Magnetic Resonance Imaging Features in Triple-Negative Breast Cancer: Comparison With Luminal and HER2-Overexpressing Tumors

2012 ◽  
Vol 12 (5) ◽  
pp. 331-339 ◽  
Author(s):  
Melania Costantini ◽  
Paolo Belli ◽  
Daniela Distefano ◽  
Enida Bufi ◽  
Marialuisa Di Matteo ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Imaging Features ◽  
Resonance Imaging

scholarly journals Direct comparison of magnetic resonance imaging and pathological shrinkage patterns of triple-negative breast cancer after neoadjuvant chemotherapy

2020 ◽  
Author(s):  
Katsuhiro Yoshikawa ◽  
Mitsuaki Ishida ◽  
Naoki Kan ◽  
Hirotsugu Yanai ◽  
Koji Tsuta ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Neoadjuvant Chemotherapy ◽  
Triple Negative Breast Cancer ◽  
Tumor Size ◽  
Triple Negative ◽  
Residual Tumor ◽  
Predictive Equation ◽  
Resonance Imaging

Abstract Background We aimed to investigate the usefulness of magnetic resonance imaging (MRI) and histopathological shrinkage patterns to formulate a predictive equation for estimating residual tumor size after neoadjuvant chemotherapy (NAC) in triple-negative breast cancer (TNBC) patients.Methods We enrolled 34 TNBC patients who underwent MRI before and after NAC. The MRI and histopathological shrinkage patterns were analyzed and classified into five categories—types I and II (concentric shrinkage without or with surrounding lesions, respectively), type III (shrinkage with residual multinodular lesions), type IV (diffuse contrast enhancement in the entire quadrant), and non-visualization. The residual tumor sizes following MRI and histopathological examination were also compared.Results The most common MRI and histopathological shrinkage pattern was type I (41.2% and 38.2%, respectively), followed by non-visualization (26.5% and 32.4%, respectively); the concordance rate between MRI and histopathological shrinkage patterns was 41.2%. There was a strong correlation between MRI tumor size and pathological tumor size (r = 0.89). Based on these findings, a predictive equation for pathological tumor size was formulated as follows: pathological tumor size \left(mm\right) = 1.1502 \times \left(MRI tumor size \right[mm\left]\right) + 8.4277.Conclusions Our equation may aid accurate preoperative assessment. Further studies are needed to determine its predictive value and applicability.

Sign in / Sign up

Export Citation Format

Share Document