Letter: Unforeseen Hurdles Associated With Magnetic Resonance Imaging in Patients With Deep Brain Stimulation Devices
Bibliographic record
Abstract
To the Editor: Modern deep brain stimulation (DBS) devices are often advertized as being “whole-body conditional,” and this label is an important consideration when assessing the suitability of DBS for a given patient (eg, a patient who would likely require spinal imaging in the future). However, we found that unforeseen contradictions between DBS vendor guidelines and MRI manufacturer manuals rendered diagnostic “whole-body” (eg, spine) imaging unfeasible at our center, leading to deleterious effects on patient care. As described previously,1 the main risk of MRI on deep DBS patients is heating at the DBS lead tips. To mitigate this risk, DBS vendor guidelines typically include 2 heating-related thresholds that scans must be acquired within: most commonly (1) specific absorption rate (SAR) or, if available, (2) B1 + rms. Of the 2, SAR thresholds are extremely restrictive while the more permissive B1 + rms metric is less established and not universally available. Although these factors have been useful in preventing adverse events, they also have limited MRI for DBS patients.2 At our institution, our previous MRI (1.5T GE-Signa; software: HDxT 23.0_V021406.a) did not offer B1 + rms, and the SAR thresholds specified in DBS vendor guidelines meant that it was only practical to acquire diagnostic quality imaging of the head. Given the demand for MRI in DBS patients—1 study estimating that up to 75% of patients require MRI within 10 years of DBS surgery, the majority (62%) of whom calling for body and/or spine scans3—we performed rigorous phantom testing to ensure the safety of off-label (ie, outside SAR threshold) spinal scans on our GE machine.4 Recently, we upgraded our MRI to the one enabling B1 + rms measurements (1.5T Siemens-Magnetom; software: XA20), theoretically allowing us to leverage a more permissive heating-related threshold and acquire diagnostic scans within DBS guidelines. However, we found that the Siemens system displayed a warning prohibiting scans based on B1 rms values: “The actual B1 rms value may be much higher than the value displayed. Do not scan patients with implants based on this value.” This is in conflict with the recommendations of DBS vendor guidelines, which even acknowledge potential discrepancies between real and predicted B1 + rms: “The actual B1 + rms value may differ slightly from the predicted value… The MRI Guidelines for Medtronic …requires only that the predicted B1 + rms value for the protocol is <2.0 µT.”5 Consequently, our MRI department was unable to perform clinically practical scans for extracranial pathology (eg, for the spine) without breaching DBS vendor guidelines or MRI manufacturer recommendations. The delays caused by this impasse have compromised patient care and ultimately led us back to square 1, in which we had to reproduce our phantom safety experiments using the Siemens MRI to facilitate off-label whole-body imaging. It is important that the DBS and radiology community are aware of the contradictory guidelines set by major MRI and DBS manufacturers, which we have not previously seen described in the literature and the considerable hurdles that they can impose.
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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 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.020 | 0.016 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".