Estimation of intra-operator variability in perfusion parameter measurements using DCE-US  被引量:6

Estimation of intra-operator variability in perfusion parameter measurements using DCE-US

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作  者:Marianne Gauthier Ingrid Leguerney Jessie Thalmensi Mohamed Chebil Sarah Parisot Pierre Peronneau Alain Roche Nathalie Lassau 

机构地区:[1]IR4M,UMR 8081,CNRS,Paris-Sud 11 Univ,Gustave Roussy Institute [2]Department of Imaging,Ultrasonography Unit,Gustave Roussy Institute

出  处:《World Journal of Radiology》2011年第3期70-81,共12页世界放射学杂志(英文版)(电子版)

摘  要:AIM:To investigate intra-operator variability of semiquantitative perfusion parameters using dynamic contrast-enhanced ultrasonography(DCE-US),following bolus injections of SonoVue.METHODS:The in vitro experiments were conducted using three in-house sets up based on pumping a fluid through a phantom placed in a water tank.In the in vivo experiments,B16F10 melanoma cells were xenografted to five nude mice.Both in vitro and in vivo,images were acquired following bolus injections of the ultrasound contrast agent SonoVue(Bracco,Milan,Italy) and using a Toshiba Aplio ultrasound scanner connected to a 2.9-5.8 MHz linear transducer(PZT,PLT 604AT probe)(Toshiba,Japan) allowing harmonic imaging("Vascular Recognition Imaging") involving linear raw data.A mathematical model based on the dye-dilution theory was developed by the Gustave Roussy Institute,Villejuif,France and used to evaluate seven perfusion parameters from time-intensity curves.Intra-operator variability analyses were based on determining perfusion parameter coefficients of variation(CV).RESULTS:In vitro,different volumes of SonoVue were tested with the three phantoms:intra-operator variability was found to range from 2.33% to 23.72%.In vivo,experiments were performed on tumor tissues and perfusion parameters exhibited values ranging from 1.48% to 29.97%.In addition,the area under the curve(AUC) and the area under the wash-out(AUWO) were two of the parameters of great interest since throughout in vitro and in vivo experiments their variability was lower than 15.79%.CONCLUSION:AUC and AUWO appear to be the most reliable parameters for assessing tumor perfusion using DCE-US as they exhibited the lowest CV values.AIM: To investigate intra-operator variability of semi-quantitative perfusion parameters using dynamic contrast-enhanced ultrasonography (DCE-US), following bolus injections of SonoVue?.METHODS: The in vitro experiments were conducted using three in-house sets up based on pumping a fluid through a phantom placed in a water tank. In the in vivo experiments, B16F10 melanoma cells were xenografted to five nude mice. Both in vitro and in vivo, images were acquired following bolus injections of the ultrasound contrast agent SonoVue? (Bracco, Milan, Italy) and using a Toshiba Aplio? ultrasound scanner connected to a 2.9-5.8 MHz linear transducer (PZT, PLT 604AT probe) (Toshiba, Japan) allowing harmonic imaging (“Vascular Recognition Imaging”) involving linear raw data. A mathematical model based on the dye-dilution theory was developed by the Gustave Roussy Institute, Villejuif, France and used to evaluate seven perfusion parameters from time-intensity curves. Intra-operator variability analyses were based on determining perfusion parameter coefficients of variation (CV).RESULTS: In vitro, different volumes of SonoVue? were tested with the three phantoms: intra-operator variability was found to range from 2.33% to 23.72%. In vivo, experiments were performed on tumor tissues and perfusion parameters exhibited values ranging from 1.48% to 29.97%. In addition, the area under the curve (AUC) and the area under the wash-out (AUWO) were two of the parameters of great interest since throughout in vitro and in vivo experiments their variability was lower than 15.79%.CONCLUSION: AUC and AUWO appear to be the most reliable parameters for assessing tumor perfusion using DCE-US as they exhibited the lowest CV values.

关 键 词:Dynamic CONTRAST-ENHANCED ultrasonography Intra-operator VARIABILITY Functional imaging SEMI-QUANTITATIVE PERFUSION parameters Linear raw data Quantification 

分 类 号:R739.5[医药卫生—肿瘤]

 

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