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
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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