Radiologic-pathologic correlation in breast cancer: do MRI biomarkers correlate with pathologic features and molecular subtypes?

BACKGROUND: Breast cancer (BC) includes different pathological and molecular subtypes. This study aimed to investigate whether multiparametric magnetic resonance imaging (mpMRI) could reliably predict the molecular status of BC, comparing mpMRI features with pathological and immunohistochemical results. METHODS: This retrospective study included 156 patients with an ultrasound-guided biopsy-proven BC, who underwent breast mpMRI (including diffusion-weighted imaging) on a 3-T scanner from 2017 to 2020. Histopathological analyses were performed on the surgical specimens. Kolmogorov-Smirnov Z, χ2, and univariate and multivariate logistic regression analyses were performed. RESULTS: Fifteen patients were affected with ductal carcinoma in situ, 122 by invasive carcinoma of no special type, and 19 with invasive lobular carcinoma. Out of a total of 141 invasive cancers, 45 were luminal A-like, 54 luminal B-like, 5 human epidermal growth factor receptor 2 (HER2) positive, and 37 triple negative. The regression analyses showed that size < 2 cm predicted luminal A-like status (p = 0.025), while rim enhancement (p < 0.001), intralesional necrosis (p = 0.001), peritumoural oedema (p < 0.001), and axillary adenopathies (p = 0.012) were negative predictors. Oppositely, round shape (p = 0.001), rim enhancement (p < 0.001), intralesional necrosis (p < 0.001), and peritumoural oedema (p < 0.001) predicted triple-negative status. CONCLUSIONS: mpMRI has been confirmed to be a valid noninvasive predictor of BC subtypes, especially luminal A and triple negative. Considering the central role of pathology in BC diagnosis and immunohistochemical profiling in the current precision medicine era, a detailed radiologic-pathologic correlation seems vital to properly evaluate BC.

Preoperative Staging in Breast Cancer: Intraindividual Comparison of Unenhanced MRI Combined With Digital Breast Tomosynthesis and Dynamic Contrast Enhanced-MRI.

OBJECTIVES: To evaluate the accuracy in lesion detection and size assessment of Unenhanced Magnetic Resonance Imaging combined with Digital Breast Tomosynthesis (UE-MRI+DBT) and Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI), in women with known breast cancer. METHODS: A retrospective analysis was performed on 84 patients with histological diagnosis of breast cancer, who underwent MRI on a 3T scanner and DBT over 2018-2019, in our Institution. Two radiologists, with 15 and 7 years of experience in breast imaging respectively, reviewed DCE-MRI and UE-MRI (including DWI and T2-w) + DBT images in separate reading sections, unaware of the final histological examination. DCE-MRI and UE-MRI+DBT sensitivity, positive predictive value (PPV) and accuracy were calculated, using histology as the gold standard. Spearman correlation and regression analyses were performed to evaluate lesion size agreement between DCE-MRI vs Histology, UE-MRI+DBT vs Histology, and DCE-MRI vs UE-MRI+DBT. Inter-reader agreement was evaluated using Cohen's κ coefficient. McNemar test was used to identify differences in terms of detection rate between the two methodological approaches. Spearman's correlation analysis was also performed to evaluate the correlation between ADC values and histological features. RESULTS: 109 lesions were confirmed on histological examination. DCE-MRI showed high sensitivity (100% Reader 1, 98% Reader 2), good PPV (89% Reader 1, 90% Reader 2) and accuracy (90% for both readers). UE-MRI+DBT showed 97% sensitivity, 91% PPV and 92% accuracy, for both readers. Lesion size Spearman coefficient were 0.94 (Reader 1) and 0.91 (Reader 2) for DCE-MRI vs Histology; 0.91 (Reader 1) and 0.90 (Reader 2) for UE-MRI+DBT vs Histology (p-value <0.001). DCE-MRI vs UE-MRI+DBT regression coefficient was 0.96 for Reader 1 and 0.94 for Reader 2. Inter-reader agreement was 0.79 for DCE-MRI and 0.94 for UE-MRI+DBT. McNemar test did not show a statistically significant difference between DCE-MRI and UE-MRI+DBT (McNemar test p-value >0.05). Spearman analyses showed an inverse correlation between ADC values and histological grade (p-value <0.001). CONCLUSIONS: DCE-MRI was the most sensitive imaging technique in breast cancer preoperative staging. However, UE-MRI+DBT demonstrated good sensitivity and accuracy in lesion detection and tumor size assessment. Thus, UE-MRI could be a valid alternative when patients have already performed DBT.

Breast Magnetic Resonance Spectroscopy at 3 T in Biopsy-Proven Breast Cancers: Does Choline Peak Correlate With Prognostic Factors?

OBJECTIVES: The role of functional techniques, such as magnetic resonance spectroscopy (H-MRS), as noninvasive tools to increase breast MR imaging reliability has been widely investigated during the last 2 decades. Considering the growing interest in tumor biology and its influence on functional parameters, the aim of this study was to investigate the relationship between H-MRS parameters and breast cancer biomarkers and to evaluate whether the results of H-MRS at 3 T can correlate with established breast cancer prognostic factors in our clinical experience. MATERIALS AND METHODS: One hundred two patients with biopsy-proven breast cancer underwent 3 T breast MR imaging. Single-voxel H-MRS was performed after the T1-weighted sequence, using a PRESS water-suppressed sequence (BREASE). Data were collected from a single rectangular volume of interest that encompassed the lesion. Magnetic resonance images and spectra of 102 Breast Imaging Reporting and Data System 6 lesions were prospectively evaluated by 2 radiologists in consensus. H-MRS results were considered positive if the choline peak signal-to-noise ratio was 2 or higher. H-MRS findings were then compared with morphological features and to histological findings, such as lesion size, nuclear grade, Ki-67, hormone receptor status, and Her2 expression. RESULTS: Elevated levels of total choline were detectable in 68/102 cases (66.67%) and undetectable in 34/102 (33.33%). A statistically significant association between the presence of choline peak and higher tumor grading (P < 0.0001), greater Ki-67 value (P < 0.0001), and larger lesion size (P < 0.0001) was found. No statistically significant associations were observed between choline peak and the luminal subgroups, even if higher levels of choline were more frequent in nonluminal A lesions. CONCLUSIONS: Our study confirms that 3 T breast H-MRS can be a valid additional tool to obtain further information about breast cancer biology and to predict tumor aggressiveness, because the detection of elevated levels of total choline in the spectrum is associated with a biologically aggressive breast cancer phenotype (large dimensions, grade 3, high values of Ki-67). Our results need to be validated in standardized larger-scale studies.