Physical performance and image optimization of megavoltage cone‐beam CT
Bibliographic record
Abstract
Megavoltage cone-beam CT (MVCBCT) is the most recent addition to the in-room CT systems developed for image-guided radiation therapy. The first generation MVCBCT system consists of a 6 MV treatment x-ray beam produced by a conventional linear accelerator equipped with a flat panel amorphous silicon detector. The objective of this study was to evaluate the physical performance of MVCBCT in order to optimize the system acquisition and reconstruction parameters for image quality. MVCBCT acquisitions were performed with the clinical system but images were reconstructed and analyzed with a separate research workstation. The geometrical stability and the positioning accuracy of the system were evaluated by comparing geometrical calibrations routinely performed over a period of 12 months. The beam output and detector intensity stability during MVCBCT acquisition were also evaluated by analyzing in-air acquisitions acquired at different exposure levels. Several system parameters were varied to quantify their impact on image quality including the exposure (2.7, 4.5, 9.0, 18.0, and 54.0 MU), the craniocaudal imaging length (2, 5, 15, and 27.4 cm), the voxel size (0.5, 1, and 2 mm), the slice thickness (1, 3, and 5 mm), and the phantom size. For the reconstruction algorithm, the study investigated the effect of binning, averaging and diffusion filtering of raw projections as well as three different projection filters. A head-sized water cylinder was used to measure and improve the uniformity of MVCBCT images. Inserts of different electron densities were placed in a water cylinder to measure the contrast-to-noise ratio (CNR). The spatial resolution was obtained by measuring the point-spread function of the system using an iterative edge blurring technique. Our results showed that the geometric stability and accuracy of MVCBCT were better than 1 mm over a period of 12 months. Beam intensity variations per projection of up to 35.4% were observed for a 2.7 MU MVCBCT acquisition. These variations did not cause noticeable reduction in the image quality. The results on uniformity suggest that the cupping artifact occurring with MVCBCT is mostly due to off-axis response of the detector and not scattered radiation. Simple uniformity correction methods were developed to nearly eliminate this cupping artifact. The spatial resolution of the baseline MVCBCT reconstruction protocol was approximately 2 mm. An optimized reconstruction protocol was developed and showed an improvement of 75% in CNR with a penalty of only 8% in spatial resolution. Using this new reconstruction protocol, large adipose and muscular structures were differentiated at an exposure of 9 MU. A reduction of 36% in CNR was observed on a larger (pelvic-sized) phantom. This study demonstrates that soft-tissue visualization with MVCBCT can be substantially improved with proper system settings. Further improvement is expected from the next generation MVCBCT system with an optimized megavoltage imaging beamline.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".