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Abstract #0942

Intravoxel incoherent motion improves diffusion-weighted imaging in detection of response towards neoadjuvant chemotherapy in breast cancer

Sai Man Cheung1, Wing Shan Wu1, Nicholas Senn1, Ravi Sharma2, Trevor McGoldrick2, Tanja Gagliardi1,3, Ehab Husain4, Yazan Masannat5, and Jiabao He1
1Institute of Medical Sciences, University of Aberdeen, Aberdeen, United Kingdom, 2Oncology Department, Aberdeen Royal Infirmary, Aberdeen, United Kingdom, 3Radiology Department, Royal Marsden Hospital, London, United Kingdom, 4Pathology Department, Aberdeen Royal Infirmary, Aberdeen, United Kingdom, 5Breast Unit, Aberdeen Royal Infirmary, Aberdeen, United Kingdom


Breast cancer is a major and expanding health challenge, and neoadjuvant chemotherapy (NACT) is increasingly prescribed to facilitate breast surgery in advanced breast cancer with an ongoing demand for improved imaging methods accurately reflecting disease load. Tissue perfusion, a sensitive marker of cancer metabolism, can be derived from intravoxel incoherent motion (IVIM) model, and recent Bayesian algorithm yields improved sensitivity and precision in breast cancer by us and pancreatic cancer. We therefore hypothesise that IVIM model powered by Bayesian algorithm is able to detect early treatment-induced changes in tumour perfusion and diffusion, with the potential to impact patient care pathway.

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