobin content, and all these correlates can be estimated with MRI.

The cell-sickness stage of any disease typically affects the basal metabolic rate of oxygen consumption, and relying on the basal state to map anatomical sites of dysfunction enhances parametric quantification and spatial resolution. Indeed, the basal changes of energy metabolism associated with disease have been detected relying on all metabolic correlates—glucose uptake, CBF, CBV, and deoxyhemoglobin content. Among these variables, however, only MRI measures of CBV and deoxyhemoglobin content can achieve the spatial resolution required to visualize individual hippocampal subre-gions. Indeed, studies have used MRI measures of basal CBV or deoxyhemoglobin content to investigate the hippocampal circuit in aging and AD, and these will be reviewed in the next sections.

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