An approach to evaluate myocardial perfusion defect assessment for projection-based DECT: A phantom study.
Clin Imaging
; 63: 10-15, 2020 Jul.
Article
em En
| MEDLINE
| ID: mdl-32120307
ABSTRACT
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.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Imagem de Perfusão do Miocárdio
Tipo de estudo:
Diagnostic_studies
Limite:
Humans
Idioma:
En
Revista:
Clin Imaging
Assunto da revista:
DIAGNOSTICO POR IMAGEM
Ano de publicação:
2020
Tipo de documento:
Article
País de afiliação:
Estados Unidos