Developments from CERN could make CT scanners even better at detecting early cancer cells or other disease indicators. The facility’s work to create photon counters that can count ten million photons per second – up by a factor of one hundred from previous generation counters – have been integrated into CT systems and had their first trial run with patients. There are more developments that will have to take place before the photon-counters can fullfill their full potential, but early work presented at the meeting looks promising.
While CERN made the progress in photon counter technology, it has been representatives from industry who put them together with CT scanners. At the AIP and AAPM meeting, Reuven Levinson, a Technology Development Leader at GE Healthcare in the CT Engineering group in Haifa, Israel, announced the first use of a photon counting CT system on human patients. The CT’s X-ray detector counts the individual photons and measures their energy. Levinson and his team built the photon counting CT system and had it installed last year at the Rabin Medical Center in Tel Aviv, Israel.
CT scans, introduced in the 1970′s, revolutionized X-rays by giving doctors a sharper look inside their patients. Traditional X-rays can only produce straight on 2D- projection images, while CT scans provide cross sectional slices; revealing internal structures otherwise concealed by overlying layers. In hospitals, CT scans are helpful, and in many cases irreplaceable, in diagnosing diseases and injuries like internal bleeding, strokes, and lung disease. In the US, 68 million CT scans are performed year.
One of the requirements for CT scanning is that the image must be acquired quickly. As with photography, if the patient moves during the scan, the final image will be blurred, so modern CT scanners capture an image in less than 1 second.
These modern CT systems use x-ray detectors, which operate much like digital cameras, with the exception that the CT detectors essentially produce “black and white” photos. The detectors only record the total energy of all the x-rays transmitted through the patient’s body, not the individual energies of each photon. In the optical range, the energy of a photon determines its color, so the CT scanners are in a sense color blind.
And for the most part, CT scanners don’t need to see individual photon energies. For the majority of uses, the black and white photo tells the physician everything they need to know. But in some cases, “color-sensitive” X-ray detectors would be beneficial.
Previous generations of photon counting detectors could count up to only 100,000 x-rays per second, which was not fast enough to produce an adequate CT image.
That was until about five years ago when particle physicists at CERN, the facility in Geneva that is home to the Large Hadon Collider, broke the previous barrier of photon counting by ten orders of magnitude. In need of highly sensitive detectors for their experiments hunting subatomic particles, they increased the capabilities of photon counters to over 10 million photons per second. This increase would allow a photon counter to measure the energy of each individual photon striking the detector from a CT scan.
The results reported by Levinson explained the first use of the photon counting detecor on humans, yet this can not yet assist in detecting specific types of cells. To highlight specific cells that the CT scans can target, the team would like to attach nanoparticles that the photon counter CT system can easily detect – such as gold or other metals – to biomarkers that will attach to the target cells. So, attaching gold nanoparticles to a peptide that bonds to “vulnerable” plaque cells will illuminate the cells in little gold halos. Another company has reported results using the gold nanoparticles in rats and rabbits.
Eventually the same technology could also be used in cancer detection. While many cancerous tumors are visible on regular CT scanners, there are significant limitations. A CT scanner cannot distinguish between cancer and normal tissue following radiation or chemotherapy treatment. The imaging of a tumor following the anti-cancer treatment is critical in determining the patient’s status and also in evaluating the efficacy of different treatments in curing the cancer. Current medical practice utilizes PET/CT for the status evaluation of post-treatment cancer patient, which is an expensive and time consuming procedure. The challenge would be for CT plus nanoparticle systems to replace the PET/CT procedure with a simpler, higher resolution and less expensive alternative.