Prospective Correlation of Prognostic Immunohistochemical Markers With SUV and ADC Derived From Dedicated Hybrid Breast 18F-FDG PET/MRI in Women With Newly Diagnosed Breast Cancer.

Purpose: The aim of this study was to correlate prognostically relevant immunohistochemical parameters of breast cancer with simultaneously acquired SUVs and apparent diffusion coefficient (ADC) values derived from hybrid breast PET/MRI.

Patients And Methods: Fifty-six women with newly diagnosed, therapy-naive, histologically proven breast cancer (mean age, 54.1 ± 12.0 years) underwent dedicated prone 18F-FDG breast PET/MRI. Diffusion-weighted imaging (b-values: 0, 500, 1000 s/mm2) was performed simultaneously with the PET acquisition. A region of interest encompassing the entire primary tumor on each patient's PET/MRI scan was used to determine the glucose metabolism represented by maximum and mean SUV as well as into corresponding ADC maps to assess tumor cellularity represented by mean and minimum ADC values. Histopathological tumor grading and prognostically relevant immunohistochemical markers, that is, Ki67, progesterone receptor, estrogen receptor, and human epidermal growth factor receptor 2 (HER2), were assessed. Pearson correlation coefficients were calculated to compare SUV and ADC values as well as the immunohistochemically markers and molecular subtype. For the comparison with the tumor grading, a Wilcoxon test was used.

Results: A significant inverse correlation between SUV and ADC values derived from breast PET/MRI (r = -0.49 for SUVmean vs ADCmean; r = -0.43 for SUVmax vs ADCmin; both P's < 0.001) was found. Tumor grading and Ki67 both showed a positive correlation with SUVmean from breast PET/MRI (r = 0.37 and r = 0.32, P < 0.01). For immunohistochemical markers, HER2 showed an inverse correlation with ADC values from breast PET/MRI (r = -0.35, P < 0.01). Molecular subtypes significantly correlate with SUVmax and SUVmean (r = 0.52 and r = 0.42, both P's < 0.05). In addition, estrogen receptor expression showed an inverse correlation with SUVmax and SUVmean from breast PET/MRI (r = -0.45 and r = -0.42, P < 0.001).

Conclusions: The present data show a correlation between increased glucose metabolism, cellularity, tumor grading, estrogen and HER2 expression, as well as molecular subtype of breast cancer primaries. Hence, simultaneous 18F-FDG PET and diffusion-weighted imaging from hybrid breast PET/MRI may serve as a predictive tool for identifying high-risk breast cancer patients in initial staging and guide-targeted therapy.