Near-infrared (NIR) spectroscopic measurement of blood and tissue chemistry often requires a large set of subject data
for training a prediction model. We have previously developed the principal component analysis loading correction
(PCALC) method to correct for subject related spectral variations. In this study we tested the concept of developing
PCALC factors from simulated spectra. Thirty, two-layer solid phantoms were made with 5 ink concentrations (0.004%-
0.02%), 2 μs' levels, and 3 fat thicknesses. Spectra were collected in reflectance mode and converted to absorbance by
referencing to a 99% reflectance standard. Spectra (5733) were simulated using Kienle's two-layer turbid media model
encompassing the range of parameters used in the phantoms. PCALC factors were generated from the simulated spectra
at one ink concentration. Simulated spectra were corrected with the PCALC factors and a PLS model was developed to
predict ink concentration from spectra. The best-matched simulated spectrum was identified for each measured phantom
spectrum. These best-matched simulated spectra were corrected with the PCALC factors derived from the simulated
spectra set, and they were used in the PLS model to predict ink concentrations. The ink concentrations were predicted
with an R2=0.897, and an estimated error (RMSEP) of 0.0037%. This study demonstrated the feasibility of using
simulated spectra to correct for inter-subject spectral differences and accurately determine analyte concentrations in
turbid media.
Noninvasive near infrared (NIR) spectroscopic measurement of muscle oxygenation requires the penetration of
light through overlying skin and fat layers. We have previously demonstrated a dual-light source design and
orthogonalization algorithm that corrects for inference from skin absorption and fat scattering. To achieve
accurate muscle oxygen saturation (SmO2) measurement, one must select the appropriate source-detector
distance (SD) to completely penetrate the fat layer. Methods: Six healthy subjects were supine for 15min to
normalize tissue oxygenation across the body. NIR spectra were collected from the calf, shoulder, lower and
upper thigh muscles with long SD distances of 30mm, 35mm, 40mm and 45mm. Spectral preprocessing with the
short SD (3mm) spectrum preceded SmO2 calculation with a Taylor series expansion method. Three-way
ANOVA was used to compare SmO2 values over varying fat thickness, subjects and SD distances. Results:
Overlying fat layers varied in thickness from 4.9mm to 19.6mm across all subjects. SmO2 measured at the four
locations were comparable for each subject (p=0.133), regardless of fat thickness and SD distance. SmO2
(mean±std dev) measured at calf, shoulder, low and high thigh were 62±3%, 59±8%, 61±2%, 61±4%
respectively for SD distance of 30mm. In these subjects no significant influence of SD was observed (p=0.948).
Conclusions: The results indicate that for our sensor design a 30mm SD is sufficient to penetrate through a
19mm fat layer and that orthogonalization with short SD effectively removed spectral interference from fat to
result in a reproducible determination of SmO2.
It is estimated that 750,000 cases of severe sepsis occur in the United States
annually, at least 225,000 of which are fatal, resulting in significant utilization of
healthcare resources and expenses. Significant progress in the understanding of
pathophysiology and treatment of this condition has been made lately. Among the newer
treatment strategies for critically ill patients are the administration of early goal directed
therapy, and Recombinant Human Activated Protein C (Drotrecogrin alfa (activated)
[DTAA]) for severe sepsis. However, mortality remains unacceptably high.
The application of multivariate calibration models, specifically those using partial least squares (PLS) regression to relate near infrared (NIR) spectral data to analyte concentrations, relies upon accurate knowledge of the concentrations during model building. In a physiologic system, such as human skeletal muscle, these concentrations can be measured using invasive sensors which may have material properties that limit diffusion of analytes to the sensing chemistry, thus taking several minutes to fully respond to an analyte change which actually occurs in seconds. This results in a poor time correlation between reference measurements of analyte concentrations and spectral data, which in turn degrades the performance of the PLS model. We mathematically modeled the response of an invasive sensor measurement and used this response to develop a filter to time-match the raw NIR spectra before building the PLS model. PLS models for interstitial pH in exercising human flexor digitorum profundus muscle were developed with and without the time-matching filter. In a single exercising subject, root mean square error of prediction (RMSEP) = 0.05 pH units and r2 = 0.39 without filtering, but improved to RMSEP = 0.02 pH units with r2 = 0.91 after the time-matching filter was implemented. The time-matching filter was shown to be effective in improving model performance when spectral response is more rapid than the invasive sensor reference measurement.
Muscle pH is an important indicator of inadequate blood flow and available oxygen. Muscle pH can be used to triage and help treat trauma victims and indicate poor peripheral blood flow in diabetic patients. Muscle pH can also be used to indicate exercise intensity and fatigue. We have developed methods to non-invasively measure muscle pH using Near-Infrared Spectroscopy (NIRS) and Partial Least Squares (PLS) analysis. A multi-subject PLS model correlating near infrared tissue spectra, acquired from healthy subjects during repetitive hand-grip exercise, to invasive tissue pH measurements, has been developed and validated. Subject related variations in the spectral signal; impede the development of viable multi-subject model. Within-subject variations in tissue NIR spectra often result from uncontrolled motion or blood volume changes during exercise, while subject-to-subject variations arise from differences in skin pigmentation and the fat layer thickness. We have developed signal processing techniques to account for these mitigating factors. By incorporating this signal processing techniques with PLS calibration, we can generate a pH model that has a relative standard error of prediction of 1.7%
In order to measure muscle physiological parameters such as pH and oxygen partial pressure (PO2) by continuous wave (CW) diffuse reflectance near-infrared spectroscopy (NIRS), light must penetrate through skin and subcutaneous fat layers overlying muscle. In this study, the effect of skin and subcutaneous fat layer and on the spatial sensitivity profile of CW diffuse reflectance near-infrared spectra is investigated through Monte Carlo simulations. The simulation model uses a semi-infinite medium consisting of skin, fat and muscle. The optical properties of each layer are taken from the reported optical data at 750 nm. The skin color is either Caucasian or Negroid and the fat thickness is varied from 0 ~ 20 mm. The spatial sensitivity profile, penetration depth, and sensitivity ratio as functions of optical fiber source-detector separation (SD, 2.5 mm, 5.0 mm, 10.0 mm, 20.0 mm, 30.0 mm and 40.0 mm), skin color and fat thicknesses are predicted by the simulations. It is shown that skin color only slightly influenced the spatial sensitivity profile, while the presence of the fat layer greatly decreased the detector sensitivity. It is also shown that probes with longer SD separations can detect light from deeper inside the medium. The simulation results are used to design a fiber optic probe which ensures that enough light is propagated inside the muscle in NIRS measurement on a leg with a fat layer of normal thickness.
KEYWORDS: Diffuse reflectance spectroscopy, Optical properties, Monte Carlo methods, Absorption, Scattering, Blood, Near infrared spectroscopy, Photons, Tissue optics, Refractive index
Continuous wave near-IR spectroscopy (CW-NIRS) has been increasingly applied for the noninvasive, in vivo measurement of tissue and blood chemistry. It is hypothesized that there is a quantifiable relationship between fat thickness and near infrared diffuse reflectance spectra at all wavelengths, and this relationship can be used to remove the spectral influence of the overlying fat layer from the muscle spectrum. The hypothesis was investigated at a single wavelength using Monte Carlo simulations of a two-layer structure and with phantom experiments. The influence of a range of optical coefficients (absorption and reduced scattering) for fat and muscle over the known range of human physiological values was also investigated. A polynomial relationship was established between the fat thickness and the detected diffuse reflectance. It is also shown that the optical properties of the muscle and fat layers influence this relationship under certain conditions. Subject-to-subject variation in the fat optical coefficients and thickness can be ignored if the fat thickness is less than 5 mm, such as on the forearm. If NIRS measurement is to be performed on an anatomical region with a thicker fat layer, a spectral correction for fat will be needed to account for its thickness and the variation in optical coefficients for both the fat and the muscle layers.
We have previously demonstrated the correlation of continuous-wave near infrared (CW-NIR) tissue measurements, to blood and tissue metabolic parameters using Partial Least Squares (PLS) regression. The practical use of this non-invasive measurement technique depends on the transfer of PLS calibration models from a single calibration unit to multiple secondary units. Variations in the spectral characteristics of the optical components across multiple units result in marked differences in the spectral output, preventing the direct transfer of parameter models from one unit to another. Consequently, we have developed a method for standardizing the spectral output across units that utilizes physical, traceable, reference materials for aligning the wavelength and intensity axes to fixed values, followed by spectral normalization via Standard Normal Variate transformation. The approach employed in this study adjusts the slope and bias differences in the optical spectra across multiple units, without the loss of useful information needed for parameter estimation. In this study, phantoms containing Agar, intralipid and lyophilized human hemoglobin (met-hemoglobin) were used to mimic human tissue. Using PLS regression, a hemoglobin calibration model was developed on the tissue-like phantoms on a prototype of the portable NIR medical monitor. The calibration model was successfully transferred to a second, distinctly different system. The Root Mean Squared Error of Prediction of met-hemoglobin in the phantom samples measured in the second system, improved from 4.94g/dl to 1.15g/dl after the standardization procedure. This compares favorably the PLS model error on the primary instrument (0.94g/dl).
A visible-near IR (500-1,000nm) fiber optic sensor is under development that is intended to non-invasively assess muscle metabolism through the measurement of tissue pH and oxygen partial pressure. These parameters are calculated from the spectra of hemoglobin and myoglobin in muscle. The sensor consists of transmit (illumination) fibers and receive (detection) fibers that are coupled to a spectrometer. Light from the probe must penetrate below the surface of the skin and into a 5-10mm thick layer of muscle. A study was conducted to quantify the relationship between transmit and receive fiber separation and sensor penetration depth below the surface of the skin. A liquid phantom was created to replicate the absorption (μa) and reduced scatter coefficient (μs') profiles typically found in human blood and tissue. The phantom consisted of a solution of Intralipid and India ink in the appropriate concentrations to achieve desired reduced scatter coefficient and absorption profiles. The reduced scatter coefficient of the liquid phantom was achieved to an accuracy of +/-10% compared to previously published data. A fixed illumination fiber and translatable detector fiber were placed in the liquid phantom, and the fiber separation was varied from 3-40mm. Values of μa and μs' varied from 0.03-0.40 cm-1 and 5.0-15.0 cm-1 respectively. Results from the experiment demonstrate a strong correlation between penetration depth and fiber separation. Additionally, it was found that penetration depth was not substantially influenced by absorption and scatter concentration. As signal-to-noise is an important parameter in many non-invasive biomedical applications, the relative signal as a function of fiber separation was determined to follow an exponential relationship.
Despite major advances in cardiovascular science and technology during the past three decades, approximately half of all myocardial infarctions and sudden deaths occur unexpectedly. It is widely accepted that coronary atherosclerotic plaques and thrombotic complications resulting from their rupture or erosion are the underlying causes of this major health problem. The majority of these vulnerable plaques exhibit active inflammation, a large necrotic lipid core, a thin fibrous cap, and confer a stenosis of less than 70%. These lesions are not detectable by stress testing or coronary angiography. Our group is exploring the possibility of a functional classification based on physiological variables such as plaque temperature, pH, oxygen consumption, lactate production etc. We have shown that heat accurately locates the inflamed plaques. We also demonstrated human atherosclerotic plaques are heterogeneous with regard to pH and hot plaques and are more likely to be acidic. To develop a nonsurgical method for locating the inflamed plaques, we are developing both IR fiber optic imaging and NIR spectroscopic systems in our laboratory to detect hot and acidic plaque in atherosclerotic arterial walls. Our findings introduce the possibility of an isolated/combined IR and NIR fiber optic catheter that can bring new insight into functional assessment of atherosclerotic plaque and thereby detection of active and inflamed lesions responsible for heart attacks and strokes.
The liver has been identified as an ideal site to spectroscopically monitor for changes in oxygen saturation during liver transplantation and shock because it is susceptible to reduced blood flow and oxygen transport. Near-IR spectroscopy, combined with multivariate calibration techniques, has been shown to be a viable technique for monitoring oxygen saturation changes in various organs in a minimally invasive manner. The liver has a dual system circulation. Blood enters the liver through the portal vein and hepatic artery, and leaves through the hepatic vein. Therefore, it is of utmost importance to determine how the liver NIR spectroscopic information correlates with the different regions of the hepatic lobule as the dual circulation flows from the presinusoidal space into the post sinusoidal region of the central vein. For NIR spectroscopic information to reliably represent the status of liver oxygenation, the NIR oxygen saturation should best correlate with the post-sinusoidal region. In a series of six pigs undergoing induced hemorrhagic chock, NIR spectra collected from the liver were used together with oxygen saturation reference data from the hepatic and portal veins, and an average of the two to build partial least-squares regression models. Results obtained from these models show that the hepatic vein and an average of the hepatic and portal veins provide information that is best correlate with NIR spectral information, while the portal vein reference measurement provides poorer correlation and accuracy. These results indicate that NIR determination of oxygen saturation in the liver can provide an assessment of liver oxygen utilization.
Tissue pH electrodes have been used in research and in humans to evaluate various myocardial protection methods during heart surgery. Near IR spectroscopic measurement of myocardial tissue pH is a feasible, minimally invasive method that can be used to identify regional areas of ischemia and provide the surgeon with information continuously and postoperatively. Inhomogeneous, depth dependent tissue pH levels in ischemic myocardium make a robust in-vivo optical measurement challenging. Tissue heterogeneity requires a well-defined optical probe geometry capable of detecting light with adequate localization. Monte Carlo modeling of light propagation for purely scattering and relevant absorbing and scattering media were use4d to identify possible source-detector fiber separations for a matched boundary. In the region approximately 0.3 to 0.8 mm away from the source, the models demonstrated that minimization of the wavelength dependence of scattering is possible. Wavelength dependence is apparent at separations greater than approximately 1.2 mm. Adequate localization of NIR light is tissue is feasible within this source-detector separation range based on the simulations with hemoglobin as the only absorber. The application to a small fiber sensor's fabrication is discussed.
Body-worn noninvasive physilogical sensors are needed to continuously monitor soldiers for hemorrhage and to provide real-time information for minimally skilled medics to treat the injured. In the hospital intramucosal pHi of the gut is used to monitor shock and its treatment. We hypothesize that abdominal wall muscle (AWM) pH can be measured noninvasively using near infrared (NIR) spectroscopy and partial least squares analysis (PLS) and will correlate with pHi. METHODS: AWM pH was measured with microelectrodes and gastric pHi was measured with a tonometric catheter simultaneously while NIR spectra were collected using prototype LED spectrometers placed on the pig's flanks. Animals were subject to hemorrhagic shock at 45 mm Hg for 45 minutes, then resuscitated with blood and lactated ringers. Relationships between electrode pH, pHi and NIR spectra were developed using PLS with cross validation. RESULTS: NIR spectral changes noninvasively acquired through the skin were shown to be from the muscle, not from changes in skin blood flow. Trending ability (R2) model accuracy (RMSD), and relative error were calculated for individual pigs. Using electrode pH as the reference, average R2 was 0.88 with a predicted accuracy of 0.17 pH units, a 9.3% relative error. Slightly degraded results were observed when pHi was used as a reference. CONCLUSIONS: NIR measurement of tissue pH can be used to noninvasively monitor for shock and guide its treatment in a swine model. These measurements correlate with gastric pHi, a clinically accepted measure of shock, providing an approach to develop similar methodology for humans.
KEYWORDS: Ischemia, Blood circulation, Tissues, Body temperature, Temperature metrology, Calibration, Data modeling, Animal model studies, Blood, Near infrared
It has been shown that near-infrared spectroscopy is a feasible technique to non-invasively measure tissue pH in vivo. Since this technique relies on pH-induced changes in heme protein spectra, other factors that affect those spectra were investigated. In this study, the correlation between spectra collected from the bowel (575 - 1100 nm) with local tissue temperature and blood flow were investigated simultaneously with pH changes during eight independent swine hemorrhagic shock experiments.
Hematocrit (Hct) is one of the most important parameters to monitor when the patient has large blood loss or blood dilution. The current standard method for measuring hematocrit is off-line and invasive. An accurate, continuous, and noninvasive method of measuring hematocrit is highly desired for physicians to response rapidly in life-threatening situations. A set of instrumental characterization experiments was performed to assess the effects of spectrometer drift and probe placement on patient's forearm. Several factors were investigated in order to minimize the patient-dependent offset encountered in a previous study.
Nitric oxide (NO), in concentrations between 0 and 20 ppm, is currently being used as an inhaled agent to treat patients with post surgical complications and respiratory disorders. Because excessive levels of NO can be detrimental to the patient, NO must be monitored accurately and continuously. Currently available instruments have problems that limit their usefulness for this application. This paper discusses the development of an inexpensive, direct and continuous sensor for the measurement of inhaled nitric oxide. The sensor incorporates a 0.05 inch, gas permeable, flow-through liquid cell into a probe, which can be incorporated into a ventilator circuit. Sensor operation is based on the complexation reaction of NO with cytochrome-c, a biologically derived heme. The complex is monitored spectrophotometrically by measuring the absorbance in the visible region of the spectrum at 563 nm. The sensor is specific to NO in the presence of oxygen. This paper will address experiments to optimize sensitivity of the sensor. Increasing the flow rate and pressure of NO into the sensing chamber increased the optical absorbance at a high concentration of NO. Increasing the concentration of cytochrome-c increased the sensitivity of the sensor. The sensor is currently sensitive to a minimum concentration of 5 ppm and linear in the range of 5 to 175 ppm.
pH electrodes have been used during open heart surgery to ensure adequate delivery of blood and oxygen to the myocardium during the surgical procedure. The electrodes are cumbersome and suffer from motion artifacts. Near infrared spectroscopy was evaluated as a noninvasive method of measuring myocardial pH during regional ischemia in seven beating dog hearts. Two pH microelectrodes were implanted in the distribution area of the left anterior descending (LAD) coronary artery. The LAD was occluded to stop the myocardial blood flow and to initialize regional ischemia. Ischemia was maintained for 20 minutes before the LAD was released to resume blood flow. A fiber-optic probe was used to collect the reflected NIR light over the spectral region of 575 nm to 1100 nm from the heart muscle. Partial least-squares multivariate calibration technique was applied to relate the myocardial pH changes to the NIR spectral changes in the region of 700 to 1100 nm. Calibration models based on data collected on each individual dog heart had an average of 7 factors with an R2 of 0.84. The standard error of prediction (SEP) averaged 0.09 pH units for a mean pH change of 0.73 pH units, adequate for monitoring pH changes during cardiac surgery.
Tissue pH is an important physiological parameter which indicates both blood flow and cell metabolic state. Continuous monitoring of tissue pH can provide an assessment of the level of anaerobic metabolism and a measure of whether organs or muscles are revivable or have died. A noninvasive, optical technique for deep tissue pH determination has been demonstrated in-vivo using near infrared (NIR) spectroscopy and partial least-squares (PLS) multivariate calibration. NIR reflectance spectra (700 - 1100 nm) were collected from skin covered muscle in a rabbit, canine myocardium, and swine bowel along with reference pH values measured in the same tissue using microelectrodes. Muscle and myocardial pH were varied by controlling the blood supply through vessel occlusion; bowel pH was altered through hemorrhagic shock. PLS cross- validation techniques and data preprocessing methods were used to relate the tissue pH to spectra. The standard error of prediction for each of the multivariate calibrations was less than 13% of the average pH change in each of the animal models. Optically measured tissue pH promises to provide a noninvasive monitor for ischemia during heart and plastic surgery and an early indicator of shock in the ICU patient.
Nitric Oxide is a simple gaseous compound which serves as a regulatory molecule in a number of physiological processes. Due to its biological role as a potent local vasodilator,there has been widespread interest in the therapeutic use of gaseous nitric oxide a selective pulmonary vasodilator. Our goal is the development of a sensor for the direct and continuous measurement of inhaled nitric oxide concentrations. This study evaluated the reversibility of potential sensing compounds upon reaction with nitric oxide. Previously, absorption spectroscopy was used to study the sensitivity of the Fe II, Fe III and oxygenated forms of three biologically active hemes known to rapidly react with NO: hemoglobin, myoglobin, and cytochrome-c. This study focused on the photo-reversibility of the hem's reaction with nitric oxide. Hemoglobin, myoglobin and cytochrome-c in the Fe III state reversibly reacted with nitric oxide. Hemoglobin and myoglobin in the Fe II state non-reversibly reacted with nitric oxide to form an unstable product. Cytochrome-c (FeII) does not react with nitric oxide. The oxy forms of hemoglobin and myoglobin react with nitric oxide to form their respective met forms, unreversible via photolysis. For all reversible reactions, photolysis was gradual and complete within five minutes.
Nitric oxide (NO) is an important regulatory molecule in physiological processes including neurotransmission and the control of blood pressure. It is produced in excess during septic shock, the profound hypotensive state which accompanies severe infections. In-vivo measurement of NO would enhance the understanding of its varied biological roles. Our goal is the development of an intravascular fiber-optic sensor for the continuous measurement of NO. This study evaluated nitric oxide sensitive compounds as potential sensing materials in the presence and absence of oxygen. Using absorption spectroscopy we studied both the Fe II and Fe III forms of three biologically active hemes known to rapidly react with NO: hemoglobin, myoglobin, and cytochrome-c. The Fe II forms of hemoglobin and myoglobin and the Fe III form of cytochrome-c were found to have the highest sensitivity to NO. Cytochrome c (Fe III) is selective for NO even at high oxygen levels, while myoglobin is selective only under normal oxygen levels. NO concentrations as low as 1 (mu) M can be detected with our fiber-optic spectrometer using cytochrome c, and as low as 300 nM using myoglobin. Either of these materials would be adequate to monitor the increase in nitric oxide production during the onset of septic shock.
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