摘要
AIM:To correlate dual-energy computed tomography(DECT) pulmonary angiography derived iodine maps with parameter maps of quantitative pulmonary perfusion magnetic resonance imaging(MRI).METHODS:Eighteen patients with pulmonary perfusion defects detected on DECT derived iodine maps were included in this prospective study and additionally underwent time-resolved contrast-enhanced pulmonary MRI [dynamic contrast enhanced(DCE)-MRI].DCE-MRI data were quantitatively analyzed using a pixel-by-pixel deconvolution analysis calculating regional pulmonary blood flow(PBF),pulmonary blood volume(PBV) and mean transit time(MTT) in visually normal lung parenchyma and perfusion defects.Perfusion parameterswere correlated to mean attenuation values of normal lung and perfusion defects on DECT iodine maps.Two readers rated the concordance of perfusion defects in a visual analysis using a 5-point Likert-scale(1 = no correlation,5 = excellent correlation).RESULTS:In visually normal pulmonary tissue mean DECT and MRI values were:22.6 ± 8.3 Hounsfield units(HU);PBF:58.8 ± 36.0 mL/100 mL per minute;PBV:16.6 ± 8.5 mL;MTT:17.1 ± 10.3 s.In areas with restricted perfusion mean DECT and MRI values were:4.0 ± 3.9 HU;PBF:10.3 ± 5.5 mL/100 mL per minute,PBV:5 ± 4 mL,MTT:21.6 ± 14.0 s.The differences between visually normal parenchyma and areas of restricted perfusion were statistically significant for PBF,PBV and DECT(P < 0.0001).No linear correlation was found between MRI perfusion parameters and attenuation values of DECT iodine maps(PBF:r = 0.35,P = 0.15;PBV:r = 0.34,P = 0.16;MTT:r = 0.41,P = 0.08).Visual analysis revealed a moderate correlation between perfusion defects on DECT iodine maps and the parameter maps of DCE-MRI(mean score 3.6,k 0.45).CONCLUSION:There is a moderate visual but not statistically significant correlation between DECT iodine maps and perfusion parameter maps of DCE-MRI.
AIM:To correlate dual-energy computed tomography(DECT) pulmonary angiography derived iodine maps with parameter maps of quantitative pulmonary perfusion magnetic resonance imaging(MRI).METHODS:Eighteen patients with pulmonary perfusion defects detected on DECT derived iodine maps were included in this prospective study and additionally underwent time-resolved contrast-enhanced pulmonary MRI [dynamic contrast enhanced(DCE)-MRI].DCE-MRI data were quantitatively analyzed using a pixel-by-pixel deconvolution analysis calculating regional pulmonary blood flow(PBF),pulmonary blood volume(PBV) and mean transit time(MTT) in visually normal lung parenchyma and perfusion defects.Perfusion parameterswere correlated to mean attenuation values of normal lung and perfusion defects on DECT iodine maps.Two readers rated the concordance of perfusion defects in a visual analysis using a 5-point Likert-scale(1 = no correlation,5 = excellent correlation).RESULTS:In visually normal pulmonary tissue mean DECT and MRI values were:22.6 ± 8.3 Hounsfield units(HU);PBF:58.8 ± 36.0 mL/100 mL per minute;PBV:16.6 ± 8.5 mL;MTT:17.1 ± 10.3 s.In areas with restricted perfusion mean DECT and MRI values were:4.0 ± 3.9 HU;PBF:10.3 ± 5.5 mL/100 mL per minute,PBV:5 ± 4 mL,MTT:21.6 ± 14.0 s.The differences between visually normal parenchyma and areas of restricted perfusion were statistically significant for PBF,PBV and DECT(P < 0.0001).No linear correlation was found between MRI perfusion parameters and attenuation values of DECT iodine maps(PBF:r = 0.35,P = 0.15;PBV:r = 0.34,P = 0.16;MTT:r = 0.41,P = 0.08).Visual analysis revealed a moderate correlation between perfusion defects on DECT iodine maps and the parameter maps of DCE-MRI(mean score 3.6,k 0.45).CONCLUSION:There is a moderate visual but not statistically significant correlation between DECT iodine maps and perfusion parameter maps of DCE-MRI.
