Implementation of dual‐ and triple‐energy cone‐beam micro‐CT for postreconstruction material decomposition
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Bibliographic record
Abstract
Micro-CT has become a powerful tool for small animal research, having the ability to obtain high-resolution in vivo and ex vivo images for analyzing bone mineral content, organ vasculature, and bone microarchitecture extraction. The use of exogenous contrast agents further extends the use of micro-CT techniques, but despite advancements in contrast agents, single-energy micro-CT is still limited in cases where two different materials share similar grey-scale intensity values. This study specifically addresses the development of multiple-energy cone-beam micro-CT, for applications where bone must be separated from blood vessels filled with a Pb-based contrast material (Microfil) in ex vivo studies of rodents and tissue specimens. The authors report the implementation of dual- and triple-energy CT algorithms for material-specific imaging using postreconstruction decomposition of micro-CT data; the algorithms were implemented on a volumetric cone-beam micro-CT scanner (GE Locus Ultra). For the dual-energy approach, extrinsic filtration was applied to the x-ray beam to produce spectra with different proportions of x rays above the K edge of Pb. The optimum x-ray tube energies (140 kVp filtered with 1.45 mm Cu and 96 kVp filtered with 0.3 mm Pb) that maximize the contrast between bone and Microfil were determined through numerical simulation. For the triple-energy decomposition, an additional low-energy spectrum (70 kVp, no added filtration) was used. The accuracy of decomposition was evaluated through simulations and experimental verification of a phantom containing a cortical bone simulating material (SB3), Microfil, and acrylic. Using simulations and phantom experiments, an accuracy greater than 95% was achieved in decompositions of bone and Microfil (for noise levels lower than 11 HU), while soft tissue was separated with accuracy better than 99%. The triple-energy technique demonstrated a slightly higher, but not significantly different, decomposition accuracy than the dual-energy technique for the same achieved noise level in the micro-CT images acquired at the multiple energies. The dual-energy technique was applied to the decomposition of an ex vivo rat specimen perfused with Microfil; successful decomposition of the bone and Microfil was achieved, enabling the visualization and characterization of the vasculature both in areas where the vessels traverse soft tissue and when they are surrounded by bone. In comparison, in single energy micro-CT, vessels surrounded by bone could not be distinguished from the cortical bone, based on grey-scale intensity alone. This work represents the first postreconstruction application of material-specific decomposition that directly takes advantage of the K edge characteristics of a contrast material injected into an animal specimen; the application of the technique resulted in automatic, accurate segmentation of 3D micro-CT images into bone, vessel, and tissue components. The algorithm uses only reconstructed images, rather than projection data, and is calibrated by an operator with signal values in regions identified as being comprised entirely of either cortical bone, contrast-enhanced vessel, or soft tissue; these required calibration values are observed directly within reconstructed CT images acquired at the multiple energies. These features facilitate future implementation on existing research micro-CT systems.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it