What is a computed tomography (CT) scan?
How does CT work?
Unlike a conventional x-ray—which uses a fixed x-ray tube—a CT scanner uses a motorized x-ray source that rotates around the circular opening of a donut-shaped structure called a gantry. During a CT scan, the patient lies on a bed that slowly moves through the gantry while the x-ray tube rotates around the patient, shooting narrow beams of x-rays through the body. Instead of film, CT scanners use special digital x-ray detectors, which are located directly opposite the x-ray source. As the x-rays leave the patient, they are picked up by the detectors and transmitted to a computer.
Each time the x-ray source completes one full rotation, the CT computer uses sophisticated mathematical techniques to construct a 2D image slice of the patient. The thickness of the tissue represented in each image slice can vary depending on the CT machine used, but usually ranges from 1-10 millimeters. When a full slice is completed, the image is stored and the motorized bed is moved forward incrementally into the gantry. The x-ray scanning process is then repeated to produce another image slice. This process continues until the desired number of slices is collected.
Image slices can either be displayed individually or stacked together by the computer to generate a 3D image of the patient that shows the skeleton, organs, and tissues as well as any abnormalities the physician is trying to identify. This method has many advantages including the ability to rotate the 3D image in space or to view slices in succession, making it easier to find the exact place where a problem may be located.
When would I get a CT scan?
What is a CT contrast agent?
As with all x-rays, dense structures within the body—such as bone—are easily imaged, whereas soft tissues vary in their ability to stop x-rays and, thus, may be faint or difficult to see. For this reason, intravenous (IV) contrast agents have been developed that are highly visible in an x-ray or CT scan and are safe to use in patients. Contrast agents contain substances that are better at stopping x-rays and, thus, are more visible on an x-ray image. For example, to examine the circulatory system, a contrast agent based on iodine is injected into the bloodstream to help illuminate blood vessels. This type of test is used to look for possible obstructions in blood vessels, including those in the heart. Oral contrast agents, such as barium-based compounds, are used for imaging the digestive system, including the esophagus, stomach, and GI tract.
Are there risks?
CT scans can diagnose possibly life-threatening conditions such as hemorrhage, blood clots, or cancer. An early diagnosis of these conditions could potentially be life-saving. However, CT scans use x-rays, and all x-rays produce ionizing radiation. Ionizing radiation has the potential to cause biological effects in living tissue. This is a risk that increases with the number of exposures added up over the life of an individual. However, the risk of developing cancer from radiation exposure is generally small.
A CT scan in a pregnant woman poses no known risks to the baby if the area of the body being imaged isn’t the abdomen or pelvis. In general, if imaging of the abdomen and pelvis is needed, doctors prefer to use exams that do not use radiation, such as MRI or ultrasound. However, if neither of those can provide the answers needed, or there is an emergency or other time constraint, CT may be an acceptable alternative imaging option.
In some patients, contrast agents may cause allergic reactions, or in rare cases, temporary kidney failure. IV contrast agents should not be administered to patients with abnormal kidney function since they may induce a further reduction of kidney function, which may sometimes become permanent.
Children are more sensitive to ionizing radiation and have a longer life expectancy and, thus, a higher relative risk for developing cancer than adults. Parents may want to ask the technologist or doctor if their machine settings have been adjusted for children.
What are examples of NIBIB-funded projects using computed tomography?
Reduction in Radiation from Routine CT Scans: NIBIB put out a call for researchers to submit groundbreaking ideas that will help to radically decrease the amount of radiation used in CT scans. Five new projects are underway from this new funding opportunity, representing creative, innovative, interdisciplinary approaches that would not have been funded otherwise. You can read more about them below:
Web Stayman, Johns Hopkins University
The amount of radiation required for a CT scan depends on a number of variables, including the size of the patient, the part of the body being scanned, and the diagnostic task at hand. For example, smaller patients require less radiation than larger patients, and scanning a denser part of the body, such as soft tissue near the pelvis, requires more radiation than scanning the lungs. In addition, diagnostic tasks that require high image clarity, such as locating a faint tumor, generally require more radiation. The goal of this project is to modify both the hardware and software of modern CT systems so that the device can adapt the shape, position, and intensity of the x-ray beam to the specific imaging scenario. The research leverages patient-specific anatomical models and mathematical models of imaging performance to direct x-rays where they are needed and, consequently, to avoid or to limit x-ray exposure where it is not needed. This will help maximize imaging performance for specific diagnostic tasks while minimizing radiation exposures.
Constructing tools for researchers
Cynthia McCollough, Mayo Clinic
The goal of this work is to develop resources that enable the research community to easily create and compare new approaches to reducing radiation dose of routine CT scans without compromising diagnostic accuracy. So far, this has entailed creating a library of raw data from patient CT scans that researchers can manipulate to test new approaches, and developing computer-based methods for evaluating new approaches, so that researchers don’t have to rely on radiologists, which can be costly and time consuming. Using these assets, researchers have demonstrated that there is considerable potential for radiation dose reduction in CT exams of the abdomen, which are among the highest dose CT exams in common clinical use.
Jeffrey Fessler, University of Michigan
To reduce radiation yet still produce good quality CT images, more sophisticated methods are needed to process the raw data from the CT system. Those advanced methods, called image reconstruction algorithms, can require undesirably long computing times, so they can be used only for some patients currently. The goal of this project is to develop algorithms that are fast enough to allow low-dose CT imaging to be used for every patient.
An integrated approach
Norbert Pelc, Stanford Medical School
At every stage in the design of CT scanners, there are opportunities to make changes that reduce radiation dose. Because these changes are inter-related, the goal of this project is to take an integrated approach, exploring approaches such as modifying the photon counting detector (the part of the CT scanner that detects x-rays), dynamic x-ray illumination (adjusting the amount of radiation used throughout the duration of a scan), and image reconstruction methods. These will be tested using a table top experimental system. The researchers believe that these combined strategies can lead to as much as 80% reduction in radiation dose compared to today’s typical systems, and also enable higher resolution images.
Ricardo Otazo and Daniel Sodickson, New York University School of Medicine
Investigators at New York University School of Medicine, Brigham and Women's Hospital, and Siemens Healthineers are working together to develop a new ultra-low-dose CT technique called SparseCT. The key idea behind SparseCT is to block most of the X-rays in a CT scan before they reach the patient, but to do so in a way that preserves all the essential image information. The approach combines a new x-ray blocking device with the mathematics of compressed sensing, which allows images to be reconstructed from reduced datasets. Compression sensing can be likened to filming a movie with a very fast, but low-pixel camera and then using math to convert the image to high-definition quality.