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Power law spectral photon-counting CT for quantitative effective atomic number and electron density imaging
Mohammed Alzaabi1, Abderaouf Behouch1,2, Briya Tariq1
1Khalifa University, Abu Dhabi, United Arab Emirates.
Physics in Medicine and Biology
|July 14, 2026
Summary
A new scanner-specific power law method accurately images effective atomic number (Zeff) and electron density (ρe) using spectral photon-counting CT. This technique enables precise tissue characterization in complex samples with high accuracy.
Area of Science:
- Medical Physics
- Radiological Imaging
- Materials Science
Background:
- Spectral photon-counting CT (SPCCT) offers advanced material decomposition capabilities.
- Accurate voxelwise material decomposition requires precise modeling of X-ray interactions.
- Existing methods may lack scanner-specificity or robustness in heterogeneous samples.
Purpose of the Study:
- To develop and validate a scanner-specific power law method for effective atomic number (Zeff) and electron density (ρe) imaging.
- To assess the method's accuracy and applicability for tissue characterization using SPCCT.
- To demonstrate quantitative imaging in heterogeneous samples.
Main Methods:
- Modeled X-ray linear attenuation coefficient µ(E) using a power law sum of photoelectric, Compton, and correction terms.
- Fitted model coefficients to NIST cross sections for elements Z = 6-21.
- Applied a scanner-specific power law model with bin-wise linear calibration to SPCCT data from phantoms and a heterogeneous meat sample.
Main Results:
- The four-window formalism achieved ~1% absolute error for Zeff and ρe using NIST µ as input.
- On calibrated SPCCT images, errors were 4.9% for Zeff and 2.1% for ρe (four-window), and 3.6% for Zeff and 1.7% for ρe (dual-energy).
- The method successfully differentiated fat, muscle, bone, and iodine in a heterogeneous meat sample without retuning.
Conclusions:
- A scanner-specific power law model combined with linear calibration provides accurate Zeff and ρe from single SPCCT acquisitions.
- Optimized dual-energy windows achieve high accuracy for ρe, supporting quantitative tissue characterization.
- This approach offers a robust framework for material decomposition and tissue analysis in photon-counting CT.
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