The value of whole-tumor histogram and texture analysis based on apparent diffusion coefficient (ADC) maps for the discrimination of breast fibroepithelial lesions: corresponds to clinical management decisions

PurposeThis study aims to comprehensively evaluate the diagnostic value of quantitative parameters extracted from apparent diffusion coefficient (ADC) maps in distinguishing fibroepithelial tumors using whole-tumor histogram and texture analysis.Materials and methodsThis retrospective study included 66 female patients with single phyllodes tumor (PT) and 29 female patients with single fibroadenoma (FA) who underwent preoperative magnetic resonance imaging. By independently performing whole-tumor histogram and texture analysis based on ADC maps, two radiologists extracted seven histogram parameters and four texture parameters. The extracted parameters were compared using univariate analysis to determine their ability to distinguish FAs from PTs, benign PTs from FAs, as well as benign PTs from borderline and malignant PTs.ResultsWhen FAs and PTs were compared, ADC_skewness values of PTs were significantly lower than those of FAs (p < 0.05), whereas other significant extracted parameter values of PTs were significantly higher than those of FAs (p ≤ 0.001); the area under the curve of significant parameters combined was 0.936. Regarding the differences between FAs and benign PTs, ADC_SD, ADC_95th percentile and ADC_kurtosis of FAs were significantly lower than those of benign PT group, and ADC_skewness was higher than that of benign PT group (all p < 0.05). Furthermore, ADC_SD, ADC_95th percentile and all texture parameters are significantly higher in the borderline and malignant PT group than in FA and benign PT group (p < 0.05). In addition, ADC_kurtosis of malignant PT group was significantly lower than that of borderline PT group (p = 0.045).ConclusionThe extracted whole-tumor histogram and texture features of ADC maps can improve differential diagnosis of breast fibroepithelial tumors and contribute to optimal selection for clinical management of patients with fibroepithelial tumors.