A High-Frequency Ultrasound Endoscope for Minimally Invasive Spine Surgery
Bibliographic record
Abstract
The transition to minimally invasive spinal surgery over traditional open procedures requires the development of imaging techniques that meet the size constraints. Due to size restrictions associated with minimally invasive spine surgery (MISS), current imaging techniques are largely limited to microscopy, which is only capable of line-of-sight imaging of the tissue surface. A miniature, high-resolution ultrasound imaging endoscope has been developed as a potential alternative imaging method that would enable intraoperative guidance. We have designed and developed a 30-MHz miniature, 64-element high-resolution imaging endoscope using PIN-PMT-PT single crystal as the piezoelectric substrate. The packaged probe had cross-sectional dimensions of $3.8\times 4.2$ mm and a length of 14 cm. Two editions of the endoscope were created with a forward facing and 40° angle to enable visualization of structures during a medial and lateral approach, respectively. The probe was combined with a custom imaging system that produced real-time images with a field of view ranging between ±32° and an image depth of 15 mm. The two-way axial resolution was measured to be $38~\mu $ m based on the -6-dB width of the pulse envelope. The -6-dB lateral resolution was measured to be 113, 131, and $158~\mu $ m at steering angles of 0°, 12°, and 25°, respectively, which were close to the simulated values of 106, 118, and $144~\mu $ m. Preliminary clinical imaging studies successfully demonstrated the visualization of pertinent spinal anatomy during minimally invasive surgeries. The imaging probe was also able to demonstrate compression and decompression of nerve roots, supporting its potential use as a clinical tool.
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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 | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".