title: Comparison of choline and pharmacokinetic parameters in breast cancer measured by MR spectroscopic imaging and dynamic contrast enhanced MRI.
abstract: Although an MRI scanner is a single stand-alone modality, different acquisition techniques may be applied to collect structural and functional information, including vascular or angiogenic properties measured by dynamic contrast enhanced MRI (DCE-MRI) and Choline (Cho) metabolism measured by proton MR spectroscopy imaging (MRSI). They may provide complementary information for a better characterization of neoplasm. In this study, we investigated the correlation between Choline measured by MRSI and vascular parameters measured by DCE-MRI in breast cancer. Fourteen patients with histologically proven invasive breast cancer were included. MRSI from a grid of 8 x 8 voxels within a selected slab from each lesion was performed. Each voxel was 1.0 x 1.0 x 1.2 cm3. Choline signal-to-noise ratio (SNR) was measured from each voxel showing an identifiable Choline peak. Corresponding DCE kinetics was measured from each voxel, and analyzed with a 2-compartmental model to obtain pharmacokinetic parameters Ktrans and k(ep). All parameters showed a wide variation within each lesion, and there were no consistent correlations between regional Cho and DCE parameters within the lesion of each individual patient. This finding might be attributed to the heterogeneous nature of breast cancer. The characteristic Cho and DCE-MRI parameters were obtained for each patient by averaging over all Cho-positive voxels. In these 14 patients there was a significant linear correlation between Cho with percent enhancement at 2 min after injection, SE%-2min (r = 0.75, p = 0.002), and pharmacokinetic parameters Ktrans (r = 0.74, p = 0.003), and k(ep) (r = 0.76, p = 0.002). The results suggested that overall there is a correlation between Choline metabolism and angiogenesis activity. Since Choline is associated with cell replication and angiogenesis is required to support tumor growth, this might explain the correlation between these two sets of measures among different lesions.
authors.affiliation: John Tu and Thomas Yuen Center for Functional Onco-Imaging, University of California, Irvine, CA 92697-5020, USA. msu@uci.edu
authors.forename: Min-Ying
authors.initials: MY
authors.lastname: Su
authors.forename: Hyun-Man
authors.initials: HM
authors.lastname: Baik
authors.forename: Hon J
authors.initials: HJ
authors.lastname: Yu
authors.forename: Jeon-hor
authors.initials: JH
authors.lastname: Chen
authors.forename: Rita S
authors.initials: RS
authors.lastname: Mehta
authors.forename: Orhan
authors.initials: O
authors.lastname: Nalcioglu
mesh_terms: D000328:Adult; D000368:Aged; D001943:Breast Neoplasms / Q000175:diagnosis / Q000473:pathology*; D002794:Choline / Q000737:chemistry*; D003287:Contrast Media / Q000493:pharmacokinetics*; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D007700:Kinetics; D008279:Magnetic Resonance Imaging / Q000379:methods*; D009682:Magnetic Resonance Spectroscopy / Q000379:methods*; D008875:Middle Aged; D020360:Neoadjuvant Therapy / Q000379:methods; D015203:Reproducibility of Results
chemical_list: D003287:Contrast Media; D002794:Choline