Differentiation Between Phyllodes Tumors and Fibroadenomas of Breast Using Mammography-based Machine Learning Methods: A Preliminary Study

Predicting Prognosis of Phyllodes Tumors Using a Mammography- and Magnetic Resonance Imaging-Based Radiomics Model: A Preliminary Study

PURPOSE

To investigate whether a radiomics model based on mammography (MG) and magnetic resonance imaging (MRI) can be used to predict disease-free survival (DFS) after phyllodes tumor (PT) surgery.

METHOD

About 131 PT patients who underwent MG and MRI before surgery between January 2010 and December 2020 were retrospectively enrolled, including 15 patients with recurrence and metastasis and 116 without recurrence. 884 and 3138 radiomic features were extracted from MG and MR images, respectively. Then, multiple radiomics models were established to predict the recurrence risk of the patients by applying a support vector machine classifier. The area under the ROC curve (AUC) was calculated to evaluate model performance. After dividing the patients into high- and low-risk groups based on the predicted radiomics scores, survival analysis was conducted to compare differences between the groups.

RESULTS

In total, 3 MG-related and 5 MRI-related radiomic models were established; the prediction performance of the T1WI feature fusion model was the best, with an AUC value of 0.93. After combining the features of MG and MRI, the AUC increased to 0.95. Furthermore, the MG, MRI and all-image radiomic models had statistically significant differences in survival between the high- and low-risk groups (P < .001). All-image radiomics model showed higher survival performance than the MG and MRI radiomics models alone.

CONCLUSIONS

Radiomics features based on preoperative MG and MR images can predict DFS after PT surgery, and the prediction score of the image radiomics model can be used as a potential indicator of recurrence risk.

Understanding Fibroadenoma of the Breast: A Comprehensive Review of Pre-operative and Post-operative Clinicopathological Correlations

Fibroadenomas of the breast are common benign lesions that predominantly affect young women. This review provides a comprehensive overview of fibroadenoma management, encompassing their definition, clinical presentation, diagnostic tools, surgical management, clinicopathological correlations, treatment outcomes, complications, and emerging research. Fibroadenomas typically present as palpable breast lumps, often with no associated nipple discharge, and their diagnosis relies on a combination of clinical examination, breast imaging, and pathological confirmation. Surgical interventions, including excisional biopsy and lumpectomy, offer symptom relief and favorable long-term outcomes. Minimally invasive techniques and ongoing research into genomics and molecular aspects hold promise for the future of fibroadenoma management. Multidisciplinary collaboration among healthcare providers is paramount, ensuring accurate diagnosis, personalized treatment decisions, and holistic patient care. As research advances, the management of fibroadenomas is poised to evolve, providing improved diagnostic accuracy, minimally invasive treatments, and enhanced patient outcomes.