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An algorithm to calculate physical density of biomedical objects having 3 ≤ Zeff ≤ 20: an application study using
Hiroaki Hayashi1, Rina Nishigami2, Takashi Asahara3
1College of Transdisciplinary Sciences for Innovation, Kanazawa University, Kakuma-machi, Kanazawa, Ishikawa, 920-1192, Japan.
A new algorithm calculates effective physical density (ρeff) using photon-counting computed tomography (PC-CT) without calibration. This method provides physically interpretable contrast information, advancing X-ray diagnostics.
Area of Science:
- Medical Physics
- Radiology
- Biomedical Engineering
Background:
- Photon-counting computed tomography (PC-CT) offers advanced quantitative imaging capabilities for X-ray diagnosis.
- Conventional CT methods have limitations in providing detailed physical property information of biological tissues.
- Developing algorithms for accurate material decomposition is crucial for PC-CT applications.
Purpose of the Study:
- To propose and validate a novel algorithm for calculating the effective physical density (ρeff) of biological objects.
- To enable physical interpretation of contrast mechanisms in X-ray imaging using effective atomic number (Zeff) and ρeff.
- To demonstrate the algorithm's independence from substance-specific calibration.
Main Methods:
- Developed an algorithm to determine ρeff by fitting interaction cross sections to linear attenuation coefficients derived from virtual monochromatic images (VMIs).
- Integrated Zeff analysis, feeding back information to refine ρeff calculation.
- Validated the algorithm using a clinical PC-CT scanner with various phantoms and samples.
Main Results:
- The algorithm successfully calculated ρeff for water with a 4.5% uncertainty.
- Demonstrated that contrast factors can be physically interpreted using Zeff and ρeff, a capability beyond conventional CT.
- The procedure does not require calibration with specific substances, allowing analysis of diverse materials.
Conclusions:
- The proposed algorithm enables accurate ρeff calculation for biological objects using PC-CT data.
- This method allows for a deeper physical understanding of image contrast, moving beyond empirical CT values.
- The algorithm is expected to enhance diagnostic information in X-ray imaging, particularly with PC-CT and dual-energy CT systems.
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