Pretreatment synthetic MRI features for triple-negative breast cancer

Zhang, Q.; Zhao, Y.; Nie, J.; Long, Q.; Wang, X.; Wang, X.; Gong, G.; Liao, L.; Yi, X.; Chen, B.T.

doi:10.1016/j.crad.2023.10.015

Cited by 1 publication

(1 citation statement)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…20 21 In breast cancer imaging diagnostics, MRI and mammography are crucial tools; however, distinguishing TNBC from non-TNBC differs significantly between these modalities and ultrasound. Recent research 22 has revealed the utility of synthetic MRI in identifying predictors specific to TNBC-showcasing T2 values and cystic/ necrotic lesions as independent biomarkers. This research addresses the demand for precise non-invasive identification methods before surgery.…”

Section: Discussionmentioning

confidence: 99%

Ultrasound-based comparative analysis and nomogram development for predicting triple-negative and non-triple-negative breast cancer: a 4-year institutional study in Quanzhou First Hospital

Su,

Xie,

Chen

et al. 2024

BMJ Open

View full text Add to dashboard Cite

ObjectiveThe objective of this study was to compare ultrasound features and establish a predictive nomogram for distinguishing between triple-negative breast cancer (TNBC) and non-TNBC.DesignA retrospective cohort study.SettingThis study was conducted at Quanzhou First Hospital, a grade A tertiary hospital in Quanzhou, China, with the research data set covering the period from September 2019 to August 2023.ParticipantsThe study included a total of 205 female patients with confirmed TNBC and 574 female patients with non-TNBC, who were randomly divided into a training set and a validation set at a ratio of 7:3.Main outcome measuresAll patients underwent ultrasound examination and received a confirmatory pathological diagnosis. Nodules were classified according to the Breast Imaging-Reporting and Data System standard. Subsequently, the study conducted a comparative analysis of clinical characteristics and ultrasonic features.ResultsA statistically significant difference was observed in multiple clinical and ultrasonic features between TNBC and non-TNBC. Specifically, in the logistic regression analysis conducted on the training set, indicators such as posterior echo, lesion size, presence of clinical symptoms, margin characteristics, internal blood flow signals, halo and microcalcification were found to be statistically significant (p<0.05). These significant indicators were then effectively incorporated into a static and dynamic nomogram model, demonstrating high predictive performance in distinguishing TNBC from non-TNBC.ConclusionThe results of our study demonstrated that ultrasound features can be valuable in distinguishing between TNBC and non-TNBC. The presence of posterior echo, size, clinical symptoms, margin, internal flow, halo and microcalcification was identified as predictive factors for this differentiation. Microcalcification, hyperechoic halo, internal flow and clinical symptoms emerged as the strongest predictive factors, indicating their potential as reliable indicators for identifying TNBC and non-TNBC.

show abstract

Section: Discussionmentioning

confidence: 99%