Abstract
BackgroundTraditional 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 methodsIn 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 (SIslope), initial percentage of enhancement (Einitial), percentage of peak enhancement (Epeak), 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.ResultsAccording 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 SIslope, 65.24% for MSI, 58.45% for Einitial, 66.20% for Epeak, 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.ConclusionCompared 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.
Highlights
Traditional subjective method for the analysis of time-intensity curves (TICs) from breast dynamic contrast enhanced Magnetic Resonance Imaging (MRI) (DCE-MRI) presented a low specificity
For the mean TICs derived from the semi-automatic method, the accuracies were 77.47% for signal intensity slope (SIslope), 65.24% for maximum slope of increase (MSI), 58.45% for Einitial, 66.20% for Epeak, 71.83% for early signal enhancement ratio (ESER), and 54.93% for second enhancement percentage (SEP), respectively
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
Summary
Traditional subjective method for the analysis of time-intensity curves (TICs) from breast dynamic contrast enhanced MRI (DCE-MRI) presented a low specificity. Due to its three-dimensional nature, MRI has been considered as complementary to conventional mammography for the evaluation of suspicious breast lesions [4]. It can detect cancers missed by mammography or ultrasound in women who have dense breasts. The time intensity curve (TIC) of signal from DCE-MRI has been frequently used clinically to characterize the biological and clinical aggressiveness of breast lesions [7,8,9]. The mean TIC of signals within the ROI was calculated, and was subjectively classified as persistently enhancing (type I), where the signal intensity continued to increase over time; plateau (type II), where the signal intensity did not change over time after its initial increase during the delayed phase; and washout (type III), where the signal intensity decreased after reaching the highest point of its initial increase during the delayed phase [10,11,12,13,14,15,16]
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