Coronary CT angiography: automatic cardiac-phase selection for image reconstruction.
We evaluated an algorithm for automatic selection of the cardiac phase with the least motion for image reconstruction at coronary computed tomography (CT) angiography (CCTA). We analyzed data of 100 patients (49 female, mean age 59 years) who had undergone retrospectively ECG-gated CCTA. Two experienced observers visually identified the most suitable end-systolic and end-diastolic phases using a series of image reconstructions in 5% increments across the RR cycle. The same data were then reconstructed using an automatic phase finding algorithm based on a 4D weighting function of cardiac motion. On average, the algorithm determined the most suitable systolic reconstruction phase at 40.11 +/- 6.29% RR compared with 40.07 +/- 5.58% RR by the human observers (p = NS). The most suitable diastolic phase was found at 72.71 +/- 7.37% RR by the automatic algorithm, compared with 76.43 +/- 6.35% RR by the observers (p < 0.05). No statistically significant difference was found between automatically and visually determined reconstruction phases regarding motion and stair-step artifacts in either systole or diastole (p > 0.05). Thus, there appears to be no relevant difference between an automatic phase finding algorithm and visual selection by experienced observers for determining the phase with the least cardiac motion for CCTA image reconstruction. The use of automatic phase finding may therefore facilitate the performance of cardiac CT and reduce human error.
Ruzsics
Balazs
B
Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, 25 Courtenay Dr., Charleston, SC 29401, USA.
Gebregziabher
Mulugeta
M
Lee
Heon
H
Brothers
Robin L
RL
Allmendinger
Thomas
T
Vogt
Sebastian
S
Costello
Philip
P
Schoepf
U Joseph
UJ
D000465:Algorithms; D016477:Artifacts; D001185:Artificial Intelligence; D055424:Cardiac-Gated Imaging Techniques / Q000379:methods*; D017023:Coronary Angiography / Q000379:methods*; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods; D008297:Male; D008875:Middle Aged; D009068:Movement; D010363:Pattern Recognition, Automated / Q000379:methods; D011856:Radiographic Image Enhancement / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*