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Scientists at the Rochester Institute of Technology, Rochester, NY, are developing imaging software that, they say, could give radiologists a tool to measure the growth of nodules in patients at risk of lung cancer. In a two-year study, Nathan Cahill, an associate professor in RIT’s School of Mathematical Sciences, is creating algorithms to quantify the growth of lung nodules imaged on CT scans. The study compares existing scans of individual patients. The algorithms will analyze these medical images and measure changes in nodules to identify small cancers or, if stable, eliminate the need for biopsies.

He said, that many factors can complicate the comparison of CT scans, including differences in position and inhalation during imaging, weight gain, and artifacts. The project’s goal is to develop an algorithm that tries to compensate for all those potential background factors.

Radiologists mentally compute the doubling time of a nodule, or the range of time it takes for the size of the nodule to increase twofold. A mass that doubles in less than 30 days is growing fast and could be an infection, Cahill said. “If it takes more than one and a half years to double, it’s growing slowly and is probably benign. If it’s anywhere between that, one month and 1.5 years, then, it could be malignant and you have to do further testing and do biopsy.”

The process geometrically transforms one three-dimensional image into another and compensates for background information that blurs edges of nodules, even when underlying diseases like emphysema or fibrosis make intensities in the background brighter. The technology will be part of the free software libraries offered by Kitware, a North Carolina-based, open-source software company that specializes in medical image analyses.

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