The Utility of [18]F-Fluorocholine Positron Emission Computed Tomography and [18]F-Fluorodeoxyglucose Positron Emission Tomography-Computed Tomography in Evaluating Breast Cancer Phenotypes: A Pilot Study.

Abstract

The utility of the [18]F fluorodeoxyglucose positron emission tomography-computed tomography ([18]F FDG PET-CT) marker for breast cancer is well established. Given its limitations in localizing FDG-negative malignant tumors, the expression of [18]F-fluorocholine ([18]-FCH) may potentially be helpful to improve the overall accuracy in evaluating breast cancer. This study determined the potential of [18]- FCH PET CT as a potential marker in assessing breast cancer phenotypes. We recruited consecutive patients with biopsy-proven breast carcinoma who underwent [18] F-FCH PET-CT following the [18]F-FDG PET-CT imaging. The subjects were dichotomized into human epidermal growth factor receptor 2 (HER2)-negative and HER2-positive genotypes. The maximum standardized uptake value (SUVmax; g/dL) was used to predict the two groups of variables. Global health status (GHS) score based on the EORTC quality of life questionnaire (QLQ) was used to evaluate the outcome of the cohort subjects at 6, 12, and 24 months. There were 21 females with a mean age of 54.48 ± 12.17 years. Eighteen patients had invasive ductal carcinoma (18/21;85.8%) on histology, with 11 (52.4%) were HER2-negative genotype. There was higher sensitivity and specificity of [18]-FCH-PET/CT in breast lesions at 40% and 68.8% compared to [18]FDGPET/CT with 33.3% and 66.7%, respectively. There were significant differences between [18]F-FCH SUVmax (g/dL) of the HER-negative as compared to the HER2- positive group (1.99 g/dL vs. 0.2 g/dL; P < .05). High SUVmax (g/dL) of [18]F-FCH had predicted the HER-negative genotype at the cutoff value of 0.75 (P < .05). High [18]F-FCH showed significantly poor scoring of GHS parameters compared to low FCH at 6 months (mean SUVmax 8.06 vs. 5.40 respectively; P < .05). [18]F-FCH PET-CT is a potential marker in localizing and predicting aggressive breast carcinoma phenotypes.