Scientists at the National Institute of Standards and Technology (NIST) have proposed a new measurement approach to calibrate computed tomography (CT) scanners, potentially streamlining patient treatment by improving communication among doctors.
This new way shows that the x-ray beams generated by the CT scanners could be measured to allow scans from different devices to be usefully compared to one another. It also provides a way to create the first CT measurement standards connected to the International System of Units (SI) by creating a more precise definition of the units used in CT.
Calibration of a CT machine, something every radiology facility has to perform regularly, involves scanning an object of known radiodensity called a phantom and checking whether these measurements give the right number of HUs.
A problem is that a CT scanner’s tube—essentially its X-ray generating “light bulb”—creates a beam that is the X-ray version of white light, full of photons with different wavelengths that correspond to their energy. (If the human eye could see X-rays, you could run the tube’s beam through a prism and see it break into a spectrum of colors.)
Because a photon’s penetrating power depends on its energy, the beam’s overall effect on the phantom has to be averaged out, making it challenging to define the calibration.
Further complicating the situation is the way the tube’s X-ray light has to change depending on the type of scan. Denser body parts need more penetrating X-rays, so the tube has a sort of color switch allowing its operator to adjust the tube voltage to match the job.
Adjusting the tube’s voltage alters the spectrum of the beam so that it ranges between something like a “cool white” and a “warm white” light bulb. The variable spectrum makes it tougher to ensure that the calibration is correct for all voltages.
NIST’s Zachary Levine, a physicist and one of the paper’s authors said, “You want interchangeable answers regardless of what CT machine you use and when. For one thing, you want doctors to be able to communicate between hospitals. Let’s say a patient needs a follow-up but is somewhere far from home, or the same scanner got a software upgrade that changes the number of HUs. If you can’t measure accurately, you can’t improve your technology.”
“Better calibration could make diagnosis more efficient and less costly as well. Better comparisons among scanners might allow us to establish cutoff points for disease—such as emphysema getting a particular Hounsfield score or lower.”
“It’s also common for CT scans to turn up suspicious growths that might be cancerous, and a doctor commonly orders an MRI as a follow-up. We might eliminate the need for that second procedure.”
The NIST group needed to beat the vulnerabilities made by the tube’s broad X-ray spectrum and tube voltage setting. Their thought was to fill a few phantoms with various concentrations of powdered chemicals that are common in the body, and compare the phantoms’ radiodensity utilizing CT. The examination would help connect HUs to the number of moles per cubic meter, which are both SI units.
Though, the idea was literally difficult to execute as the volume of a mole depends on the size of a given chemical molecule.
Levine said, “A mole of salt takes up more space than a mole of carbon, for example. And the air in the powders represented a further complication.”
The trickiness would make all but a math aficionado wince: Each chemical in the mixture could be characterized by two numbers, but the entire phantom created a 13-dimensional space that complicated the data analysis. Fortunately, the team was able to use a linear algebra technique well-known to data science to simplify the data down to two dimensions, which was far more manageable.
Levine said, “Basically, we’ve shown that you can create a CT scanner performance target that any design engineer can hit. Manufacturers have been getting different answers in their machines for decades because no one told their engineers how to handle the X-ray spectrum. Only a small change to existing practice is required to unify their measurements.”
The approach is detailed in a research paper in the journal PLOS One.