Functional MRI Safety and Artifacts during Deep Brain Stimulation: Experience in 102 Patients
Bibliographic record
Abstract
Background With growing numbers of patients receiving deep brain stimulation (DBS), radiologists are encountering these neuromodulation devices at an increasing rate. Current MRI safety guidelines, however, limit MRI access in these patients. Purpose To describe an MRI (1.5 T and 3 T) experience and safety profile in a large cohort of participants with active DBS systems and characterize the hardware-related artifacts on images from functional MRI. Materials and Methods In this prospective study, study participants receiving active DBS underwent 1.5- or 3-T MRI (T1-weighted imaging and gradient-recalled echo [GRE]–echo-planar imaging [EPI]) between June 2017 and October 2018. Short- and long-term adverse events were tracked. The authors quantified DBS hardware–related artifacts on images from GRE-EPI (functional MRI) at the cranial coil wire and electrode contacts. Segmented artifacts were then transformed into standard space to define the brain areas affected by signal loss. Two-sample t tests were used to assess the difference in artifact size between 1.5- and 3-T MRI. Results A total of 102 participants (mean age ± standard deviation, 60 years ± 11; 65 men) were evaluated. No MRI-related short- and long-term adverse events or acute changes were observed. DBS artifacts were most prominent near the electrode contacts and over the frontoparietal cortical area where the redundancy of the extension wire is placed subcutaneously. The mean electrode contact artifact diameter was 9.3 mm ± 1.6, and 1.9% ± 0.8 of the brain was obscured by the coil artifact. The coil artifacts were larger at 3 T than at 1.5 T, obscuring 2.1% ± 0.7 and 1.4% ± 0.7 of intracranial volume, respectively (P < .001). The superficial frontoparietal cortex and deep structures neighboring the electrode contacts were most commonly obscured. Conclusion With a priori local safety testing, patients receiving deep brain stimulation may safely undergo 1.5- and 3-T MRI. Deep brain stimulation hardware–related artifacts only affect a small proportion of the brain. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Martin in this issue.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".