Magnetic resonance imaging shows kurtosis may be a promising biomarker for the identification of triple-negative breast cancer, according to a study published in the journal Radiology.
Researchers from Canada and France performed a retrospective study to evaluate whether features from texture analysis of breast cancers were associated with pathologic complete response (pCR) after neoadjuvant chemotherapy and to explore the association between texture features and tumor subtypes at pretreatment MR imaging.
The study included 85 patients with 85 breast cancers who underwent breast MR imaging before neoadjuvant chemotherapy between April 10, 2008, and March 12, 2015. Each woman underwent two-dimensional texture analysis that used software at T2-weighted MR imaging and contrast material–enhanced T1-weighted MR imaging. The researchers compared quantitative parameters between patients with pCR and those with non-pCR and between patients with triple-negative breast cancer and those with non–triple-negative cancer.
The results found 18 tumors (22 percent) were triple-negative breast cancers and pCR was achieved in 30 of the 85 tumors (35 percent). Other findings included:
• Univariate analysis, mean pixel intensity with spatial scaling factor (SSF) of 2 and 4 on T2-weighted images and kurtosis on contrast-enhanced T1-weighted images showed a significant difference between triple-negative breast cancer and non–triple-negative breast cancer;
• Kurtosis (SSF, 2) on T2-weighted images showed a significant difference between pCR and non-pCR;
• At multiple logistic regression, kurtosis on T2-weighted images was independently associated with pCR in non–triple-negative breast cancer; and
• Multivariate model incorporating T2-weighted and contrast-enhanced T1-weighted kurtosis showed good performance for the identification of triple-negative breast.
The researchers concluded that using pretreatment MR imaging to determine kurtosis may provide a promising biomarker for the identification of triple-negative breast cancer.