Related Experiment Video
Updated: Jul 16, 2025

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Published on: December 15, 2014
Assessment of Apparent Diffusion Coefficient Parameters and Coefficient of Variance in Discrimination of Receptor
Ozlem Ozkul1, Ibrahim Halil Sever2, Bahattin Ozkul3
1Istanbul Aydin University, Medicalpark Hospital, Department of Oncology, Akasya sok. No:4 Kucukcekmece/Istanbul, Turkey.
Objective:
The objective of this study was to investigate the diagnostic power of apparent diffusion coefficient/coefficient of variance (ADCcV) as well as ADC parameters formed based on magnetic resonance images (MRI) in the distinction of molecular breast cancer subtypes.
Methods:
The study involved 205 patients who had breast cancer at stages 1-3. Estrogen receptor (EsR), progesterone receptor (PrR), human epidermal growth factor receptor 2 (Her2), and proliferation index (Ki-67) were histologically analyzed in the tumor. The correlations between the immunohistochemistry and intrinsic subtypes were analyzed using ADC and ADCcV.
Results:
The maximum whole tumor (WTu) ADC (p=0.004), minimum WTu ADC (p<0.001), and mean WTu ADC (p<0.001) values were significantly smaller in the EsR-positive tumors than those in the EsR-negative tumors. Compared to the PrR-negative tumors, the PrR-positive tumors showed significantly smaller maximum, minimum, and mean WTu ADC values (p=0.005, p=0.001, and p<0.001, respectively). In the comparisons of the molecular subtypes in terms of ADCcV, the p-values indicated statistically significant differences between the luminal A (lumA) group and the triple negative (TN) group, between the luminal B (lumB) group and the TN group, and between the Her2-enriched and TN groups (p<0.001, p=0.011, and p=0.004, respectively). Considering the luminal and non-luminal groups, while a significant difference was observed between the groups considering their minimum, maximum, and mean WTu ADC values, their ADCcV values were similar (p<0.001, p=0.004, and p<0.001, respectively).
Conclusion:
Using ADCcV in addition to ADC parameters increased the diagnostic power of diffusion weighted-MRI (DW-MRI) in the distinction of molecular subtypes of breast cancer.

