Metal artifact reduction and tumor detection using photon-counting multi-energy computed tomography

Area of Science:

• Medical Imaging
• Radiology
• Photon-Counting Detector Technology

Background:

• Metal artifacts pose significant challenges in computed tomography (CT), impacting diagnostic accuracy and patient treatment.
• Existing methods for metal artifact reduction (MAR) have limitations in complex clinical scenarios.

Purpose of the Study:

• To evaluate the clinical potential of a novel photon-counting detector (PCD) CT system for reducing metal artifacts in head CT scans.
• To assess the system's ability to recover visualization of iodine-enhanced regions, such as oral tumors, obscured by metal artifacts.

Main Methods:

• A prototype PCD CT system with three energy thresholds was used to acquire data from physical phantoms.
• Iodine quantification accuracy was assessed using iodine phantoms.
• Material decomposition (MD) and virtual monochromatic images (VMIs) were generated using a multi-energy CT phantom.
• An ATOM phantom with metal insertions, including an iodine-mimicking tumor, was used to evaluate metal artifact reduction (MAR) and image quality via contrast-to-noise ratio (CNR) measurements.

Main Results:

• The PCD CT system demonstrated accurate iodine quantification.
• Lower energy bins (bin 1) showed higher contrast for iodine, while higher energy bins (bin 3) exhibited reduced metal artifacts.
• Normalized metal artifact reduction (NMAR) combined with MD and VMI reconstruction significantly improved the contrast of the iodine-enhanced region (CNR: 20.6 ± 1.2) compared to conventional CT images (CNR: 10.4 ± 0.5).

Conclusions:

• The PCD-based multi-energy CT imaging system shows significant potential for simultaneous reduction of metal artifacts and enhancement of target tissue contrast.
• This technology could enable novel diagnostic and therapeutic applications, particularly in cases involving metallic implants.