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April 24, 2026Physics in Medicine and Biology1 citations

Reduction of CT Number Location Dependency Using Photon-Counting Detector CT and Virtual Monoenergetic Imaging

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MSMaryam SadeghianJSJoseph SwicklikCMCynthia H McCollough

Key Points

  • The aim is to investigate how photon-counting-detector CT reduces location dependency of CT numbers in comparison to energy-integrated-detector CT.
  • Used a multi-energy CT phantom with tissue inserts and scanned using PCD and EID techniques.
  • Evaluated CT numbers at multiple locations on varying phantom sizes.
  • Analyzed data using statistical tests for locational variation assessment.
  • PCD-VMI showed a 70.3% reduction in CT number variation for cortical bone compared to single-energy PCD and EID-CTs.
  • CT number coefficient of variation remained below 1% for small and below 3% for larger phantoms with PCD-VMI.
  • Significantly lower locational variation was observed for PCD-VMI across most tissue types and phantom sizes.

Abstract

CT number accuracy is critical in radiotherapy planning. This study aimed to investigate the potential of photon-counting-detector (PCD) CT to reduce location dependency of CT numbers compared to energy-integrated-detector (EID) CT across imaging modes, tissue types, and patient sizes. Approach: Four inserts of typical tissue types: cortical bone, liver, lung, and adipose were placed inside a body size (40 x 30 cm2) multi-energy CT phantom (Gammex). To simulate a larger patient, tissue-equivalent material (Superflab) was added to increase phantom lateral width to 50 cm. Both phantoms were scanned on a PCD-CT (NAEOTOM Alpha, Siemens), a dual-source EID-CT (Force, Siemens; EID-A), and a dual-layer EID-CT (7500 Spectral, Philips; EID-B). All scans were performed with 120 kV, except dual-energy mode of EID-A (100/Sn150 kV, Sn: Tin filter). Volume CT dose index (CTDIvol) was matched across scanners. Each insert was scanned in seven locations: iso-center and six peripheral locations. In addition to single-energy images, 70 keV virtual-monoenergetic images (VMIs) were reconstructed. CT numbers were measured using circular regions of interest. Mean CT number, standard deviation (std), coefficient of variation (CV), max-to-min and central-to-peripheral differences were quantified. CT number variation across seven locations was assessed using the Friedman test and Bonferroni corrected pairwise Wilcoxon signed-rank tests. Main results: PCD-VMI demonstrated lower CT number locational variation compared to EID-CTs among most tissue inserts and phantom sizes. For cortical bone in the standard phantom, PCD-VMI achieved std of 3.31 HU, showing 70.3% reduction compared to single-energy PCD (11.15 HU) and lower than single-energy EID-A (9.75 HU), single-energy EID-B (10.93 HU), EID-A VMI (12.65 HU), and EID-B VMI (4.10 HU). PCD-VMI CV remained below 1% and 3% for small and large phantoms, respectively. Increasing phantom size increased CT number variations, with lowest differences for PCD-VMI. PCD-VMI showed significantly lower CT number locational variation than all other scans across most inserts and phantom sizes. Significance: PCD-VMI reduces CT number locational dependency compared to most imaging modes. The greatest improvements were observed for high-Z materials and larger patients. PCD-VMIs are promising for radiation therapy applications.

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Cite This Study

Sadeghian et al. (2026) studied this question.

synapsesocial.com/papers/69eb0899553a5433e34b3797https://doi.org/10.1088/1361-6560/ae62f1
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