Imaging Guidance for Therapeutic Delivery: The Dawn of Neuroenergetics

Abstract

Modern neurocritical care relies on ancillary diagnostic testing in the form of multimodal monitoring to address acute changes in the neurological homeostasis. Much of our armamentarium rests upon physiological and biochemical surrogates of organ or regional level metabolic activity, of which a great deal is invested at the metabolic-hemodynamic-hydrodynamic interface to rectify the traditional intermediaries of glucose consumption. Despite best efforts to detect cellular neuroenergetics, current modalities cannot appreciate the intricate coupling between astrocytes and neurons. Invasive monitoring is not without surgical complication, and noninvasive strategies do not provide an adequate spatial or temporal resolution. Without knowledge of the brain's versatile behavior in specific metabolic states (glycolytic vs oxidative), clinical practice would lag behind laboratory empiricism. Noninvasive metabolic imaging represents a new hope in delineating cellular, nigh molecular level energy exchange to guide targeted management in a diverse array of neuropathology.

Keywords: Brain metabolism; MRI; Metabolic imaging; Neurocritical care; Neuroenergetics; Stroke.

Fig. 1

Resolution and invasiveness among brain metabolic measurement techniques. Comparisons of spatial resolution, temporal resolution, and invasiveness among various techniques used to measure brain metabolism. Modified from Hyder and Rothman [22] (Advances in imaging brain metabolism, Annu Rev Biomed Eng 19:485-515. Copyright (2017), with permission from Annual Reviews)

Fig. 2

Laws governing oxygen transaction to the brain. Equation 1: (C_aO₂) = Arterial oxygen content. Hb = Hemoglobin concentration. S_aO₂ = Arterial oxygen saturation. P_aO₂ = Arterial oxygen partial pressure; 0.0031 represents the solubility coefficient of oxygen. Each gram of hemoglobin is capable of carrying 1.34 ml of oxygen. Equation2: VO₂ = Oxygen consumption. CO = Cardiac output. C_aO₂ = Arterial oxygen content. C_vO₂ = Venous O₂ content. Q = blood flow. (O₂)in = the oxygen content of the afferent blood (analogous to C_aO₂ globally). (O₂)out = the oxygen content of the efferent blood (analogous to C_vO₂ globally). Equation 3: VO₂I = Oxygen consumption index. CI = Cardiac index. C_aO₂ = Arterial oxygen content. C_vO₂ = Venous O₂ content. Equation 4: O₂ER = Oxygen extraction ratio, which is the proportion of arterial oxygen that is removed from the blood as it passes through the microcirculation. C_aO₂ = Arterial oxygen content. C_vO₂ = Venous O₂ content. Equation 5: O₂ER = Oxygen extraction ratio. (O₂)in = the oxygen content of the afferent blood (analogous to C_aO₂ globally). (O₂)out = the oxygen content of the efferent blood (analogous to C_vO₂ globally). Equation 6: OEF = Oxygen extraction fraction. CMRO₂ = Cerebral metabolic rate of oxygen. C_aO₂ = Arterial oxygen content. CBF = Cerebral blood flow

Fig. 3

Metabolic targets in microdialysis monitoring. CMD cerebral microdialysis, CSD cortical spreading depressions, EBI early brain injury, L/P lactate/pyruvate, NAA, n-acetyl aspartate. Reprinted from Carteron (Neurointensive Care Therapy: An Update of Recent Clinical Data. Front Neurol. 2017;8:601. Copyright (2017). Creative Commons license 4.0 (CC BY 4.0)

Fig. 4

General depiction of brain metabolism. Diagram of glucose metabolism. Glucose can be processed through 3 main metabolic pathways. The first metabolic pathway is glycolysis (i), which gives rise to 2 molecules of pyruvate as well as one molecule of ATP and NADH each. Then, this pyruvate enters the mitochondria, where it is metabolized through the tricarboxylic acid cycle and oxidative phosphorylation, producing ATP and CO₂ using oxygen as electron acceptor (iv). Lactate dehydrogenase, during hypoxia or depending on the cellular metabolic profile, reduces pyruvate to lactate, which can be liberated to extracellular by monocarboxylate transporter. Compared to glycolysis (2 ATPs), the complete oxidation of glucose produces larger amounts of energy in the form of ATP in the mitochondria (30–36 ATPs). Alternatively, the pentose phosphate pathway (PPP) can process the glucose-6P (ii), leading to the production of reducing equivalents in the form of NADPH, which is important for defense against oxidative stress. Then, the glutathione reductase uses NADPH as an electron donor to recycle back the oxidized glutathione (GSSG) formed to glutathione. In astrocytes, glucose-6P can also be used to store glucosyl units as glycogen (iii). Reprinted from Magistretti and Allaman [1] (A cellular perspective on brain energy metabolism and functional imaging. Neuron 86:883-901. Copyright (2015), with permission from Elsevier)

Fig. 5

Differential cellular metabolic signatures. Main different features in metabolic profiles between neurons and astrocytes. Astrocytes are the only cells in the brain that store glycogen, which can be seen by the high levels of expression and activity of Pfkfb3 in astrocytes. On the other hand, the reduced expression and activity of Pfkfb3 in neurons demonstrates that neurons do not store any glycogen. Cell-specific differential splicing of pyruvate kinase results in the expression of the PKM1 isoform in neurons and the expression of the PKM2 isoform in astrocytes. Additionally, due to pyruvate dehydrogenase’s high degree of phosphorylation in neurons, it has more activity in neurons than in astrocytes. These cell-specific expression and activity profiles result in opposing effects in neurons and in astrocytes. In neurons, there is a limited capacity glycolysis and an active TCA cycle as well as oxidative phosphorylation in neurons. On the other hand, in astrocytes, there is a more active glycolysis, which can be upregulated, and a TCA cycle that is limited in capacity due to the nature of its pyruvate processing. Furthermore, in astrocytes, the expression and activity of the glyoxalase system, which can detoxify cells of methylglyoxal, are considerably higher. Reprinted from Magistretti and Allaman [1] (A cellular perspective on brain energy metabolism and functional imaging. Neuron 86:883-901. Copyright (2015), with permission from Elsevier)

Fig. 6

Neural and vascular contents of a voxel. The left panel displays the relative density of vessels in the visual cortex of monkeys. The tissue is perfused with barium sulfate and imaged with synchrotron-based X-ray microtomography in order to display the dense vascular mesh (courtesy of B. Weber, MPI for Biological Cybernetics). At the top, the cortical surface without pial vessels is shown, and at the bottom, the white matter (wm) is shown. On the left side of the panel, a Nissl slice displaying the neural density from layers II through the wm is shown. The vessels seem to be high in density in this three-dimensional representation; however, in actuality, the density is less than 3% as displayed on the right by the white spots that represent the cross-sections of the vessels. The average distance between the small vessels is about 50 mm, which is approximately the distance that oxygen molecules travel by diffusion within the limited transit time of the blood. A dense population of neurons, synapses, and glial cells occupy the intervascular space. A hypothetical distribution of these vascular and neural elements is depicted in the image at the top right by the small section in the red rectangle. The images above the rectangle display some of the typical neuronal types and their processes. For example, the large pyramidal cell is exhibited by the red, the inhibitory basket cells by the dark blue, the chandelier inhibitory neurons by the light blue, and stellate cells by the gray. Reprinted by permission from Nikos [37] (What we can do and what we cannot do with fMRI. Nature 453:869-878. Logothetis, Copyright (2008))

Fig. 7

rCMRO₂ of the infarcted area. Absolute (A) and relative (B) rCMRO₂ at the center of the infarcted area. Relative rCMRO₂ was calculated as a percent of the value in the symmetrical regions of interest in the contralateral cerebral hemispheres. The x-axis indicates the time of the PET scan in relation to the onset of stroke symptoms. Patients were divided into “good” (open circles) and “poor” (filled circles) outcome groups according to their clinical evolution. The shaded area in (A) indicates the mean rCMRO₂ for the normal elderly population ± 1 SD. The lines in (B) interconnecting different studies indicate individual patients who had follow-up PET scans. In the first days after a stroke, 6 of the 9 patients with a poor clinical outcome had an rCMRO₂ below 1.25 ml O₂/100 ml/min (A). (B) All the patients with a poor final outcome have an rCMRO₂ that does not attain 50% of the value in the contralateral mirror locus. Lenzi et al. [116] (Cerebral oxygen metabolism and blood flow in human cerebral ischemic infarction. J Cereb Blood Flow Metab 2:321-335. Copyright 1982, by Sage Publications. Reprinted with permission from Sage Publications, Ltd)

Fig. 8

CMRO₂ and CBF measurements in MCAO mouse. Comparison of CMRO₂ and CBF measurements between the ¹⁷O-MRI voxels located in the MCAO-affected region (red circles) and the voxels located in the contralateral hemisphere of the same mouse brain (blue circles). (A, B) The anatomic images, selected voxels, and their corresponding dynamic ¹⁷O signal changes before, during, and after a 2.5-min inhalation of ¹⁷O-oxygen gas from 2 image slices in the same MCAO mouse. In the MCAO-affected region, the slope of the ¹⁷O signal increase during the inhalation phase was substantially smaller and the rate of signal decay in the post-inhalation phase was also significantly reduced, indicating a large decrease in both CMRO₂ and CBF. (C) Similar results from a different mouse brain. Reprinted from Zhu et al. [130] (Simultaneous and noninvasive imaging of cerebral oxygen metabolic rate, blood flow and oxygen extraction fraction in stroke mice. Neuroimage 64:437-447. Copyright (2013), with permission from Elsevier)