Siemens Healthineers Achieves Important Milestone in Quantifiable Tissue Analysis Using MR

Siemens HealthineersAt the ISMRM (International Society for Magnetic Resonance in Medicine) in Montreal, Canada, Siemens Healthineers is the first supplier in the world to offer magnetic resonance fingerprinting (MRF) as a product for tissue analysis in clinical neurological research. The MRF application is the result of an exclusive, multi-year research partnership with Case Western Reserve University and the University Hospitals in Cleveland, which aims to make MR measurements much more quantifiable and reproducible. Thanks to this approach, a reliable judgment will be possible as to whether tissue is healthy or how badly it is damaged. This is a further means by which Siemens Healthineers is paving the way to personalized treatment and precision medicine. The MRF application and the associated database will initially be made available for the 3-Tesla Magnetom Vida magnetic resonance imaging system. Corresponding software packages for other 3T scanners from Siemens Healthineers will follow.

"MRF represents a paradigm shift in MR image acquisition," says Arthur Kaindl, head of Magnetic Resonance at Siemens Healthineers. "We generate unique ‘fingerprints’ that reflect the properties of the scanned tissue, and so we can describe the target anatomy numerically instead of visually for the first time. This information forms the basis for machine-assisted analysis for tissue classification, and thus also personalized treatment programs. The data also offers excellent opportunities for utilization and further development of artificial intelligence and Deep Learning."

Jeffrey Sunshine, Chief Medical Information Officer at the Cleveland University Hospitals and interim Co-Chair of Radiology at Case Western Reserve University and the University Hospitals adds: "I firmly believe that MRF will revolutionize the world of MR imaging. MRF lets us perform reliable tissue analyses. For example, we can assist tumor staging in cancer cases, which can save the patient from undergoing a biopsy and thus a surgical intervention. At the same time, the fact that tissue analyses are comparable means we can perform reliable progress checks."

The MRF method

MRF measures signal evolutions within each recorded voxel. The parameters for image acquisition are pseudo-randomized in the process, and the changes in signal are recorded. An algorithm compares the acquired datasets against a previously established database and locates the entry that most closely matches the signal evolution in question. This information can be compared to the fingerprints used in forensic investigations. Just like fingerprints, evaluation is possible only with access to a database that’s as comprehensive as possible. The forensic database links the fingerprint, and its unique characteristics, with the person’s own features (name, height, eye color, etc.). Likewise, the MRF database contains T1 and T2 values and can later be complemented with other parameters like relative spin density, B0, and diffusion. The clinic can link this information to the data for the underlying tissue type (bone, healthy tissue, diseased tissue).

MR images provide excellent information for diagnostics. But the images can differ greatly depending on the system, patient, and user, and are limited in terms of reproducibility and comparability. Although it has previously been possible to obtain absolute measurements of individual tissue properties, like diffusion, fat and iron deposits, perfusion, and relaxation times, lengthy measurement times were necessary. The previous deficits are comprehensively addressed by the new MRF method.

Magnetic Resonance Fingerprinting is currently under development and not commercially available. It is not for sale. Its future availability cannot be guaranteed.

About Siemens Healthineers

Siemens Healthineers enables healthcare providers worldwide to increase value by empowering them on their journey towards expanding precision medicine, transforming care delivery, improving patient experience and digitalizing healthcare. A leader in medical technology, Siemens Healthineers is constantly innovating its portfolio of products and services in its core areas of diagnostic and therapeutic imaging and in laboratory diagnostics and molecular medicine. Siemens Healthineers is also actively developing its digital health services and enterprise services. In fiscal 2018, which ended on September 30, 2018, Siemens Healthineers generated revenue of €13.4 billion and adjusted profit of €2.3 billion and has about 50,000 employees worldwide.

Most Popular Now

Researchers Find Telemedicine may Help R…

Low-value care - medical tests and procedures that provide little to no benefit to patients - contributes to excess medical spending and both direct and cascading harms to patients. A...

AI may Help Clinicians Personalize Treat…

Individuals with generalized anxiety disorder (GAD), a condition characterized by daily excessive worry lasting at least six months, have a high relapse rate even after receiving treatment. Artificial intelligence (AI)...

Accelerating NHS Digital Maturity: Paper…

Digitised clinical noting at South Tees Hospitals NHS Foundation Trust is creating efficiencies for busy doctors and nurses. The trust’s CCIO Dr Andrew Adair, deputy CCIO Dr John Greenaway, and...

Mobile App Tracking Blood Pressure Helps…

The AHOMKA platform, an innovative mobile app for patient-to-provider communication that developed through a collaboration between the School of Engineering and leading medical institutions in Ghana, has yielded positive results...

Can AI Help Detect Cognitive Impairment?

Mild cognitive impairment (MCI) can be an early indicator of Alzheimer's disease or dementia, so identifying those with cognitive issues early could lead to interventions and better outcomes. But diagnosing...

AI can Open Up Beds in the ICU

At the height of the COVID-19 pandemic, hospitals frequently ran short of beds in intensive care units. But even earlier, ICUs faced challenges in keeping beds available. With an aging...

Customized Smartphone App Shows Promise …

A growing body of research indicates that older adults in assisted living facilities can delay or even prevent cognitive decline through interventions that combine multiple activities, such as improving diet...

New Study Shows Promise for Gamified mHe…

A new study published in Multiple Sclerosis and Related Disorders highlights the potential of More Stamina, a gamified mobile health (mHealth) app designed to help people with Multiple Sclerosis (MS)...

AI Model Predicting Two-Year Risk of Com…

AFib (short for atrial fibrillation), a common heart rhythm disorder in adults, can have disastrous consequences including life-threatening blood clots and stroke if left undetected or untreated. A new study...

Patients' Affinity for AI Messages …

In a Duke Health-led survey, patients who were shown messages written either by artificial intelligence (AI) or human clinicians indicated a preference for responses drafted by AI over a human...

New Research Explores How AI can Build T…

In today’s economy, many workers have transitioned from manual labor toward knowledge work, a move driven primarily by technological advances, and workers in this domain face challenges around managing non-routine...

AI Tool Helps Predict Who will Benefit f…

A study led by UCLA investigators shows that artificial intelligence (AI) could play a key role in improving treatment outcomes for men with prostate cancer by helping physicians determine who...