10:10pm Monday 16 October 2017

Patient Safety: Reducing the Risks of Radiation Exposure From CT Scans and X-Rays

A new $1.2 million study led by Rensselaer Polytechnic Institute seeks to develop software for calculating and tracking a patient’s radiation exposure from diagnostic X-ray CT scans.

Funded by the U.S. Institutes of Health (NIH) National Institute of Biomedical Imaging and Bioengineering (NIBIB), the software aims to arm radiologists, medical physicists,  and patients with more accurate data for making informed decisions about the potential risks and benefits of CT scan procedures.

This plays into a larger goal of governmental agencies and hospitals of reducing the number of unnecessary CT scans performed in the United States and around the world, said project leader Rensselaer Professor X. George Xu.

“Radiation exposure from imaging procedures such as CT scans has elevated to an alarming level in the United States and elsewhere in recent years,” said Xu, a nuclear engineering professor in the Department of Mechanical, Aerospace, and Nuclear Engineering at Rensselaer. “The radiation exposure from a single CT scan is still relatively small when compared with the clinical benefit of the procedure, but patients often receive multiple scans during the course of their diagnostic or therapeutic procedure. Our new software should help to record the exposures more accurately and more consistently.”

A recent report by the National Council on Radiation Protection and Measurements (NCRM), of which Xu is a member, details how the U.S. population is now exposed to seven times more radiation every year from medical imaging exams than it was in 1980. While CT scans only account for 10 percent of diagnostic radiological exams, the procedure contributes disproportionately — about 67 percent — to the national collective medical radiation exposure.

To help mitigate this risk, several national and international bodies have called for the establishment of a centralized, patient-specific “dose registry” system. Such a system would track over time the amount of CT scans a patient undergoes, and the radiation exposure resulting from those procedures. However, current software packages for tracking CT scan radiation exposure have fundamental imitations and are insufficient for such a critical task, Xu said.

The new software Xu and his team are developing, VirtualDose, takes into consideration a patient’s individual characteristics, including age, sex, pregnancy, height, and weight. By entering these data into the software, the program creates a virtual 3-D “phantom” closely matching with the patient. These anatomically realistic phantoms accurately model the patient’s internal organs, and detail how radiation interacts with each organ. The phantom, in turn, allows physicians and researchers to compare the levels of radiation exposure a patient gets from different CT scanning protocols or different scanner designs.

Current software for CT radiation dose reporting uses outdated models of patients, and often lacks necessary software features, Xu said. This makes it nearly impossible to accurately track and record radiation exposure to organs from X-rays.

Xu said personalized virtual phantoms are particularly important for predicting radiation exposure from CT scans for the groups most sensitive to radiation — children and pregnant women. These groups are ignored by nearly all dose measurement software, he said.

This project builds from Xu’s research on virtual phantoms for computer simulation using Monte Carlo methods. Among phantoms developed by Xu and his students are VIP-Man and a set of pregnant patient phantoms. An international leader in this research area, Xu edited and published the 2009 book, Handbook of Anatomical Models for Radiation Dosimetry.

Collaborating with Xu on VirtualDose is Peter Caracappa, radiation safety officer and clinical assistant professor of nuclear engineering at Rensselaer. Additional collaborators include Wesley Bolch from University of Florida, as well as software firm Virtual Phantoms Inc. Clinical testing of the software will take place at several hospitals, including Massachusetts General Hospital and Shands Hospital at the University of Florida.

For more information on Xu’s research at Rensselaer, see:

Contact: Michael Mullaney
Phone: (518) 276-6161
E-mail: mullam@rpi.edu

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