Abstract
Objective
To demonstrate the potential of low-dose ultra-high-resolution CT (UHRCT) images to generate high-quality radiographic images on extremity phantoms and to estimate the radiation dose required for this.
Materials and methods
A hand and knee phantom containing real human bones was imaged on an UHRCT scanner at full-dose, half-dose, and quarter-dose levels using a high-resolution extremity protocol. The raw data was reconstructed using both filtered back projection (FBP) and an iterative reconstruction algorithm (AIDR3D). Using custom designed software, each CT volume data set was converted to attenuation coefficients, and then a synthesized radiograph (synDX) was generated by forward projecting the volume data sets from a point source onto a 2D synthetic detector. The signal-to-noise ratio (SNR) was measured in the synDXs across all dose levels and the root-mean-squared error (RMSE) was computed with the FD synDXs as the reference.
Results
The proposed workflow generates high-quality synDXs at any arbitrary angle. For FBP, the SNR largely tracked with the radiation dose levels for both the knee and hand phantoms. For the knee phantom, iterative reconstruction provided a 6.1% higher SNR when compared to FBP. The RMSE was overall higher for the lowest dose levels and monotonically decreased with increasing dose. No substantial differences were observed qualitatively in the visualization of skeletal detail of the phantoms.
Conclusion
The fine detail provided by UHRCT acquisitions of extremities facilitates the ability to generate quality radiographs, potentially eliminating the need for additional scanning on a conventional digital radiography system.
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Data availability
The algorithm (in MATLAB) used to generate the synthesized radiographs from UHRCT acquisitions is available from the corresponding author upon request.
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Authors A.M.H. and J.M.B. have research funding from Canon.
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Hernandez, A.M., Bayne, C.O., Bateni, C. et al. Extremity radiographs derived from low-dose ultra-high-resolution CT: a phantom study. Skeletal Radiol (2024). https://doi.org/10.1007/s00256-024-04600-y
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DOI: https://doi.org/10.1007/s00256-024-04600-y