title: Can image enhancement allow radiation dose to be reduced whilst maintaining the perceived diagnostic image quality required for coronary angiography?
abstract: OBJECTIVE
  The aim of this research was to quantify the reduction in radiation dose facilitated by image processing alone for percutaneous coronary intervention (PCI) patient angiograms, without reducing the perceived image quality required to confidently make a diagnosis.
  
  
  METHODS
  Incremental amounts of image noise were added to five PCI angiograms, simulating the angiogram as having been acquired at corresponding lower dose levels (10-89% dose reduction). 16 observers with relevant experience scored the image quality of these angiograms in 3 states-with no image processing and with 2 different modern image processing algorithms applied. These algorithms are used on state-of-the-art and previous generation cardiac interventional X-ray systems. Ordinal regression allowing for random effects and the delta method were used to quantify the dose reduction possible by the processing algorithms, for equivalent image quality scores.
  
  
  RESULTS
  Observers rated the quality of the images processed with the state-of-the-art and previous generation image processing with a 24.9% and 15.6% dose reduction, respectively, as equivalent in quality to the unenhanced images. The dose reduction facilitated by the state-of-the-art image processing relative to previous generation processing was 10.3%.
  
  
  CONCLUSIONS
  Results demonstrate that statistically significant dose reduction can be facilitated with no loss in perceived image quality using modern image enhancement; the most recent processing algorithm was more effective in preserving image quality at lower doses. Advances in knowledge: Image enhancement was shown to maintain perceived image quality in coronary angiography at a reduced level of radiation dose using computer software to produce synthetic images from real angiograms simulating a reduction in dose.
authors.affiliation: 1 Division of Biomedical Imaging, University of Leeds, Leeds, UK.
authors.forename: Anuja
authors.initials: A
authors.lastname: Joshi
authors.affiliation: 1 Division of Biomedical Imaging, University of Leeds, Leeds, UK.
authors.forename: Amber J
authors.initials: AJ
authors.lastname: Gislason-Lee
authors.affiliation: 1 Division of Biomedical Imaging, University of Leeds, Leeds, UK.|2 Division of Epidemiology and Biostatistics, University of Leeds, Leeds, UK.
authors.forename: Claire
authors.initials: C
authors.lastname: Keeble
authors.affiliation: 3 Cardiology Department, Leeds General Infirmary, Leeds, UK.
authors.forename: Uduvil M
authors.initials: UM
authors.lastname: Sivananthan
authors.affiliation: 1 Division of Biomedical Imaging, University of Leeds, Leeds, UK.
authors.forename: Andrew G
authors.initials: AG
authors.lastname: Davies
mesh_terms: D017023:Coronary Angiography / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D011829:Radiation Dosage; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods; D011859:Radiography / Q000379:methods*