Intratumoral Agreement of High-Resolution Magic Angle Spinning Magnetic Resonance Spectroscopic Profiles in the Metabolic Characterization of Breast Cancer

Abstract

High-resolution magic angle spinning (HR-MAS) magnetic resonance (MR) spectroscopy data may serve as a biomarker for breast cancer, with only a small volume of tissue sample required for assessment. However, previous studies utilized only a single tissue sample from each patient. The aim of this study was to investigate whether intratumoral location and biospecimen type affected the metabolic characterization of breast cancer assessed by HR-MAS MR spectroscopy. This prospective study was approved by the institutional review board and informed consent was obtained. Preoperative core-needle biopsies (CNBs), central, and peripheral surgical tumor specimens were prospectively collected under ultrasound (US) guidance in 31 patients with invasive breast cancer. Specimens were assessed with HR-MAS MR spectroscopy. The reliability of metabolite concentrations was evaluated and multivariate analysis was performed according to intratumoral location and biospecimen type. There was a moderate or higher agreement between the relative concentrations of 94.3% (33 of 35) of metabolites in the center and periphery, 80.0% (28 of 35) of metabolites in the CNB and central surgical specimens, and 82.9% (29 of 35) of metabolites between all 3 specimen types. However, there was no significant agreement between the concentrations of phosphocholine (PC) and phosphoethanolamine (PE) in the center and periphery. The concentrations of several metabolites (adipate, arginine, fumarate, glutamate, PC, and PE) had no significant agreement between the CNB and central surgical specimens. In conclusion, most HR-MAS MR spectroscopic data do not differ based on intratumoral location or biospecimen type. However, some metabolites may be affected by specimen-related variables, and caution is recommended in decision-making based solely on metabolite concentrations, particularly PC and PE. Further validation through future studies is needed for the clinical implementation of these biomarkers based on data from a single tissue sample.