Dynamic magnetic resonance imaging in determining histopathological prognostic factors of invasive breast cancers

• Published in: European journal of radiology Vol. 53; no. 2; pp. 199 - 205
• Main Authors: Tuncbilek, Nermin, Karakas, Hakkı Muammer, Okten, Ozerk Omur
• Format: Journal Article
• Language: English
• Published: Shannon Elsevier Ireland Ltd 01.02.2005; Elsevier Science
• Subjects: Adult; Aged; Aged, 80 and over; Analysis of Variance; Biological and medical sciences; Breast Neoplasms - pathology; Chi-Square Distribution; Contrast enhancement; Contrast Media; Dynamic MRI; Female; Gynecology. Andrology. Obstetrics; Humans; Image Processing, Computer-Assisted; Imaging, Three-Dimensional; Invasive breast cancer; Magnetic Resonance Imaging - methods; Mammary gland diseases; Medical sciences; Middle Aged; Neoplasm Invasiveness; Prognosis; Prognostic factors; Regression Analysis; Tumors; Invasive breast cancer; Dynamic MRI; Contrast enhancement; Prognostic factors; Mammary gland diseases; Histopathology; Prognosis; Medical imagery; Breast cancer; Malignant tumor; Contrast; Nuclear magnetic resonance imaging
• ISSN: 0720-048X; 1872-7727
• DOI: 10.1016/j.ejrad.2003.11.004

Objective: To evaluate the relation between morphological features and enhancement parameters in dynamic contrast-enhanced magnetic resonance (DCE-MR) imaging with histopathological prognostic factors. Materials and methods: Fifty-five patients with surgicopathological diagnosis of breast carcinoma were evaluated with 1.0 T MR scanner as a part of their preoperative diagnostic work-up. Dynamic studies were performed in axial plane using 3D fast low angle shot (FLASH) sequence. Time intensity curves (TICs) were obtained from the regions showing maximal enhancement in subtraction images. The correlations between enhancement parameters and histopathological findings were analyzed using stepwise multiple regression analysis, Student’s t-test, χ 2-tests and Pearson’s moment correlation coefficient. Results: Significant correlations were found between the presence of lymph node metastasis and tumor size ( P<0.05) and edge characteristics ( P<0.05). A highly significant correlation was found between histopathological grades and qualitative enhancement patterns ( r=0.403, P<0.01). Statistically significant differences were found between the groups with and without lymph node metastasis regarding enhancement in the first minute ( P<0.01) and TIC slope ( P<0.05). A significant difference was found between the histopathological grades I and III regarding all quantitative enhancement parameters, whereas no difference was found between the grades I–II, and II–III. Conclusion: DCE-MR imaging helps to predict prognostic factors of breast cancer by revealing morphological features and enhancement parameters of the primary tumor. Additional morphological factors further improve our ability to predict lymphatic metastasis.