Title
3d Analysis Of Myocardial Perfusion From Vasodilator Stress Computed Tomography: Can Accuracy Be Improved By Iterative Reconstruction?
Abstract
Computed tomography (CT) is an emerging tool to detect stress-induced myocardial perfusion abnormalities. We hypothesized that iterative reconstruction (IR) could improve the accuracy of the detection of significant coronary artery disease using quantitative 3D analysis of myocardial perfusion during vasodilator stress.We studied 39 patients referred for CT coronary angiography (CTCA) who agreed to undergo additional imaging with regadenoson (Astellas). Images were acquired using 256-channel scanner (Philips) and reconstructed using 2 different algorithms: filtered back-projection (FBP) and IR (iDose7, Philips). Custom software was used to analyze both FBP and IR images. An index of severity and extent of perfusion abnormality was calculated for each 3D myocardial segment and compared to perfusion defects predicted by coronary stenosis >50% on CTCA.Five patients with image artifacts were excluded. Ten patients with normal coronaries were used to obtain reference values, which were used to correct for x-ray attenuation differences among normal myocardial segments. Compared to the conventional FBP images, IR images had considerably lower noise levels, resulting in tighter histograms of x-ray attenuation. In the remaining 24 patients, IR improved the detection of perfusion abnormalities.Quantitative 3D analysis of MDCT images allows objective detection of stress-induced perfusion abnormalities, the accuracy of which is improved by IR.
Year
Venue
Keywords
2013
2013 COMPUTING IN CARDIOLOGY CONFERENCE (CINC)
iterative methods,muscle,image reconstruction
Field
DocType
Volume
Iterative reconstruction,Nuclear medicine,Coronary artery disease,Idose,Stenosis,Computed tomography,Radiology,Regadenoson,Medicine,Angiography,Perfusion
Conference
40
ISSN
Citations 
PageRank 
2325-8861
0
0.34
References 
Authors
0
8
Name
Order
Citations
PageRank
Victor Mor-Avi102.70
Nadjia Kachenoura275.89
nicole m bhave300.68
benjamin h freed400.34
Michael W. Vannier51380360.85
Karin E Dill630.79
Roberto M Lang785.14
Amit Patel883.88