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17 October 2024 Photon-counting computed tomography versus energy-integrating computed tomography for detection of small liver lesions: comparison using a virtual framework imaging
Nicholas Felice, Benjamin Wildman-Tobriner, William Paul Segars, Mustafa R. Bashir, Daniele Marin, Ehsan Samei, Ehsan Abadi
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Journal of Medical Imaging, Vol. 11, Issue 5, 053502 (October 2024). https://doi.org/10.1117/1.JMI.11.5.053502
Abstract

Purpose

Photon-counting computed tomography (PCCT) has the potential to provide superior image quality to energy-integrating CT (EICT). We objectively compare PCCT to EICT for liver lesion detection.

Approach

Fifty anthropomorphic, computational phantoms with inserted liver lesions were generated. Contrast-enhanced scans of each phantom were simulated at the portal venous phase. The acquisitions were done using DukeSim, a validated CT simulation platform. Scans were simulated at two dose levels (CTDIvol 1.5 to 6.0 mGy) modeling PCCT (NAEOTOM Alpha, Siemens, Erlangen, Germany) and EICT (SOMATOM Flash, Siemens). Images were reconstructed with varying levels of kernel sharpness (soft, medium, sharp). To provide a quantitative estimate of image quality, the modulation transfer function (MTF), frequency at 50% of the MTF (f50), noise magnitude, contrast-to-noise ratio (CNR, per lesion), and detectability index (d′, per lesion) were measured.

Results

Across all studied conditions, the best detection performance, measured by d′, was for PCCT images with the highest dose level and softest kernel. With soft kernel reconstruction, PCCT demonstrated improved lesion CNR and d′ compared with EICT, with a mean increase in CNR of 35.0% (p<0.001) and 21% (p<0.001) and a mean increase in d′ of 41.0% (p<0.001) and 23.3% (p=0.007) for the 1.5 and 6.0 mGy acquisitions, respectively. The improvements were greatest for larger phantoms, low-contrast lesions, and low-dose scans.

Conclusions

PCCT demonstrated objective improvement in liver lesion detection and image quality metrics compared with EICT. These advances may lead to earlier and more accurate liver lesion detection, thus improving patient care.
© 2024 Society of Photo-Optical Instrumentation Engineers (SPIE)
Citation Download Citation
Nicholas Felice, Benjamin Wildman-Tobriner, William Paul Segars, Mustafa R. Bashir, Daniele Marin, Ehsan Samei, and Ehsan Abadi "Photon-counting computed tomography versus energy-integrating computed tomography for detection of small liver lesions: comparison using a virtual framework imaging," Journal of Medical Imaging 11(5), 053502 (17 October 2024). https://doi.org/10.1117/1.JMI.11.5.053502
Received: 26 April 2024; Accepted: 23 September 2024; Published: 17 October 2024
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KEYWORDS
Liver
Computed tomography
Image quality
Scanners
Modulation transfer functions
Optical computing
Brain-machine interfaces
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