Spectral performance of a whole-body research photon counting detector CT: quantitative accuracy in derived image sets

Abstract

Photon-counting computed tomography (PCCT) uses a photon counting detector to count individual photons and allocate them to specific energy bins by comparing photon energy to preset thresholds. This enables simultaneous multi-energy CT with a single source and detector. Phantom studies were performed to assess the spectral performance of a research PCCT scanner by assessing the accuracy of derived images sets. Specifically, we assessed the accuracy of iodine quantification in iodine map images and of CT number accuracy in virtual monoenergetic images (VMI). Vials containing iodine with five known concentrations were scanned on the PCCT scanner after being placed in phantoms representing the attenuation of different size patients. For comparison, the same vials and phantoms were also scanned on 2nd and 3rd generation dual-source, dual-energy scanners. After material decomposition, iodine maps were generated, from which iodine concentration was measured for each vial and phantom size and compared with the known concentration. Additionally, VMIs were generated and CT number accuracy was compared to the reference standard, which was calculated based on known iodine concentration and attenuation coefficients at each keV obtained from the U.S. National Institute of Standards and Technology (NIST). Results showed accurate iodine quantification (root mean square error of 0.5 mgI/cc) and accurate CT number of VMIs (percentage error of 8.9%) using the PCCT scanner. The overall performance of the PCCT scanner, in terms of iodine quantification and VMI CT number accuracy, was comparable to that of EID-based dual-source, dual-energy scanners.

Figure 1

The research PCCT scanner was built on the platform of a 2nd generation dual source scanner with an energy integrating detector (EID) replaced by a photon counting detector (PCD).

Figure 2

Vials containing different iodine solutions (left) were placed inside water phantoms representing patient torso with different sizes (right).

Figure 3

PCCT images of the low-energy threshold (A, [25, 140] keV), high-energy threshold (B, [65, 140] keV), bin 1 (C, [25, 65] keV) and bin 2 (D, [65, 140] keV). High-energy threshold and bin 2 images are identical. All images are displayed with window width and window center of 462 and 133 HU.

Figure 4

Iodine image (A), water image (B) and fused image (iodine overlaid on the water image, C) generated from the PCCT bin images using a material decomposition algorithm. ROIs placed at the iodine vials and water background showed measured iodine concentrations. The water image was displayed with window width and window center of 464 HU and 250 HU. Measured iodine concentration was compared to the true concentration (D).

Figure 5

Comparison of measured iodine concentration versus true concentration for the 2nd generation dual source scanner with dual energy modes of 80/Sn140 (A) and 100/Sn140 (B), and 3rd generation dual source scanner with dual energy modes of 70/Sn150 (C), 80/Sn150 (D), 90/Sn150 (E), and 100/Sn150 (F).

Figure 6

Virtual monoenergetic images of 50, 60, 80, 100, 120 and 140 keV generated from the 30 cm phantom scanned on the PCCT.

Figure 7

Measured and reference VMI CT numbers of different iodine concentrations from the 30 cm phantom scanned on the PCCT.

Figure 8

Measured and reference VMI CT numbers of different iodine concentrations from the 25 (A), 35 (B), 40 (C) and 45 cm (D) phantoms scanned on the PCCT.

Figure 9

VMI CT numbers at 60 keV of 10 mgI/cc across phantom sizes, at different DE modes and scanner types. The reference VMI CT number that calculated based on attenuation and iodine concentration was 366 HU.