Original Article
Diffusion-tensor imaging as an adjunct to dynamic contrast-enhanced MRI for improved accuracy of differential diagnosis between breast ductal carcinoma in situ and invasive breast carcinoma
Abstract
Objective: To determine the value of diffusion-tensor imaging (DTI) as an adjunct to dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for improved accuracy of differential diagnosis between breast ductal carcinoma in situ (DCIS) and invasive breast carcinoma (IBC).
Methods: The MRI data of 63 patients pathologically confirmed as breast cancer were analyzed. The conventional MRI analysis metrics included enhancement style, initial enhancement characteristic, maximum slope of increase, time to peak, time signal intensity curve (TIC) pattern, and signal intensity on FS-T2WI. The values of apparent diffusion coefficient (ADC), directionally-averaged mean diffusivity (Davg), exponential attenuation (EA), fractional anisotropy (FA), volume ratio (VR) and relative anisotropy (RA) were calculated and compared between DCIS and IBC. Multivariate logistic regression was used to identify independent factors for distinguishing IBC and DCIS. The diagnostic performance of the diagnosis equation was evaluated using the receiver operating characteristic (ROC) curve. The diagnostic efficacies of DCE-MRI, DWI and DTI were compared independently or combined.
Results: EA value, lesion enhancement style and TIC pattern were identified as independent factor for differential diagnosis of IBC and DCIS. The combination diagnosis showed higher diagnostic efficacy than a single use of DCE-MRI (P=0.02), and the area of the curve was improved from 0.84 (95% CI, 0.67-0.99) to 0.94 (95% CI, 0.85-1.00).
Conclusions: Quantitative DTI measurement as an adjunct to DCE-MRI could improve the diagnostic performance of differential diagnosis between DCIS and IBC compared to a single use of DCE-MRI.
Methods: The MRI data of 63 patients pathologically confirmed as breast cancer were analyzed. The conventional MRI analysis metrics included enhancement style, initial enhancement characteristic, maximum slope of increase, time to peak, time signal intensity curve (TIC) pattern, and signal intensity on FS-T2WI. The values of apparent diffusion coefficient (ADC), directionally-averaged mean diffusivity (Davg), exponential attenuation (EA), fractional anisotropy (FA), volume ratio (VR) and relative anisotropy (RA) were calculated and compared between DCIS and IBC. Multivariate logistic regression was used to identify independent factors for distinguishing IBC and DCIS. The diagnostic performance of the diagnosis equation was evaluated using the receiver operating characteristic (ROC) curve. The diagnostic efficacies of DCE-MRI, DWI and DTI were compared independently or combined.
Results: EA value, lesion enhancement style and TIC pattern were identified as independent factor for differential diagnosis of IBC and DCIS. The combination diagnosis showed higher diagnostic efficacy than a single use of DCE-MRI (P=0.02), and the area of the curve was improved from 0.84 (95% CI, 0.67-0.99) to 0.94 (95% CI, 0.85-1.00).
Conclusions: Quantitative DTI measurement as an adjunct to DCE-MRI could improve the diagnostic performance of differential diagnosis between DCIS and IBC compared to a single use of DCE-MRI.
