Korean J Radiol.  2018 Dec;19(6):1187-1195. 10.3348/kjr.2018.19.6.1187.

Impact of Model-Based Iterative Reconstruction on the Correlation between Computed Tomography Quantification of a Low Lung Attenuation Area and Airway Measurements and Pulmonary Function Test Results in Normal Subjects

• Kim DJ
• Kim C
• Shin C
• Lee SK
• Ko CS
• Lee KY

• KMID: 2424858
• DOI: http://doi.org/10.3348/kjr.2018.19.6.1187

Abstract

OBJECTIVE
To compare correlations between pulmonary function test (PFT) results and different reconstruction algorithms and to suggest the optimal reconstruction protocol for computed tomography (CT) quantification of low lung attenuation areas and airways in healthy individuals.
MATERIALS AND METHODS
A total of 259 subjects with normal PFT and chest CT results were included. CT scans were reconstructed using filtered back projection, hybrid-iterative reconstruction, and model-based IR (MIR). For quantitative analysis, the emphysema index (EI) and wall area percentage (WA%) were determined. Subgroup analysis according to smoking history was also performed.
RESULTS
The EIs of all the reconstruction algorithms correlated significantly with the forced expiratory volume in one second (FEV1)/forced vital capacity (FVC) (all p < 0.001). The EI of MIR showed the strongest correlation with FEV1/FVC (r = −0.437). WA% showed a significant correlation with FEV1 in all the reconstruction algorithms (all p < 0.05) correlated significantly with FEV1/FVC for MIR only (p < 0.001). The WA% of MIR showed the strongest correlations with FEV1 (r = −0.205) and FEV1/FVC (r = −0.250). In subgroup analysis, the EI of MIR had the strongest correlation with PFT in both ever-smoker and never-smoker subgroups, although there was no significant difference in the EI between the reconstruction algorithms. WA% of MIR showed a significantly thinner airway thickness than the other algorithms (49.7 ± 7.6 in ever-smokers and 49.5 ± 7.5 in never-smokers, all p < 0.001), and also showed the strongest correlation with PFT in both ever-smoker and never-smoker subgroups.
CONCLUSION
CT quantification of low lung attenuation areas and airways by means of MIR showed the strongest correlation with PFT results among the algorithms used, in normal subjects.

Keyword

Computed tomography; Iterative reconstruction; Pulmonary emphysema; Airway; Pulmonary function test

MeSH Terms

Emphysema
Forced Expiratory Volume
Lung*
Pulmonary Emphysema
Respiratory Function Tests*
Smoke
Smoking
Tomography, X-Ray Computed
Vital Capacity
Smoke

Figure

• 

  Fig. 1 Axial CT images of study population.A. Filtered back projection. B. Hybrid iterative reconstruction (iDose4; Philips Healthcare). C. MIR (IMR with “body routine” image definition [IMR-R1; Philips Healthcare]). D. MIR (IMR with “soft tissue” image definition [IMR-ST1; Philips Healthcare]). E. MIR (IMR with “sharp plus” image definition [IMR-SP1; Philips Healthcare]). CT = computed tomography, MIR = model-based iterative reconstruction

• 

  Fig. 2 Representative example of CT quantification of low lung attenuation area and airway from 64-year-old male.A. For quantitative analysis of low lung attenuation area, −950 HU was used as threshold. Area under −950 HU curve is displayed as red-dotted area. B. For quantitative analysis of airway thickness, three-dimensional image of tracheobronchial tree was automatically generated. Then, segment of bronchus of right upper lobe, from most proximal portion to bifurcation, was selected. In this area, average value of each of several airway parameters, including LA, WA, and WA% (WA% = WA / [WA + LA]) were automatically measured. LA = luminal area, WA = wall area, WA% = wall area percentage

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