Paola Locicero, N. Weingertner, V. Noblet, M. Mondino, C. Mathelin, S. Molière
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An integrative ultrasound-pathology approach to improve preoperative phyllodes tumor classification: A pilot study.
OBJECTIVE
Preoperative diagnosis of phyllodes tumor (PT) is challenging, core-needle biopsy (CNB) has a significant rate of understaging, resulting in suboptimal surgical planification. We hypothesized that the association of imaging data to CNB would improve preoperative diagnostic accuracy compared to biopsy alone.
METHODS
In this retrospective pilot study, we included 59 phyllodes tumor with available preoperative imaging, CNB and surgical specimen pathology.
RESULTS
Two ultrasound features: tumor heterogeneity and tumor shape were associated with tumor grade, independently of CNB results. Using a machine learning classifier, the association of ultrasound features with CNB results improved accuracy of preoperative tumor classification up to 84%.
CONCLUSION
An integrative approach of preoperative diagnosis, associating ultrasound features and CNB, improves preoperative diagnosis and could thus optimize surgical planification.
期刊介绍:
The recent expansion of work in the field of breast cancer inevitably will hasten discoveries that will have impact on patient outcome. The breadth of this research that spans basic science, clinical medicine, epidemiology, and public policy poses difficulties for investigators. Not only is it necessary to be facile in comprehending ideas from many disciplines, but also important to understand the public implications of these discoveries. Breast Disease publishes review issues devoted to an in-depth analysis of the scientific and public implications of recent research on a specific problem in breast cancer. Thus, the reviews will not only discuss recent discoveries but will also reflect on their impact in breast cancer research or clinical management.