双能量Mono+技术联合虚拟平扫与常规3期扫描在颈部CT增强扫描中的对比研究

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[Abstract]Objective：Toinvestigatethefeasibilityofusingdual-energyForceCTincervicalCTenhancementscas，by generatingvirtalnon-contrast（VNC）andMono+technique，toobtain VNCimagesfromvenousphaseimagesandvirtualarterial phase（Vart）images.Methods：Aretrospectiveanalysiswasconductedon56 patientswhounderwent dual-energyCTcervical enhancementscans.The post-processingonthevenousphaseimages were performedtoobtainVNCimagesandarterial phase imagessimulatedby40keVvirtualmono-energyimages（Vart）．Theseimageswerecomparedwithtruenon-contrast（TNC） imagesandtruearterialphase（CIart）images.Intermsofimagequalityasessment，a5-pointdouble-blindsubjectivescoring methodwasusedtoevaluatethedisplayofsofttisuestructures，asessmentofcarotidstenosis，andartifact.Objective evaluationindicatorsincludedCTvaluesoftisseandvessels，noise（SD），SNRandCNR.Results：VNC imageshad the higherSNRintheleftvertebralartery，spinalmusclesandthelowerSNRinthyroidcomparedwithTNCimages（al P< （204号 0.05）.Vartimages had thehigher SNRinall evaluated tissuesandveselscompared with CIart images（all P<0.05 ）.In theVNCimages，xceptfortheCNRvaluesoftheleftandrightvertebralarterieswhichshowednostatisticallsignificant diferencecomparedwithTNCimages，the CNRvaluesoftheremainingvesels，thyroidandsubmandibulargland were all smaller than those in the TNC images（all P<0.05 ）.Comparedwith CIart images，the CNR values of the left and right internal carotid arteries，thyroid and submandibular gland in Vart images were increased （all P<0.05 ）. Conclusions：Force CT Mono+ technique in venous phase imaging of cervical enhancement scans，through post-processing to reconstruct 40keV virtual mono-energyimagescombinedwithwindowtechnology，canefectivelysimulateCIartimages，emonstratingitsfeasibilityinthe diagnosis ofvascular lesions.Furthermore，when combined withVNC，this technique can replace traditional cervical contrast-enhancedthree-phaseimaging withinacertain range，thus demonstrating its significant value in low-dose

目前，在后处理重建技术领域，Siemens公司在ForceCT第1代能谱成像算法MonoE的基础上，推出了第2代能谱成像算法——MonoenergeticPlus（Mono+） 。（剩余8809字）