TY - JOUR
T1 - An approach to evaluate myocardial perfusion defect assessment for projection-based DECT
T2 - A phantom study
AU - Han, Donghee
AU - Shah, Sunny
AU - Lee, Ji Hyun
AU - Elmore, Kimberly
AU - Gransar, Heidi
AU - Danad, Ibrahim
AU - Kumar, Vidhya
AU - Raman, Subha
AU - Hartaigh, Bríain
AU - Dunham, Simon
AU - Lin, Fay Y.
AU - Min, James K.
N1 - Publisher Copyright:
© 2019
PY - 2020/7
Y1 - 2020/7
N2 - Introduction: Dual-energy CT (DECT) can improve the accuracy of myocardial perfusion CT with projection-based monochromatic (DECT-MCE) and quantification of myocardial iodine in material decomposition (DECT-MD) reconstructions. However, evaluation of multiple reconstructions is laborious and the optimal reconstruction to detect myocardial perfusion defects is unknown. Methods: Left ventricular (LV) phantoms with artificial perfusion defects were scanned using DECT and single energy cardiac computed tomography angiography (SECT). Reconstructions of DECT-MCE at 40, 70, 100 and 140 keV, DECT-MD pairs of water, iodine, iron and fat, and SECT were evaluated using a 17-segment myocardial model. The diagnostic performance of each reconstruction was calculated on a per-segment basis and compared across DECT reconstructions. Results: Over 34 phantoms with artificial perfusion defects were found in 64/578 (11%) of segments, the sensitivity of DECT-MCE at 40, 70, 100, and 140 keV was 100% (95% confidence interval (CI): 93–100), 100% (95% CI: 93–100), 71% (95% CI: 56–83), and 25% (95% CI: 14–40), respectively, with a significant decline between 70 keV and 100 keV (p < 0.001). The specificity of DECT-MCE was 100% at all energies (95% CI: 99–100). As a group, the DECT-MD iodine background reconstructions had significantly lower sensitivity than the remaining modes (2.1% [95% CI, 0.05–11.1], vs. 100% [95% CI, 92.6–100], p < 0.001). Specificity of all material pair modes remained 100%. Conclusions: Using LV phantom models, the approach with the best sensitivity and specificity to assess myocardial perfusion defects with DECT are reconstructions of DECT-MCE at 40 or 70 KeV and DECT-MD without iodine background.
AB - Introduction: Dual-energy CT (DECT) can improve the accuracy of myocardial perfusion CT with projection-based monochromatic (DECT-MCE) and quantification of myocardial iodine in material decomposition (DECT-MD) reconstructions. However, evaluation of multiple reconstructions is laborious and the optimal reconstruction to detect myocardial perfusion defects is unknown. Methods: Left ventricular (LV) phantoms with artificial perfusion defects were scanned using DECT and single energy cardiac computed tomography angiography (SECT). Reconstructions of DECT-MCE at 40, 70, 100 and 140 keV, DECT-MD pairs of water, iodine, iron and fat, and SECT were evaluated using a 17-segment myocardial model. The diagnostic performance of each reconstruction was calculated on a per-segment basis and compared across DECT reconstructions. Results: Over 34 phantoms with artificial perfusion defects were found in 64/578 (11%) of segments, the sensitivity of DECT-MCE at 40, 70, 100, and 140 keV was 100% (95% confidence interval (CI): 93–100), 100% (95% CI: 93–100), 71% (95% CI: 56–83), and 25% (95% CI: 14–40), respectively, with a significant decline between 70 keV and 100 keV (p < 0.001). The specificity of DECT-MCE was 100% at all energies (95% CI: 99–100). As a group, the DECT-MD iodine background reconstructions had significantly lower sensitivity than the remaining modes (2.1% [95% CI, 0.05–11.1], vs. 100% [95% CI, 92.6–100], p < 0.001). Specificity of all material pair modes remained 100%. Conclusions: Using LV phantom models, the approach with the best sensitivity and specificity to assess myocardial perfusion defects with DECT are reconstructions of DECT-MCE at 40 or 70 KeV and DECT-MD without iodine background.
KW - Computed tomography
KW - Dual energy
KW - Material decomposition
KW - Monochromatic
KW - Myocardial perfusion imaging
KW - Phantom
UR - http://www.scopus.com/inward/record.url?scp=85080069102&partnerID=8YFLogxK
U2 - 10.1016/j.clinimag.2019.09.016
DO - 10.1016/j.clinimag.2019.09.016
M3 - Article
C2 - 32120307
AN - SCOPUS:85080069102
SN - 0899-7071
VL - 63
SP - 10
EP - 15
JO - Clinical Imaging
JF - Clinical Imaging
ER -