Note to Readers: This article is a corrected version of the piece that appeared in Tuesday’s edition of the daily. The university regrets the errors.
At the recent 24th annual meeting of the International Society for Magnetic Resonance in Medicine (ISMRM) in Singapore, Case Western Reserve University, University Hospitals Case Medical Center and Siemens Healthcare announced an exclusive research partnership to further develop a quantitative imaging method known as Magnetic Resonance Fingerprinting (MRF). University and hospital researchers and Siemens’ developers will further refine the promising method of quantitative tissue analysis.
“We have been working with Siemens for over 30 years, developing and applying emerging MRI technologies, and we are excited to continue this great partnership,” said Mark Griswold, professor of radiology at Case Western Reserve and program chair at the ISMRM conference. “The goal of MR Fingerprinting is to specifically identify and characterize individual tissues and diseases, but to try to get there, we’ve had to rethink a lot of what we do in MRI.”
“This Siemens partnership with University Hospitals and CWRU builds on a rich history of collaboration resulting in cutting edge discoveries such as MR Fingerprinting, which has the potential to be a game changer in disease diagnostics,” said Pablo R. Ros, the Theodore J. Castele University Professor and chairman of the CWRU Department of Radiology and Radiologist-in-Chief for University Hospitals Health System. “We look forward to advancing this ground-breaking approach in the service of improved patient care.”
Christoph Zindel, head of the business line Magnetic Resonance at Siemens Healthcare added: “We are very proud and excited to be the exclusive partner to further develop MR Fingerprinting. The most innovative applications can only be brought to life through the collaborative efforts of industry and research.”
After more than a decade of work supported by a range of federal grants and support from Siemens, the Case Western Reserve and UH Case Medical Center researchers announced their breakthrough in the esteemed international scientific journal Nature. Their quantitative approach has to potential to identify a range of diseases far earlier than is possible today. MRF more precisely assesses a range of properties of a tissue, providing information about whether it is healthy and, if not, just how bad the damage is.
Vikas Gulani, an associate professor of radiology and director of MRI for UH Case Medical Center, played a critical role in co-developing the concept behind the approach with Griswold. Jeffrey Sunshine, professor of radiology and vice chairman for radiology at UH Case Medical Center, co-developed MRF and will continue work to refine it through the new agreement with Siemens. Nicole Seiberlich, an assistant professor of biomedical engineering, has been a key developer of the technology from its beginnings, and will continue to have a special focus on the refinement of MRF in cardiac applications.
Planned for characterizing disease tissue earlier and faster
MRF is an innovative, highly versatile and insightful method of measurement, intended to provide non-invasive, user- and scanner-independent quantification of tissue properties. The MRF method is designed to measure a wide range of parameters simultaneously, quantifying many important tissue properties.
Presently, the evaluation of MR images is generally qualitative. In doing so, the properties of the pathology are determined by observing differences in contrast between tissues, instead of being based on absolute measurements of individual tissue properties.
Quantitative approaches exist, involving the measurement of diffusion, fat/iron deposits, perfusion or relaxation times, for example. But these sequences often require significant amounts of scan time, and the results vary depending on the scanner and the user.
Given the potential low level of variance across a large number of examinations and its expected reproducibility across scanners and in different institutions, MRF could achieve more accurate monitoring and evaluation of patient treatment.
MR Fingerprinting explained
The MRF technique does not acquire traditional clinical images, but instead is designed to gather tissue information based on the signal evolution from each voxel. Acquisition parameters are varied in a pseudorandom fashion, while the signal evolutions are recorded. These are then compared to a database, or “dictionary,” to find the entry that best represents the acquired signal evolution of each voxel.
The signal evolutions equate in many ways to “fingerprints” of tissue properties, which, like the identification of human fingerprints in forensics, can only be analyzed by comparing them with a file containing all known fingerprints. The dictionary is equivalent to the database where all the known fingerprints are stored, together with all the information relative to each person. In the forensic case, each fingerprint points to the feature identification of the associated person such as name, height, weight, eye color, date of birth, etc. In the case of MRF, each fingerprint in the dictionary points to the MR related identification features of the associated tissue.
The university and hospital research team is driving the expansion of this method for a range of different tissue properties. At the same time, the researchers are working toward expanding the technology to cover additional fields of application. The research team has successfully performed initial tests with brain and prostate tumor patients as well as breast cancer patients with liver metastases. MRF has also been used in cardiac examinations and with patients with multiple sclerosis.
For Siemens, the focus of this collaboration is to improve reproducibility and possibly to extend the procedure to different MR scanners and field strengths. Case Western Reserve uses numerous systems from Siemens, and employs the Magnetom Skyra 3-tesla system for the purposes of this research project.
Work-in-Progress package users confirm potential benefits of method
An initial result of this collaborative process launched in September 2015 is a “Work-in-Progress” (WIP) package, an imaging package for selected Siemens scanners used in research. These WIP packages have been successfully tested since January 2016 at University Hospitals Case Medical Center, Cleveland Clinic, the University Hospital Essen, Germany, and the Medical University of Vienna, Austria, using further Siemens MRI systems.