Intravoxel incoherent motion for quantitative evaluating chronic allograft dysfunction / 中国医学影像技术
Chinese Journal of Medical Imaging Technology
; (12): 93-97, 2024.
Article
in Zh
| WPRIM
| ID: wpr-1026285
Responsible library:
WPRO
ABSTRACT
Objective To observe the value of diffusion weighted imaging intravoxel incoherent motion(IVIM)for quantitative evaluating chronic allograft dysfunction(CAD).Methods Totally 104 CAD patients were prospectively enrolled and were assigned into CAD 1,2 and 3 groups(n=11,61,32)based on impairment severity of estimated renal function,and 36 healthy volunteers were enrolled as control group.The true diffusion coefficient(D value),microcirculation perfusion diffusion coefficient(D*value)and perfusion score(f value)of renal cortex and medulla IVIM parameters were compared among groups and within groups to assess the value of IVIM parameters for diagnosing CAD.Results The D value of transplanted renal cortex in all CAD groups were lower than that in control group(all P<0.05),which decreased among CAD 1,2 and 3 groups(all P<0.05).The D value of transplanted kidney medulla in CAD 2 and 3 groups were lower than that in control group(both P<0.05).The D*values of transplanted renal cortex in all CAD groups were lower than that in control group,while of renal medulla in CAD 2 and 3 groups were lower than that in control group(both P<0.05).The f values of cortex and medulla in CAD 2 and 3 groups were lower than those in control group(all P<0.05),while of cortex in CAD 3 group was lower than that in CAD 1 and 2 groups(both P<0.05).The area under the curve(AUC)of cortical IVIM combined model for diagnosing CAD was 0.96,better than the D*value and f value(AUC=0.74,0.83,P<0.05)but not significantly different with that of the D value(AUC=0.94,P=0.32).AUC of medullary IVIM combined model for diagnosing CAD was 0.91,better than that of D,D*and f value(AUC=0.80,0.67 and 0.80,all P<0.05).Conclusion IVIM parameters could be used to quantitatively evaluate CAD.
Full text:
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Index:
WPRIM
Language:
Zh
Journal:
Chinese Journal of Medical Imaging Technology
Year:
2024
Type:
Article