RSNA 2019: Digital X-Ray Preview

New flat-panel detector could improve dual-energy imaging

By Wayne Forrest, AuntMinnie.com staff writer

November 13, 2019 --

Tuesday, December 3 | 3:20 p.m.-3:30 p.m. | SSJ21-03 | Room N228
A novel triple-layer flat-panel digital detector design could solve current deficiencies in dual-energy digital radiography.

Dual-energy imaging has become an important tool, with its ability to reduce anatomical noise and subsequently help radiologists improve their reading accuracy. At the same time, radiologists have to deal with trade-offs that include motion artifacts from two exposures.

To help solve those issues, KA Imaging in Kitchener, Ontario, a designer and manufacturer of high-performance x-ray detectors, is developing a triple-layer flat-panel detector for single-shot dual-energy imaging, designed to eliminate motion artifacts and maintain high sensitivity.

The company's flat-panel detector prototype features three stacked sensors, each with its own cesium iodide scintillator, that generate three images per exposure. The combination includes a digital radiography (DR) image, equivalent to one obtained with a conventional detector, and two tissue-subtracted images acquired through the algorithmic subtraction of bone and soft tissue.

To evaluate image quality, a team led by Sebastian Maurino, a medical imaging physicist with KA Imaging, measured the detector's detective quantum efficiency (DQE) and modulation transfer function (MTF). The triple-layer detector's tissue-subtraction capabilities were then evaluated by studying three chest x-ray images obtained from an ongoing clinical trial.

The researchers found high DQE and MTF, indicating that the addition of the dual-energy technology did not adversely affect the main function of the triple-layer flat-panel detector and that tissue subtraction also enhanced image quality.

The results support the triple-layer detector's potential for clinical use, especially because both high-quality DR and dual-energy images can be obtained in a single exposure, they concluded.

This paper received a Roadie 2019 award for the most popular abstract by page views in this Road to RSNA section.


Last Updated bc 11/19/2019 10:31:08 AM