Abstract
In this study, the feasibility of high resolution magic angle spinning (HR MAS) magnetic resonance spectroscopy (MRS) of small tissue biopsies to distinguish between tumor and non-involved adjacent tissue was investigated. With the current methods, delineation of the tumor borders during breast cancer surgery is a challenging task for the surgeon, and a significant number of re-surgeries occur. We analyzed 328 tissue samples from 228 breast cancer patients using HR MAS MRS. Partial least squares discriminant analysis (PLS-DA) was applied to discriminate between tumor and non-involved adjacent tissue. Using proper double cross validation, high sensitivity and specificity of 91% and 93%, respectively was achieved. Analysis of the loading profiles from both principal component analysis (PCA) and PLS-DA showed the choline-containing metabolites as main biomarkers for tumor content, with phosphocholine being especially high in tumor tissue. Other indicative metabolites include glycine, taurine and glucose. We conclude that metabolic profiling by HR MAS MRS may be a potential method for on-line analysis of resection margins during breast cancer surgery to reduce the number of re-surgeries and risk of local recurrence.
Highlights
Cancer is a major cause of death, with incidences predicted to increase with the aging population [1]
In order to minimize the risk of local recurrences, infiltrating tumors should be removed with free resection margins
The low molecular weight metabolites are still visible in the spectra due to the T2-filtering applied for MR acquisition
Summary
Cancer is a major cause of death, with incidences predicted to increase with the aging population [1]. Breast cancer is the most common malignancy in women, and annually nearly 3000 women receive surgery and additional treatment for breast cancer in Norway [2]. Resection margins are evaluated by a pathologist after surgery, and a significant number of patients is scheduled for resurgery [3,4]. In addition to the increased burden for the patient, this has a cost and capacity downside for the hospital. Providing information to distinguish between tumor and noninvolved adjacent tissue during breast cancer surgery can help surgeons delineate the tumor margins more accurately, thereby significantly reducing the number of necessary re-surgeries
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