Rad AI Showcases THM-Grown CZT Simulations Aiming to Boost Photon-Counting CT Performance

Rad AI is spotlighting new simulation work suggesting that tellurium‑haze method (THM) grown CdZnTe crystals could materially outperform traditional Bridgman‑grown CZT in photon‑counting CT detectors. Monte Carlo simulations show charge collection efficiency improving from 78% at 10‑nanosecond hole lifetime to 99.8% at 2,000 nanoseconds, with THM material modeled in the high‑lifetime range.

Bridgman‑grown CZT is described as constrained by crystal defects and tellurium inclusions that limit hole lifetime, undermining spectral performance under clinical CT photon flux. Rad AI argues that even a roughly 4% efficiency gap between typical Bridgman material and high‑quality THM CZT could translate into better K‑edge image quality, energy resolution, and lower X‑ray dose requirements.

The company notes that higher bias voltages can partially compensate for weaker material, but its simulations still show THM‑grown CZT maintaining an advantage across voltage levels. Although THM crystals are typically more expensive, Rad AI frames them as a premium option for applications where photon‑counting CT image quality and dose efficiency are critical.

Strategically, Rad AI is positioning its detector‑physics and Monte Carlo simulation capabilities as tools to optimize spectral CT detector design before fabrication. This simulation‑driven approach could underpin proprietary designs and support partnerships with CT system OEMs and crystal suppliers, enhancing the company’s competitive stance in advanced medical imaging.

The company’s recent communications stop short of detailing commercial contracts, pricing, or deployment timelines, leaving the financial implications dependent on execution and broader adoption of photon‑counting CT. Still, the emphasis on high‑end THM‑based CZT solutions signals a focus on the upper tier of the CT detector market, where performance gains may justify higher system costs.