Quantitative computed tomography of lung parenchyma in patients with emphysema: Analysis of higher-density lung regions

Dror Lederman, Joseph K. Leader, Bin Zheng, Frank C. Sciurba, Tan Jun, David Gur

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Quantitative computed tomography (CT) has been widely used to detect and evaluate the presence (or absence) of emphysema applying the density masks at specific thresholds, e.g., -910 or -950 Hounsfield Unit (HU). However, it has also been observed that subjects with similar density-mask based emphysema scores could have varying lung function, possibly indicating differences of disease severity. To assess this possible discrepancy, we investigated whether density distribution of "viable" lung parenchyma regions with pixel values > -910 HU correlates with lung function. A dataset of 38 subjects, who underwent both pulmonary function testing and CT examinations in a COPD SCCOR study, was assembled. After the lung regions depicted on CT images were automatically segmented by a computerized scheme, we systematically divided the lung parenchyma into different density groups (bins) and computed a number of statistical features (i.e., mean, standard deviation (STD), skewness of the pixel value distributions) in these density bins. We then analyzed the correlations between each feature and lung function. The correlation between diffusion lung capacity (DLCO) and STD of pixel values in the bin of -910HU ≤ PV <-750HU was -0.43, as compared with a correlation of -0.49 obtained between the post-bronchodilator ratio (FEV1/FVC) measured by the forced expiratory volume in 1 second (FEV1) dividing the forced vital capacity (FVC) and the STD of pixel values in the bin of -1024HU ≤PV <-910HU. The results showed an association between the distribution of pixel values in "viable" lung parenchyma and lung function, which indicates that similar to the conventional density mask method, the pixel value distribution features in "viable" lung parenchyma areas may also provide clinically useful information to improve assessments of lung disease severity as measured by lung functional tests.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2011
Subtitle of host publicationBiomedical Applications in Molecular, Structural, and Functional Imaging
Volume7965
DOIs
StatePublished - May 16 2011
EventMedical Imaging 2011: Biomedical Applications in Molecular, Structural, and Functional Imaging - Lake Buena Vista, FL, United States
Duration: Feb 13 2011Feb 16 2011

Other

OtherMedical Imaging 2011: Biomedical Applications in Molecular, Structural, and Functional Imaging
CountryUnited States
CityLake Buena Vista, FL
Period2/13/112/16/11

Fingerprint

emphysema
Emphysema
lungs
Tomography
tomography
Pixels
Bins
Lung
Masks
pixels
standard deviation
Pulmonary diseases
Vital Capacity
Forced Expiratory Volume
masks
Bronchodilator Agents
pulmonary functions
Lung Volume Measurements
skewness
Testing

Keywords

  • Computed tomography
  • Density mask
  • Lung function
  • Quantitative CT analysis

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Biomaterials
  • Radiology Nuclear Medicine and imaging

Cite this

Lederman, D., Leader, J. K., Zheng, B., Sciurba, F. C., Jun, T., & Gur, D. (2011). Quantitative computed tomography of lung parenchyma in patients with emphysema: Analysis of higher-density lung regions. In Medical Imaging 2011: Biomedical Applications in Molecular, Structural, and Functional Imaging (Vol. 7965). [79651X] https://doi.org/10.1117/12.877542

Quantitative computed tomography of lung parenchyma in patients with emphysema : Analysis of higher-density lung regions. / Lederman, Dror; Leader, Joseph K.; Zheng, Bin; Sciurba, Frank C.; Jun, Tan; Gur, David.

Medical Imaging 2011: Biomedical Applications in Molecular, Structural, and Functional Imaging. Vol. 7965 2011. 79651X.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Lederman, D, Leader, JK, Zheng, B, Sciurba, FC, Jun, T & Gur, D 2011, Quantitative computed tomography of lung parenchyma in patients with emphysema: Analysis of higher-density lung regions. in Medical Imaging 2011: Biomedical Applications in Molecular, Structural, and Functional Imaging. vol. 7965, 79651X, Medical Imaging 2011: Biomedical Applications in Molecular, Structural, and Functional Imaging, Lake Buena Vista, FL, United States, 2/13/11. https://doi.org/10.1117/12.877542
Lederman D, Leader JK, Zheng B, Sciurba FC, Jun T, Gur D. Quantitative computed tomography of lung parenchyma in patients with emphysema: Analysis of higher-density lung regions. In Medical Imaging 2011: Biomedical Applications in Molecular, Structural, and Functional Imaging. Vol. 7965. 2011. 79651X https://doi.org/10.1117/12.877542
Lederman, Dror ; Leader, Joseph K. ; Zheng, Bin ; Sciurba, Frank C. ; Jun, Tan ; Gur, David. / Quantitative computed tomography of lung parenchyma in patients with emphysema : Analysis of higher-density lung regions. Medical Imaging 2011: Biomedical Applications in Molecular, Structural, and Functional Imaging. Vol. 7965 2011.
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abstract = "Quantitative computed tomography (CT) has been widely used to detect and evaluate the presence (or absence) of emphysema applying the density masks at specific thresholds, e.g., -910 or -950 Hounsfield Unit (HU). However, it has also been observed that subjects with similar density-mask based emphysema scores could have varying lung function, possibly indicating differences of disease severity. To assess this possible discrepancy, we investigated whether density distribution of {"}viable{"} lung parenchyma regions with pixel values > -910 HU correlates with lung function. A dataset of 38 subjects, who underwent both pulmonary function testing and CT examinations in a COPD SCCOR study, was assembled. After the lung regions depicted on CT images were automatically segmented by a computerized scheme, we systematically divided the lung parenchyma into different density groups (bins) and computed a number of statistical features (i.e., mean, standard deviation (STD), skewness of the pixel value distributions) in these density bins. We then analyzed the correlations between each feature and lung function. The correlation between diffusion lung capacity (DLCO) and STD of pixel values in the bin of -910HU ≤ PV <-750HU was -0.43, as compared with a correlation of -0.49 obtained between the post-bronchodilator ratio (FEV1/FVC) measured by the forced expiratory volume in 1 second (FEV1) dividing the forced vital capacity (FVC) and the STD of pixel values in the bin of -1024HU ≤PV <-910HU. The results showed an association between the distribution of pixel values in {"}viable{"} lung parenchyma and lung function, which indicates that similar to the conventional density mask method, the pixel value distribution features in {"}viable{"} lung parenchyma areas may also provide clinically useful information to improve assessments of lung disease severity as measured by lung functional tests.",
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