Summary of Invention
This new algorithm completely suppresses the fat signal in magnetic resonance imaging (MRI), facilitating more precise tissue characterization. Fat-free nuclear magnetic imaging represents a significant improvement over traditional MRI fat-suppression techniques, which suppress only approximately 60% of fat signals at maximum and are prone to heterogeneity of the magnetic field.
Fat signals can compromise MRI quality by overwhelming the relevant water images in fat-abundant regions. Such fat signals thereby produce artifacts and hinder tissue characterization, complicating interpretation of many routine clinical imaging procedures. A strong fat signal can negatively impact the precision of tumor detection. The technology presented here improves the precision of tumor detection in fat-rich tissues, such as breast tissue. In addition to improving tumor detection, this technology should also be useful for imaging studies to assess liver pathologies, myelin deposition, inflamed tissues or bone marrow abnormalities.
By eliminating 100% of the fat-signal in MRI images, this novel technology renders MRI images more sensitive to magnetization transfer and to water density and relaxation time, providing the possibility of additional contrast. It is insensitive to the heterogeneity of both the static and radio frequency fields and is equally efficient for all fat resonances, independent of their chemical shift frequency.
This technology suppresses 100% of MRI fat signals, thereby permitting:
- Improved detection of fatty tumors (liposarcoma);
- Improved detection of retroperitoneal tumors;
- Improved detection of breast cancer;
- Improved prediction of tumor response to therapy through edema-free imaging; and
- Improved ability to distinguish edema versus tumor in brain tumor patients.
At MSKCC, over 34,000 MRI procedures performed in 2009 could have benefited from this method. As an indication of the potential market for this new technology, there are over 7,000 MRI facility sites in the U.S. alone.
Stage of Development
Clinical data collection
Sam Singer, MD, FACS
U.S. patent application published: US2010/0156413
Chen JH, et al. (2010) Magn Reson Med. Mar;63(3):713-8.
Imke Ehlers, PhD, CLP