Parametric imaging: optical properties

Section 1. Optical properties: attenuation coefficient

1) Introduction

Conventional optical coherence tomography (OCT) imaging presents images of the intensity of backscattered light from biological samples. Detection of disease relies upon the user identifying the pathological structures in the OCT images, based on intrinsic optical contrast of the tissue. Often, this contrast is insufficient for reliable and repeatable detection of this pathology by qualitative analysis of OCT images.

We have developed a method of processing 3D-OCT data to quantitatively measure the optical properties of biological tissue, specifically the total attenuation coefficient µt. It has been show that the attenuation coefficient changes for different tissue types, and importantly for diseased and pathological tissue. By extracting the local attenuation coefficients from 3D-OCT volumes, we can measure the ranges of attenuation coefficients of different tissue types. We have also generated quantitative parametric OCT images of the local attenuation coefficients, which improve differentiation of tissue types and identification of pathology, when compared to standard OCT backscatter images alone.

2) Method

Assuming a single-scattering model of light propagation in tissue, in which light contributing to the OCT signal experiences only a single back-scattering event, the reflectance R(z) of light detected from a homogeneous tissue is determined from the exponential decay of irradiance versus depth z, in accordance with the Beer-Lambert law.

formula

The attenuation coefficient µt [mm-1] describes this decay and is a result of scattering and absorption. The contribution of tissue absorption is very low at the near infrared wavelengths used in OCT and can be considered negligible in comparison to scattering. The OCT system introduces modulations to the biological sample reflectance, and this first needs to be corrected for and removed from the detected OCT signal before the attenuation coefficient can be calculated. After correction, the localised attenuation coefficient can be extracted from the OCT reflectance profiles at different lateral positions containing different tissue types, as shown in the below Figure 1, and we then also generate a parametric map of µt (x,y) [mm-1]. The resulting parametric maps are correlated with corresponding histology to determine the range of values of and demonstrate that quantitative parametric OCT images provide improved differentiation of attenuation coefficient for different tissue types, and also improve contrast and identification of these different tissue types and pathology in subsequent results, compared to standard OCT backscatter images alone.

Measured attenuation coefficients for a section of healthy lymph node. (A) Co-registered H&E-stained histology identifying tissue regions: MS, medullary sinuses (thick white arrow); P, paracortex (white double-headed arrow); FC, fibrous capsule (white arrowhead); and AT, adipose tissue (black arrow). (B) En face (x-y) OCT image at a depth of 240 μm from the window/tissue interface. Colored boxes at this depth indicate regions over which attenuation coefficients were measured. (C) Parametric image of measured attenuation coefficients (mm−1) with a custom color map. Points with poor goodness-of-fit (R2  0.98 are shown in: (E) paracortex (dark blue); (F) medullary sinuses (light blue); and (G) fibrous capsule (red). Signal peaks at z = 0 are due to specular reflection from the window/tissue interface. Scale bars = 1 mm.

Measured attenuation coefficients for a section of healthy lymph node. (A) Co-registered H&E-stained histology identifying tissue regions: MS, medullary sinuses (thick white arrow); P, paracortex (white double-headed arrow); FC, fibrous capsule (white arrowhead); and AT, adipose tissue (black arrow). (B) En face (x-y) OCT image at a depth of 240 μm from the window/tissue interface. Colored boxes at this depth indicate regions over which attenuation coefficients were measured. (C) Parametric image of measured attenuation coefficients (mm−1) with a custom color map. Points with poor goodness-of-fit (R2 < 0.7) are excluded and are shown in white. (D) An example of the correction profile (red) used to generate a corrected reflectance profile (black) from its raw A-scan (grey). The dashed region of the correction profile is not used in the correction as the reflectance profile is below the noise floor for this region. Resulting averaged reflectance profiles at the centre of the colored boxes given in A and B and their linear fittings with R2 > 0.98 are shown in: (E) paracortex (dark blue); (F) medullary sinuses (light blue); and (G) fibrous capsule (red). Signal peaks at z = 0 are due to specular reflection from the window/tissue interface. Scale bars = 1 mm.

Reactive lymph node with an area of necrotic tissue containing dystrophic calcifications and a loss of normal tissue architecture. (A) Co-registered H&E-stained histology identifying tissue regions of interest: N, necrotic tissue (thick black arrow), C, calcifications (black arrowhead), TFC, thickened fibrous capsule (white arrowhead); AT, adipose tissue (thin black arrow), P, paracortex (white double-headed arrow), MS, medullary sinuses (thick white arrow). (B) En face (x-y) OCT image at a depth of 240 μm from the window/tissue interface. (C) Gray- scale parametric image of measured attenuation coefficients (mm−1). Sharp tissue interfaces particularly at the capsule cause AF, artifacts (white asterisk) in the attenuation measurement. (D) Parametric image of attenuation coefficients presented with a custom color map. Lower panels 2 × magnified regions represented by white dashed boxes in the corresponding upper panels and colored boxes indicate regions of distinct tissue type over which attenuation coefficients were measured: necrotic tissue (beige); foci of dystrophic calcification (yellow); thickened fibrous capsule (blue); medullary sinus (light blue); paracortex (dark blue). Scale bars = 1mm.

Reactive lymph node with an area of necrotic tissue containing dystrophic calcifications and a loss of normal tissue architecture. (A) Co-registered H&E-stained histology identifying tissue regions of interest: N, necrotic tissue (thick black arrow), C, calcifications (black arrowhead), TFC, thickened fibrous capsule (white arrowhead); AT, adipose tissue (thin black arrow), P, paracortex (white double-headed arrow), MS, medullary sinuses (thick white arrow). (B) En face (x-y) OCT image at a depth of 240 μm from the window/tissue interface. (C) Gray- scale parametric image of measured attenuation coefficients (mm−1). Sharp tissue interfaces particularly at the capsule cause AF, artifacts (white asterisk) in the attenuation measurement. (D) Parametric image of attenuation coefficients presented with a custom color map. Lower panels 2 × magnified regions represented by white dashed boxes in the corresponding upper panels and colored boxes indicate regions of distinct tissue type over which attenuation coefficients were measured: necrotic tissue (beige); foci of dystrophic calcification (yellow); thickened fibrous capsule (blue); medullary sinus (light blue); paracortex (dark blue). Scale bars = 1mm.

1) Key applications

2) Key researchers:

3) Collaborators:

  • Christobel Saunders
  • Peter Robbins
  • Matthew Edmond
  • Benjamin A. Wood
  • Steven L. Jacques
  • Tea Shavlakadze
  • Miranda D. Grounds
  • Fiona M. Wood

4) Publications

  1. Robert A. McLaughlin, Loretta Scolaro, Peter Robbins, Christobel Saunders, Steven L. Jacques, David D. Sampson, “Parametric imaging of cancer with optical coherence tomography”, Journal of Biomedical Optics, 15(4), 046029 (2010).
  2. Loretta Scolaro, Robert A. McLaughlin, Blake R. Klyen, Benjamin A. Wood, Peter D. Robbins, C Christobel M. Saunders, Steven L. Jacques, and David D. Sampson, “Parametric imaging of the local attenuation coefficient in human axillary lymph nodes assessed using optical coherence tomography”, Biomedical Optics Express, 3(2), pp. 366-379 (2012).
  3. Blake R. Klyen, Loretta Scolaro, Tea Shavlakadze, Miranda D. Grounds, and David D. Sampson, “Optical coherence tomography can assess skeletal muscle tissue from mouse models of muscular dystrophy by parametric imaging of the attenuation coefficient”, Biomedical Optics Express, 5(4), pp. 1217–1232 (2014).
  4. Peijun Gong, Robert A. McLaughlin, Yih Miin Liew, Peter R. T. Munro, Fiona M. Wood, and David D. Sampson, “Assessment of human burn scars with optical coherence tomography by imaging the attenuation coefficient of tissue after vascular masking”, Journal of Biomedical Optics, 19(2), 021111 (2014).