A low radiation computed tomography protocol for monitoring shunted hydrocephalus
Bibliographic record
Abstract
BACKGROUND: Computed tomography (CT) requires highest radiation doses in radiology. The collective dose from the use of radiation in medicine is rising, partly due to increase in CT use as well as the growing popularity of multislice scanners. There is growing concern from multiple studies that radiation from repeated CT scans could induce malignancies later in life. Patients with hydrocephalus are unique in that they are often subjected to repeated CT imaging throughout their lives to monitor whether their hydrocephalus is under control. We designed a study to see whether a low dose radiation CT protocol could provide effective information for monitoring hydrocephalus. METHODS: A pilot study was done with 10 patients with hydrocephalus who needed CT scanning to monitor their hydrocephalus. The CT protocol was altered for each patient to sequentially bring down the radiation dose to the minimum level, which would provide sufficient diagnostic information. Based on the pilot study, a new low dose CT scanning protocol was devised and tested on 25 shunted patients who needed monitoring of their hydrocephalus. All images were carefully scrutinized by a consultant neuroradiologist and consultant neurosurgeon to ensure that the following diagnostic information could be analyzed: 1. ventricular size, 2. cisterns, 3. sulcii, and 4. cathet er position RESULTS: All low-dose CT images were diagnostically acceptable and provided sufficient information to the requesting clinician. None of the subjects required repeat imaging. The effective radiation dose was reduced from 2.2 mSv using a conventional CT protocol to 0.29 mSv with the new low dose CT protocol. The new CT protocol provides 87% less effective radiation dose compared with conventional scans. CONCLUSIONS: We propose a new low dose CT protocol which can be used for monitoring shunted hydrocephalus. The radiation to the patient with this protocol is comparable to that of a skull X-ray. However, this protocol should only be requested by a clinician who is aware of its limitations.
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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 | 0.005 |
| 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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".