2018 Laboratory A: Tissue Absorption and Scattering Spectra

GOALS: Gain familiarity with wavelength dependence of tissue optical properties and associated length and time scales for radiative transport

Bring up the Vts.Gui.Wpf GUI

Select Spectral Panel. Note that Tissue Types lists various tissues. Each tissue is modeled as a composite of individual chromophores (e.g. water, blood, fat, etc.). Each chromophore is assigned a specific concentration representative of the tissue type under consideration. In this exercise, we will study how absorption and scattering properties of tissues (as well as their constituent chromophores) vary with the wavelength of light.

I. Absorption Spectra of Tissue Constituents

Goal: This portion of the GUI Interaction is to provide an introduction to the functionality of the Spectral Panel.
  1. Select Custom in Tissue Types.
  2. In Absorber Concentrations set concentrations to 1 μM for Hb and 0 μM for the other optical absorbers. This change updates Blood Concentration values automatically.
  3. Ignore Scattering settings (Power Law/Intralipid and Single λ calculator) for this analysis.
  4. In Wavelength Range set Begin to 600, End to 1000, and Number to 41.
  5. Enter "Hb" in Plot Label box.
  6. Click the Plot μa Spectrum button at the bottom of the panel.
  7. Plot provides μa as a function of wavelength, λ, for Hb ("pure" Hb spectrum).
  8. Confirm that the output is consistent with results shown in lecture 1 for 600 nm<=λ<=1000 nm.
  9. Confirm the Hold On checkbox is checked (under the graphing area on the left).
  10. Repeat the steps I.1-I.7 for HbO2.
  11. Click the Clear All button under the graphing area.

II. Tissue spectra

Goal: It is known that the liver is a highly cellular and blood filled tissue, while skin, by contrast, has less cellular content and more extracellular matrix proteins. As you do this exercise examine whether the μa and μ's spectra are consistent with the known composition and morphological properties of these tissues. Comment on the similarities/differences in their spectra.
  1. Select Skin in Tissue Types.
  2. Notice the defaults in Absorber Concentrations.
  3. In Wavelength Range set Begin to 600, End to 1000, and Number to 41
  4. Enter "Skin" in Plot Label box.
  5. Plot μa of skin versus wavelength.
  6. Confirm that the Hold On checkbox is checked.
  7. Repeat the steps II.1-II.5 for tissue type Liver.
  8. Record the minimum and maximum values of μa for these two tissues. (If you click on the nodes of the plots, you will see the corresponding numeric values.)
  9. Using the definitions given in lecture 1, estimate the minimum/maximum values of labs within the spectral range of λ = 600-1000nm.
  10. Click the Clear All button. Plot μ's spectra on the same axis for these tissue types.
  11. Record the minimum and maximum values of μ's for these two tissues. Estimate the minimum/maximum values of lsc within the spectral range of λ = 600-1000nm. Assume g = 0.8. (Hint: lsc= 1/ μs and μ's = μs(1-g)).
  12. Click the Clear All button. Plot μa and μ's for Skin on the same plot, in the plot view window. Click the Export Data button to save the data in a text file. Use the text file data to compute μa+ μ's to estimate the minimum/maximum values of l*.
  13. Return to μa and μ's plot in II.12 and click the Curve Radio Button in the Normalization Controls. This operation divides the second plot μ's results (and any other plots plotted after the first) in the plot view window by the results for the first plot for μa. Thus the first result gets transformed to a series of '1' values while the second result is represented as μ's / μa. Use the values to estimate the minimum and maximum of the ratio μ's / μa within the spectral range λ = 600-1000nm.
  14. Repeat II.12 and II.13 for tissue type Liver.

Additional Question:

  1. You have designed a device that can detect changes in μa as small as 0.01 mm-1 at λ = 600nm. Assuming that changes in your system are limited to changes in Hb concentration, what is the smallest Hb concentration change that you can detect? Similarly for HbO2 what is the smallest concentration change that you can detect?