Safety assessment of spine MRI in deep brain stimulation patients
Bibliographic record
Abstract
OBJECTIVE: Many centers are hesitant to perform clinically indicated MRI in patients who have undergone deep brain stimulation (DBS). Highly restrictive guidelines prohibit the use of most routine clinical MRI protocols in these patients. The authors' goals were to assess the safety of spine MRI in patients with implanted DBS devices, first through phantom model testing and subsequently through validation in a DBS patient cohort. METHODS: A phantom was used to assess DBS device heating during 1.5-T spine MRI. To establish a safe spine protocol, routinely used clinical sequences deemed unsafe (a rise in temperature > 2°C) were modified to decrease the rise in temperature. This safe phantom-based protocol was then used to prospectively run 67 spine MRI sequences in 9 DBS participants requiring clinical imaging. The primary outcome was acute adverse effects; secondary outcomes included long-term adverse clinical effects, acute findings on brain MRI, and device impedance stability. RESULTS: The increases in temperature were highest when scanning the cervical spine and lowest when scanning the lumbar spine. A temperature rise < 2°C was achieved when 3D sequences were modified to 2D and when the number of slices was decreased by the minimum amount compared to routine spine MRI protocols (but there were still more slices than allowed by vendor guidelines). Following spine MRI, no acute or long-term adverse effects or acute findings on brain MR images were detected. Device impedances remained stable. CONCLUSIONS: Patients with DBS devices may safely undergo spine MRI with a fewer number of slices compared to those used in routine clinical protocols. Safety data acquisition may allow protocols outside vendor guidelines with a maximized number of slices, reducing the need for radiologist supervision.Clinical trial registration no.: NCT03753945 (ClinicalTrials.gov).
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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 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".