Synopsis
Quantitative evaluation of brain
hemodynamics and metabolism, particularly the relationship between brain
function and oxygen utilization, is important for understanding normal human
brain operation as well as pathophysiology of neurological disorders. It can
also be of great importance for evaluation of hypoxia within tumors of the
brain and other organs. Most of the currently used methods are based on
measuring blood oxygenation level and directly related to it oxygen extraction
fraction, OEF. Combining measurement of OEF with measurement of CBF allows
evaluation of oxygen consumption, CMRO2.Quantitative
evaluation of brain hemodynamics and metabolism, particularly the relationship
between brain function and oxygen utilization, is important for understanding
normal human brain operation as well as pathophysiology of neurological
disorders. It can also be of great importance for evaluation of hypoxia within
tumors of the brain and other organs. A fundamental discovery by Ogawa and
co-workers of the BOLD (Blood Oxygenation Level Dependent) contrast opened a
possibility to use this effect to study brain hemodynamic and metabolic
properties by means of MRI measurements. Most of the currently used methods are
based on measuring blood oxygenation level and directly related to it oxygen
extraction fraction, OEF. Combining measurement of OEF with measurement of CBF
allows evaluation of oxygen consumption, CMRO
2.
In
my talk I will first discuss magnetic properties of blood – magnetic
susceptibility and MR relaxation. Then, I will describe a “through-space”
effect – the influence of inhomogeneous magnetic fields, created in the
extravascular space by intravascular deoxygenated blood, on the MR signal
formation. Further I describe several experimental techniques for measuring
tissue hemodynamic properties. Some of these techniques - MR susceptometry, and
T2-based quantification of
oxygen OEF – utilize intravascular MR signal. Another technique – qBOLD –
evaluates OEF by making use of through-space effects.
Fick’s
principle
According to Fick’s principle (1), CMRO2 can be calculated by
using the following relationship:
CMRO2 =
CBF • Cblood • (Ya –Yv) [1]
where Ya and Yv
are oxygenation levels of arterial and venous blood (i.e., the fraction of
hemoglobin in the form of oxyHb; Y = 1 corresponds to fully oxygenated blood
and Y =0 corresponds to fully deoxygenated blood); and Cblood is blood
oxygen carrying capacity. Strictly speaking, Eq. [1] corresponds to oxygen combined with hemoglobin, ignoring oxygen
dissolved in blood plasma which has much lower concentration but can also be
taken into consideration (2). Usually dissolved
oxygen does not exceed 1.5% of total oxygen in blood though it can be higher in
abnormal conditions, e.g. hyperoxia (3).
By introducing blood hematocrit
level Hct and oxygen carrying capacity of red blood cells (CRBC), Eq.
[1] can be written as follows:
CMRO2
= CRBC • CBF • Hct • Ya • OEF [2]
where oxygen extraction fraction OEF
is defined as (Ya – Yv)/Ya.
According to Eqs. [1], [2], if CBF and OEF are known, oxygen consumption CMRO2 can be calculated.
Most of the current MR methods of measuring OEF
are based, in fact, on measuring blood oxygenation level.
Blood
Oxygenation and MR Signal
One of the important
parameters characterizing magnetic properties of all tissues is their magnetic
susceptibility χ – a proportionality coefficient between tissue magnetization, M,
induced by an external magnetic field B0 (M = χ B0) and
the magnetic field strength.
Most components of biological
tissues, such as water, proteins, lipids, are diamagnetic (their magnetic
susceptibility χ is negative). The diamagnetism is a common property of all
atoms and molecules; it is due to the effect of changing microscopic atomic currents
of orbiting electrons, sometimes called Ampèrian currents, in the presence of
magnetic field B0. If
atoms or molecules contain uncompensated electronic spin moments (that is
always accompanied by magnetic moment), they also exhibit additional magnetic
susceptibility which is positive and is called paramagnetic susceptibility. The
paramagnetic effect is due to “orientational nature” of magnetic field that
tends to align electron spin magnetic moments against “de-orientational nature”
of thermal motion.
Biologically relevant examples
of paramagnetic molecules include non-heme iron and heme iron in
deoxyhemoglobin (see detail discussion in (4-6)),
and dissolved oxygen molecule O2. Importantly, heme iron is
paramagnetic because of its state. When heme iron
combines with oxygen, it changes its electronic configuration and the total
spin magnetic moment of heme complex becomes zero (7,8). When heme iron releases oxygen, it returns to a paramagnetic
state. Hence, magnetic state of heme iron can be used as a biomarker of blood
oxygenation level. When blood passes through the capillary bed and releases
oxygen, the state of heme iron changes from zero-spin at the arterial side to a
high spin at the venous side.
Due to these reversible
changes of heme complexes in deoxygenated red blood cells (RBC) (7,8), the blood vessel network in biological
tissues modifies MR signal. Importantly, this modification depends on blood
oxygenation level. This phenomenon forms the basis of the BOLD (blood oxygen
level dependent) contrast in MRI. Two effects should be separated – intravascular
and extravascular. The intravascular effect is due to the inhomogeneous
magnetic fields created by red blood cells in blood (9). The extravascular (through-space) effect is mainly due to inhomogeneous
magnetic fields created by blood vessels in the surrounding tissue (10). Because these magnetic field
inhomogeneities are tissue specific, they can provide important information on
tissue hemodynamic properties.
Blood
Magnetic Susceptibility
A
detailed theoretical consideration of blood magnetic susceptibility and the detailed
experimental studies employing in vitro
samples that were well representative of human blood in situ were provided in (11).
The magnetic susceptibility of whole blood is
determined by a weighted sum of magnetic susceptibilities of RBC and plasma:
χblood = Hct • χRBC + (1 –
Hct) • χplasma [3]
Thus, the magnetic susceptibility
of RBCs can be described as (11):
χRBC = -0.736 + Δχ0 • (1
– Y) [ppm] [4]
χplazma = -0.722 ppm [5]
where Y is blood oxygenation level
and the susceptibility difference between completely deoxygenated (Y = 0) and completely oxygenated (Y = 1) RBC is equal to
Δχ0 = 0.27 ppm [6]
Equation [6] was confirmed by two independent MR and SQUID magnetometer
measurements in (11) and recently by detail
magnetic susceptometry measurements (12).
Extravascular MR Signal
The
total MR signal includes signal from blood and from surrounding tissue where
inhomogeneous magnetic field is induced due to the susceptibility difference Δχ
between blood containing paramagnetic deoxyHb and tissue. Thus, spins of water
protons in the extravascular space sustain different phase shift, leading to MR
signal decay. Several theoretical approaches have been proposed to calculate MR
signal. Detail discussion and references can be found in (2).
Experimental Methods
qBOLD
- Quantitative Mapping of Brain Hemodynamics and Metabolism
One of the experimental methods for
quantifying brain hemodynamic properties is quantitative BOLD (qBOLD). This
technique was proposed in (13) and
verified on animal model in (14). It is
based on a theory of MR signal formation in the presence of blood vessel
network (15), experimental method GESSE
proposed and verified on phantoms in (16)
and a realistic consideration of multi-compartment tissue structure. qBOLD technique based on gradient echo acquisition was developed
in (17).
A robustness of qBOLD
quantification can be improved by independent measurements of some model
parameters. In the framework of a single compartment model this idea was
implemented by Christen, et al, (18-20). Further
improvements in qBOLD technique can also be achieved by accounting for water
diffusion effects in the model (21).
ASL-qBOLD technique for
quantitative mapping of CMRO2
Combining
qBOLD measurements of OEF with ASL measurements of CBF, allows quantitative
mapping of tissue oxygen consumption CMRO2 – Eq. [1]. The method
described in (22) is based on a GESSE
sequence with arterial spin labeling (ASL) preparation pulses and is similar to
previously used for studying water exchange in brain tissue (23).
MR Susceptometry-based CMRO2
quantification
Simultaneous
estimation of oxygen saturation and cerebral blood flow in the major vessels
draining and feeding the brain can be used for rapid non-invasive
quantification of whole-brain CMRO2. The vessel of interest often
includes internal jugular vein and/or superior sagittal sinus (SSS). The
principle of the MR susceptometry of the whole brain is based on the
measurement of the susceptibility difference between blood in the draining vein
(such as jugular vein or SSS), and its surrounding tissue by measuring the
phase difference with a GRE sequence (field mapping) (24-28). The SSS is often preferred over the internal jugular vein
where severe susceptibility artifacts, caused by the proximity of air spaces
such as the oral cavity and trachea, may complicate measurements. An additional
benefit of the SSS is the elimination of contamination by the blood from
extra-cranial sources (29).
T2-based
CMRO2 quantification
Another approach for quantifying
biological tissue hemodynamic properties is based on measuring blood T2 relaxation that is related
to blood oxygenation level. In (30), CPMG pulse sequence was used to measure the
blood transverse relaxation rate constant.
Lu
et al (31) proposed a spin-labeling technique, TRUST (T2-Relaxation-Under-Spin-Tagging),
which can isolate pure venous blood signal
(see also (32)). TRUST technique
minimizes the partial volume effect and avoids the need for judicious selection
of voxels containing blood. The T2
relaxation time of the TRUST signal can then be determined and converted to
venous oxygenation Yv
using a calibration plot (33-35).
A direct measurement of
CMRO2 is also possible by using tracers such as 17O2.
This technique is described in detail in (36).
Acknowledgements
No acknowledgement found.References
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