Imaging – Computed Tomography
indications and derive information that can help people better understand their overall health and risks of serious adverse events.” The study used five AI computer programs on abdominal CT scans to accurately measure liver volume and fatty change, visceral fat volume, skeletal muscle volume, spine bone mineral density, and artery narrowing. Researchers found that not only did the combination of automated CT-based biomarkers compare favourably with the FRS and BMI for predicting cardiovascular events and death before any symptoms were present but in fact, the CT measure of aortic calcification, that is build-up of calcium deposits in the aortic valve, alone significantly outperformed the FRS for major cardiovascular events and overall survival.
The researchers also observed that BMI was a poor predictor of cardiovascular events and overall survival, and all five automated CT-based measures clearly outperformed BMI for adverse event prediction. “This opportunistic use of additional CTbased biomarkers provides objective value to what doctors are already doing,” said Perry J. Pickhardt, M.D., of the University of Wisconsin School of Medicine & Public Health, lead and corresponding author of the study. “This automated process requires no additional time, effort, or radiation exposure to patients, yet these prognostic measures could one day impact patient health through presymptomatic detection of elevated cardiovascular or other health risks.” This research builds on prior efforts de-
signing AI algorithms that Dr Summers has undertaken in his lab in the NIH Clinical Center’s Radiology and Imaging Sciences Department and his previous collaboration with Dr Pickhardt to develop, train, test, and validate fully automated algorithms for measuring body composition using abdominal CT. The researchers plan to test the approach in other studies, including more racially diverse populations. Reference: Automated CT biomarkers for opportunistic prediction of future cardiovascular events and mortality in an asymptomatic screening population: a retrospective cohort study. The Lancet Digital Health. https://doi. org/10.1016/S2589-7500(20)30025-X
With a five-year, $3.2 million grant from the US National Institute of Biomedical Imaging and Bioengineering, Mini Das, associate professor of physics at the University of Houston, will help usher in the next generation of micro computed tomography (CT) imaging. The project’s goal is to lower radiation dose in X-ray micro-CT imaging while improving the resolution and enhancing the contrast of three-dimensional pictures of small specimens, like tumours or biomaterials. “This has the potential to transform the landscape of micro-CT imaging,” said Das, who recently developed the theory, instrumentation and algorithms for spectral phase-contrast imaging (PCI) to enable the use of much lower doses of radiation while delivering higher levels of image detail. Das’s work addresses the challenge of current in-vivo micro-CT scanning – long imaging times, harmful, yet required, high radiation dose levels needed to follow the same subject over time, and poor image contrast. “Current X-ray and CT systems have
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inherent contrast limitations and dense tissue and cancer can often look similar. Even if you increase the radiation dose, there is a limit to what you can see. In addition, image noise becomes significant when increasing resolution to see fine details, often desirable when scanning small objects,” said Das. PCI detects how X-rays bend, or refract, particularly at the interface between tissues, providing a higher amount of contrast between different types of tissue. It also measures absorption and phase changes from X-ray transmission through the body. The resulting phase-enhanced contrast depicts high fine-structure visibility adding new image features. The developed methods can also translate to-large scale CT systems. Detecting the bending of X-rays is challenging because the bend is small and they are both bending and being absorbed in tissues at the same time, complicating interpretation. “X-rays, like visible light, exhibit what is called dual nature – they behave both as particles, called photons or packets of light, and waves. Phase imaging methods capture information relevant to wave nature of X-rays unlike conventional imag-
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University of Houston
Next-gen micro-CT scan can lower radiation, offer better pictures
University of Houston associate professor of physics Mini Das developed the theory, instrumentation and algorithms for spectral phasecontrast imaging (PCI) to enable the use of much lower doses of radiation while delivering higher levels of image detail in micro-CT scanning.
ing systems found in clinics today,” said Das. Das is using a new multi-energy, or spectral, detector which can see the energy of every light particle and will develop a unique spectral micro-CT system with both PCI and non-PCI capabilities. “We are the first to show how to use photon-counting detectors in a phasecontrast imaging setting while extracting the absorption and phase effects with quantitative accuracy. This accurate phase retrieval, or recovery, is so important if you want to discriminate between cancers and normal tissues,” she said.
