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J Cardiovasc Comput Tomogr ; 12(3): 212-219, 2018.
Artículo en Inglés | MEDLINE | ID: mdl-29730016

RESUMEN

AIMS: To determine the diagnostic accuracy of semi-automatic quantitative metrics compared to expert reading for interpretation of computed tomography perfusion (CTP) imaging. METHODS: The CORE320 multicenter diagnostic accuracy clinical study enrolled patients between 45 and 85 years of age who were clinically referred for invasive coronary angiography (ICA). Computed tomography angiography (CTA), CTP, single photon emission computed tomography (SPECT), and ICA images were interpreted manually in blinded core laboratories by two experienced readers. Additionally, eight quantitative CTP metrics as continuous values were computed semi-automatically from myocardial and blood attenuation and were combined using logistic regression to derive a final quantitative CTP metric score. For the reference standard, hemodynamically significant coronary artery disease (CAD) was defined as a quantitative ICA stenosis of 50% or greater and a corresponding perfusion defect by SPECT. Diagnostic accuracy was determined by area under the receiver operating characteristic curve (AUC). RESULTS: Of the total 377 included patients, 66% were male, median age was 62 (IQR: 56, 68) years, and 27% had prior myocardial infarction. In patient based analysis, the AUC (95% CI) for combined CTA-CTP expert reading and combined CTA-CTP semi-automatic quantitative metrics was 0.87(0.84-0.91) and 0.86 (0.83-0.9), respectively. In vessel based analyses the AUC's were 0.85 (0.82-0.88) and 0.84 (0.81-0.87), respectively. No significant difference in AUC was found between combined CTA-CTP expert reading and CTA-CTP semi-automatic quantitative metrics in patient based or vessel based analyses(p > 0.05 for all). CONCLUSION: Combined CTA-CTP semi-automatic quantitative metrics is as accurate as CTA-CTP expert reading to detect hemodynamically significant CAD.


Asunto(s)
Angiografía por Tomografía Computarizada/métodos , Angiografía Coronaria/métodos , Enfermedad de la Arteria Coronaria/diagnóstico por imagen , Circulación Coronaria , Vasos Coronarios/diagnóstico por imagen , Tomografía Computarizada Multidetector/métodos , Imagen de Perfusión Miocárdica/métodos , Interpretación de Imagen Radiográfica Asistida por Computador/métodos , Anciano , Anciano de 80 o más Años , Área Bajo la Curva , Asia , Automatización , Angiografía por Tomografía Computarizada/normas , Angiografía Coronaria/normas , Enfermedad de la Arteria Coronaria/fisiopatología , Vasos Coronarios/fisiopatología , Europa (Continente) , Femenino , Humanos , Modelos Logísticos , Masculino , Persona de Mediana Edad , Tomografía Computarizada Multidetector/normas , Imagen de Perfusión Miocárdica/normas , América del Norte , Variaciones Dependientes del Observador , Valor Predictivo de las Pruebas , Estudios Prospectivos , Curva ROC , Interpretación de Imagen Radiográfica Asistida por Computador/normas , Estándares de Referencia , Reproducibilidad de los Resultados , Índice de Severidad de la Enfermedad , América del Sur , Tomografía Computarizada de Emisión de Fotón Único
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