Role of dynamic and parametric whole-body FDG PET/CT imaging in molecular characterization of primary breast cancer:...

The aim of this pilot study was to assess the role of dynamic whole-body PET and parametric imaging in the biological characterization of primary breast cancer.

In total 24 histologically proven primary breast cancer lesions in 21 consecutive patients were retrospectively analyzed. Each patient underwent 18F-fluoro-deoxyglucose whole-body dynamic PET-CT before any treatment. Dynamic PET images were acquired in the list mode for a total duration of 70 min. The reconstructed parametric imaging generated Patlak plot-based 'Slope' and 'Intercept' images, from which parametric indices ki and DV were obtained. The standard uptake value (SUV) metric was also obtained by summing the last few frames of the dynamic study. ki, distribution volume (DV) and SUV were correlated with the histological tumor grade, biomarkers [hormone receptors and human epidermal growth factor receptor 2 (HER-2) neu expression] and molecular subtypes (A, B and C) as well as with tumor size, regional nodal metastases and distant metastases.

The mean ki was found to be significantly higher in grade III than II lesions (P = 0.005), HER-2 neu positive status (P = 0.04) and molecular subtype B (P = 0.04) as well as in greater than T1 lesions(P = 0.0003 and P = 0.04, respectively) and node-positive lesions (P = 0.009). Though mean ki was not found to be significant for the hormone receptors status (P = 0.08), it showed the best correlation compared to the other parameters (P = 0.8 for DV and P = 0.1 for SUV). Spearman's correlation test, area under the curve (AUC) and mismatch percentage also revealed ki to predict tumor grade (AUC, 0.95; r = 0.7; P = 0.0001), HER-2 neu status and molecular subtypes (AUC, 0.81; r = 0.49 and P = 0.01) along with the hormone receptors status (AUC, 0.83; r = 0.32; P = 0.1). The mean DV failed to show any association with any of the biological or anatomical staging parameters. Though ki was found to be comparable to that of SUV in almost all the assessed parameters, it appeared to be better for predicting hormone receptors status even though both parameters were not statistically significant.

Our initial observation in a small cohort of breast cancer patients suggests that ki is promising in stratifying primary breast cancer lesions according to the tumor grade and biological characteristics.