Malignant Phyllodes Tumor: Imaging Features With Histopathologic Correlation

Metastatic and Malignant Phyllodes Tumors of the Breast: An Update for Current Management

Metastatic, malignant phyllodes tumor (PT) of the breast is a rare and aggressive neoplasm. Currently, there is no agreed upon consensus as to best management practices. A systematic review of literature was conducted investigating surgical, chemotherapeutic, and radiotherapeutic management for metastatic PT. Databases employed to identify articles included Embase, PubMed, and SAGE Journals. Diagnosis of metastatic PT has been of significant difficulty to radiologists as it is often confused with fibroadenomas. Surgically, metastatectomy has been correlated with increased overall survival (of 25.9 versus 9.9 months; P = .01). Radiotherapy has often been associated with palliation and pain control in metastatic, malignant neoplasia. However, one study showed that in malignant PT, radiation was associated with significantly lower rates of local recurrence (OR: 0.048 versus 0.209). Anthracycline containing chemotherapy regimens has been associated with improved overall survival (22.4 months versus 13.2 months; P = .040). Further research must be conducted into this rare malignancy to elucidate accurate diagnosis and care for patients with advanced metastatic or malignant phyllodes tumors.

High grade phyllodes tumor with osteosarcomatous differentiation: Case report and review of the literature

Phyllodes tumors (PTs) are rare fibroepithelial malignancies of the breast, accounting for less than 1% of malignant breast tumors. PTs are usually solitary tumors but can be associated with other malignancies, such as DCIS or invasive carcinomas and sarcomas. Osteosarcomatous differentiation of a malignant phyllodes tumor is rare, and differentiation of this rare breast tumor from other entities is of vital importance to clinicians due for appropriate treatment and prognosis. We present a case of rare high-grade phyllodes tumor with osteosarcomatous differentiation presenting on mammogram as a calcified lobulated mass; ultrasound revealed a 1.5 cm irregularly calcified mass, suggestive of bone. An ultrasound-guided core biopsy and subsequent lumpectomy revealed a cellular stroma with osteoid stromal matrix and cytologic atypia with bone formation. At 18 months postprocedure, a recurrence was identified at the previous surgical site, and the patient underwent a mastectomy. Here we present a single case of high-grade PT with osteosarcomatous differentiation and a comprehensive literature review, highlighting the mammographic and histologic characteristics of this rare presentation.

Discrimination between phyllodes tumor and fibro-adenoma: Does artificial intelligence-aided mammograms have an impact?

Background

The indulgence of artificial intelligence (AI) has been considered recently in the work up for the detection and diagnosis of breast cancer through algorithms that could supply diagnosis as the radiologist do. The algorithm learns from a supervised and continuous input of large and new data sets unlike the standard programming, which requires clear step-by-step instructions. The aim of this study is to assess the ability of AI scanned mammograms to aid the ultrasound in the discrimination between phyllodes tumors and fibro-adenomas.

Results

This is a retrospective analysis included 374 proven phyllodes tumors (PT) and fibro-adenomas (FA). Digital mammogram and breast ultrasound was performed for all the cases and each breast was given a “Breast Imaging Reporting and Data System” (BI-RADS) score. Included mammograms were scanned by AI with resultant a qualitative heatmap and a quantitative abnormality scoring of suspicion percentage.

The study included 164 PT (43.9%) and 210 FA (56.1%). BI-RADS category 2 was assigned in 40.1%, category 3 in 38.2%, category 4 in 18.5% and category 5 in 3.2% with median value of the AI abnormality scoring of 23%, 44%, 65% and 90% respectively. Sensitivity and specificity of the conventional imaging were 59.2% and 75.8% respectively. The AI abnormality scoring of 49.5% upgraded the sensitivity to 89.6% and specificity to 94.8% in the ability to discriminate PT from FA masses.

Conclusion

Artificial intelligence-aided mammograms could be used as method of distinction between PT from FA detected on sono-mammogram. The color hue and the quantification of the abnormality scoring percentage could be used as a one setting method for specification and so guide clinicians in their decision of conservative management or the choice of the surgical procedure.

Radiologic-Pathologic Correlation of Fibroepithelial Lesions: A Pictorial Review

Fibroepithelial lesions (FEL) of the breast encompass a spectrum of masses ranging from benign to malignant. Although these lesions are on the same biologic spectrum, differences in their clinical behaviors necessitate different management approaches. While imaging features are nonspecific, small size (less than 3 cm), oval shape, circumscribed margins, growth in diameter less than 20% in six months, and homogeneous echotexture on US favor fibroadenoma (FA). Conversely, larger size (3 cm or larger), rapid growth, irregular shape, noncircumscribed margins, and heterogeneous echotexture suggest possible phyllodes tumor (PT). Histopathologically, increased stromal cellularity, stromal atypia, and mitotic activity characterize PT, while FA typically lack these features. In this review, we summarize the imaging and pathology characteristics of nonmalignant FEL, including simple, juvenile, and complex FA, and benign and borderline PT and highlight the collaborative role of radiologists and pathologists in informing diagnosis and clinical management.