Prospective Comparison of Standard- Versus Low-Radiation-Dose CT Enterography for the Quantitative Assessment of Crohn Disease
Bibliographic record
Abstract
OBJECTIVE: CT enterography (CTE) is sensitive and specific for active inflammatory changes of Crohn disease (CD), but its use has been limited by exposure to ionizing radiation. The objective of this study is to show the noninferiority of a model-based iterative reconstruction (MBIR) technique using lower radiation doses compared with standard-dose CTE in the assessment of CD. SUBJECTS AND METHODS: Patients referred to a hospital radiology department for CTE for the evaluation of CD underwent both a standard examination (used to generate filtered back-projection and adaptive statistical iterative reconstruction [ASIR] images) and low-dose MBIR CTE performed in a random sequence on the same day. Images were reviewed by two radiologists for signs of small-bowel CD. Radiologic findings obtained using ASIR and clinical assessments of disease activity served as the reference standard for comparison with low-dose CTE findings. RESULTS: A total of 163 patients, 92 (56.4%) of whom had active disease, underwent CTE. MBIR was found to be noninferior to the two standard-dose techniques, with no significant differences noted between the three types of images when compared with the clinical reference standard. As compared with the radiologic standard of ASIR, the very-low-dose scans had a high degree of accuracy, with sensitivity ranging from 0.85 to 0.94 and specificity ranging from 0.84 to 0.97 depending on the reader. A significant reduction in radiation exposure was noted with MBIR (mean [± SD] reduction, 3.30 ± 3.17 mSv) versus standard-dose imaging (7.16 ± 4.61 mSv; p < 0.001). CONCLUSION: Low-dose CTE using MBIR is sensitive and specific for the detection of active inflammatory changes of CD while utilizing radiation doses substantially lower than those associated with standard techniques.
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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 | 0.011 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".