An integrative ultrasound-pathology approach to improve preoperative phyllodes tumor classification: A pilot study.
Fiche publication
Date publication
janvier 2022
Journal
Breast disease
Auteurs
Membres identifiés du Cancéropôle Est :
Pr MATHELIN Carole, Dr NOBLET Vincent
Tous les auteurs :
Locicero P, Weingertner N, Noblet V, Mondino M, Mathelin C, Molière S
Lien Pubmed
Résumé
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.
Mots clés
Phyllodes tumor, Ultrasound, machine learning classifier, preoperative diagnosis
Référence
Breast Dis. 2022 ;41(1):221-228