The efficiency of volumetric apparent diffusion coefficient histogram analysis in breast papillary neoplasms

Background/Aim: Papillary neoplasia encompasses both malignant and benign lesions, and core needle biopsy (CNB) is crucial in their diagnosis. Histological findings determine their management. Here we compare volumetric apparent diffusion coefficient (ADC) histogram analysis of carcinomas and benign pathologies identified by histopathology from excisional biopsies. Methods: This retrospective study included 524 patients who underwent breast magnetic resonance imaging (MRI) for a suspicious breast mass from January 2018 to October 2022. Patients with benign lesions, incompatible ultrasound-guided CNB results with papillary neoplasia, and those with MRI exams insufficient for diagnosis due to motion artifacts were excluded. After applying the exclusion criteria, the study included 48 patients (average aged 61.5 (14.8) years; range, 31 to 72 years). After excisional biopsies, 30 benign lesions and 18 carcinomas were identified. MRI was acquired at 1.5 T (Verio; Siemens Medical Solutions, Erlangen, Germany), and the b-values for diffusion-weighted imaging were calculated at 1000 s/mm2. Histogram parameters were computed. Receiver operating characteristic (ROC) curve analysis was performed to investigate diagnostic accuracy, evaluate histogram analysis performance, and determine threshold values. Results: The ADCmin, ADCmean, ADCmax, and all ADC value percentiles were significantly lower in the carcinoma group than in the benign group (P<0.001). The variance, skewness, and kurtosis were higher in the carcinoma group. ADCmax had the highest area under the curve (AUC: 0.985; cut-off 1.247 × 10-3 mm2/s; sensitivity 86%, and specificity 92%), followed by ADCmean (AUC: 0.950; cut-off 0.903 × 10-3 mm2/s; sensitivity 94%, and specificity 96%). Conclusion: Volumetric ADC histogram analysis of papillary neoplasia at higher b-values can be an imaging marker to detect carcinoma and quantitatively reveal the lesions’ diffusion characteristics.