Recombinant Tissue Plasminogen Activator Increases Blood-Brain Barrier Disruption in Acute Ischemic Stroke: An MR Imaging Permeability Study
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Although thrombolytic therapy (recombinant tissue plasminogen activator [rtPA]) represents an important step forward in acute ischemic stroke (AIS) management, there is a clear need to identify high-risk patients. The purpose of this study was to investigate the role of quantitative permeability (KPS) MR imaging in patients with AIS treated with and without rtPA. We hypothesized that rtPA would increase KPS and that KPS MR imaging can be used to predict the risk of hemorrhagic transformation (HT). MATERIALS AND METHODS: Thirty-six patients with AIS were examined within a mean of 3.6 hours of documented symptom onset. KPS MR imaging was performed as part of our AIS protocol. KPS coefficients in the stroke lesion were estimated for all patients, and the relationship between KPS and both HT and rtPA was investigated by using Student t tests. Receiver operating characteristic (ROC) curves were computed for predicting HT from KPS. RESULTS: The occurrence rate of HT for patients who received rtPA and those who did not was 43% and 37%, respectively. Assessment of KPS in the lesion revealed significant differences between those who hemorrhaged and those who did not (P < .0001) as well as between rtPA-treated and untreated patients (P = .008). ROC analysis indicated a KPS threshold of 0.67 mL/100 g/min, with a sensitivity of 92% and a specificity of 78%. CONCLUSIONS: The results of this study indicate that KPS is able to identify patients at higher risk of HT and may allow use of physiologic imaging rather than time from onset of symptoms to guide treatment decision.
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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) | 0.001 | 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 | 0.001 |
| 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".