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Reduced contrast agent volume using a heart-rate dependent and free-breathing scanning protocol in coronary computed tomography angiography (CTA) for patients with chronic obstructive pulmonary disease (COPD)

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Abstract

Background

The personalized, free-breathing, heart rate-dependent computed tomography angiography (CTA) protocol can significantly reduce the utilization of contrast medium (CM). This proves especially beneficial for patients with chronic obstructive pulmonary disease (COPD) undergoing coronary artery CTA examinations.

Objective

The aim of this study was to evaluate the feasibility of a personalized CT scanning protocol that was tailored to patients’ heart rate and free-breathing for coronary CTA of patients with COPD.

Methods

A total of 400 patients with COPD who need to undergo the coronary CTA were prospectively randomized into two groups (patients with vascular occlusion were excluded). Group A (n = 200) underwent CTA following a traditional protocol (70mL). The timing of the scans in Group B (n = 200) was determined according to the patient’s HR and free-breathing (30mL).

Results

No difference was found between the two groups in the CT values of RCA, LA, or LCX; (p = 0.131, 0.195 and 0.116). Subjective ratings of image quality (Table 2) were not statistically different between the two groups (p = 0.825).

Conclusion

By adopting a heart-rate dependent and free-breathing protocol, the contrast medium volume were reduced in coronary CTA for patients with COPD, while the image quality was remained comparable to those acquired with routine CTA protocol.
Title
Reduced contrast agent volume using a heart-rate dependent and free-breathing scanning protocol in coronary computed tomography angiography (CTA) for patients with chronic obstructive pulmonary disease (COPD)
Authors
Zengkun Wang
Guoyue Chen
Dewei Song
Xiaodie Xu
Chu Chu
Shuning Zhang
Huijing Chai
Hairong Yu
Xiaomei Luan
Peiji Song
Publication date
01-12-2025
Publisher
BioMed Central
Published in
BMC Cardiovascular Disorders / Issue 1/2025
Electronic ISSN: 1471-2261
DOI
https://doi.org/10.1186/s12872-024-04437-2
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Case-Based Insights teaser image/© Eva Künzel