A new measurement approach proposed by scientists at the National Institute of Standards and Technology (NIST) could lead to a better way to calibrate computed tomography (CT) scanners, potentially streamlining patient treatment by improving communication among doctors.
The approach, detailed in a research paper in the journal PLOS ONE, suggests how the X-ray beams generated by CT can be measured in a way that allows scans from different devices to be usefully compared to one another. It also offers a pathway 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–something the field has lacked.
“If the technical community could agree on a definition, then the vendors could create measurements that are interchangeable,” said NIST’s Zachary Levine, a physicist and one of the paper’s authors. “Right now, calibration is not as thorough as it could be.”
An object’s ability to block X-rays–its “radiodensity”–is measured in Hounsfield Units (HUs), named for the Nobel Prize winning co-inventor of CT. Calibration of a CT machine, something every radiology facility must perform regularly, involves scanning an object of known radiodensity called a phantom and checking whether these measurements give the right number of HUs.
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.
Add these complications to the differences that exist among various CT machine manufacturers, and you get a lot of trouble for anyone who wants to link the calibration of any given scanner to a universal standard. Better calibration could make diagnosis more efficient and less costly as well, Levine said.
