What question did this study set out to answer?

The aim is to differentiate triple-negative breast cancer (TNBC) from non-triple-negative breast cancer (NTNBC) using multiparametric MRI.

February 8, 2026SHILAP Revista de lepidopterología0 citationsOpen Access

Differentiation of Triple-Negative Phenotypes of Breast Cancer from Others Using Multiparametric Magnetic Resonance Imaging: A Prospective Imaging Study

PSPavithra SanthanamAll India Institute of Medical Sciences Bhubaneswar SMSudipta MohakudAll India Institute of Medical Sciences Bhubaneswar DMDillip Kumar Muduly

Key Points

The aim is to differentiate triple-negative breast cancer (TNBC) from non-triple-negative breast cancer (NTNBC) using multiparametric MRI.
Categorized 102 patients based on immunohistochemistry results after ultrasound-guided biopsy.
Utilized various MRI techniques including T1-weighted, T2-weighted, DCE-MRI, diffusion-weighted imaging, and magnetic resonance spectroscopy.
Analyzed imaging parameters and applied statistical tests to determine associations with TNBC and NTNBC.
Performed logistic regression analyses to identify independent predictors.
TNBC exhibited more circumscribed margins (51.7%) and rim enhancement (65.5%).
Higher occurrence of axillary lymphadenopathy (73.3%) and unifocal lesions (76.7%) in TNBC.
MRS showed higher frequency of choline peaks in TNBC (60%).
Significant differences in MRI parameters like Ktrans, Ve, and ADC values support differentiation.
Identified independent predictors for TNBC subtype include rim enhancement and Ktrans values.

Abstract

Abstract To predict and differentiate triple-negative (TNBC) from non-triple-negative breast cancer (NTNBC) phenotypes using multiparametric magnetic resonance imaging (MpMRI). One hundred and two patients with BI-RADS 5/6 lesions who underwent MpMRI (3 Tesla) and were diagnosed with invasive ductal carcinoma on histopathological analysis after ultrasound-guided biopsy were categorized into TNBC and NTNBC groups based on immunohistochemistry. MRI included T1-weighted imaging, T2-weighted imaging, dynamic contrast-enhanced MRI (DCE-MRI), diffusion-weighted imaging, and magnetic resonance spectroscopy (MRS). Morphological, semiquantitative, and quantitative DCE parameters, apparent diffusion coefficient (ADC) values, and MRS (tCho) were studied. Nonparametric categorical variables were analyzed using the chi-square test, continuous nonparametric variables using the Kruskal–Wallis, and continuous parametric variables using the ANOVA test to determine the association of parameters with NTNBC/TNBC subtypes. Receiver operating characteristic and logistic regression analyses were done to determine the diagnostic performance and independent predictors. Seventy-two cases were NTNBCs, and 30 cases were TNBCs. TNBCs showed more circumscribed margins (51.7%), rim enhancement (65.5%), perilesional edema (80%), unifocal lesions (76.7%), and axillary lymphadenopathy (73.3%). NTNBCs showed more irregular shapes (81.8%) and spiculated margins (56.1%). Choline peaks on MRS were more frequent in TNBC (60%). TNBCs had higher mean Ktrans (>0.53 min−1), higher signal enhancement ratio (>72.95), lower mean Ve (<0.34), and lower ADC values (<0.83 × 10−3 mm2/s). Multivariate regression analysis identified rim enhancement (odds ratio OR: 25.11), high mean Ktrans (OR: 17.25), and low Ve (OR: 0.004 for high Ve) as independent predictors of the TNBC subtype. MpMRI parameters could differentiate TNBC from NTNBC, offering potential noninvasive biomarkers, enhancing diagnostic precision, indicating revision of histopathological evaluation reports in doubtful cases, prognostication, and personalized patient management.

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