Coronary computed tomography angiography. Review uri icon

Overview

abstract

  • PURPOSE OF REVIEW: Significant limitations exist for traditional noninvasive cardiac imaging with regard to equivocal or indeterminate findings that result in repetitive testing or unnecessary referral to invasive coronary angiography (ICA). Recent hardware and software advances in multislice computed tomography angiography have achieved high spatial and temporal resolution to allow accurate noninvasive assessment of coronary arteries. This poses a paradigm shift in management of patients with suspected coronary artery disease (CAD). RECENT FINDINGS: Multicenter studies showed that coronary computed tomography angiography (CCTA) has a very high diagnostic accuracy, and, in particular, a very high negative predictive value (>98%) in detecting coronary stenosis when compared with ICA. In addition to its diagnostic ability, recent evidence-based outcome data have also validated the value of CCTA in predicting cardiac events. Absence of CAD on CCTA conveys excellent prognosis, whereas increasing disease severity and extent are associated with worsening outcome. Furthermore, CCTA allows comprehensive assessment of coronary stenosis, plaque burden, left ventricular morphology, function, perfusion and viability. One concern with CCTA is the issue of ionizing radiation exposure. Recent technical progress allows dramatic reduction of radiation dose. The newest generation scanner is capable of producing CCTA of diagnostic quality with a dose of less than 1 mSv. A multisociety guideline for appropriate clinical indications for cardiac computed tomography was recently published. SUMMARY: When used appropriately, CCTA has been established as a valid noninvasive imaging alternative to ICA in selected patients at low to intermediate risk of CAD.

publication date

  • September 1, 2011

Research

keywords

  • Coronary Angiography
  • Coronary Artery Disease
  • Tomography, X-Ray Computed

Identity

Scopus Document Identifier

  • 80051798705

Digital Object Identifier (DOI)

  • 10.1097/HCO.0b013e32834938c6

PubMed ID

  • 21743316

Additional Document Info

volume

  • 26

issue

  • 5