Calibration of Non-Invasive Non-Ionizing Imaging Techniques to Study Vasculature of Healthy Volunteers
This study is designed to calibrate three non-invasive and non-ionizing imaging techniques
on 12 healthy volunteers. The three imaging techniques-- thermography, laser Doppler imaging
and multi-spectral imaging-- have been approved since 2001 for four clinical protocols
already approved by the NIH/NCI IRB for use on patients with Kaposi's sarcoma (KS). However,
as our laboratory continues to study and analyze the images collected on these protocols, we
have found that our analysis algorithms require some additional data from healthy
We aim to use the information we gather from healthy volunteers on this protocol to train
our imaging systems and calibrate our analysis methods to validate the results of the KS
data already collected. We aim to study different skin types, such as Caucasian, Asian and
African American, so that we can calibrate the melanin input value in our multi-spectral
imaging reconstruction algorithm. We also need to study the vasculature networks in the
forearms of the volunteers to compare to 'normal' values in the literature for the
parameters we are exploring, including temperature, vasculature, blood volume and blood
oxygenation to validate our reconstruction algorithm. We will also perform experiments of
reactive hyperemia, where the arm of the volunteer is occluded with an arm pressure cuff for
five minutes, to study how blood volume and blood oxygenation change during the experiment.
Trends of increasing/decreasing blood volume and blood oxygenation can also be compared with
published literature to validate our reconstruction algorithm.
Since we started collecting data from the KS patients, we have noticed that hair and
curvature of the surface of the skin interfere with our analysis techniques as well.
Therefore, we aim to assess algorithms developed to remove the effects of curvature and hair
on the images as part of our image analysis training. The intensity in the images is
affected by the curvature and must be corrected. We have developed algorithms to correct for
this curvature, but need to study normal disease-free skin to make sure that the values for
blood volume and blood oxygenation remain the same after the curvature correction is
performed. We also plan to collect images from a healthy volunteer's arm, remove the hair
from the arm using a topical hair removal solution, and then image the arm again. With this
information, we can optimize our hair removal algorithm. Combining all of the aforementioned
information will allow us to develop a non-invasive strategy for repeated serial assessments
of tissue vasculature.
When following KS lesions over time, the vascular / metabolic changes in the lesion are
important. An additional parameter is of interest when following the treatment over time,
which is the structure of the lesion. Optical Coherence Tomography (OCT) is a non-invasive,
non-contact optical imaging technology, which provides this desired structural information
with high resolution and in three dimensions (3D) over the area of interest. Therefore we
aim to combine OCT with multi-spectral data, relating the metabolic state of the tissue with
structure. By doing this, we hypothesize that we can not only get deeper understanding of
tissue vasculature, but that we can also improve the multi-spectral imaging modality, by
using the structure as prior information for the reconstruction.
Time Perspective: Prospective
Margaret F Bevans, Ph.D.
National Institutes of Health Clinical Center (CC)
United States: Federal Government
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