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A patient‐ and acquisition‐tailored injection approach for improving consistency of CT enhancement towards a target CT value in coronary CT angiography

Authors :
Gert Van Gompel
Laurence Delombaerde
Federica Zanca
Kaoru Tanaka
Dries Belsack
Johan de Mey
Nico Buls
Brussels Heritage Lab
Supporting clinical sciences
Radiology
Medical Imaging
Artificial Intelligence supported Modelling in clinical Sciences
Body Composition and Morphology
Source :
Journal of Applied Clinical Medical Physics. 24
Publication Year :
2022
Publisher :
Wiley, 2022.

Abstract

BACKGROUND: Unoptimized coronary CT angiography (CTA) exams typically result in a highly variable arterial enhancement (HUa ) across patients. This study aimed at harmonizing arterial enhancement by implementing a patient-, contrast- and kV-tailored injection protocol. METHODS: First, the optimal body size metric to predict HUa was identified by retrospectively analysing images of 76 patients, acquired with 70 ml contrast media (G1). Second, using phantom experiments, correction factors for the effect of kV and contrast concentration on HUa were determined. Third, a model was developed, prescribing the optimal contrast dose to be injected to obtain a diagnostically appropriate arterial target enhancement HUtarget . The model was then validated on 278 prospectively collected patients, in two groups with two different HUtarget : 525 HU (207 patients, G2A) and 425 HU (71 patients, G2B). The HUa histograms were compared among groups and to the target enhancement through their mean and standard deviation (SD) at 100 kVp reference level. Also, signal-to-noise ratio was obtained and compared among the groups. RESULTS: Fat free mass (FFM) showed the highest correlation with HUa (r = 0.69). KVp correction factors ranged from 0.65 at 70 kVp to 1.22 at 140 kVp. The obtained model reduced the group heterogeneity (SD) from 101HU for reference G1 to 75HU (p

Details

ISSN :
15269914
Volume :
24
Database :
OpenAIRE
Journal :
Journal of Applied Clinical Medical Physics
Accession number :
edsair.doi.dedup.....3bfec5f2cd9de1c6593605991fc2323f