Helical CT Protocols for the Abdomen and Pelvis
Bibliographic record
Abstract
OBJECTIVE: We surveyed members of the Society of Computed Body Tomography/Magnetic Resonance to evaluate current techniques used for helical CT in the abdomen and pelvis. MATERIALS AND METHODS: The survey was distributed to 70 members (36 institutions) of the Society of Computed Body Tomography/Magnetic Resonance. The survey included general questions related to abdominal and pelvic helical CT and also asked the members to write a protocol for 12 hypothetical requisitions. RESULTS: Thirty-two members (46%) responded, representing 28 institutions (78%). The number of protocols for helical CT of the abdomen and pelvis at each institution ranges from 2 to 35 (median, 11). IV contrast material is administered for 90% (median) of abdominal and pelvic CT examinations. Nonionic contrast material is used for 68% (median) of these examinations. IV contrast material is used by 100% of institutions for tumor staging protocols except for one institution that does not use IV contrast material for lymphoma staging. Fifty percent of the institutions obtain two- or three-phases of liver images for breast cancer staging. For all protocols, the average collimation and reconstruction interval is 7 mm except for renal (5 mm) and adrenal (4 mm) protocols. Rectal contrast material is administered most commonly for colon cancer staging (39% of institutions). CONCLUSION: There is a wide range in the number of protocols used for helical CT in the abdomen and pelvis among the responding institutions. Most protocols include use of nonionic IV contrast material injected at a rate of 3 ml/sec and a collimation of 7 mm.
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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 | 0.004 | 0.011 |
| 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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".