An Ultrasound-Guided Hemispherical Phased Array for Microbubble-Mediated Ultrasound Therapy
Bibliographic record
Abstract
GOAL: To develop a low-cost magnetic resonance imaging (MRI)-free transcranial focused ultrasound (FUS) system for microbubble-mediated therapy. METHODS: A 128-element 11 MHz array for skull localization was integrated within a 256-module multi-frequency (306/612/1224 kHz) dual-mode phased array. The system's transcranial transmit and receive performance was evaluated with ex-vivo human skullcaps using phase aberration corrections calculated from computed tomography (CT)-based simulations via ultrasound-based (USCT) and landmark-based (LMCT) registrations, and a gold-standard fixed source emitter (FSE)-based method. RESULTS: were obtained using USCT, resulting in sub-millimeter transmit targeting errors driven at 306 kHz (0.9 ± 0.2 mm) and 612 kHz (0.9 ± 0.3 mm), and source localization errors of 1.0 ± 0.3 mm and 0.6 ± 0.2 mm at receive frequencies of 306 kHz and 612 kHz, respectively (mean ± SD). Similar errors were obtained using LMCT and no significant differences between these two approaches were found on either transmit (p = 0.64/0.99) or receive (p = 0.45/0.36) at 306 kHz/612kHz. During volumetric multi-point exposures, approximately 70% and 60% of the transmit frames in which microbubble activity was detected via FSE were recovered using USCT when imaging at the second-harmonic and half-harmonic, respectively, compared to 60% and 69% using LMCT. CONCLUSION: This low-cost ultrasound-guided transcranial FUS system affords USCT skull registration with accuracy comparable to LMCT methods. SIGNIFICANCE: Such systems have great potential to advance the adoption of microbubble-mediated FUS brain therapy by improving access to the technology.
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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".