Dataset Information

Calculating air volume fractions from computed tomography images for chronic obstructive pulmonary disease diagnosis.

ABSTRACT: Quantitative evaluation using image biomarkers calculated from threshold-segmented low-attenuation areas on chest computed tomography (CT) images for diagnosing chronic obstructive pulmonary diseases (COPD) has been widely investigated. However, the segmentation results depend on the applied threshold and slice thickness of the CT images because of the partial volume effect (PVE). In this study, the air volume fraction (AV/TV) of lungs was calculated from CT images using a two-compartment model (TCM) for COPD diagnosis. A relative air volume histogram (RAVH) was constructed using the AV/TV values to describe the air content characteristics of lungs. In phantom studies, the TCM accurately calculated total cavity volumes and foam masses with percent errors of less than 8% and ±4%, respectively. In patient studies, the relative volumes of normal and damaged lung tissues and the damaged-to-normal RV ratio were defined and calculated from the RAVHs as image biomarkers, which correctly differentiated COPD patients from controls in 2.5- and 5-mm-thick images with areas under receiver operating characteristic curves of >0.94. The AV/TV calculated using the TCM can prevent the effect of slice thickness, and the image biomarkers calculated from the RAVH are reliable for diagnosing COPD.

SUBMITTER: Chuang CC

PROVIDER: S-EPMC7162278 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Calculating air volume fractions from computed tomography images for chronic obstructive pulmonary disease diagnosis.

Chuang Chun-Chao CC Chou Ying-Hsiang YH Peng Shin-Lei SL Tai Jou-Erh JE Lee Shan-Chih SC Tyan Yeu-Sheng YS Shih Cheng-Ting CT

PloS one 20200416 4

Quantitative evaluation using image biomarkers calculated from threshold-segmented low-attenuation areas on chest computed tomography (CT) images for diagnosing chronic obstructive pulmonary diseases (COPD) has been widely investigated. However, the segmentation results depend on the applied threshold and slice thickness of the CT images because of the partial volume effect (PVE). In this study, the air volume fraction (AV/TV) of lungs was calculated from CT images using a two-compartment model ...[more]

PMID: 32298358

Similar Datasets

Project description:Rationale: Airway remodeling in chronic obstructive pulmonary disease (COPD) is due to luminal narrowing and/or loss of airways. Existing computed tomographic metrics of airway disease reflect only components of these processes. With progressive airway narrowing, the ratio of the airway luminal surface area to volume (SA/V) should increase, and with predominant airway loss, SA/V should decrease.Objectives: To phenotype airway remodeling in COPD.Methods: We analyzed the airway trees of 4,325 subjects with COPD Global Initiative for Chronic Obstructive Lung Disease stages 0 to 4 and 73 nonsmokers enrolled in the multicenter COPDGene (Genetic Epidemiology of COPD) cohort. Surface area and volume measurements were estimated for the subtracheal airway tree to derive SA/V. We performed multivariable regression analyses to test associations between SA/V and lung function, 6-minute-walk distance, St. George's Respiratory Questionnaire, change in FEV1, and mortality, adjusting for demographics, total airway count, airway wall thickness, and emphysema. On the basis of the change in SA/V over 5 years, we categorized subjects into predominant airway narrowing [positive ∆(SA/V) more than 0] and predominant airway loss [negative ∆(SA/V) less than 0] and compared survival between the two groups.Measurements and Main Results: Airway SA/V was independently associated with FEV1/FVC (β = 0.12; 95% confidence interval [CI], 0.09-0.14; P < 0.001) and FEV1% predicted (β = 20.10; 95% CI, 15.13-25.08; P < 0.001). Airway SA/V was also independently associated with 6-minute-walk distance, respiratory quality of life, and lung function decline. Compared with subjects with predominant airway narrowing (n = 2,914; 66.3%), those with predominant airway loss (n = 1,484; 33.7%) had worse survival (adjusted hazard ratio for all-cause mortality = 1.58; 95% CI, 1.18-2.13; P = 0.002).Conclusions: Computed tomography-based airway SA/V is an imaging biomarker of airway remodeling and provides differential information on predominant airway narrowing and loss in COPD. SA/V is associated with respiratory morbidity, lung function decline, and survival.

Project description:OBJECTIVES: To compare the accuracy of pulmonary lobar volumetry using the conventional number of segments method and novel volumetric computer-aided diagnosis using 3D computed tomography images. METHODS: We acquired 50 consecutive preoperative 3D computed tomography examinations for lung tumours reconstructed at 1-mm slice thicknesses. We calculated the lobar volume and the emphysematous lobar volume < -950 HU of each lobe using (i) the slice-by-slice method (reference standard), (ii) number of segments method, and (iii) semi-automatic and (iv) automatic computer-aided diagnosis. We determined Pearson correlation coefficients between the reference standard and the three other methods for lobar volumes and emphysematous lobar volumes. We also compared the relative errors among the three measurement methods. RESULTS: Both semi-automatic and automatic computer-aided diagnosis results were more strongly correlated with the reference standard than the number of segments method. The correlation coefficients for automatic computer-aided diagnosis were slightly lower than those for semi-automatic computer-aided diagnosis because there was one outlier among 50 cases (2%) in the right upper lobe and two outliers among 50 cases (4%) in the other lobes. The number of segments method relative error was significantly greater than those for semi-automatic and automatic computer-aided diagnosis (P < 0.001). The computational time for automatic computer-aided diagnosis was 1/2 to 2/3 than that of semi-automatic computer-aided diagnosis. CONCLUSIONS: A novel lobar volumetry computer-aided diagnosis system could more precisely measure lobar volumes than the conventional number of segments method. Because semi-automatic computer-aided diagnosis and automatic computer-aided diagnosis were complementary, in clinical use, it would be more practical to first measure volumes by automatic computer-aided diagnosis, and then use semi-automatic measurements if automatic computer-aided diagnosis failed.

Dataset Information

Calculating air volume fractions from computed tomography images for chronic obstructive pulmonary disease diagnosis.

Publications

Calculating air volume fractions from computed tomography images for chronic obstructive pulmonary disease diagnosis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure