Bioimpedance technique for monitoring cerebral artery stenosis in a 3D numerical model of the head
Bibliographic record
Abstract
Insufficient blood supply to the brain causes a transient ischemic attack (TIA) or a stroke. One of the causes to insufficient blood supply is cerebral artery stenosis. In this study, the feasibility of bioimpedance for monitoring such stenosis was analyzed. Simulations were conducted on a realistic numerical model of the head, focusing on the left middle cerebral artery (LMCA). Tissues were assumed to act as linear isotropic volume conductors, and the quasi-static approximation was applied. Electrical potentials were calculated by solving Poisson's equation, using the finite volume method (FVM) and the successive over relaxation (SOR) method. The best sensitivity found was 0.471 μV/% stenosis, using this electrode configuration: one injector near the left eye and the other injector near the right ear, one measurement position near the left eye and the other one in the right ear, keeping a distance of at least 2.5 cm between measurement and injection positions. The maximal sensitivity achieved in the numerical model under the applied assumptions supports the feasibility of bioimpedance technique for monitoring cerebral artery stenosis. However, according to sensitivity [1/m(4)] maps, calculated for the preferable electrode configurations, the measurements' specificity to the stenosis degree might be inadequate and should be further studied.
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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 | 0.001 |
| 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".