Susceptibility Weighted Imaging in Acute Stroke with Co-morbids: Magnetic Resonance Imaging Protocol Revisited
Bibliographic record
Abstract
Introduction: We aim to investigate ischemic penumbra using Diffusion weighted imaging- Susceptibility weighted imaging mismatch using DWI Alberta Stroke Program Early Computed tomography Stroke Score scoring in patients with multiple co morbid.
 Methods: From January 2011 to December, 2017; 70 consecutive patients (50 men, 20 women; mean age 64.5; range 45-82 years) with acute infarct on Diffusion weighted imaging (DWI) were selected for the study. Stroke protocol performed including DWI and susceptibility weighted imaging (SWI) on first day and repeat within three days. All initial MR images were interpreted by one Neuroradiologist with more than ten years blind to the clinical findings of each patient. The definition of an acute infarct area was high signal intensity on DWI with dark signal intensity on Apparent diffusion weighted imaging (ADC). The infarct extent was scored using the Alberta Stroke Program Early CT Score (ASPECTS) system. Infarct growth was defined as any new or larger lesion on the second DWI.
 For correlation with infarct growth, the same topographic system was used to record the extent of the Prominent vessel sign (PVS) on SWI.
 Spearman’s rank correlation test was used to examine the correlations between PVS score and infarct growth score. Regression was computed, with P<0.05 considered significant.
 Results: The study included 12 women and 10 men, (mean age 67.1 years).
 MRI images were initially acquired as stroke protocol (mean 12 hours) in acute stage and the next MRI was done within 3 days after the acute stage.
 9 patients had right sided and 13 patients had left sided MCA territory infarct, the mean DWI-ASPECTS score was 4.3 (range 0–9). PVS was detected in 15 patients (mean score 4.1, range 0–10).
 Out of 22 patients 9 patients showed no evolution in infarct however in 13 patients evolution was from (ASPECTS mean score 3.95, range 0–9; mean infarct growth score 7.4, range 0–10).
 7 patients devoid of PVS in initial MRI, did not exhibited evolution of infarction. Of 15 patients with PVS on initial MRI, 13 (87%) had infarct growth. Correlation between the evolution in infarct size and PVS score was observed (r = 0.86, P<0.001).
 Conclusion: PVS seen in infarcted territory is related to poor prognosis and this can be reliably used as a surrogate marker of oxygen extraction in penumbra.
 SWI can predict tissue at risk and can be a replacement for perfusion scan in clinical scenerio of acute ischaemic infarct.
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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 | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".