Abstract #3420

Pre-clinical Fast Field-Cycling NMR for the detection and classification of breast cancer

Katie Hanna¹, Ehab Husain², Yazan Masannat³, Rasha Abu-Eid⁴, David Lurie⁵, Valerie Speirs¹, and Lionel Broche⁵

¹Institute of Medical Sciences, School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Aberdeen, Scotland, ²Department of Pathology, Aberdeen Royal Infirmary, Aberdeen, Scotland, ³Breast Unit, Aberdeen Royal Infirmary, Aberdeen, Scotland, ⁴Institute of Dentistry, School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Aberdeen, Scotland, ⁵Aberdeen Biomedical Imaging Centre, University of Aberdeen, Aberdeen, Scotland

Synopsis

This study aims to explore novel biomarkers of breast cancer using FFC-NMR. NMR dispersion profiles were generated by analysing patient-matched tumour, peritumoral zone and distant normal fixed tissue samples from twenty breast cancer patients. These profiles were analysed using piecewise power models and the numerical parameters derived from these models could significantly classify the different regions of breast tissue and distinguish patients from different prognostic categories. The numerical parameters investigated in this study may have potential as quantitative biomarkers for breast cancer detection and risk stratification.

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