Abstract
Breast Cancer is the most diffuse cancer among women and the treatment outcome is largely determined by its early detection. MRI at fixed magnetic field is already widely used for cancer detection. Herein it is shown that the acquisition of proton T1 at different magnetic fields adds further advantages. In fact, Fast Field Cycling Nuclear Magnetic Resonance Dispersion (FFC-NMRD) profiles have been shown to act as a high -sensitivity tool for cancer detection and staging in ex vivo murine breast tissues collected from Balb/NeuT mice. From NMRD profiles it was possible to extract two new cancer biomarkers, namely: (i) the appearance of 14N-quadrupolar peaks (QPs) reporting on tumor onset and (ii) the slope of the NMRD profile reporting on the progression of the tumor. By this approach it was possible to detect the presence of tumor in transgenic NeuT mice at a very early stage (5-7 weeks), when the disease is not yet detectable by using conventional high field (7 T) MRI and only minimal abnormalities are present in histological assays. These results show that, NMRD profiles may represent a useful tool for early breast cancer detection and for getting more insight into an accurate tumor phenotyping, highlighting changes in composition of the mammary gland tissue (lipids/proteins/water) occurring during the development of the neoplasia.
Original language | English |
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Article number | 4624 |
Journal | Scientific Reports |
Volume | 9 |
DOIs | |
Publication status | Published - 15 Mar 2019 |
Bibliographical note
We acknowledge COST Action AC15209 (EURELAX) for scientific support. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 668119 (project “IDentIFY”). The Italian Ministry for Education and Research (MIUR) is gratefully aknowledged for yearly FOE funding to the Euro-BioImaging Multi-Modal Molecular Imaging Italian Node (MMMI). E.D.G. and G.F. gratefully acknowledge FIRC-AIRC (Fondazione Italiana per la Ricerca sul Cancro AIRC) for their fellowships. We gratefully acknowledge Lionel Broche for the interesting discussion about mathematical models and procedures for the fitting of NMRD data.Keywords
- breast cancer
- diagnostic markers
- magnetic resonance imaging
- molecular imaging
- ONCOGENE
- MAGNETIC-FIELD DEPENDENCE
- 1/T1
- TUMORS