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

Year: 2026

Type: article

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: > 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.

Source: International Journal of Biomedical Imaging

DOI: 10.1155/ijbi/7436511

Authors: Rahma Saad Mohamed, Ahmed Sayed Abd El Bassset, Ahmed A. G. El-Shahawy

Institution: Beni-Suef University

Language: English

Topic: Chronic Obstructive Pulmonary Disease (COPD) Research

Subfield: Pulmonary and Respiratory Medicine

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $1,000