An integrative ultrasound-pathology approach to improve preoperative phyllodes tumor classification: A pilot study.

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

https://www.ncbi.nlm.nih.gov/pubmed/35404267

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