Predicting the Pathological Grade of Breast Phyllodes Tumors: a Nomogram Based on Clinical and Magnetic Resonance Imaging Features

Overview

Journal Br J Radiol

Publisher Oxford University Press

Specialty Radiology

Date 2021 Jul 8

PMID 34233487

Citations 5

Authors

Xiaowen Ma

Lijuan Shen

Feixiang Hu

Wei Tang

Yajia Gu

Weijun Peng

Affiliations

Soon will be listed here.

Abstract

Objective: To explore the potential factors related to the pathological grade of breast phyllodes tumors (PTs) and to establish a nomogram to improve their differentiation ability.

Methods: Patients with PTs diagnosed by post-operative pathology who underwent pretreatment magnetic resonance imaging (MRI) from January 2015 to June 2020 were retrospectively reviewed. Traditional clinical features and MRI features evaluated according to the fifth BI-RADS were analyzed by statistical methods and introduced to a stepwise multivariate logistic regression analysis to develop a prediction model. Then, a nomogram was developed to graphically predict the probability of non-benign (borderline/malignant) PTs.

Results: Finally, 61 benign, 73 borderline and 48 malignant PTs were identified in 182 patients. Family history of tumor, diameter, lobulation, cystic component, signal on fat saturated weighted imaging (FS WI), BI-RADS category and time-signal intensity curve (TIC) patterns were found to be significantly different between benign and non-benign PTs. The nomogram was finally developed based on five risk factors: family history of tumor, lobulation, cystic component, signal on FS WI and internal enhancement. The AUC of the nomogram was 0.795 (95% CI: 0.639, 0.835).

Conclusion: Family history of tumor, lobulation, cystic components, signals on FS WI and internal enhancement are independent predictors of non-benign PTs. The prediction nomogram developed based on these features can be used as a supplemental tool to pre-operatively differentiate PTs grades.

Advances In Knowledge: More sample size and characteristics were used to explore the factors related to the pathological grade of PTs and establish a predictive nomogram for the first time.

Citing Articles

Expression of amine oxidase-related proteins in breast phyllodes tumor.

Kim H, Koo J Histol Histopathol. 2024; 40(1):39-47.

PMID: 38887035 DOI: 10.14670/HH-18-773.

Differentiation between Phyllodes Tumors and Fibroadenomas through Breast Ultrasound: Deep-Learning Model Outperforms Ultrasound Physicians.

Shi Z, Ma Y, Ma X, Jin A, Zhou J, Li N Sensors (Basel). 2023; 23(11).

PMID: 37299826 PMC: 10255878. DOI: 10.3390/s23115099.

Prognostic factors of breast phyllodes tumors.

Shin E, Koo J Histol Histopathol. 2023; 38(8):865-878.

PMID: 36866915 DOI: 10.14670/HH-18-600.

An Update on the General Features of Breast Cancer in Male Patients-A Literature Review.

Ionescu S, Nicolescu A, Marincas M, Madge O, Simion L Diagnostics (Basel). 2022; 12(7).

PMID: 35885460 PMC: 9323942. DOI: 10.3390/diagnostics12071554.

Editorial for "Pretreatment Multiparametric MRI-Based Radiomics Analysis for the Diagnosis of Breast Phyllodes Tumors".

Do Q J Magn Reson Imaging. 2022; 57(2):646-647.

PMID: 35661474 PMC: 9720037. DOI: 10.1002/jmri.28285.

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