Background Metaplastic carcinomas are ductal carcinomas that display metaplastic transformation of the glandular epithelium to non-glandular mesenchymal tissue. Metaplastic carcinoma has a poorer prognosis than most other breast cancers, so the differential diagnosis is important. Although many clinical and pathologic findings have been reported, to our knowledge, few imaging findings related to metaplastic carcinoma have been reported. Purpose To investigate whole-breast imaging findings, including mammography, sonography, MRI, and pathologic findings, including immunohistochemical studies of metaplastic carcinomas of the breast. Material and Methods We analyzed 33 cases of metaplastic carcinoma between January 2001 and January 2011. Mammography, ultrasonography, and MRI were recorded retrospectively using the American College of Radiology (ACR) breast imaging reporting and data system (BI-RADS) lexicon. Immunohistochemical studies of estrogen receptor (ER), progesterone receptor (PR), p53, and C-erbB-2 were performed. Results The most common mammographic findings were oval shape (37%), circumscribed margin (59%), and high density (74%). The most common sonographic findings were irregular shape (59.4%), microlobulated margin (41%), complex echogenicity (81%), parallel orientation (97%), and posterior acoustic enhancement (50%). Axillary lymph node metastases were noted for 25% of the sonographic examinations. On MRI, the most common findings of margin and shape were irregularity (57% and 52.4%, respectively). High signal intensity was the most common finding on T2-weighted images (57%). Immunohistochemical profile was negative for ER (91%, 29/32) and PR (81%, 26/32). Conclusion Metaplastic carcinomas might display more benign features and less axillary lymph node metastasis than IDC. High signal intensity on T2 MRI images and hormone receptor negativity would be helpful in differentiating this tumor from other breast cancers.

The aims of this study were to evaluate the associations between the maximum standardized uptake value (SUVmax) and prognostic factors in invasive lobular carcinoma (ILC) and to compare these results with those in invasive ductal carcinoma (IDC). The study included pathologically confirmed ILCs (n = 32) and IDCs (n = 73). We retrospectively evaluated the preoperative 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) and measured the SUVmax. The pathologic results were reviewed regarding the size, histological type, histological grade, estrogen receptor (ER) and progesterone receptor (PR) status, human epidermal growth factor receptor 2 (HER2), epidermal growth factor receptor (EGFR), and Ki-67 of the primary tumor. We also compared the associations between the SUVmax and prognostic factors. The mean SUVmax of the ILCs was significantly lower compared with that of the IDCs (P = 0.032). The SUVmax increased with tumor grade (P < 0.001) and was higher with ER negativity compared with ER positivity (P = 0.007) in IDC. The SUVmax was higher with EGFR positivity compared with EGFR negativity (P = 0.013) in IDC and higher with Ki-67 positivity compared with Ki-67 negativity in IDC and ILC (P < 0.001 and P = 0.002, respectively). The SUVmax was not significantly different regarding PR or HER2 for both tumor groups. The correlation between the tumor size and the SUVmax was demonstrated for IDCs (r = 0.57), but not for ILCs (r = 0.25). The SUVmax was significantly different according to the tumor grade, ER, EGFR, and Ki-67 for IDCs. The SUVmax exhibited a positive association with Ki-67 in ILC; however, it was not significantly different with other factors, which suggests that the role of 18F-FDG PET/CT may be limited in ILC.

Yun SU, et al. J Breast Cancer. 2012 Mar;15(1):57-64. http://dx.doi.org/10.4048/jbc.2012.15.1.57

Background: Invasive cribriform carcinoma (ICC) of the breast is a rare type of invasive carcinoma which shows a favorable prognosis and a lower frequency of axillary nodal metastases. Few imaging findings related to ICC have been reported. Purpose: To evaluate imaging findings with multiple imaging techniques in ICC of the breast. Material and Methods: Twenty-eight cases of histopathologically proven ICC of the breast were gathered for this study. We retrospectively reviewed the mammographic, sonographic, and magnetic resonance imaging (MRI) findings of ICC according to the American College of Radiology (ACR) breast imaging reporting and data system (BI-RADS) lexicon. 18 F-fluorodeoxyglucose positron emission tomography-computed tomography (18 F-FDG PET-CT) findings were also evaluated. Microscopic slides of surgical specimens were reviewed by a breast pathologist. Results: The mean age of the patients was 51 years. The most common mammographic findings were irregular shape (72.8%), spiculated margin (63.7%), and a high density (81.8%) mass. Microcalcifications were noted in 9/28 cases. The most common shape was pleomorphic (66.7%). The most common sonographic findings were irregular shape (77.8%), spiculated margin (29.6%), hypoechogenicity (81.5%), and no posterior acoustic features (85.2%). On MRI, most ICCs presented as irregular shaped mass (62.0%) and irregular (42.9%) margin. All four patients (16.0%) who presented with non-mass-like enhancement pattern showed a segmental distribution. The 18 F-FDG PET-CT showed a mean maximum standardized uptake value (SUVmax) of 5.90. Axillary nodal metastases were found in 17.9% (5/28) of the surgical specimens. Immunohistochemical studies showed a high positivity for estrogen and progesterone receptor (100% and 87.5%, respectively). Conclusion: The imaging features of invasive cribriform carcinoma are highly suggestive of malignancy and are not distinguishable from those of other breast cancers like infiltrating ductal carcinoma.

Background/Objectives: Accurate visual categorization of small enhancing lesions on contrast-enhanced breast MRI remains challenging. The purpose of this study was to develop a deep learning (DL) model for detecting small (≤2 cm) invasive breast cancers using multi-institutional breast MRI data. Methods: This retrospective study included a total of 1721 women (mean age: 54 years; range, 21–87 years) with T1-stage invasive breast cancer across five hospitals. All patients underwent dynamic contrast-enhanced breast MRI before surgery between 2010 and 2020. Enhancing breast masses on early postcontrast T1-weighted images (14,917 labeled cancer images and 1443 labeled benign images) were used as the ground truth. In this multicenter cancer-enriched cohort, a DL model was developed to distinguish cancerous lesions from noncancerous lesions. MR images were independently reviewed by three breast imaging radiologists to detect subcentimeter (≤1 cm) cancers, and the readers were informed that each examination contained a single cancer. The performance of the model was evaluated using the area under the precision–recall curve (AUPRC), sensitivity, precision, and F1 score. Results: The DL model achieved an AUPRC of 0.42 in detecting small (≤2 cm) invasive breast cancers presenting as enhancing masses on MRI (sensitivity, 83.2%; precision, 33.2%; F1 score, 0.47). For subcentimeter (≤1 cm) cancers, the detection performance of the model was lower (sensitivity, 75.3%; precision, 20.8%; F1 score, 0.33) than that of the radiologists (mean sensitivity, 89.5%; mean precision, 72.9%; mean F1 score, 0.80). When the radiologists used the DL model, their mean precision in detecting subcentimeter invasive breast cancers improved from 72.9% to 83.2%, with no significant change in sensitivity (89.5% vs. 86.8%, p > 0.05). Conclusions: The DL model demonstrated potential as an assistive tool by improving radiologists’ precision for detecting small invasive breast cancers on contrast-enhanced breast MRI in this enriched reader-study setting, although it did not significantly improve their sensitivity.