title: Four-dimensional image processing of myocardial CT perfusion for improved image quality and noise reduction.
abstract: BACKGROUND
  Image noise and multiple sources of artifact may affect the accurate interpretation of myocardial CT perfusion (CTP) studies. Although artifact within the image is often time dependent, tissue characteristics remain unchanged irrespective of cardiac phase.
  
  
  OBJECTIVE
  We assessed a new technique of 4-dimensional, spatiotemporal analysis, using redundant time domain information within additional phase acquisitions to reduce CTP image noise.
  
  
  METHODS
  Four-dimensional analysis was assessed in a static phantom and in 10 CTP studies with invasive fractional flow reserve (FFR) correlation. For each voxel within the CTP study the distribution of local Hounsfield values was measured in both time and space with the use of a customized program within MATLAB software. These values were filtered to eliminate those likely to represent noise or rapidly changing beam hardening artifact. All CTP images were acquired within a single heartbeat with 320 detector-row CT. Image noise was quantified as the SD of voxel values within myocardial segments. Contrast was measured between normal and abnormal vascular territories as assessed by FFR.
  
  
  RESULTS
  The mean image noise within the unprocessed CTP images was 30 HU (range, 23-42 HU). After 4-dimensional filtering the mean image noise was 22 HU (range, 15-29 HU). The mean reduction in image noise was 28% (P < 0.001). The mean contrast between normally perfused and ischemic segments was not significantly changed. The mean increase in contrast-to-noise ratio between ischemic territories and the myocardial average was 52% (P < 0.001).
  
  
  CONCLUSIONS
  Four-dimensional analysis of CTP significantly reduces image noise and may assist in the assessment of myocardial perfusion studies.
authors.affiliation: St Vincent's Hospital, Sydney, Australia.
authors.forename: James M
authors.initials: JM
authors.lastname: Otton
authors.forename: J Tobias
authors.initials: JT
authors.lastname: Kühl
authors.forename: Klaus F
authors.initials: KF
authors.lastname: Kofoed
authors.forename: Jane
authors.initials: J
authors.lastname: McCrohon
authors.forename: Michael
authors.initials: M
authors.lastname: Feneley
authors.forename: Neville
authors.initials: N
authors.lastname: Sammel
authors.forename: Chung-Yao
authors.initials: CY
authors.lastname: Yu
authors.forename: Amedeo
authors.initials: A
authors.lastname: Chiribiri
authors.forename: Eike
authors.initials: E
authors.lastname: Nagel
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D016477:Artifacts; D017023:Coronary Angiography / Q000379:methods*; D003324:Coronary Artery Disease / Q000000981:diagnostic imaging*; D005260:Female; D056973:Four-Dimensional Computed Tomography / Q000379:methods*; D006801:Humans; D008297:Male; D008875:Middle Aged; D055414:Myocardial Perfusion Imaging / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D059629:Signal-To-Noise Ratio