Model-Based Iterative Reconstruction in CT Enterography
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to analyze the performance of pure model-based iterative reconstruction (MBIR) in low-dose CT enterography. SUBJECTS AND METHODS: Forty-four patients with Crohn disease referred for CT enterography were included. Low-dose modified-protocol and conventional-protocol CT datasets were contemporaneously acquired. Conventional-protocol image formation was performed with 40% adaptive statistical iterative reconstruction (ASIR). Modified-protocol data were reconstructed with 100% MBIR and 40% ASIR. Image quality was assessed subjectively and objectively at six levels. Independent clinical interpretations by two fully blinded radiologists were compared with reference standard consensus reviews by two nonblinded readers who had access to clinical information, previous imaging studies, and medical records. RESULTS: A 74.7% average radiation dose reduction was seen: low-dose modified-protocol effective dose, 1.61 ± 1.18 mSv (size-specific-dose-estimate, 2.47 ± 1.21 mGy); conventional-protocol effective dose, 6.05 ± 2.84 mSv (size-specific-dose-estimate, 9.25 ± 2.9 mGy). Image quality assessment yielded 9372 data points. Objective noise on modified-protocol MBIR images was superior (p < 0.05) to that with the conventional protocol at three of six levels and comparable at the other three levels. Modified-protocol images were superior to conventional-protocol ASIR images (p < 0.05 in all cases) for subjective noise, spatial resolution, contrast resolution, streak artifact, and diagnostic acceptability on coronal reconstructions. Axial diagnostic acceptability was superior for conventional-protocol ASIR (p = 0.76). For both readers, modified-protocol MBIR clinical readings agreed more closely with reference standard readings than did conventional-protocol ASIR readings with regard to bowel wall disease assessment (κ = 0.589 and 0.700 vs 0.583 and 0.564). Overall Crohn disease activity grade (κ = 0.549 and 0.441 vs 0.315 and 0.596) and detection of acute complications (κ = 1.0 and 0.689 vs 0.896 and 0.896) were comparable when evaluated on conventional-protocol ASIR and modified-protocol MBIR images. CONCLUSION: Low-dose CT enterography with MBIR yields images that are comparable to or superior to conventional images.
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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 | 0.003 | 0.012 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".