Ian S. Rogers, M.D., M.P.H.

Publication Details

  • A comparison of reconstruction and viewing parameters on image quality and accuracy of stress myocardial CT perfusion JOURNAL OF CARDIOVASCULAR COMPUTED TOMOGRAPHY Ghoshhajra, B. B., Rogers, I. S., Maurovich-Horvat, P., Techasith, T., Verdini, D., Sidhu, M. S., Drzezga, N. K., Medina, H. M., Blankstein, R., Brady, T. J., Cury, R. C. 2011; 5 (6): 459-466


    Myocardial stress computed tomography perfusion (CTP) has similar diagnostic accuracy for detecting perfusion defects (PDs) versus single-photon emission computed tomography (SPECT). However, the optimal diagnostic viewing and image processing parameters for CTP are unknown.We sought to compare the diagnostic accuracy of different image processing techniques, cardiac phases, slice thicknesses, and viewing parameters for detection of PDs.A stress and rest dual-source CTP protocol was performed with adenosine. Twelve subjects with severe stenosis proven by quantitative coronary angiography (QCA), with corresponding territorial defects at SPECT, were selected as well as 7 controls (subjects with similar clinical suspicion but negative QCA and SPECT). Short-axis stress images were processed with 3 techniques: minimum intensity projection (MinIP), maximum intensity projection, and average intensity multiplanar reconstruction (MPR), 3 thicknesses (1, 3, 8 mm), and 2 phases (systolic, mid-diastolic). The resulting images (n = 1026) were randomized and interpreted by independent readers.Diastolic reconstructions (8-mm MPR) showed the highest sensitivity (81%) to detect true PDs. The highest accuracy was achieved with the 8-mm (61%) and 1-mm (61%) MPR diastolic images. The most sensitive and accurate systolic reconstructions were 3-mm MinIP images. These findings related to viewing in relatively narrow window width and window level settings.Viewing parameters for optimal accuracy in detection of perfusion defects on CTP differ for systolic and diastolic images.

    View details for DOI 10.1016/j.jcct.2011.10.011

    View details for Web of Science ID 000310933700013

    View details for PubMedID 22146505

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