SU-E-I-90: Characterizing Small Animal Lung Properties Using Speckle Observed with An In-Line X-Ray Phase Contrast Benchtop System

Authors

  • Garson A,

    1. Washington University in St. Louis, St. Louis, MO
    2. Washington University in St. Louis, St. Louis, MO
    3. MetroHealth Medical Center, Case Western Reserve University, Cleveland, OH
    Search for more papers by this author
  • Gunsten S,

    1. Washington University in St. Louis, St. Louis, MO
    2. Washington University in St. Louis, St. Louis, MO
    3. MetroHealth Medical Center, Case Western Reserve University, Cleveland, OH
    Search for more papers by this author
  • Guan H,

    1. Washington University in St. Louis, St. Louis, MO
    2. Washington University in St. Louis, St. Louis, MO
    3. MetroHealth Medical Center, Case Western Reserve University, Cleveland, OH
    Search for more papers by this author
  • Vasireddi S,

    1. Washington University in St. Louis, St. Louis, MO
    2. Washington University in St. Louis, St. Louis, MO
    3. MetroHealth Medical Center, Case Western Reserve University, Cleveland, OH
    Search for more papers by this author
  • Brody S,

    1. Washington University in St. Louis, St. Louis, MO
    2. Washington University in St. Louis, St. Louis, MO
    3. MetroHealth Medical Center, Case Western Reserve University, Cleveland, OH
    Search for more papers by this author
  • Anastasio M

    1. Washington University in St. Louis, St. Louis, MO
    2. Washington University in St. Louis, St. Louis, MO
    3. MetroHealth Medical Center, Case Western Reserve University, Cleveland, OH
    Search for more papers by this author

Abstract

Purpose:

We demonstrate a novel X-ray phase-contrast (XPC) method for lung imaging representing a paradigm shift in the way small animal functional imaging is performed. In our method, information regarding airway microstructure that is encoded within speckle texture of a single XPC radiograph is decoded to produce 2D parametric images that will spatially resolve changes in lung properties such as microstructure sizes and air volumes. Such information cannot be derived from conventional lung radiography or any other 2D imaging modality. By computing these images at different points within a breathing cycle, dynamic functional imaging will be readily achieved without the need for tomography. Methods: XPC mouse lung radiographs acquired in situ with an in-line X-ray phase contrast benchtop system. The lung air volume is varied and controlled with a small animal ventilator. XPC radiographs will be acquired for various lung air volume levels representing different phases of the respiratory cycle. Similar data will be acquired of microsphere-based lung phantoms containing hollow glass spheres with known distributions of diameters. Image texture analysis is applied to the data to investigate relationships between texture characteristics and airspace/microsphere physical properties.

Results:

Correlations between Fourier-based texture descriptors (FBTDs) and regional lung air volume indicate that the texture features in 2D radiographs reveal information on 3D properties of the lungs. For example, we find for a 350 × 350 πm2 lung ROI a linear relationship between injected air volume and FBTD value with slope and intercept of 8.9×105 and 7.5, respectively.

Conclusion:

We demonstrate specific image texture measures related to lung speckle features are correlated with physical characteristics of refracting elements (i.e. lung air spaces). Furthermore, we present results indicating the feasibility of implementing the technique with a simple imaging system design, short exposures, and low dose which provides potential for widespread use in laboratory settings for in vivo studies.

This research was supported in part by NSF Award CBET1263988.

Ancillary