Parametric imaging: the time is now

3min
Published on October 23, 2017

With tracing glucose into the body the parametric system obtains a better scan. PET tracer distribution—a dynamic process altered by a number of factors specific to each organ and region of interest—cannot always be accurately accounted for with SUV. Welcome, parametric imaging.

Photos: Steve Belkowitz

For medical technology to have real value, there must be a large track record of success. A new medical test is only viable once there is enough successful data to demonstrate the technology’s viability. This truth applies to parametric imaging: a diagnostic procedure where an image of an administered tracer is derived mathematically, potentially enabling doctors to identify cancerous lesions or map things like blood flow and cardiac activity. One great image from a PET/CT scan is fine, but consistently and routinely producing high-quality images is, for healthcare technology professionals, the proverbial Holy Grail.

For this reason alone, now is the time for parametric imaging. Because of the growing use of parametric imaging, medical professionals will soon have a much larger amount of data from successful scans, thereby opening more opportunities for its use in scanning an entire human body. “In the early days, imaging was very much organ-specific,” explains Anne Smith, a systems engineer at Siemens Healthineers who leads the feature development of parametric imaging. “You would look at the brain … or the heart … or kidneys. There was no whole-body scan as we have now.”

Whole-body scans with a parametric system can lead to an improvement in healthcare.

FlowMotion™ Multiparametric PET Suite introduces an end-to-end clinical solution to provide multiparametric PET images outside of the research setting. The solution is completely automated and integrated into the PET/CT workflow, allowing users to obtain images of SUV, metabolic glucose rate (Ki), and distribution volume (DV) all at once, allowing for:

  • More efficient information for planning and therapy strategy
  • Acquisitions based on continuous bed motion for a more complete picture
  • Fast reproduction from original data
  • Flexible, fully automated acquisition protocol
  • Whole-body dynamic acquisitions for more accurate images

“We can basically trace the metabolism of glucose in the human anatomy, using a more robust parametric system, which gives doctors a lot of useful data,” she explains. Parametric imaging gives doctors meaningful quantitative measurements, and having good measurements can potentially lead to an improvement in patient care.


“The technology ultimately makes now the right time,” explains Smith. “We can create a four-dimensional reconstruction of an image and push a lot of data into the hands of doctors.” The data, she explains, has always been there, and it provides information to physicians that assists them in making meaningful medical decisions. She describes the quantity of the additional data as the difference between what one can see in a snapshot versus what one can see in a movie.
The amount of data now available will determine what impact the new technology has on the cost of care.

Figures: Ki images show high metabolic rate of glucose in the lung nodule, which shows SUV of 3.90 in summed SUV images, suggesting malignancy.
(Liver Ki value (0.42 mg/min/100ml) and SUV (2.39 SUVpeak) appear normal). Ki images show improved visualization of the malignant lung nodule due to absence of effect of circulating tracer in blood volume with lower levels of liver, spleen, and mediastinal uptake. DV images reflect similar blood volume level within the nodule and the liver, which may reflect relative hypovascularity of the tumor.1


Automating the process is a big step, too, Smith says. “With our new parametric feature, all a clinic will do is inject the patient on the bed, push ‘start’ on the scanner, then walk away. Built-in quality control checks aide the scan process as well.”
Smith describes the new system as, “going back to the future. Parametric was PET when it was first commercialized. It was a scientific research quantitative technique. Now we are getting back to the system’s roots because of the workflow, the automation, and all of the technology improvements.”