Optimising protocol of acquisition and post-processing procedures in the assessment of coronary artery disease by computed tomography

Maria Margarida Ribeiro, Nuno Caldeira Gonçalves, Inês Baião Bate, João Goyri O'Neill, Jaime Cruz Maurício

Research output: Contribution to journalArticlepeer-review

Abstract

Coronary artery disease (CAD) is currently one of the most prevalent diseases in the world population and calcium deposits in coronary arteries are one direct risk factor. These can be assessed by the calcium score (CS) application, available via a computed tomography (CT) scan, which gives an accurate indication of the development of the disease. However, the ionising radiation applied to patients is high. This study aimed to optimise the protocol acquisition in order to reduce the radiation dose and explain the flow of procedures to quantify CAD. The main differences in the clinical results, when automated or semi-automated post-processing is used, will be shown, and the epidemiology, imaging, risk factors and prognosis of the disease described. The software steps and the values that allow the risk of developing CAD to be predicted will be presented. A 64-row multidetector CT scan with dual source and two phantoms (pig hearts) were used to demonstrate the advantages and disadvantages of the Agatston method. The tube energy was balanced. Two measurements were obtained in each of the three experimental protocols (64, 128, 256 mAs). Considerable changes appeared between the values of CS relating to the protocol variation. The predefined standard protocol provided the lowest dose of radiation (0.43 mGy). This study found that the variation in the radiation dose between protocols, taking into consideration the dose control systems attached to the CT equipment and image quality, was not sufficient to justify changing the default protocol provided by the manufacturer.

Original languageEnglish
Pages (from-to)91-100
Number of pages10
JournalComputer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization
Volume3
Issue number2
DOIs
Publication statusPublished - 3 Apr 2015

Keywords

  • computational bio-imaging and visualisation
  • data processing and analysis
  • medical clinics
  • medical imaging and visualisation

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