title: An observer study methodology for evaluating detection of motion abnormalities in gated myocardial perfusion SPECT.
abstract: To address the task of detecting nonischemic motion abnormalities from animated displays of gated myocardial perfusion single photon emission computed tomography data, we performed an observer study to evaluate the difference in detection performance between gating to 8 and 16 frames. Images were created from the NCAT mathematical phantom with a realistic heart simulating hypokinetic motion in the left lateral wall. Realistic noise-free projection data were simulated for both normal and defective hearts to obtain 16 frames for the cardiac cycle. Poisson noise was then simulated for each frame to create 50 realizations of each heart, All datasets were processed in two ways: reconstructed as a 16-frame set, and collapsed to 8 frames and reconstructed. Ten observers viewed the cardiac images animated with a realistic real-time frame rate. Observers trained on 100 images and tested on 100 images, rating their confidence on the presence of a motion defect on a continuous scale. None of the observers showed a significant difference in performance between the two gating methods. The 95% confidence interval on the difference in areas under the ROC curve (Az8 - Az16) was -0.029-0.085. Our test did not find a significant difference in detection performance between 8-frame gating and 16-frame gating. We conclude that, for the task of detecting abnormal motion, increasing the number of gated frames from 8 to 16 offers no apparent advantage.
authors.affiliation: Joint Department of Biomedical Engineering of North Carolina State University and The University of North Carolina at Chapel Hill, NC State University, Raleigh, NC 27695-7115, USA. david_lalush@ncsu.edu
authors.forename: David S
authors.initials: DS
authors.lastname: Lalush
authors.forename: Megan K
authors.initials: MK
authors.lastname: Jatko
authors.forename: W Paul
authors.initials: WP
authors.lastname: Segars
mesh_terms: D001185:Artificial Intelligence; D015637:Gated Blood-Pool Imaging / Q000295:instrumentation / Q000379:methods*; D006352:Heart Ventricles / Q000000981:diagnostic imaging / Q000503:physiopathology; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D009068:Movement; D015588:Observer Variation; D019047:Phantoms, Imaging; D015203:Reproducibility of Results; D018401:Sample Size; D012680:Sensitivity and Specificity; D013647:Task Performance and Analysis; D015899:Tomography, Emission-Computed, Single-Photon / Q000295:instrumentation / Q000379:methods*; D018487:Ventricular Dysfunction, Left / Q000000981:diagnostic imaging* / Q000503:physiopathology; D014741:Video Recording / Q000379:methods