The Impact of CT Reconstruction Parameters on Emphysema Index Quantification, HU-Based Measurements, and Goddard Score in COPD Assessment: A Prospective Study

Abstract

Background: Quantitative computed tomography (CT) plays a crucial role in assessing emphysema severity in chronic obstructive pulmonary disease (COPD). However, variations in CT reconstruction parameters-slice thickness (ST), kernel selection, field of view (FOV), and reconstruction gaps-can affect emphysema index (EI) quantification, impacting diagnostic accuracy and study comparability.

Objective: This study examines how CT reconstruction parameters influence EI quantification using Hounsfield Unit (HU)-based measurements and the Goddard Score (GS) to refine imaging protocols for emphysema assessment.

Methods: Low-dose CT scans were performed on 31 subjects, with images reconstructed using ST (0.6-10 mm), kernel settings (Br and Hr series), FOV ranges (250-370 mm), and reconstruction gaps (0.25-3 mm). EI was defined as the percentage of lung volume with attenuation values below - 950 HU, while GS provided a semi-quantitative assessment of emphysema severity. Statistical analyses evaluated the effects of reconstruction parameters on EI and GS.

Results: Variations in FOV, kernel selection, and reconstruction gaps had negligible effects on the GS (p > 0.05), suggesting that these parameters do not introduce structural distortions in pulmonary imaging. However, ultra-thin slices (0.6 mm) enhanced the detection of subtle emphysematous changes, slightly increasing GS, though higher image noise may affect interpretation. Additionally, ST significantly influenced EI values due to partial volume effects, with thinner slices yielding lower attenuation values.

Conclusion: These findings confirm the reliability of CT-based emphysema quantification and highlight the importance of optimizing ST to balance sensitivity and image clarity. Standardized imaging protocols and AI-driven texture analysis could further enhance quantitative emphysema assessment, improving disease monitoring and therapeutic decision-making in COPD management.

Keywords: CT imaging; Goddard score (GS); chronic obstructive pulmonary disease (COPD); emphysema index (EI); reconstruction parameters; slice thickness (ST).

Figure 1

Relationship between CT slice thickness and median HU values. The data demonstrate a progressive increase in median HU values as slice thickness increases from 0.6 mm to 10.0 mm, thinner slices (0.6 mm to 2.0 mm) exhibit relatively stable HU values with narrow confidence intervals, while slices thicker than 3.0 mm show an upward shift in HU values due to partial volume effects.

Figure 2

Scatter plot illustrating the positive correlation between CT slice thickness and median HU values (r = 0.40, p < 0.001). The regression model (y = −1000.714 + 7.818x) suggests that HU values increase by approximately 7.8 units per millimeter of slice thickness This trend is primarily attributed to partial volume averaging, where adjacent tissue signals blend within thicker slices, leading to elevated HU values and reduced spatial resolution.

Figure 3

Relationship between CT reconstruction kernel type and median HU values, with 95% confidence intervals. High‐resolution (Hr) kernels exhibit higher median HU values compared to standard (Br) kernels, with increased variability due to noise amplification and enhanced edge definition.

Figure 4

Relationship between FOV and median HU values, with 95% confidence intervals. The data demonstrate relatively stable median HU values across varying FOV settings, indicating minimal impact of FOV on emphysema quantification. However, increased confidence intervals at larger FOVs suggest increased variability, likely due to partial volume effects.

Figure 5

Scatter plot illustrating the correlation between FOV and median HU values. The correlation coefficient (r = 0.00, p = 0.936) indicates no significant association between FOV and HU values, confirming the stability of HU‐based measurements across different FOV settings.

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