CT paves the way to more accurate kidney stone volume estimates
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“We proposed a volume estimation method based on an adaptive threshold segmentation method and a correction for the PSF (point spread function) model,” wrote Xinhui Duan, PhD, of Mayo Clinic in Rochester, Minn., and colleagues. Stone volume is often a major factor in choosing a clinical treatment, they noted.
Duan and colleagues explained their method consisted of two steps. First, a threshold equal to the average of the CT number of the object and the background was applied to get the full width at half maximum (FWHM) volume. Because FWHM is directly measurable, this method is more advantageous than the recovery coefficient method used for PET and SPECT, according to the authors.
Since blurring can cause errors in size or volume measurement, particularly with small objects, Duan et al then applied correction factors that were precalculated based on a model of a sphere and a 3D Gaussian PSF. “The point spread function was measured in a CT scanner to represent the response of the scanner to a point-like object,” wrote the authors.
The researchers validated the accuracy of this method using six small cylindrical phantoms with volumes of 21.87 or 99.9 mm3, and three attenuations, along with 76 kidney stones with a volume range of 6.3 to 317.4 mm3.
Results showed Duan et al’s method was significantly more accurate than the FWHM volume alone. The authors reported that the magnitude of improvement depended on stone volume, with stones ranging from 10 to 20 mm3 showing the largest jump in accuracy of measurement at 19.6 percent. Smaller stones benefited more from the method.
“Precise volume measurement would give the surgeon a better understanding of the true stone burden and provide direction toward a more appropriate treatment modality,” wrote Duan and colleagues. “Also, an accurate, reproducible volume estimation method would benefit the monitoring of stone growth or shrinkage, which is important to track disease development and treatment effectiveness.”
Evan Godt, Writer
Evan joined TriMed in 2011, writing primarily for Health Imaging. Prior to diving into medical journalism, Evan worked for the Nine Network of Public Media in St. Louis. He also has worked in public relations and education. Evan studied journalism at the University of Missouri, with an emphasis on broadcast media.