Very High Resolution Ultrasound Imaging for Real-Time Quantitative Visualization of Vascular Disruption after Spinal Cord Injury
Bibliographic record
Abstract
Spinal cord injury (SCI) is characterized by vascular disruption with intramedullary hemorrhage, alterations in blood-spinal cord barrier integrity, and perilesional ischemia. A safe and easily applied imaging technique to quantify evolving intraspinal vascular changes after SCI is lacking. We evaluated the utility of very high resolution ultrasound (VHRUS) imaging to assess SCI-induced vascular disruption in a clinically relevant rodent model. The spinal cords of Wistar rats were lesioned at the 11th thoracic vertebra (Th11) by a 35 g 1-minute clip compression. Three-dimensional quantification of intraspinal hemorrhage using VHRUS (at an acute 90-min and subacute 24-h time point post-SCI) was compared with lesional hemoglobin and extravasated Evans blue dye measured spectrophotometrically. The anatomy of hemorrhage was comparatively assessed using VHRUS and histology. Time-lapse videos demonstrated the evolution of parenchymal hemorrhage. VHRUS accurately depicted the structural (gray and white matter) and vascular anatomy of the spinal cord (after laminectomy) and was safely repeated in the same animal. After SCI, a hyperechoic signal extended from the lesion epicenter. Significant correlations were found between VHRUS signal and hemorrhage in the acute (r=0.88, p<0.0001) and subacute (r=0.85, p<0.0001) phases and extravasated Evans blue (a measure of vascular disruption) in the subacute phase (r=0.94, p<0.0001). Time-lapse videos demonstrated that the expanding parenchymal hemorrhage is preceded by new perilesional hemorrhagic foci. VHRUS enables real-time quantitative live anatomical imaging of acute and subacute vascular disruption after SCI in rats. This technique has important scientific and clinical translational applications.
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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 | 0.001 | 0.001 |
| 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".