Quantitative discrimination between invasive ductal carcinomas and benign lesions based on semi-automatic analysis of time intensity curves from breast dynamic contrast enhanced MRI

Journal of Experimental & Clinical Cancer Research

Wei Zhang¹  Qiyong Guo¹  Lu Han¹  Jiawen Yang¹  Jiandong Yin¹ 

[1] Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, P.R. China

关键词: Semi-automatic method;    CAD;    Diagnostic performance;    Time intensity curve;    Receiver operating characteristic;    Invasive ductal carcinoma;   

Others  :  1135791
DOI  :  10.1186/s13046-015-0140-y

 received in 2015-01-14, accepted in 2015-02-19,  发布年份 2015

【 摘 要 】

Background

Traditional subjective method for the analysis of time-intensity curves (TICs) from breast dynamic contrast enhanced MRI (DCE-MRI) presented a low specificity. Hence, a semi-automatic quantitative method was proposed and evaluated for distinguishing invasive ductal carcinomas from benign lesions.

Materials and methods

In the traditional method, the lesion was extracted by placing a region of interest (ROI) manually. The mean curve of the TICs from the ROI was subjectively classified as one of three patterns. Only one quantitative parameter, the mean value of maximum slope of increase (MSI), was provided. In the new method, the lesion was identified semi-automatically, and the mean curve was classified quantitatively. Some additional parameters, the signal intensity slope (SI_slope), initial percentage of enhancement (E_initial), percentage of peak enhancement (E_peak), early signal enhancement ratio (ESER), and second enhancement percentage (SEP) were derived from the mean curves as well as the lesion areas. Wilcoxon’s test and receiver operating characteristic (ROC) analyses were performed, and P < 0.05 was considered significant.

Results

According to the TIC classification results, the accuracies were 59.16% for the traditional manual method and 76.05% for the new method (P < 0.05). For the mean MSI values from the manual method, the accuracy was 63.35%. For the mean TICs derived from the semi-automatic method, the accuracies were 77.47% for SI_slope, 65.24% for MSI, 58.45% for E_initial, 66.20% for E_peak, 71.83% for ESER, and 54.93% for SEP, respectively. For the lesion regions identified by the semi-automatic method, the accuracies were 73.24%, 72.54%, 58.45%, 62.68%, 64.09%, and 55.64%, respectively.

Conclusion

Compared with traditional subjective method, the semi-automatic quantitative method proposed in this study showed a higher performance, and should be used as a supplementary tool to aid radiologist's subjective interpretation.

【 授权许可】

   
2015 Yin et al.; licensee BioMed Central.

【 图 表 】

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