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Advanced Neuroimaging Techniques

Basic Principles and Clinical Applications

Griauzde, Julius MD; Srinivasan, Ashok MD

Section Editor(s): Biousse, Valérie MD; Galetta, Steven MD

Journal of Neuro-Ophthalmology: March 2018 - Volume 38 - Issue 1 - p 101–114
doi: 10.1097/WNO.0000000000000539
State-of-the-Art Review
Free

Abstract: Advanced neuroimaging techniques are increasingly being implemented in clinical practice as complementary tools to conventional imaging because they can provide crucial functional information about the pathophysiology of a variety of disorders. Therefore, it is important to understand the basic principles underlying them and their role in diagnosis and management. In this review, we will primarily focus on the basic principles and clinical applications of perfusion imaging, diffusion imaging, magnetic resonance spectroscopy, functional MRI, and dual-energy computerized tomography. Our goal is to provide the reader with a basic understanding of these imaging techniques and when they should be used in clinical practice.

Department of Radiology (JG, AS), University of Michigan Health System, Ann Arbor, Michigan.

Address correspondence to Ashok Srinivasan, MD, Division of Neuroradiology, Department of Radiology, University of Michigan Health System, 1500 E Medical Center drive, Ann Arbor, MI 48109; E-mail: ashoks@med.umich.edu

The authors report no conflicts of interest.

Imaging plays a crucial role in the diagnosis and management of patients with central nervous system pathologies. Advanced neuroimaging techniques allow for real-time evaluation of pathophysiology and the underlying causative microstructural processes. A basic understanding of these techniques is paramount to physicians involved in the care of patients with neurologic diseases. In this review, we address several currently available advanced neuroimaging techniques and briefly discuss newer experimental methods that may provide new molecular and functional imaging biomarkers to clinical practice in the near future.

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ADVANCED NEUROIMAGING TECHNIQUES IN CURRENT PRACTICE

Perfusion Imaging

Basic Concepts

Perfusion imaging can be performed with both computed tomography (CT) and MRI. The goal of perfusion imaging is to noninvasively determine the perfusion characteristics of normal and abnormal tissues such as blood volume, blood flow, mean transit time (MTT), and permeability because these factors play an important role in disease detection and lesion characterization. Magnetic resonance perfusion imaging can be achieved using 3 main techniques: dynamic contrast-enhanced (DCE) imaging, dynamic susceptibility contrast (DSC) imaging, and arterial spin labelling (ASL).

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Dynamic Contrast-Enhanced Perfusion

In DCE, T1-weighted noncontrast images initially are obtained followed by acquisition of images during the administration of a T1 shortening contrast agent such as gadolinium. By calculating signal intensity increases over time, a time–signal intensity curve can be calculated, which can then be used to derive several semiquantitative parameters, including rate of enhancement and contrast washout (1). Furthermore, DCE can be used to calculate Ktrans, which is the vascular transfer constant that describes contrast movement from blood vessels into the extracellular spaces, and has been identified as a potential marker of capillary and blood–brain barrier permeability (2). DCE is highly user dependent and requires complex acquisition techniques, which are potential drawbacks to its routine use.

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Dynamic Susceptibility Contrast Perfusion

The principles of DSC magnetic resonance perfusion are similar to those of CT perfusion (CTP); therefore, both topics will be discussed here. DSC and CTP both use a bolus tracking technique in which a contrast agent (paramagnetic gadolinium in MRI and iodinated contrast in CT) is imaged during the first pass after venous injection (3). Therefore, these techniques require very rapid imaging. Although this is generally not a problem in CT, DSC requires specialized protocols to obtain several imaging slices in a very short period (hence protocols often use echo planar imaging which is fast but demonstrates more susceptibility artifacts due to their rapid gradient switching). Signal intensity (in MRI) or attenuation (in CT) then can be computed as a function of time. Using theoretical models of blood flow, these values can be correlated with contrast agent concentrations to create contrast concentration-to-time curves that track the changes in contrast concentration over the short bolus time (4). This relationship is linear in CTP, allowing for a quantitative measurement, and CTP can achieve greater spatial resolution than DSC MRI. However, CTP is associated with a relatively high dose of ionizing radiation. Once contrast concentration-to-time curves are known in the vascular spaces and brain tissue, they can be used to calculate blood flow (CBF), calculate blood volume, and MTT according to the central volume principle (product of blood flow and MTT is the blood volume) (3,5).

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Arterial Spin Labelling Perfusion

ASL uses radiofrequency pulses to “label” the protons of flowing blood (6). Intravascular arterial blood which is flowing into the imaging slice is exposed to a continuous or intermittent pulse which saturates the magnetization of protons. By comparing these labelled slices to unlabeled (control) slices, perfusion information can be obtained (7). ASL is the only perfusion technique that does not need contrast administration and can be performed in patients with altered renal function. The downside is that ASL is not as widely available as DCE and DSC because optimization and standardization is challenging and most software packages are currently only able to CBF.

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Clinical Applications

Traditionally, perfusion imaging was used in the evaluation of ischemic stroke to determine the extent of infarction and identify any salvageable tissue (Fig. 1) (4,8). In addition, CTP has been used in the assessment and response to treatment for cerebral vasospasm (9). The role of perfusion imaging has expanded over the past 2 decades, particularly in the areas of oncology and psychiatric illness. Perfusion imaging can be used to assess tumor vascularity, response to treatment, and recurrent disease (Fig. 2) as well as to differentiate neoplastic lesions from surrounding tissue changes (10,11). Specifically, lower grade gliomas show lower blood volume than higher grade gliomas, and recurrent brain tumors demonstrate higher blood volume compared with radiation necrosis (12,13). Early experience in head and neck tumors revealed that blood volume and Ktrans can be used to predict response to chemoradiation in patients with squamous cell carcinoma (14,15). In psychiatric disorders, ASL has shown localized abnormal perfusion in depressed and schizophrenic patients and has identified perfusion differences in responders and nonresponders to antidepressant medications (16,17). The clinical utility of ASL in psychiatric disease remains controversial and is still in its infancy. Finally, perfusion MRI has shown promise in the differentiation of various types of dementia types and in the assessment of hemodynamics in arteriovenous malformations (18–20).

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FIG. 1

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Functional MRI

Basic Concepts

Functional MRI (fMRI) is usually performed using the blood oxygen level–dependent (BOLD) imaging technique. BOLD takes advantage of the differences in the intrinsic magnetic properties of oxyhemoglobin (diamagnetic) and deoxyhemoglobin (paramagnetic). Paramagnetic substances augment external magnetic fields, whereas diamagnetic substances oppose external magnetic fields, as a result of the paring of their valence electrons (21). It has been shown that oxyhemoglobin and deoxyhemoglobin in venous blood can serve as markers for overall cerebral blood flow in a particular region, which correlates with regional oxygen metabolism (22,23). The paramagnetic properties of deoxyhemoglobin cause dephasing of the protons in surrounding tissues, resulting in signal loss. Therefore, as the proportion of regional oxyhemoglobin concentrations increase and the proportion of deoxyhemoglobin decreases, regional fMRI signal will increase, identifying increases in neuronal activity. Although fMRI is a robust technique, it does suffer from several limitations. First, scan times can be long (up to 1 hour), increasing patient discomfort. In addition, adequate mapping requires active patient cooperation and participation, which can exclude claustrophobic patients and those with altered mental status. Finally, fMRI results can be highly variable between centers, making standardization of results a challenge (24).

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Clinical Applications

Traditional applications of fMRI have been in preoperative planning before resection of dysplastic cortex and tumors (25). It has proved to be highly successful in determining language laterality and mapping speech areas, as well as in mapping motor and sensory cortex (see Fig. 8 of subsequent section) (26,27). More recently, fMRI has been used in the identification and classification of disorders of cognition (such as Alzheimer disease), memory, and psychiatric illnesses as well as in monitoring responses to treatment (28–30).

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Diffusion-Weighted Imaging, Diffusion Tensor Imaging, and Tractography

Basic Concepts

Diffusion of water molecules is nonrandom in human tissues because of cell membranes and other barriers to water motion. Although diffusion-weighted imaging (DWI) provides only a measure of magnitude of water motion (how free is water motion), diffusion tensor imaging (DTI) provides both magnitude and orientation dependence of water motion.

ADC refers to the apparent diffusion coefficient derived from DWI, and is a measure of the magnitude of water motion; therefore, higher ADC implies less restricted movement than lower ADC. Because DWI images have contribution from T2 properties and diffusion properties, tissues can sometimes be bright on DWI but not show low ADC. This phenomenon is referred to as “T2 shine-through.” In recent years, it has been possible to remove the T2 contribution to DWI by a mathematical process, resulting in a new series of images called exponential ADC.

Axonal cellular membranes and myelin, which are regularly oriented, act as microstructural barriers to the diffusion of water. The result of these microstructural barriers is an orientation dependence of the movement of water molecules parallel to the orientation of white matter fibers (31). This results in relatively higher freedom of water diffusion along the long axis of the axons compared with all other directions, which is referred to as anisotropy. Quantitative measurements obtained during DTI and tractography include fractional anisotropy (FA), mean diffusivity (MD), and tract volume (TV). FA describes the degree of anisotropy in any selected area and can be used to determine what the orientation dependence of water motion is in that voxel. FA is measured on a scale from zero to one with zero representing equal motion in all directions and a value of one representing motion only in one direction. Therefore, voxels with high FA are those which contain anatomical structures demonstrating a high orientation dependence of water motion. Performing DTI and calculating the orientation dependence of water motion in each voxel is the fundamental step toward creating a map of white matter tracts (tractography). In this technique, when the directionality of water motion in a voxel is determined (assumed to be the direction of the axon), processing software is able to assess the best voxel in all the adjacent anatomy that would fit best with the direction of the index voxel. By repeating this process over and over, it is then possible to map the white matter tracts within the brain (31–35). MD refers to the overall magnitude of diffusion of water in a voxel, regardless of direction, and is akin to ADC. TV is a measure of the voxels that are included in the tract and is used to assess if there are changes in tract size over time.

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Clinical Applications

In ischemic stroke, DWI demonstrates hyperintense signal in the infarcted tissue. The causative mechanism of restricted diffusion in ischemic stroke is mostly attributed to cytotoxic edema resulting from altered ion gradients because of failure of ion pumps within cell membranes. The altered ion gradients cause an influx of water into cells where its motion is relatively restricted compared with extracellular water (36). Apart from its critical role in the diagnosis of acute ischemic stroke, DWI has other applications in clinical practice. These include abscesses (demonstrating restricted diffusion-Figs. 3, 4) and hypercellular malignancies (demonstrating relatively restricted diffusion compared with benign tumors-Figs. 5, 6). DTI has shown promise in its ability to assess white matter injury in different pathological entities including demyelination, trauma, and ischemia (35,37). DTI with tractography also can be used in presurgical planning to help identify the proximity of tracts to surgical lesions (such as brain tumors) (38) (Figs. 7, 8). Recent studies have identified that in intracranial hemorrhage, FA values are decreased in affected white matter tracts, which have been shown to correlate with functional outcomes (39,40).

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Myelin Imaging

Basic Concepts

Evaluation of myelin content is important for the diagnosis and stratification of many pathological processes. The first technique used to detect myelin indirectly was magnetization transfer (MT). MT exploits the molecular property differences between free water and macromolecules (such as myelin), which cause significant differences in their T2 relaxation times (41). Using an off-resonance pulse, immobile protons in macromolecular structures (such as large proteins in myelin) are selectively saturated creating a contrast difference (41). Furthermore, MT can provide a semiquantitative estimate of white matter content and integrity by comparing signal intensity in sequences with and without off-resonance pulses (41,42). More recently, there are reports of in-homogenous magnetization transfer (IHMT), which is highly specific for myelinated tissues. IHMT uses both positive and negative off-resonance frequencies which enhance magnetization transfer properties between water and macromolecular proteins (43,44). IHMT contrast depends on the properties of lipid and phospholipid systems, which are abundant in myelin, making IHMT preferentially increased in myelin-containing tissues (43). Technological advances, such as multi-echo T2 relaxation MRI, have shown potential for separation of water within different physiologic compartments (i.e., cerebrospinal fluid, intra/extracellular, and myelin water) based on differences in their T2 relaxation times (45). Such separation could allow for more specific and quantitative assessments of myelin-based pathology (10). Myelin water fraction (MWF) is a measure of the amount of water trapped within myelin fibers (46). MWF has been shown to correlate with myelin density on histological analysis (45,46), allowing MWF the potential to be a marker of myelin damage (47).

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Clinical Applications

Although myelin imaging techniques are still in their early developmental stages, they may have broad implications in identifying and tracking the progression of white matter diseases, dementia, and aging (44,48,49). Figure 9 demonstrates the improved detection of normal myelin using the IHMT technique compared with the MT method.

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FIG. 9

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Dual-Energy Computed Tomography

Basic Principles

Modern CT imaging is performed using a polychromatic beam with the energy of the X-rays, leaving the tube spanning a large spectrum. Dual-energy CT uses 2 distinct X-ray spectra, each creating a separate beam (50). As X-rays of different energies interact with a particular substance, the degree they are attenuated varies based on the energy of the X-rays. This allows the material in question to be identified and quantified based on its specific attenuation properties at specific energies (51). This is different from the current CT method of measuring Hounsfield units alone to characterize tissues because the Hounsfield unit of a tissue will vary based on the energy of the incident beam. DECT enables the creation of CT images where different materials can be highlighted or suppressed (such as water, iodine, calcium etc.).

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Clinical Applications

The ability of DECT to characterize and quantify a variety of substances allows for a myriad of clinical applications. Differentiation and subtraction allow for the selective removal of materials from images (52). This can be used to obtain virtual noncontrast images and to differentiate iodinated contrast from blood by subtracting iodine (Figs. 10, 11); this is helpful in the poststroke thrombolysis setting. With iodine-enhanced images and/or monochromatic images at different keV (kiloelectron volt), there is improved visualization of subtle enhancing lesions and better tumor delineation (53–55) (Fig. 12). In addition, metal subtraction improves anatomic visualization in postoperative patients and calcium subtraction improves luminal assessment in carotid atherosclerotic disease and in the evaluation of vascular structures at the skull base (56,57). DECT can improve signal-to-noise ratio and image quality by creating fused images from high- and low-energy acquisitions (58).

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Magnetic Resonance Spectroscopy

Basic Principles

Human tissues are composed of many different molecules besides water that precess at different resonant frequencies when exposed to a magnetic field. Magnetic resonance spectroscopy (MRS) is based on quantification of non–water metabolite resonances in different types of tissues and different pathological conditions. The concentration of these metabolites is several orders of magnitude smaller than water, resulting in a poor signal-to-noise ratio and predisposing to significant error (59,60). Standardization and comparison of results also is a challenge because of the wide variety of available techniques and equipment (61). Despite these limitations, MRS can be very useful when used in conjunction with other imaging sequences. Each metabolite has a characteristic chemical shift measured in parts per million (Fig. 13). The most abundant soluble metabolites in brain imaging are N-acetyl aspartate (NAA), choline (Ch), and creatine (Cr). NAA is an amino acid present in high concentrations in neuronal mitochondria and is used as a marker of brain metabolism (62). Ch is a precursor to molecules used in cellular membranes and is used as a marker of membrane turnover (63). Ch is often elevated in pathological processes characterized by high cellularity and cell turnover such as malignant neoplasms (63). Cr is used as an internal standard because its values remain largely stable in various physiological and pathological conditions. Its primary use is in calculation of ratios and relative increases of other metabolites (64). Other less abundant metabolites include myo-inositol (MI) and lactate. MI is a sugar most concentrated in glial cells and is a marker for gliosis (65). Lactate is a marker of anaerobic metabolism which is elevated in conditions characterized by tissue hypoxia (66).

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FIG. 13

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Clinical Applications

MRS can aid in differentiating neoplasms from nonneoplasms, discerning radiation necrosis from recurrent neoplasm, and in identifying metabolic dyscrasias. Several disease processes have characteristic chemical spectra. For example, conditions with hypoxic areas such as ischemic parenchyma, necrotic tumor, and cerebral abscess have elevated lactate (Fig. 14). NAA is a marker of normal brain metabolism, but also is increased in patients with inborn errors of metabolism, such as Canavan disease, a leukodystrophy secondary to a genetic mutation in aspartoacylase, resulting in accumulation of NAA in the brain (Fig. 15) (67). More recently, decreased NAA levels have been found in aneurysmal subarachnoid hemorrhage, suggesting that global metabolic derangement plays a role in the disease process (68). Choline is often elevated in areas with rapidly dividing cells such as high-grade malignancies (Fig. 16). MRS is, however, limited in its specificity and hence should primarily be used as a complementary technique for problem solving.

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WHAT THE FUTURE HOLDS FOR ADVANCED NEUROIMAGING TECHNIQUES

Magnetic Resonance Fingerprinting

Magnetic resonance fingerprinting (MRF) is a novel imaging technique which uses a pseudo-randomized acquisition that causes the signals from different tissues to have a unique signal evolution (69). This unique “fingerprint” is simultaneously a function of the multiple material properties under investigation. The unique signal evolutions that are obtained are then matched with a reference database. Once the best match is found, the remaining parameters can be translated and assigned to the voxel being evaluated (69). By identifying specific parameters (T1, T2, flip angle) of tissues, MRF provides a quantitative imaging technique which can be used to assess pathophysiology in a standardized and reproducible fashion (70–72). The unique acquisition and reconstruction methods of MRF allow for faster imaging and decreased imaging artifacts (69,71). To date, the MRF technique has shown promise in creating blood volume and oxygenation maps in the brain and in identifying different stages of white matter injury in stroke (73,74). MRF also has been used in rapid cardiac imaging and in single breath hold acquisitions in the abdomen (75,76).

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Phase-Contrast CT

Phase-contrast CT is an experimental imaging technique which is based on the refraction (change in angular trajectory) of X-rays as they pass through materials. This is in contradistinction to traditional CT imaging, which is based solely on the absorption of X-rays by materials. Research has shown that phase-contrast CT allows for greatly enhanced soft tissue contrast when compared with traditional CT (77). A recent study showed that ex vivo phase-contrast CT can provide excellent quantification of carotid plaque components which correlate well with histological analysis (78).

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CONCLUSIONS

Table 1 summarizes the principles, applications, and limitations of a variety of advanced imaging techniques. These techniques have made vast improvements over the past few decades and have greatly expanded the role of neuroimaging in patient care. Future goals include improved image quality, eliminating artifacts, reducing radiation dose, and decreasing imaging time.

TABLE 1-a

TABLE 1-a

TABLE 1-b

TABLE 1-b

STATEMENT OF AUTHORSHIP

Category 1: a. Conception and design: A. Srinivasan; b. Acquisition of data: J. Griauzde, A. Srinivasan; c. Analysis and interpretation of data: J. Griauzde, A. Srinivasan. Category 2: a. Drafting the manuscript: J. Griauzde; b. Revising it for intellectual content: A. Srinivasan. Category 3: a. Final approval of the completed manuscript: A. Srinivasan, J. Griauzde.

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