Name: non-invasive optical measurement of cerebral metabolism and hemodynamics in infants
Uploaded: 2013-03-14T09:20:00
Duration: 11 min 39 s
Description: Watch this Scientific Journal Video about Non-invasive Optical Measurement of Cerebral Metabolism and Hemodynamics in Infants at JoVE.com

The authors thank all the families for their participation in this study and the nurses, physicians, and staff in the Neonatal ICU, the Special Care Nursery, Pediatric Neurology, and the maternity units at Massachusetts General Hospital, Brigham and Women's Hospital and Boston Children's Hospital for their help and support. In particular we thank Linda J. Van Marter, Robert M. Insoft, Jonathan H. Cronin, Julianne Mazzawi, and Steven A. Ringer. The authors also thank Marcia Kocienski-Filip, Yvonne Sheldon, Alpna Aggarwall, Maddy Artunguada and Genevieve Nave for their assistance during measurements. This project is supported by NIH R01-HD042908, R21- HD058725, P41- RR14075 and R43-HD071761. Marcia Kocienski-Filip and Yvonne Sheldon are supported by the Clinical Translational Science Award UL1RR025758 to Harvard University and Brigham and Women's Hospital from the National Center for Research Resources. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Center for Research Resources or the National Institutes of Health.

1. Preparation for Bedside Measures
<ol>
	<li>The FDNIRS and the DCS systems are compact and easy to move on a small cart to the infant's bedside in the hospital (Figure 1).</li>
	<li>After moving the cart with the devices to the bedside, turn on the systems and connect the optical probe to the FDNIRS and DCS devices. Ensure that two experimenters are present for every measurement: one to manage the instruments and computer, and one to hold the probe.</li>
	<li>Choose the appropriate probe according to the infant's postmenstrual age (PMA). The optical probe with FDNIRS source-detector separations of 1, 1.5, 2 and 2.5 cm is used for infants &lt;37 wks PMA and the probe with FDNIRS separations 1.5, 2, 2.5 and 3 cm is used for older infants (Figure 2-A). The choice of shorter source-detector separations is dictated by preterm infants' small size and larger head curvature. When using a larger probe with a preterm infant, the relatively smaller size of the baby's head and its significant curvature together impede effective contact between the infant's head and all sources and detectors. For this reason, the probe with FDNIRS source-detector separations of 1, 1.5, 2 and 2.5 cm is fitting for use with preterm infants. Our research has verified that the chosen source-detector separations are sufficient to measure optical properties of the cerebral cortex of both preterm and term 14. DCS source and detector fibers are arranged in a row parallel to the FDNIRS fibers with source-detector distances of 1.5 (one detector) and 2 cm (three detectors) in both premature and term infants probes.</li>
	<li>Sanitize the optical probes with a Sani-cloth disinfecting wipe and insert the probe and fibers into a single-use polypropylene plastic sleeve.</li>
</ol>
2. FDNIRS Gain Settings and Calibration
<ol>
	<li>Open the FDNIRS Graphical User Interface (GUI) and select the program settings file corresponding to the probe and calibration block being used.</li>
	<li>To adjust detector gains, gently place the probe on an area of the subject's head without hair (preferably the left side of the forehead) and maintain it in the same position without applying any pressure. Turn on sources and detectors and adjust PMT voltage until the amplitude of any of the source lasers reaches 20,000 counts. 32,000 counts is the maximum digitization of the analog to digital acquisition card, and gains need to be set below that threshold to avoid saturation during data acquisition. The gains should be set in the frontal area because this region generally has the lowest absorption of laser light and is therefore most prone to saturation.</li>
	<li>Turn off the sources and detectors and return the probe to the calibration block. The lasers need to be turned off when moving the probe for eye safety; the detectors need to be turned off because PMTs are very sensitive and exposure to any bright light increases background noise and may permanently damage them.</li>
	<li>With the probe back on the calibration block, use the neutral density (ND) filter if any source-detector pair saturates. Different ND filters may be selected due to optimizing gains in infants with different skin tones Hold the probe still for 16 sec while running the calibration procedure. Since we do not physically move one source to different distances from a single detector to achieve a multi-distance scheme, but instead use four combinations of two independent sources and two independent detectors, we need to calibrate for the different power of the two sources and the different gains of the two detectors. By measuring a calibration block of known optical properties, we estimate the amplitude and phase correction factors needed to recover the absorption and scattering coefficients of the calibration block.</li>
	<li>After calibration, acquire 16 more sec of data on the block and visually assess the adequacy of the calibration with an in-house MATLAB GUI. The measured &mu;a and &mu;s' should match the actual coefficients of the calibration block at all wavelengths. Recalibrate if the fit is poor.</li>
	<li>If detector gains need to be changed, or source and detector fibers need to be disconnected during measurements, repeat the calibration procedure of the FDNIRS device.</li>
	<li>At the end of the measurement session, acquire another 16 sec of data on the calibration block to verify whether the calibration was maintained during measurements on the subject. If the calibration has not been maintained, take a second calibration at the end of the measurement and apply to the acquired data.</li>
</ol>
3. DCS Settings
<ol>
	<li>Open the in-house DCS data acquisition GUI and load the settings file corresponding to the optical probe being used.</li>
	<li>Before starting measurements, verify that the laser power of the DCS source is appropriate for skin exposure by measuring the laser power of the DCS source with a power meter and checking the spot size with an IR viewing card (the laser emits at 785 nm, which is not visible). The DCS laser power is ~60 mW and coupled to a relatively small diameter fiber (400-600 &mu;m). To meet ANSI standards for skin exposure, the light at the probe must be attenuated and diffused across a large area. This is achieved by covering the tip of the fiber with a 3 mm diameter white Teflon sheet (Figure 2-A). The Teflon is highly scattering and widely diffuses the laser beam. At the bedside, ensure that the laser power at the probe is less than 25 mW and the spot size is larger than 3 mm in diameter. As for the FDNIRS, always turn off sources and detectors when moving the optical probe.</li>
	<li>DCS detection is photon-counting and there is no APD gain adjustment as is required for the FDNIRS device. A flag in the acquisition software indicates if too much light is detected, in which case light coupling to either source or detector fibers needs to be reduced by turning the fiber connectors. Adequate light detection is on the range of 200,000-4,000,000 detected photons (corresponding to -26~0 dB on the computer display). Avoid excessive room light to reduce background noise.</li>
	<li>The DCS does not require calibration to measure CBFi. Blood flow is proportional to the time it takes to lose correlation. A solid block does not suffice to check signal quality because there are no moving scattering particles to cause decay. An experimenter's arm instead shows decay -- the faster the blood flow, the steeper the decay.</li>
</ol>
4. Data Acquisition
<ol>
	<li>While FDNIRS and DCS measurements can be done quickly in sequence, first measure all locations with one device and then repeat the same progression with the other device, using independent acquisition software corresponding to each.</li>
	<li>Measure seven locations covering frontal, temporal and parietal areas, according to a 10-20 system (Fp1, FpZ, FP2, C3, C4, P3, P4), in sequence (Figure 2-B). Part the hair along the source-detector line and place the probe on that area of the head.</li>
	<li>Turn on FDNIRS lasers and detectors and check the signal quality: amplitude counts should be between 2,000 and 20,000 and phase shifts SNR &lt;2 degrees. If outside of these ranges, reposition the probe, ensuring hair is parted and all sources and detectors are in contact with the skin.</li>
	<li>Acquire data for 16 sec. Repeat measurements up to three times in each location (Figure 2-C), parting the hair and repositioning the probe in a slightly different spot for each acquisition. This is done to minimize effect of local inhomogeneities such as hair and superficial large vessels and to provide values representative of a region, rather than a single spot.</li>
	<li>Turn on the DCS laser and detectors and acquire data for 10 sec. Reposition the probe and repeat the acquisitions (as with the FDNIRS measures).</li>
	<li>Turn off all lasers when moving the probe between locations. Data collection in all seven locations is not always possible. Discontinue measurements if the subject manifests any sign of distress or motion. Retry the acquisition if possible. EEG electrodes or respiratory equipment may also preclude measurements in some locations.</li>
</ol>
5. Measure of Systemic Parameters
<ol>
	<li>For the calculation of CMRO2i, two systemic parameters, arterial oxygenation (SaO2) and hemoglobin in the blood (HGB), must be acquired. HGB is also needed to calculate CBV. While conventional pulse oximetry provides measures of SaO2, HGB is conventionally measured with a blood test. A new pulse oximeter, developed by Masimo Corporation, is able to measure HGB non-invasively by using multiple wavelengths. The device is FDA-approved for infants &gt;3 kg, and allows for a quick bedside measure of both SaO2 and HGB.</li>
	<li>Record SaO2 and HGB using a Masimo pulse oximeter (Pronto spot check pulse co-oximeter). For these measurements, attach an adhesive single-use sensor to the big toe of the baby's foot. HGB will be displayed on the monitor within a few seconds.</li>
	<li>When it is not possible to use the Masimo pulse co-oximeter, measure SaO2 with other FDA-approved pulse oximeters. HGB can be either recovered from patients' clinical charts or estimated using normative values.</li>
</ol>
6. Data Analysis
<ol>
	<li>Open an in-house post-processing data analysis GUI using MATLAB. This software not only estimates all hemodynamic parameters, but also uses the redundancy of data to automatically assess measurement quality and constrain results.</li>
	<li>Automatic objective criteria for quality control consist of discarding data for FDNIRS if: R2 &lt; 0.98 for the model fit of the experimental data, p-value &gt; 0.02 for the Pearson product moment correlation coefficient between the eight measured absorption coefficients and the hemoglobin fit (Figure 3-A), p-value &gt; 0.02 for the linear fit of the reduced scattering coefficients versus wavelength (Figure 3-B) 15. If more than 33 percent of the data merits discarding, the whole set is discarded. For the DCS, data is discarded if: the tail of the fitting curve differs from 1 by more than 0.02, the cumulative variation among the 3 first points of the curve is more than 0.1, or the average value of the 3 first points is more than 1.6 (Figure 4). If more than 50 percent of curves are discarded, or the fit values have a coefficient of variation &gt; 15 percent, the whole set is discarded15.</li>
	<li>Calculate absolute HbO and HbR concentrations by fitting the absorption coefficients at all wavelengths, using literature values for Hb extinction coefficients 16 and a 75 percent concentration of water in tissue 17. Derive total hemoglobin concentration (HbT = HbO + HbR) and SO2 (HbO / HbT) from HbO and HbR concentrations.</li>
	<li>Estimate cerebral blood volume using the equation described in Ijichi et al 18. CBV= (HbT &times; MWHb) / (HGB &times; Dbt), where MWHb = 64,500 [g/Mol] is the molecular weight of Hb, and Dbt = 1.05 g/ml is the brain tissue density.</li>
	<li>Calculate CBFi by fitting the measured temporal autocorrelation functions to the diffusion correlation equation. The detailed theoretical framework to calculate CBFi is in Boas et al. and Boas and Yodh 10,11. In the equations, use individual absorption coefficients measured from FDNIRS and an average of the scattering coefficients across the whole population.</li>
	<li>Calculate the index of cerebral oxygen consumption by using the FDNIRS measure of SO2 and the DCS measure of CBFi with the following equation: CMRO2i = (HGB &times; CBFi &times; (SaO2 - SO2)) / (4 &times; MWHb &times; &beta;)15, where the factor 4 reflects the four O2 molecules bound to each hemoglobin and &beta; is the percent contribution of the venous compartment to the hemoglobin oxygenation measurement 19.</li>
</ol>

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Maria Angela Franceschini, her husband David Boas, and Beniamino Barbieri (ISS Inc) hold patents on this technology.

We demonstrated a quantitative measurement of cerebral hemodynamic and metabolism with FDNIRS and DCS in the neonatal population. The probe configuration is optimized for measuring neonatal cerebral cortex 14. Blood flow changes measured by DCS have been extensively validated against other techniques in animal and human studies 22,23. By using a direct DCS measure of blood flow, we are able to reduce the variance in the calculation of CMRO2i 24. The variance from repeated measures was also smaller than the changes between brain regions and with age 20.
From our previous results, CBFi and CMRO2i showed significant changes with PMA in healthy preterm neonates. The measure of CMRO2i is better able to detect brain damage than the measure of SO2. This suggests that combined measures of vascular and metabolic parameters serve as more robust biomarkers of neonatal brain health and development than oxygen saturation alone. Technical improvements will focus on the integration of two instruments to reduce acquisition time 35-40% per session and the implementation of real-time feedback on data quality to reduce the frequency of discarded measures. In the near future, this system can be delivered to clinical end-users as a novel bedside monitor of altered cerebral oxygen metabolism. By measuring trajectories of CMRO2 over time may also increase clinical significance and predict outcomes. This tool could ultimately make a significant contribution towards improved management of neonatal brain injury.

The FDNIRS device is a customized frequency-domain system from ISS Inc. with two identical sets of 8 laser diodes emitting at eight wavelengths ranging from 660 to 830 nm, and two photomultiplier tube (PMT) detectors. Sources and detectors are modulated at 110 MHz and 110 MHz plus 5 kHz, respectively, to achieve heterodyne detection 6. Each laser diode is turned on for 10 msec in sequence, for a 160 msec total acquisition time per cycle. Sources and detectors are coupled to fiber optics and arranged in a row in an optical probe. The arrangement of fibers on the probe is such that it produces four different source-detector separations. By measuring transmitted light (amplitude attenuation and phase shift) at multiple distances, we can quantify the absorption (&mu;a) and scattering (&mu;s') coefficients of the tissue under observation. From the absorption coefficients at multiple wavelengths, we then estimate the absolute values of oxygenated (HbO) and deoxygenated (HbR) hemoglobin concentrations 7, cerebral blood volume (CBV) and hemoglobin oxygen saturation (SO2).
The DCS device is a home-built system similar to the one developed by Drs. Arjun Yodh and Turgut Durduran at the University of Pennsylvania 8,9. The DCS system that consists of a solid-state, long coherence laser at 785 nm, four photon-counting avalanche photodiode (APD) detectors (EG&amp;G Perkin Elmer SPCM-AQRH) featuring low dark counts (&lt;50 counts/sec) and a high quantum yield (&gt;40% at 785 nm), and a four channel, 256-bin multi-tau correlator, with 200 nsec resolution. With the DCS we measure microvascular blood flow in cerebral cortex by quantifying the temporal intensity fluctuations of multiply scattered light that arises from Doppler shifts produced by moving red blood cells. The technique, similar to laser Doppler blood flowmetry (i.e. they are Fourier Transform analogs), measures an autocorrelation function of the intensity fluctuations of each detector channel computed by a digital correlator over a delay time range of 200 nsec - 0.5 sec. The correlator computes the temporal intensity auto-correlation of the light re-emerging from tissue. We then fit the diffusion correlation equation to the measured autocorrelation function, acquired sequentially, about once per second, to obtain the blood flow index (CBFi) 10,11. DCS measures of blood flow changes have been extensively validated 12,13. By combining the FDNIRS measures of SO2 with the DCS measures of CBFi, we achieve an estimate of cerebral oxygen metabolism (CMRO2i).

<table border="1">
 <tbody>
 <tr>
 <td>Equipment</td>
 <td>Company</td>
 <td>Catalogue number</td>
 <td>Comments (optional)</td>
 </tr>
 <tr>
 <td>Imagent</td>
 <td>ISS</td>
 <td></td>
 <td>FDNIRS</td>
 </tr>
 <tr>
 <td>DCS laser fibers</td>
 <td>Thorlabs</td>
 <td>FT400 </td>
 <td>DCS component</td>
 </tr>
 <tr>
 <td>DCS detector fiber</td>
 <td>Thorlabs</td>
 <td>780HP</td>
 <td>DCS component</td>
 </tr>
 <tr>
 <td>DCS laser</td>
 <td>CrystaLaser</td>
 <td>DL785-070-S </td>
 <td>DCS component</td>
 </tr>
 <tr>
 <td>DCS detector</td>
 <td>Pacer International </td>
 <td>SPCM-AQRH-14-FC</td>
 <td>DCS component</td>
 </tr>
 <tr>
 <td>DCS Correlator</td>
 <td>Correlator.com</td>
 <td>Flex05-8ch</td>
 <td>DCS component</td>
 </tr>
 <tr>
 <td>Pronto co-oximeter</td>
 <td>Masimo</td>
 <td></td>
 <td>HGB and SaO2 monitor</td>
 </tr>
 <tr>
 <td>NOVA</td>
 <td>OPHIR</td>
 <td>7Z01500</td>
 <td>Laser power meter</td>
 </tr>
 <tr>
 <td>Sensor card</td>
 <td>Newport</td>
 <td>F-IRC1-S</td>
 <td>IR viewer</td>
 </tr>
 <tr>
 <td>Neutral Density filter</td>
 <td>Kodak</td>
 <td>NT54-453</td>
 <td></td>
 </tr>
 </tbody>
</table>

non-invasive optical measurement of cerebral metabolism and hemodynamics in infants

Perinatal brain injury remains a significant cause of infant mortality and morbidity, but there is not yet an effective bedside tool that can accurately screen for brain injury, monitor injury evolution, or assess response to therapy. The energy used by neurons is derived largely from tissue oxidative metabolism, and neural hyperactivity and cell death are reflected by corresponding changes in cerebral oxygen metabolism (CMRO2). Thus, measures of CMRO2 are reflective of neuronal viability and provide critical diagnostic information, making CMRO2 an ideal target for bedside measurement of brain health.
Brain-imaging techniques such as positron emission tomography (PET) and single-photon emission computed tomography (SPECT) yield measures of cerebral glucose and oxygen metabolism, but these techniques require the administration of radionucleotides, so they are used in only the most acute cases.
Continuous-wave near-infrared spectroscopy (CWNIRS) provides non-invasive and non-ionizing radiation measures of hemoglobin oxygen saturation (SO2) as a surrogate for cerebral oxygen consumption. However, SO2 is less than ideal as a surrogate for cerebral oxygen metabolism as it is influenced by both oxygen delivery and consumption. Furthermore, measurements of SO2 are not sensitive enough to detect brain injury hours after the insult 1,2, because oxygen consumption and delivery reach equilibrium after acute transients 3. We investigated the possibility of using more sophisticated NIRS optical methods to quantify cerebral oxygen metabolism at the bedside in healthy and brain-injured newborns. More specifically, we combined the frequency-domain NIRS (FDNIRS) measure of SO2 with the diffuse correlation spectroscopy (DCS) measure of blood flow index (CBFi) to yield an index of CMRO2 (CMRO2i) 4,5.
With the combined FDNIRS/DCS system we are able to quantify cerebral metabolism and hemodynamics. This represents an improvement over CWNIRS for detecting brain health, brain development, and response to therapy in neonates. Moreover, this method adheres to all neonatal intensive care unit (NICU) policies on infection control and institutional policies on laser safety. Future work will seek to integrate the two instruments to reduce acquisition time at the bedside and to implement real-time feedback on data quality to reduce the rate of data rejection.

In the past five years we have demonstrated the feasibility and clinical utility of the proposed method. In particular, we have shown CMRO2 to be more representative of brain health and development than SO2.
In a cross-sectional study on more than 50 healthy infants, we found that while CBV is more than double during the first year of life, SO2 remains constant 4 (Figure 5). In a study on 70 healthy newborns we also found that SO2 is constant across brain regions while CMRO2i, CBV and CBF are higher in temporal and parietal regions than in the frontal region (Figure 6)20, which is consistent with PET glucose uptake findings 21. In both of our studies, the constant SO2, within a 60-70 percent range indicates that oxygen delivery closely matches local consumption, while CBV, CBF and CMRO2 are more tightly coupled with neural development.
To verify that CMRO2i is a better screening tool than SO2 in detecting neonatal brain injury, we measured brain injured infants during the acute phase 5, and (in a few infants) during the chronic phase several months after injury. Results in Figure 7 show how SO2 is not significantly altered by brain injury in both early (1-15 days after insult) and chronic (months after injury) stages, while CMRO2i is significantly different than normal during both the acute and chronic stages. Specifically, CMRO2i is elevated during the acute phase because of seizure activity after brain injury, and lower than normal during the chronic phase due to neuronal loss.
Infants with hypoxic ischemic injuries are currently treated with therapeutic hypothermia (TH) to lower brain metabolism and reduce damage after the hypoxic insult. Therapeutic hypothermia is maintained for three days and we have been able to monitor 11 infants during treatment (Figure 8). We found that CMRO2i significantly decreases to levels below normal during TH, and this decrease seems to be related to response to therapy and developmental outcome. These preliminary results suggest that the FDNIRS-DCS method may be able to guide and optimize hypothermia therapy.
<img alt="Figure 1" src="/files/ftp_upload/4379/4379fig1.jpg" /> 
 Figure 1. Picture of the cart with the FDNIRS and DCS devices. The two instruments are compact enough to fit on a small cart that can be moved to the infant's bedside in the NICU.
<img alt="Figure 2" src="/files/ftp_upload/4379/4379fig2.jpg" /> 
 Figure 2. (A) Optical probe configuration. (B) The measurement location scheme. (C) A photo of a typical FDNIRS-DCS measurement on an infant.
<img alt="Figure 3" fo:content-width="5in" fo:src="/files/ftp_upload/4379/4379fig3highres.jpg" src="/files/ftp_upload/4379/4379fig3.jpg" /> 
 Figure 3. Representative examples of good and bad fit of measured (A) absorption coefficients and the hemoglobin fit (B) scattering coefficients and the linear fit. P-value &gt; 0.02 refers to a bad fit. <a href="https://www.jove.com/files/ftp_upload/4379/4379fig3large.jpg" target="_blank">Click here to view larger figure</a>.
<img alt="Figure 4" src="/files/ftp_upload/4379/4379fig4.jpg" /> 
 Figure 4. A representative example of good and bad fit of an autocorrelation function of the intensity fluctuations computed by a correlator over a delay time range of 200 nsec - 0.5 sec. In the bad fit figure the tail of the fitting curve differs from 1 by more than 0.02 and the variation of the 3 first points is more than 0.1. <a href="https://www.jove.com/files/ftp_upload/4379/4379fig4large.jpg" target="_blank"> Click here to view larger figure</a>.
<img alt="Figure 5" fo:content-width="4in" fo:src="/files/ftp_upload/4379/4379fig5highres.jpg" src="/files/ftp_upload/4379/4379fig5.jpg" /> 
 Figure 5. Changes in CBV and SO2 across frontal, temporal and parietal cortical regions in infants from birth to one year of age.
<img alt="Figure 6" fo:content-width="4in" fo:src="/files/ftp_upload/4379/4379fig6highres.jpg" src="/files/ftp_upload/4379/4379fig6.jpg" /> 
 Figure 6. CBF, SO2, CBV and CMRO2i of the frontal, temporal and parietal regions in 70 healthy newborns.
<img alt="Figure 7" src="/files/ftp_upload/4379/4379fig7.jpg" /> 
 Figure 7. Examples of abnormal oxygen consumption and normal SO2 after brain injury in infants. Brain injury is marked by changes in CMRO2 with respect to normal while SO2 is not significantly different from normal. Please note that in these two figures, CMRO2 was calculated using the Grubb relationship, because the DCS measure was not available at the time of those measurements.
<img alt="Figure 8" src="/files/ftp_upload/4379/4379fig8.jpg" /> 
 Figure 8. rCMRO2 of 11 infants during therapeutic hypothermia vs. age-matched healthy controls. Oxygen metabolism is strongly reduced in all infants with hypothermia therapy.

Watch this Scientific Journal Video about Non-invasive Optical Measurement of Cerebral Metabolism and Hemodynamics in Infants at JoVE.com

Non-invasive Optical Measurement of Cerebral Metabolism and Hemodynamics in Infants

We combined frequency-domain near-infrared spectroscopy measures of cerebral hemoglobin oxygenation with diffuse correlation spectroscopy measures of cerebral blood flow index to estimate an index of oxygen metabolism. We tested the utility of this measure as a bedside screening tool to evaluate the health and development of the newborn brain.

Perinatal brain injury remains a significant cause of infant mortality  and morbidity, but there is not yet an effective bedside tool that can  accurately ...

non-invasive-optical-measurement-cerebral-metabolism-hemodynamics

Research

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Medicine

Corneal Confocal Microscopy: A Novel Non-invasive Technique to Quantify Small Fibre Pathology in Peripheral Neuropathies

The accurate quantification of peripheral neuropathy is important to define at risk patients, anticipate deterioration, and assess new therapies. Conventional methods assess neurological deficits and electrophysiology and quantitative sensory testing quantifies functional alterations to detect neuropathy. However, the earliest damage appears to be to the small fibres and yet these tests primarily assess large fibre dysfunction and have a limited ability to demonstrate regeneration and repair. The only techniques which allow a direct examination of unmyelinated nerve fibre damage and repair are sural nerve biopsy with electron microscopy and skin-punch biopsy. However, both are invasive procedures and require lengthy laboratory procedures and considerable expertise. Corneal Confocal microscopy is a non-invasive clinical technique which provides in-vivo imaging of corneal nerve fibres. We have demonstrated early nerve damage, which precedes loss of intraepidermal nerve fibres in skin biopsies together with stratification of neuropathic severity and repair following pancreas transplantation in diabetic patients. We have also demonstrated nerve damage in idiopathic small fibre neuropathy and Fabry's disease.

Corneal Confocal microscopy is a non-invasive clinical technique which may be used to quantify C fibre damage to diagnose and stratify patients with increasing neuropathic severity.

The accurate quantification of peripheral neuropathy is important to define at risk patients, anticipate deterioration, and assess new therapies. ...

An in vivo Rodent Model of Contraction-induced Injury and Non-invasive Monitoring of Recovery

Muscle strains are one of the most common complaints treated by physicians. A muscle injury is typically diagnosed from the patient history and physical exam alone, however the clinical presentation can vary greatly depending on the extent of injury, the patient's pain tolerance, etc. In patients with muscle injury or muscle disease, assessment of muscle damage is typically limited to clinical signs, such as tenderness, strength, range of motion, and more recently, imaging studies. Biological markers, such as serum creatine kinase levels, are typically elevated with muscle injury, but their levels do not always correlate with the loss of force production. This is even true of histological findings from animals, which provide a "direct measure" of damage, but do not account for all the loss of function. Some have argued that the most comprehensive measure of the overall health of the muscle in contractile force. Because muscle injury is a random event that occurs under a variety of biomechanical conditions, it is difficult to study. Here, we describe an in vivo animal model to measure torque and to produce a reliable muscle injury. We also describe our model for measurement of force from an isolated muscle in situ. Furthermore, we describe our small animal MRI procedure.

An in vivo Rodent Model of Contraction-induced Injury and Non-invasive Monitoring of Recovery

An in vivo animal model of injury is described. The method takes advantage of the subcutaneous position of the fibular nerve. Velocity, timing of muscle activation, and arc of motion are all pre-determined and synchronized using commercial software. Post injury changes are monitored in vivo using MR imaging/spectroscopy.

Muscle strains are one of the most  common complaints treated by physicians. A muscle injury is typically diagnosed from the patient history and  physical ...

Non-invasive Assessment of Microvascular and Endothelial Function

The authors have utilized capillaroscopy and forearm blood flow techniques to investigate the role of microvascular dysfunction in pathogenesis of cardiovascular disease. Capillaroscopy is a non-invasive, relatively inexpensive methodology for directly visualizing the microcirculation. Percent capillary recruitment is assessed by dividing the increase in capillary density induced by postocclusive reactive hyperemia (postocclusive reactive hyperemia capillary density minus baseline capillary density), by the maximal capillary density (observed during passive venous occlusion). Percent perfused capillaries represents the proportion of all capillaries present that are perfused (functionally active), and is calculated by dividing postocclusive reactive hyperemia capillary density by the maximal capillary density. Both percent capillary recruitment and percent perfused capillaries reflect the number of functional capillaries. The forearm blood flow (FBF) technique provides accepted non-invasive measures of endothelial function: The ratio FBFmax/FBFbase is computed as an estimate of vasodilation, by dividing the mean of the four FBFmax values by the mean of the four FBFbase values. Forearm vascular resistance at maximal vasodilation (FVRmax) is calculated as the mean arterial pressure (MAP) divided by FBFmax. Both the capillaroscopy and forearm techniques are readily acceptable to patients and can be learned quickly.
The microvascular and endothelial function measures obtained using the methodologies described in this paper may have future utility in clinical patient cardiovascular risk-reduction strategies. As we have published reports demonstrating that microvascular and endothelial dysfunction are found in initial stages of hypertension including prehypertension, microvascular and endothelial function measures may eventually aid in early identification, risk-stratification and prevention of end-stage vascular pathology, with its potentially fatal consequences.

Capillaroscopy is a non-invasive, relatively inexpensive methodology for directly visualizing the microcirculation. The forearm blood flow technique provides accepted non-invasive measures of endothelial function.

The authors have utilized capillaroscopy and forearm blood flow techniques to investigate the role of microvascular dysfunction in pathogenesis of ...

Non-invasive Imaging and Analysis of Cerebral Ischemia in Living Rats Using Positron Emission Tomography with 18F-FDG

Stroke is the third leading cause of death among Americans 65 years of age or older1. The quality of life for patients who suffer from a stroke fails to return to normal in a large majority of patients2, which is mainly due to current lack of clinical treatment for acute stroke. This necessitates understanding the physiological effects of cerebral ischemia on brain tissue over time and is a major area of active research. Towards this end, experimental progress has been made using rats as a preclinical model for stroke, particularly, using non-invasive methods such as 18F-fluorodeoxyglucose (FDG) coupled with Positron Emission Tomography (PET) imaging3,10,17. Here we present a strategy for inducing cerebral ischemia in rats by middle cerebral artery occlusion (MCAO) that mimics focal cerebral ischemia in humans, and imaging its effects over 24 hr using FDG-PET coupled with X-ray computed tomography (CT) with an Albira PET-CT instrument. A VOI template atlas was subsequently fused to the cerebral rat data to enable a unbiased analysis of the brain and its sub-regions4. In addition, a method for 3D visualization of the FDG-PET-CT time course is presented. In summary, we present a detailed protocol for initiating, quantifying, and visualizing an induced ischemic stroke event in a living Sprague-Dawley rat in three dimensions using FDG-PET.

Non-invasive Imaging and Analysis of Cerebral Ischemia in Living Rats Using Positron Emission Tomography with 18F-FDG

Brain damage resulting from cerebral ischemia may be non-invasively imaged and studied in rats using pre-clinical positron emission tomography coupled with the injectable radioactive probe, 18F-fluorodeoxyglucose. Further, the use of modern software tools that include volume of interest (VOI) brain templates dramatically increase the quantitative information gleaned from these studies.

Stroke is the third leading cause of death among Americans 65 years of age or older1. The quality of life for patients who suffer from a stroke fails to ...

Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence

Epithelial ovarian cancer is the most lethal gynecologic malignancy in the United States. Although patients initially respond to the current standard of care consisting of surgical debulking and combination chemotherapy consisting of platinum and taxane compounds, almost 90% of patients recur within a few years. In these patients the development of chemoresistant disease limits the efficacy of currently available chemotherapy agents and therefore contributes to the high mortality. To discover novel therapy options that can target recurrent disease, appropriate animal models that closely mimic the clinical profile of patients with recurrent ovarian cancer are required. The challenge in monitoring intra-peritoneal (i.p.) disease limits the use of i.p. models and thus most xenografts are established subcutaneously. We have developed a sensitive optical imaging platform that allows the detection and anatomical location of i.p. tumor mass. The platform includes the use of optical reporters that extend from the visible light range to near infrared, which in combination with 2-dimensional X-ray co-registration can provide anatomical location of molecular signals. Detection is significantly improved by the use of a rotation system that drives the animal to multiple angular positions for 360 degree imaging, allowing the identification of tumors that are not visible in single orientation. This platform provides a unique model to non-invasively monitor tumor growth and evaluate the efficacy of new therapies for the prevention or treatment of recurrent ovarian cancer.

We describe a non-invasive animal imaging platform that allows the detection, quantification, and monitoring of ovarian cancer growth and recurrence. This intra-peritoneal xenograft model mimics the clinical profile of patients with ovarian cancer.

Epithelial ovarian cancer is the most lethal gynecologic malignancy in the United States. Although patients initially respond to the current standard of ...

Multi-electrode Array Recordings of Human Epileptic Postoperative Cortical Tissue

Epilepsy, affecting about 1% of the population, comprises a group of neurological disorders characterized by the periodic occurrence of seizures, which disrupt normal brain function. Despite treatment with currently available antiepileptic drugs targeting neuronal functions, one third of patients with epilepsy are pharmacoresistant. In this condition, surgical resection of the brain area generating seizures remains the only alternative treatment. Studying human epileptic tissues has contributed to understand new epileptogenic mechanisms during the last 10 years. Indeed, these tissues generate spontaneous interictal epileptic discharges as well as pharmacologically-induced ictal events which can be recorded with classical electrophysiology techniques. Remarkably, multi-electrode arrays (MEAs), which are microfabricated devices embedding an array of spatially arranged microelectrodes, provide the unique opportunity to simultaneously stimulate and record field potentials, as well as action potentials of multiple neurons from different areas of the tissue. Thus MEAs recordings offer an excellent approach to study the spatio-temporal patterns of spontaneous interictal and evoked seizure-like events and the mechanisms underlying seizure onset and propagation. Here we describe how to prepare human cortical slices from surgically resected tissue and to record with MEAs interictal and ictal-like events ex vivo.

We here describe how to perform multi-electrode array recordings of human epileptic cortical tissue. Epileptic tissue resection, slice preparation and multi-electrode array recordings of interictal and ictal events are demonstrated in detail.

Epilepsy, affecting about 1% of the population, comprises a group of neurological disorders characterized by the periodic occurrence of seizures, which ...

A Methodological Approach to Non-invasive Assessments of Vascular Function and Morphology

The endothelium is the innermost lining of the vasculature and is involved in the maintenance of vascular homeostasis. Damage to the endothelium may predispose the vessel to atherosclerosis and increase the risk for cardiovascular disease. Assessments of peripheral endothelial function are good indicators of early abnormalities in the vascular wall and correlate well with assessments of coronary endothelial function. The present manuscript details the important methodological steps necessary for the assessment of microvascular endothelial function using laser Doppler imaging with iontophoresis, large vessel endothelial function using flow-mediated dilatation, and carotid atherosclerosis using carotid artery ultrasound. A discussion on the methodological considerations for each of the techniques is also presented, and recommendations are made for future research.

The present article describes the methodological considerations for several non-invasive assessments of vascular function and morphology that are commonly used in medical research to assess different stages of atherosclerosis.

The endothelium is the innermost lining of the vasculature and is involved in the maintenance of vascular homeostasis.  Damage to the endothelium may ...

Non-invasive Assessments of Subjective and Objective Recovery Characteristics Following an Exhaustive Jump Protocol

Fast recovery after strenuous exercise is important in sports and is often studied via cryotherapy applications. Cryotherapy has a significant vasoconstrictive effect, which seems to be the leading factor in its effectiveness. The resulting enhanced recovery can be measured by using both objective and subjective parameters. Two commonly measured subjective characteristics of recovery are delayed-onset muscle soreness (DOMS) and ratings of perceived exertion (RPE). Two important objective recovery characteristics are countermovement jump (CMJ) performance and peak power output (PPO). Here, we provide a detailed protocol to induce muscular exhaustion of the frontal thighs with a self-paced, 3 x 30 countermovement jump protocol (30-s rest between each set). This randomized controlled trial protocol explains how to perform local cryotherapy cuff application (+ 8 &#176;C for 20 min) and thermoneutral cuff application (+ 32 &#176;C for 20 min) on both thighs as two possible post-exercise recovery modalities. Finally, we provide a non-invasive protocol to measure the effects of these two recovery modalities on subjective (i.e., DOMS of both frontal thighs and RPE) and objective recovery (i.e., CMJ and PPO) characteristics 24, 48, and 72 h post-application. The advantage of this method is that it provides a tool for researchers or coaches to induce muscular exhaustion, without using any expensive devices; to implement local cooling strategies; and to measure both subjective and objective recovery, without using invasive methods. Limitations of this protocol are that the 30 s rest period between sets is very short, and the cardiovascular demand is very high. Future studies may find the assessment of maximum voluntary contractions to be a more sensitive assessment of muscular exhaustion compared to CMJs.

This protocol describes the procedure for non-invasive recovery assessments during a 72 h recovery period. This protocol induces muscular exhaustion of the frontal thighs using countermovement jumps and uses either local cold-cuff or thermoneutral-cuff application as a recovery modality.

Fast recovery after strenuous exercise is important in sports and is often studied via cryotherapy applications. Cryotherapy has a significant ...

Invasive Hemodynamic Monitoring of Aortic and Pulmonary Artery Hemodynamics in a Large Animal Model of ARDS

One of the leading causes of morbidity and mortality in patients with heart failure is right ventricular (RV) dysfunction, especially if it is due to pulmonary hypertension. For a better understanding and treatment of this disease, precise hemodynamic monitoring of left and right ventricular parameters is important. For this reason, it is essential to establish experimental pig models of cardiac hemodynamics and measurements for research purpose. 
This article shows the induction of ARDS by using oleic acid (OA) and consequent right ventricular dysfunction, as well as the instrumentation of the pigs and the data acquisition process that is needed to assess hemodynamic parameters. To achieve right ventricular dysfunction, we used oleic acid (OA) to cause ARDS and accompanied this with pulmonary artery hypertension (PAH). With this model of PAH and consecutive right ventricular dysfunction, many hemodynamic parameters can be measured, and right ventricular volume load can be detected. 
All vital parameters, including respiratory rate (RR), heart rate (HR) and body temperature were recorded throughout the whole experiment. Hemodynamic parameters including femoral artery pressure (FAP), aortic pressure (AP), right ventricular pressure (peak systolic, end systolic and end diastolic right ventricular pressure), central venous pressure (CVP), pulmonary artery pressure (PAP) and left arterial pressure (LAP) were measured as well as perfusion parameters including ascending aortic flow (AAF) and pulmonary artery flow (PAF). Hemodynamic measurements were performed using transcardiopulmonary thermodilution to provide cardiac output (CO). Furthermore, the PiCCO2 system (Pulse Contour Cardiac Output System 2) was used to receive parameters such as stroke volume variance (SVV), pulse pressure variance (PPV), as well as extravascular lung water (EVLW) and global end-diastolic volume (GEDV). Our monitoring procedure is suitable for detecting right ventricular dysfunction and monitoring hemodynamic findings before and after volume administration.

We present a protocol of creating right ventricular dysfunction in a pig model by inducing ARDS. We demonstrate invasive monitoring of left and right ventricular cardiac output using flow probes around the aorta and the pulmonary artery, as well as blood pressure measurements in the aorta and pulmonary artery.

One of the leading causes of morbidity and mortality in patients with heart failure is right ventricular (RV) dysfunction, especially if it is due to ...

Non-invasive Assessment of Dorsiflexor Muscle Function in Mice

Assessment of skeletal muscle contractile function is an important measurement for both clinical and research purposes. Numerous conditions can negatively affect skeletal muscle. This can result in a loss of muscle mass (atrophy) and/or loss of muscle quality (reduced force per unit of muscle mass), both of which are prevalent in chronic disease, muscle-specific disease, immobilization, and aging (sarcopenia). Skeletal muscle function in animals can be evaluated by a range of different tests. All tests have limitations related to the physiological testing environment, and the selection of a specific test often depends on the nature of the experiments. Here, we describe an in vivo, non-invasive technique involving a helpful and easy assessment of force frequency-curve (FFC) in mice that can be performed on the same animal over time. This permits monitoring of disease progression and/or efficacy&#160;of a potential therapeutic treatment.

Measurement of rodent skeletal muscle contractile function is a useful tool that can be used to track disease progression as well as efficacy of therapeutic intervention. We describe here the non-invasive, in vivo assessment of the dorsiflexor muscles that can be repeated over time in the same mouse.

Assessment of skeletal muscle contractile function is an important measurement for both clinical and research purposes. Numerous conditions can negatively ...