Automated algorithm for quantifying the extent of cystic change on volumetric chest CT: initial results in Lymphangioleiomyomatosis

AJR Am J Roentgenol. 2009 Apr;192(4):1037-44. doi: 10.2214/AJR.07.3334.

Abstract

Objective: The purpose of our study was to develop a new method for quantifying the severity of cystic lung disease using chest CT and to evaluate this method in patients with lymphangioleiomyomatosis (LAM).

Subjects and methods: Eighteen patients with LAM (all women; mean age, 43.6 years) underwent chest CT and pulmonary function testing including diffusing capacity for carbon monoxide (DLCO). All patients were at their clinical baseline on the day of imaging. Standard quantitative CT metrics including the percentage of the lung volume < -910 HU and the 15th percentile of Hounsfield units were computed from the histogram of lung voxels. A new histogram analysis method was developed to compute the cyst volume and the volume of the remaining lung by segmenting the entire lung attenuation histogram into two underlying distributions, one from the cysts and the other from the remaining lung tissue.

Results: The mean +/- SD for quantitative lung metrics was 21% +/- 16% for percentage < -910 HU, -915 +/- 47 HU for 15th percentile of Hounsfield units, and 19% +/- 13% for cyst volume. The correlation between pulmonary function tests and CT metrics was strongest for the percentage of cyst volume for all pulmonary function testing indexes, with correlations between forced expiratory volume in 1 second (FEV(1)) percentage predicted and the CT metrics of r = -0.52, r = 0.50, and r = -0.86 for the percentage of lung < -910 HU, the 15th percentile of Hounsfield units, and the percentage of cyst volume, respectively.

Conclusion: A new method for quantifying cyst volume as a percentage of total lung volume using chest CT correlates with pulmonary function parameters in patients with LAM and may have utility in the assessment of disease severity and progression of cystic lung diseases.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Algorithms*
  • Cone-Beam Computed Tomography / methods*
  • Female
  • Humans
  • Lung Neoplasms / diagnostic imaging*
  • Lung Neoplasms / physiopathology
  • Lymphangioleiomyomatosis / diagnostic imaging*
  • Lymphangioleiomyomatosis / physiopathology
  • Middle Aged
  • Radiographic Image Interpretation, Computer-Assisted / methods*
  • Radiography, Thoracic
  • Respiratory Function Tests
  • Severity of Illness Index