Magnetic resonance imaging features of invasive breast cancer association with the tumour stromal ratio

• Published in: PLOS ONE
• Main Authors: Ab Mumin, Nazimah; Hamid, Marlina Tanty Ramli; Hamid, Shamsiah Abdul; Chiew, Seow-Fan; Saman, Mohd Shahril Ahmad; Rahmat, Kartini
• Format: Article
• Language: English
• Published: PUBLIC LIBRARY SCIENCE 2023
• Subjects: Science & Technology - Other Topics
• Online Access: https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001096169400067

Objective To assess the association between breast cancer tumour stroma and magnetic resonance imaging (MRI) features. Materials and methods A total of 84 patients with treatment-naive invasive breast cancer were enrolled into this retrospective study. The tumour stroma ratio (TSR) was estimated from the amount of tumour stroma in the pathology specimen of the breast tumour. The MRI images of the patients were analysed based on Breast Imaging Reporting and Data Systems (ACR-BIRADS) for qualitative features which include T2- weighted, diffusion-weighted images (DWI) and dynamic contrast-enhanced (DCE) for kinetic features. The mean signal intensity (SI) of Short Tau Inversion Recovery (STIR), with the ratio of STIR of the lesion and pectoralis muscle (L/M ratio) and apparent diffusion coefficient (ADC) value, were measured for the quantitative features. Correlation tests were performed to assess the relationship between TSR and MRI features. Results There was a significant correlation between the margin of mass, enhancement pattern, and STIR signal intensity of breast cancer and TSR. There were 54.76% (n = 46) in the low stromal group and 45.24% (n = 38) in the high stromal group. A significant association were seen between the margin of the mass and TSR (p = 0.034) between the L/M ratio (p <0.001), and between STIR SI of the lesion and TSR (p<0.001). The median L/M ratio was significantly higher in the high TSR group as compared to the lower TSR group (p < 0.001). Conclusion Breast cancer with high stroma had spiculated margins, lower STIR signal intensity, and a heterogeneous pattern of enhancement. Hence, in this preliminary study, certain MRI features showed a potential to predict TSR.