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1 Institute for Exercise and Environmental Medicine, Presbyterian Hospital of Dallas, Dallas 75231; 2 Department of Veterans Affairs Medical Center and Departments of 3 Biomedical Engineering, 4 Neurology, and 5 Radiology, University of Texas Southwestern Medical Center, Dallas, Texas 75235
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ABSTRACT |
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 TOP
 ABSTRACT
 INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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Near-infrared spectrometry (NIRS) is a well-known method used to measure in vivo tissue oxygenation and hemodynamics. This method is used to derive relative measures of hemoglobin (Hb) + myoglobin (Mb) oxygenation and total Hb (tHb) accumulation from measurements of optical attenuation at discrete wavelengths. We present the design and validation of a new NIRS oxygenation analyzer for the measurement of muscle oxygenation kinetics. This design optimizes optical sensitivity and detector wavelength flexibility while minimizing component and construction costs. Using in vitro validations, we demonstrate 1) general optical linearity, 2) system stability, and 3) measurement accuracy for isolated Hb. Using in vivo validations, we demonstrate 1) expected oxygenation changes during ischemia and reactive hyperemia, 2) expected oxygenation changes during muscle exercise, 3) a close correlation between changes in oxyhemoglobin and oxymyoglobin and changes in deoxyhemoglobin and deoxymyoglobin and limb volume by venous occlusion plethysmography, and 4) a minimal contribution from movement artifact on the detected signals. We also demonstrate the ability of this system to detect abnormal patterns of tissue oxygenation in a well-characterized patient with a deficiency of skeletal muscle coenzyme Q10. We conclude that this is a valid system design for the precise, accurate, and sensitive detection of changes in bulk skeletal muscle oxygenation, can be constructed economically, and can be used diagnostically in patients with disorders of skeletal muscle energy metabolism.
near-infrared spectrometry; hemoglobin; myoglobin; exercise; movement artifacts; metabolic disease; coenzyme Q10 deficiency
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INTRODUCTION |
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TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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NEAR-INFRARED SPECTROMETRY (NIRS) is a well-established
technique for monitoring hemoglobin (Hb) and myoglobin (Mb) oxygenation in vivo and noninvasively at the site of tissue (8, 9, 12). Briefly,
with this method, optical absorption is measured across tissue (such as
the forearm or head) at multiple wavelengths. Relative estimates of
changes in oxygenation are calculated from the wavelength-specific
absorption and the specific extinction coefficients of Hb and Mb (also
known in the literature as the NIRS "algorithm")
(29). As valuable as these sorts of measurements may be, there are very
few available, much less affordable, NIRS devices (Table
1). Although a few can be purchased
commercially (7, 9, 17, 26), others are available only if constructed on the basis of their descriptions in the literature (10, 11). In
general, commercially available instruments are very simple in
construction (e.g., RunMan, NIM), at the possible expense of signal-to-noise ratio and optical sensitivity, or are very complex in
construction [e.g., NIRO 500 (Hamamatsu, Bridgewater, NJ) or Oximeter (ISS)] and expensive (Table 1).
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None of the available instruments, either those described in the literature or those that are commercially available, are designed in a modular fashion or to allow for changes to be made in wavelengths at which measurements are made. Therefore, we present the design of a new NIRS system that addresses all these design limitations. Although the described NIRS system is based on methodology previously reported (7, 9, 24, 29), the principal advantages of the design presented here are that 1) it is based on a broadband light source in combination with continuous light measurement (i.e., without light intensity modulation), 2) it is modular (i.e., it provides the flexibility to vary the wavelengths at which measurements are made), 3) it is simple, 4) it is easy to build, and 5) because it relies on readily available and relatively inexpensive optoelectronic components, any analog-to-digital converter, and any desktop personal computer, it is inexpensive to build.
Using a combination of in vitro and in vivo measurements, we demonstrate that 1) this design produces a stable and optically linear instrument, 2) it can detect biological absorbances in vitro that are accurate, 3) it can be used on the skeletal muscle of healthy human subjects to produce data that are consistent with NIRS measurements produced by other NIRS devices and with parallel measurements that use other methodologies, 4) it can detect the expected evidences of abnormal patterns of tissue oxygenation and deoxygenation in a human patient with an inborn error of skeletal muscle metabolism that should preclude normal skeletal muscle O2 extraction, and 5) the data collected from this patient are of sufficient quality that they may be used as a component of sophisticated clinical neuromuscular diagnosis.
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METHODS |
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TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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System Design
A modular design paradigm was used for construction of the NIRS system (Fig. 1), thereby allowing the flexibility to change the light source intensity, the light source spectral characteristics, the number of wavelengths to be sampled, and the detector wavelengths or sensitivity. A 100-W, quartz tungsten halogen lamp (model 6333, Oriel, Stratford, CT) driven by a constant-current power supply (model 68830, Oriel) was used as the light source. The output of the lamp was filtered using a colored glass filter (model 59545, Oriel) to remove ultraviolet and visible light and then coupled to a fiber-optic bundle (model 77533, Oriel), hereafter called the source fiber bundle, by a fiber bundle-focusing assembly (model 77799, Oriel). Light emerging from tissue was collected using a fiber-optic bundle (detector fiber bundle; Fiberguide Industries, Stirling, NJ) placed directly over the muscle of interest (flexor digitorum profundus) (3), ~5 cm lateral from the source fiber-optic bundle. The detector fibers were divided into four legs, and light output from each individual leg was band-pass filtered using readily commercially available narrow-band interference filters at wavelengths of 770, 820, 870, and 905 nm (models S10-770-A, S10-820-A, S10-870-A, and S10-905-A, respectively, Corion, Holliston, MA). The 905-nm channel was not used in the present validation. The wavelengths were chosen to cover the near-infrared range of interest over an even spacing (7) and to maximize the sensitivity of absorption changes in response to tissue oxygenation (7, 29). Light outputs of the interference filters were measured in parallel by use of separate gallium-arsenide photocathode photomultiplier tubes (PMTs; model R928, Hamamatsu). PMTs were chosen as optical detectors because of their intrinsically high optical sensitivity. Each PMT was enclosed in light-tight aluminum housing with the inner surfaces coated in black paint, and fiber-to-PMT adapters were constructed as stepped cylinders and fitted onto the enclosures. High-voltage socket power supplies (HC123-01, Hamamatsu) were incorporated inside PMT housings and driven from a ±15 V regulated power supply. The output currents of each of the PMTs were signal conditioned in parallel; briefly, a current-to-voltage converter converted the PMT output current to a voltage that was amplified and low-pass filtered.
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The output voltage of each channel was sampled using a data acquisition
system (NI-DAQ-16L, LabView version 3.1, National Instruments, Austin,
TX) interfaced to a computer (Macintosh Quadra 700, Apple Computer,
Cupertino, CA). All voltage signals were sampled at 10 Hz and filtered
using a five-point decimation-smoothing filter. Changes in optical
absorption (
A) of tissue were
calculated at each wavelength from the logarithmic ratio of measured
output voltage
(Vo) as follows
![−&Dgr;log[<IT>V</IT><SUB>o</SUB> − <IT>V</IT><SUB>dark</SUB>] ≡ −log<FENCE><FR><NU><IT>V</IT><SUB>o</SUB>(<IT>t</IT>) − <IT>V</IT><SUB>dark</SUB></NU><DE><IT>V</IT><SUB>b</SUB> − <IT>V</IT><SUB>dark</SUB></DE></FR></FENCE> = &Dgr;<IT>A</IT>(<IT>t</IT>)](/content/vol88/issue1/fulltext/315/img001.gif)
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(1) |
A(t),
with reference to the baseline absorption of tissue (i.e., at rest). As
in other optical systems, the accuracy of
A is a function of the linearity of
the optical detector subsystem and the implicit assumption that lumped
system losses remain constant through the duration of the measurement.
This is validated in Optical and Electrical Performance Validation.
The measured changes in optical absorption were converted to changes
() in concentrations of oxygenated (Hb + Mb) and deoxygenated (Hb + Mb)
[oxy(Hb + Mb)
and
deoxy(Hb + Mb)] and oxidized cytochrome
aa3 (ox-cyt)
on the basis of the method of Wray et al. (29). Briefly, by making the
assumption that the change in absorption at each wavelength is the
linear combination of the three changing concentrations
(i), Eq. 2 results, where 
,i is the molar
extinction coefficient of chromophore i at wavelength 
,
Ci is the change in
concentration of chromophore i, and
d is the optical pathlength. Thus the
measured absorptions were multiplied by a matrix of NIRS coefficients
obtained by substituting the intrinsic molar extinction coefficients of oxy(Hb + Mb) and
deoxy(Hb + Mb) (29)
and oxidized minus reduced absorption coefficients of cytochrome aa3 (7) into
Eq. 2 and inverting the matrix
(Eq. 3). This provides three
equations for the three unknowns
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(2) |
oxy(Hb + Mb) and deoxy(Hb + Mb) were
expressed in units of millimolar times centimeters. Although the ox-cyt
signal could be calculated from Eq. 3,
these calculations are not presented, because we do not have a
satisfactory combination of in vitro and in vivo validations for these
signals. Additionally, the changes in total Hb (tHb) were calculated
by summing the
oxy(Hb + Mb) and deoxy(Hb + Mb) signals.
Thus Eq. 2 states that the change in
absorption at a given is equal to the sum of the molar extinction
coefficients at that given wavelength times the change in concentration
of the chromophore exhibiting the absorption times the mean pathlength
traveled by the photons absorbed by that chromophore
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(3) |
Optical and Electrical Performance Validation
The absorption linearity measurement was determined by cascading two filter wheels containing neutral density filters of known absorption and placing them between the source and detector fiber bundles. Percent linearity over the range of 3-5 optical density units (OD; this absorption range was chosen by comparing the voltage outputs from the human forearm with neutral density filters) was 3% and was within manufacturer specification of accuracy for the filters. Because such an in vitro method is not sensitive to small deviations from linearity, two additional approaches were used: 1) in vitro measurements of Hb solutions of known oxygenation and 2) comparison of thetHb signal
with blood volume measured in vivo by strain-gauge plethysmography.
System outputs were also evaluated for drift and random noise. Absorptions at the three wavelengths were measured at 4 OD for 1 h, and a 5-min moving-average filter was imposed to significantly attenuate random noise during the measurement of drift. System drift was defined as the maximum deviation of the absorption from its starting reference value in 1 h. Random noise was estimated as the standard deviation of absorption over a duration equal to 5 min at 4 OD.
System Validation
In vitro.
To validate the
oxy(Hb + Mb) and
deoxy(Hb + Mb)
signal outputs of the NIRS system in vitro, an oxygenated Hb solution
was prepared (29) from human erythrocytes, and its concentration was
measured using the CO-oximeter add-on unit (model IL482,
Instrumentation Laboratories, Norwood, MA) of a standard laboratory
blood gas analyzer. The Hb solution was diluted to the physiological
concentration range of 30-420 mM and placed in a custom 1-in. vial
between the source and detector fibers of the NIRS system, and sodium
dithionite was added to completely reduce
HbO2 (30). NIRS measurements were
then compared with tHb measured using the CO-oximeter.
In vivo: measurement of skeletal muscle O2 availability. In vivo validations of the system were performed in humans on skeletal muscle during rest, ischemia, hyperemia, and exercise. After the subjects gave informed consent to the protocol (approved by the Institutional Review Boards of Presbyterian Hospital and the University of Texas Southwestern Medical Center), we performed a series of in vivo validation studies on a total of 12 healthy human subjects. To assess the ability of this device to detect disorders of skeletal muscle oxidative metabolism, we compared these results with those collected from a well-characterized (23) patient with coenzyme Q10 deficiency, a deficiency in one of the enzymes of the electron transport chain. In the conduct of these in vivo validations, five of the healthy subjects participated during ischemia and exercise and five during venous occlusion; three healthy subjects were controls for the coenzyme Q10-deficient patient.
The coenzyme Q10-deficient patient was chosen for study, because the underlying biochemical defect and the pathophysiology of large muscle exercise have been well characterized (23). Because this enzyme deficiency severely limits muscle oxidative phosphorylation, systemic arteriovenous difference is virtually unchanged from rest during peak exercise, consistent with severely impaired O2 extraction by working muscle. Thus we would expect that the tissue deoxygenation normally seen in healthy subjects during exercise would not occur in this patient.Statistics
oxy(Hb + Mb) and
deoxy(Hb + Mb) are
usually expressed in units of millimolar times centimeters as changes
from baseline values (defined as 0) during rest. Differences between
calculated means (of the form
xi vs.
xj) were
determined by two-tailed group t-test
(19). Statistical significance was defined for
P < 0.05. Rates of decline during
ischemia were calculated from a linear regression into the 1st
min of the
oxy(Hb + Mb) decay
after circulatory occlusion. The time to ischemic steady state for
oxy(Hb + Mb) was
defined as the time elapsed from circulatory occlusion to time beyond
which continuing circulatory occlusion produced no change in the
magnitude of the signal.
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RESULTS |
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TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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Optical Performance
Signal stability and random noise. The measured output drift was 0.004, 0.001, and 0.004 OD/h at wavelengths of 770, 820, and 870 nm, respectively. Random noise standard deviations were measured as 0.005, 0.005, and 0.008 OD at wavelengths of 770, 820, and 870 nm, respectively.
Absorbance linearity.
The absorption measured across neutral density filters
(Ameas) with
the custom-designed NIRS device was compared with the manufacturer-specified absorption
(Af) for
each filter at the wavelengths of 770, 820, and 870 nm. The
least-squares estimates of the slope and intercept of the linear fit at
770 nm [0.97 ± 0.02 and 0.01 ± 0.02 (SE),
respectively] were not different
(P > 0.05) from unity or zero,
respectively. Similar results were obtained from the least-squares
linear fits to absorptions measured at the other discrete wavelengths.
Linearity was 97% when calculated by dividing the maximum difference
between the absorption and the least-squares fit by the absorption
range of 1.8 OD (20).
In Vitro Validations
Accuracy of Hb oxygenation measurements.
The reduction of Hb by use of sodium dithionite produced a decrease in
the oxy(Hb) signal and an
increase in the deoxy(Hb) signal. Because of equal and opposite changes in the
oxy(Hb) and
deoxy(Hb) signals, variations
in tHb were limited to signal fluctuations observed as a result of
initial sample stirring. To quantitatively validate the linearity (and
accuracy) of the measurement in vitro,
oxy(Hb) and
deoxy(Hb) were compared with the concentration of (HbO2 + Hb)
measured using a standard clinical blood laboratory CO-oximeter. A
linear response was observed (Fig. 2)
between the NIRS and CO-oximeter measurements, with maximum deviation
of the oxy(Hb) and
deoxy(Hb) signals from the line of identity being 5 and 2% (of the range), respectively.
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In Vivo Validations in Normal Healthy Human Skeletal Muscle
Muscle ischemia.
Data were collected during 5 min of rest. Circulatory occlusion was
then imposed, and the outputs of the NIRS algorithm indicated that,
immediately after arterial occlusion, the
oxy(Hb + Mb) signal
decreased below its rest control value (Fig.
3), concurrent with a proportional increase
in the
deoxy(Hb + Mb) signal, and therefore produced no net change
(P > 0.05) in the tHbvolume signal.
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Muscle hyperemia.
After the muscle oxygenation reached a stable nadir, the occluding cuff
was deflated. At this point (Fig. 3), the
oxy(Hb + Mb) signal
increased and the
deoxy(Hb + Mb)
signal decreased rapidly. This led to an increase of
tHbvolume because of a greater
increase in the
oxy(Hb + Mb) vs. the deoxy(Hb + Mb)
signal, which reached its maximum value within 1 min after cuff
release, and then a return to control level within 7 min.
Muscle rhythmic exercise.
Immediately at the onset of rhythmic handgrip (RHG) exercise (5 s of
static finger flexion at 33% of the maximal voluntary contractile
force alternated with 5 s of rest), there was an immediate decrease in
the average
oxy(Hb + Mb) signal
by ~0.3 mM · cm within the first 30 s (over the
first 3 exercise-rest cycles) after the onset of exercise (Fig.
4) and then a stable and repeatable cycling
of the signal (at a frequency of ~0.1 Hz), which was the same period
as that of the RHG. The 0.1-Hz transient decreases of the
oxy(Hb + Mb) signal
were coincident with the corresponding transient increases in the
deoxy(Hb + Mb) signal and the transient increase in force during each contraction.
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Movement artifacts.
Optical measurements can be very sensitive to movement artifacts.
During RHG exercise in normal nonischemic muscle (Fig.
5), the
oxy(Hb + Mb) signal
contained two components: 1) a
decrease in the average or filtered
oxy(Hb + Mb) signal
over the entire exercise period (Fig.
5C) and
2) cyclical changes during each
contraction-relaxation cycle (Fig.
5B). To estimate the contribution of
movement artifacts to the above signal, RHG was repeated under two
different conditions where tissue oxygenation could be expected to
remain constant: 1) normal
"loaded" exercise performed after 10 min of ischemia
(Fig. 5, D and
E) and
2) "no-load" exercise, i.e.,
exercise (with normal finger flexion activity) performed without
resistance to movement (Fig. 6).
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oxy(Hb + Mb) signal
reached a steady-state nadir (normalized to 
1.0 in Fig. 5,
D and
E). Therefore, because exercise in
such a condition of an ischemic nadir could not cause a further reduction in the tissue oxygenation, any cyclical signal changes detected during RHG exercise in this condition could only arise from
movement artifacts. This amplitude of cyclical
oxy(Hb + Mb) signal
changes during ischemic exercise (Fig. 5), expressed as a percentage of
the filtered
oxy(Hb + Mb) change during RHG exercise, performed at the same intensity but without circulatory occlusion, was 16%. Similarly, the amplitude of cyclical oxy(Hb + Mb) signal
changes during ischemic exercise, as a percentage of the cyclical
oxy(Hb + Mb)
changes during RHG exercise, was 34%.
Similarly, during unloaded finger flexion exercise (Fig. 6), there was
no distinct change in the average
oxy(Hb + Mb) signal. Thus this procedure could be used to estimate the contribution to the overall signal from movement with tissue "normally"
oxygenated. Additionally, there was no distinctly different cyclical
oxy(Hb + Mb) signal
during no-load exercise.
Validation of tHb with venous occlusion plethysmography.
During venous occlusion, the initial rate of increase of total limb
cross-sectional volume (tVI)
during the first 20 s, measured using strain-gauge plethysmography, was
4.3 ± 0.7 ml · 100 ml tissue
1 · min1. The
tVI was the same for all venous
occlusion pressures (20-70 mmHg; Fig.
7). Each of the signals was normalized, at
their respective occlusion pressures, to the total signal change.
Expressed in this manner, the
tVI was 2.3 ± 0.3%/s. The
changes in total Hb volume
(tHbvolume) were linearly
correlated with the change in total volume (tV;
r2 = 0.99; Fig.
8). Likewise, the initial rate of increase
of tHbvolume (tHbI), normalized to the
maximum signal change at each occlusion pressure, was 2.3 ± 0.5%/s
and was not different from tVI.
With cuff deflation after venous occlusion, tV and
tHbvolume decreased in a
characteristic biphasic manner, with a rapid decline lasting ~5 s
followed by a slower decline to rest values over ~1 min (Fig. 7).
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In Vivo Validations in Skeletal Muscle of the Coenzyme Q10-Deficient Patient
Muscle ischemia.
Circulatory arrest produced an immediate decline in the
oxy(Hb + Mb)
signal. The initial rate of decline of oxy(Hb + Mb) in the
patient (0.0076
mM · cm · s1
or 56%/min) was not different from that in healthy subjects. It took
about the same time (218 s) to reach an ischemic nadir, and the level
of the ischemic steady-state nadir was about the same as in healthy
subjects. Again, as in healthy subjects, circulatory occlusion resulted
in an increase in the
deoxy(Hb + Mb) signal that was approximately stoichiometric, so that there was no net
change in tHb.
Muscle exercise.
In contrast to healthy subjects, RHG exercise caused an increase in
oxy(Hb + Mb) above
rest level (Fig. 9). During the first 110 s
after the onset of RHG exercise, the average oxy(Hb + Mb) signal
reached a peak value of 24.5% above rest level [with use of the
arbitrary range where 0 
oxy(Hb + Mb) at
rest and 100 oxy(Hb + Mb) at the
ischemic nadir]. This increase in the average
oxy(Hb + Mb) signal
was accompanied by a decrease in the
deoxy(Hb + Mb) signal and was very different from that in healthy subjects. Because the increase in the
oxy(Hb + Mb) signal
was greater than in the
deoxy(Hb + Mb)
signal, a small net increase in
tHbvolume was
detected in the coenzyme
Q10-deficient patient during RHG
exercise.
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DISCUSSION |
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TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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The inherent difficulties in making NIRS measurements of internal physiological systems often have caused the focus of much of this work to be technological. Most of the engineering approaches to making these measurements are focused on designing as thorough a measurement system as possible (5, 9, 13), at the cost of instrument expense and inflexibility, or on designing a simple and inexpensive system that can be used to examine exercising skeletal muscle, possibly at the additional cost of sensitivity (15, 16, 18). We describe an intermediate approach that is relatively inexpensive to construct and relatively simple to implement and produces adequate and stable signal-to-noise ratio. It is clear that our implementation of NIRS methodology can successfully monitor skeletal muscle metabolism in exercising human skeletal muscle, that the results can be validated in vitro and in vivo, and that the results can be extended to diagnose clinical conditions. Thus we believe that our implementation of NIRS technology will provide a much more widespread availability to study skeletal muscle oxidative metabolism.
Optical and Electrical Performance Validation
Signal stability. Our estimate of signal stability is a combination of the effect of random noise (electrical and optical) and the overall stability of the system. Over a 60-min period, the sum total of the absolute value of the system drift in the three channels combined was ~1% of the absolute value of the sum of the absorbances in all channels during ischemia. Thus it is unlikely that signal instability contributes measurable error to our calculations of tissue oxygenation.
Error propagation analysis of the NIRS system.
Beyond stability and the random noise of the absorption, a more
rigorous approach to evaluating system noise is to calculate the
magnitude of the error of the measurement itself. Because absorption is
not the final measurement, it is more valuable to calculate the errors
propagated in the process of actually calculating oxy(Hb + Mb) and
deoxy(Hb + Mb). On
the basis of our algorithm (Eq. 3),
the worst-case propagated errors were calculated from the root-square
sum of the random noise at each wavelength. Therefore, the net
worst-case drift (D) for
oxy(Hb + Mb) and
deoxy(Hb + Mb) is
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oxy(Hb + Mb) and
deoxy(Hb-Mb) is
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): for
oxy(Hb + Mb) ~3%
(0.026 mM · cm per mM · cm) of the
total signal change during ischemia and ~9% (0.026 mM · cm per 0.3 mM · cm) of the
signal change during maximal RHG exercise.
Absorbance linearity.
The linearity of the absorption measurement was defined as the maximum
Ameas from a
least-squares line fit with neutral density filters
(Af). On the
basis of the slope and intercept of the straight line relating
Ameas with
Af, the 97%
linearity (over 1.8 OD) and zero intercept indicated near-perfect linearity.
In Vitro Validations
Hb cuvette and accuracy data.
Because the NIRS outputs were so consistent with CO-oximeter
outputs, with negligible cross talk between
oxy(Hb) and
deoxy(Hb), the NIRS
algorithm (Eq. 3) was considered
valid in converting net
O2-dependent absorption change to
the individual absorptions of
oxy(Hb) and
deoxy(Hb) in vitro. The only
corrections remaining would be those for the actual pathlength in vivo
(structural impediments to photon migration plus changes in
source-detector orientation during exercise) and differential changes
in the concentrations of individual chromophores not part of the
derivation of the algorithm coefficients. We believe that most of these
are accounted for in our in vivo validations.
In Vivo Validations
Measurement of tissue oxygenation by NIRS is simple but complex. It is simple, because the biophysics of optical absorption of photons by chromophores is well understood. It is complex, because 1) the absorbances of Hb and Mb are indistinguishable (7, 22), 2) the absorbances of Hb in separate anatomic compartments (relative sizes of "arterial," "capillary," or "venous" spaces) are detected and displayed as a summed signal, 3) there is interaction between blood flow and perfusion, 4) Hb oxygenation changes monotonically from the arterial to the capillary to the venous circulation in a complex fashion (21), 5) the saturations of Hb and Mb are different and dynamically changing as a function of the rate of O2 utilization and delivery, and 6) the effect of exercise on the pattern of photon migration is unknown. Taken together, these complications require rigorous biological validations. All our biological validations are based on the use of well-known and inherently simple physiological phenomena and comparisons by independent measures.Muscle ischemia.
During arterial occlusion, the changes in absorption at all the
monitored wavelengths were qualitatively consistent with the known
absorptions of Hb in vitro (29) and data from other NIRS devices (7).
Immediately after arterial occlusion,
oxy(Hb + Mb) decreased with an increase in
deoxy(Hb + Mb)
(Fig. 3). This was reasonable, because ongoing mitochondrial
respiration would be expected to gradually deplete the
O2 stores present in Hb and Mb,
but the arterial occlusion would fix the amount of tHb. As expected,
the sum of
oxy(Hb + Mb) and deoxy(Hb + Mb)
(tHbvolume) did not change
during arterial occlusion.
oxy(Hb + Mb)
and deoxy(Hb + Mb)
signals reached a steady-state nadir after 6-7 min of ischemia, an additional 5 min (ischemic) of RHG exercise (at
33% of maximal voluntary contractile force), and then another 60 s of
rest. We found that the
oxy(Hb + Mb) and
deoxy(Hb + Mb) signals were not different from those after the initial
ischemia. So, although this methodology cannot determine
absolute concentration of O2, we
do know that this was more than twice the time previously calculated to
completely deplete the tissue of
O2 (4) and that exercise did not
result in any further deoxygenation. Although this may be a condition
where the PO2 in most compartments is
nearly equal to zero (4), it is certainly functionally
indistinguishable from "zero"; thus we believe it is most
justified to call it a "biological zero."
Meaning of a biological zero.
NIRS oxy(Hb + Mb)
and deoxy(Hb + Mb)
signals are composed of some combination of the following chromophore
absorbances: Hb in the arterial or prearteriolar space, Hb in the
capillary (postarteriole to prevenule) space, Hb in the venous or
postvenule space, and Mb in the muscle. Our definition of an ischemic
nadir was that the summed oxygenation of these spaces in the field of
view was constant at zero or at some nonzero value where the
concentration gradient does not exceed the diffusion gradient (6). Our
term biological zero cannot be an absolute measure of the
real PO2 in any subcellular space;
rather, it means that no combination of blocking supply
(ischemia) and increasing demand (muscle contractile activity)
causes any further loss of oxygenation from the sum of detected
chromophores. We believe this is the functional equivalent to a mean
tissue PO2 lower than the effective
Michaelis-Menten constant in vivo of Mb for
O2 (14, 27, 28) and no higher than
the functional Michaelis-Menten constant of mitochondria for
O2, which in vitro has been
reported to be <1.0 Torr (25).
Muscle hyperemia.
After the muscle oxygenation reached a stable nadir, the occluding cuff
was deflated. At this point, the
oxy(Hb + Mb) signal
increased and the
deoxy(Hb + Mb)
signal decreased rapidly. This led to an increase of tHb because of a greater increase in the
oxy(Hb + Mb) than
in the
deoxy(Hb + Mb)
signal, which reached its maximum value within 1 min after cuff release
(Fig. 3) and then returned to control level within 7 min. We consider
this reasonable: a transient excess of arterial blood creating a
transient increase in total blood volume.
Muscle rhythmic exercise.
During maximal RHG exercise, the
oxy(Hb + Mb) signal
decreased until a steady state was reached within 30 s (3 contraction-relaxation cycles). Normalized to the signal change from
rest to ischemic steady state, this decline was 32%. The
steady-state or average value of
oxy(Hb + Mb) (calculated by a 10-s moving-average filter) remained below rest level
until the end of exercise (Fig. 5C).
In addition to a decrease in the average
oxy(Hb + Mb),
cyclical changes were observed during each contraction-relaxation
cycle. The sustained decrease of the
oxy(Hb + Mb) signal
during RHG exercise indicated that the high
O2 consumption of muscle
during exercise was accommodated by a combination of a net
increase in O2 extraction
(oxidative phosphorylation) over delivery (blood flow), possibly in
combination with a muscle pump-mediated decrease in total venous
volume. Increases in deoxy(Hb + Mb) were
equal and opposite to that of the
oxy(Hb + Mb) signal; therefore, the sum
(tHbvolume) remained unchanged.
Estimation of movement artifacts. We calculated the magnitude of movement artifacts to overall oxygenation measurements during exercise in vivo 1) after 10 min of vascular occlusion, where muscle contraction causes no further tissue deoxygenation (4), and 2) during exercise with no load and, thus, little or no increase in muscle oxidative metabolism.
At the ischemic nadir, RHG exercise produced no further deoxygenation (Fig. 5, D and E), so we could superimpose exercise to estimate the magnitude of movement artifact in and of itself. During RHG exercise performed during this ischemia, the small variations detected inoxy(Hb + Mb) and
deoxy(Hb + Mb) must
have arisen from movement artifacts. The amplitude of cyclical variations (movement artifacts; Fig.
5D) was 16% of total average signal
change during RHG exercise (Fig. 5C)
and 34% of the cyclical oxy(Hb + Mb)
amplitude during RHG exercise (Fig. 5B). Thus the maximal contribution
of movement artifacts to the average oxygenation change during RHG
exercise could not be more than about one-third of the total cyclical
oxy(Hb + Mb) amplitude. Because the amplitude of movement artifacts was so much
smaller than actual oxygenation changes, it is valid to use this NIRS
methodology to monitor skeletal muscle deoxygenation patterns during
RHG exercise.
Validation of tHb with venous occlusion plethysmography. As one estimate of the accuracy of the NIRS algorithm, we compared its calculation of total blood volume with an independent measure of blood volume: limb volume measurements made using venous occlusion plethysmography. Our assumption was that if two independent measurements agreed, then they were both measuring the same thing equally incorrectly, they were both getting the same outputs and their summed component errors were exactly equal and offsetting, or they were both correct.
The linear proportionality (Figs. 7 and 8) betweentHbvolume (NIRS) and tV
(plethysmography) during subdiastolic venous congestion
(r2 = 0.99) means
that both are correct within the limits of each methodology. Because
these two independent measures produced the same outputs at several
different subdiastolic limb congestions, during the ascension to, the
steady state at, and the recovery from each of three different
occluding pressures (Fig. 7), we are confident that the underlying
assumptions (principally the inverse matrix solution and the
coefficients in the matrix), taken as a unit, are reasonable. Moreover,
because our implementation of NIRS in this setting should only detect
changes in concentration of Hb, our results suggest that, during acute
limb congestions, the changes in limb volume measured by strain-gauge
plethysmography are dominated by the change in limb blood volume and
that any accompanying changes in limb vs. optode geometry are
negligible in the calculation of tHb by NIRS.
Skeletal muscle coenzyme Q10 deficiency. We used our NIRS system to monitor muscle oxygenation in a well-characterized patient with a deficiency of skeletal muscle coenzyme Q10 (1, 2, 23). This patient had impaired oxidative metabolism in skeletal muscle from a reduction in coenzyme Q10 concentration to <25% of normal, impairing the catalytic activities of complexes I-II and I-III. During large muscle exercise, patients with such mitochondrial myopathies typically exhibit premature fatigue and exercise intolerance. The impairment in muscle oxidative phosphorylation is so severe that there is no increase in the arteriovenous O2 difference during exercise.
We found that muscle O2 extraction during rest was not different from that of healthy subjects, consistent with previous whole body O2 consumption measurements (23). In contrast, although this patient exhibited a cyclic pattern of tissue oxygenation in synchrony with the pattern of RHG exercise, theoxy(Hb + Mb) (Fig.
9) increased immediately at the onset of exercise. This increase in the
average
oxy(Hb + Mb) signal
indicates a net increase in perfusion over extraction, consistent with
the previously documented absence of any increase in systemic
arteriovenous O2 difference and
exaggerated systemic O2 transport
relative to O2 utilization during
cycle exercise (23).
Summary
These data demonstrate clearly the value of NIRS measurement, in that it provides a completely noninvasive measure of these summed signals with extremely high time resolution. We have presented a system design that provides signal accuracy, stability, and sensitivity in combination with detection flexibility at relatively low cost and simple implementation. We have validated its outputs and demonstrated its utility in vivo in healthy control subjects as well as in a well-characterized human patient with skeletal muscle coenzyme Q10 deficiency. We believe that use of such a system can become of widespread utility for routine clinical diagnoses as well as for the study of the interactions between O2 delivery and utilization in human skeletal muscle.| |
ACKNOWLEDGEMENTS |
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We acknowledge Dr. Benjamin D. Levine for overall support of this research; the facility support and intellectual contributions of Drs. Chun-Sing Orr, Robert W. Parkey, Craig R. Malloy, Evelyn E. Babcock, Robert C. Eberhart, and Doyle Hawkins; and Karen Aayad, Paul R. Anderson, Karen Chafee, Marguerite Gunder, Iris Lin, and Phil Wyrick for technical assistance.
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FOOTNOTES |
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This research was supported by the Presbyterian Hospital of Dallas, National Institutes of Health Biotechnology Research Facility Grant P41-RR-02584, and National Aeronautics and Space Administration Grant NAGW3582 and by the Department of Veterans Affairs (R. G. Haller). R. Wariar was supported by the Presbyterian Hospital of Dallas.
The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. §1734 solely to indicate this fact.
Address for reprint requests and other correspondence: L. A. Bertocci, Institute for Exercise and Environmental Medicine, Presbyterian Hospital of Dallas, 7232 Greenville Ave., Dallas, TX 75231 (E-mail: bertocl{at}phscare.org).
Received 18 August 1998; accepted in final form 14 September 1999.
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REFERENCES |
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TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
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