Multiple Hypointense Vessels on Susceptibility-Weighted Imaging in Acute Ischemic Stroke: Surrogate Marker of Oxygen Extraction Fraction in Penumbra?
Bibliographic record
Abstract
BACKGROUND: Multiple hypointense vessels (MHV) on susceptibility-weighted imaging (SWI) are frequently observed in patients with acute cerebral ischemia, but their implication has not been clearly established. To elucidate the clinical significance of MHV on SWI, we investigated the association of MHV on SWI with clinical data and other MR markers in patients with acute ischemic stroke. METHODS: We enrolled acute stroke patients with internal carotid or proximal middle cerebral artery occlusion who underwent MRI including SWI within 3 days from stroke onset. Baseline clinical data were reviewed. Stroke severity was measured by the National Institutes of Health Stroke Scale (NIHSS). We graded the degree of MHV on SWI as four groups of none, subtle, relative, or extensive by the modified Alberta Stroke Program Early CT Scan (ASPECTS) system. To evaluate the degree of collateral flow, distal hyperintense vessels (DHV) on FLAIR and vessels on post-contrast time-of-flight MR angiography (TOF MRA) source images were graded respectively as 3 groups: none/subtle/prominent and poor/moderate/good. Diffusion and perfusion lesion volume and diffusion-perfusion mismatch (DPM) ratio were measured in all patients. We analyzed the association of the degree of MHV on SWI with clinical data and MR markers. RESULTS: Eighty patients were included in the study. The mean MR time from stroke onset was 12.4 h (range 0.5-63.0). There is no difference in MR time from stroke onset between groups of MHV on SWI. MHV were observed in 68 (85%) of 80 patients: none in 12, subtle in 11, relative in 13, and extensive in 44. There were no statistically significant associations between MHV on SWI and vascular risk factors. Patients with more extensive MHV on SWI had a smaller diffusion volume (p < 0.001), larger DPM (p < 0.001), and lower initial NIHSS scores (p = 0.022). Prominent DHV was presented in 29 of 44 patients with extensive MHV (p < 0.001). Good collateral flow on TOF MRA source images was presented in 37 of 44 patients with extensive MHV (p < 0.001). CONCLUSIONS: More extensive MHV on SWI in acute ischemic stroke is associated with lower initial NIHSS scores, smaller diffusion lesion volume, better collateral flow, and larger DPM. Our results show the possibility that MHV on SWI may be a useful surrogate marker for predicting increased oxygen extraction fraction and diffusion-perfusion mismatch in acute ischemic hemisphere.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".