Relative Recirculation
Bibliographic record
Abstract
OBJECTIVES: To retrospectively evaluate the prognostic performance of a dynamic susceptibility contrast (DSC) MRI metric for permeability (relative recirculation or rR) for the prediction of hemorrhagic transformation (HT) in patients with acute ischemic stroke (AIS). To compare rR with dynamic contrast-enhanced (DCE) MRI estimates of blood-brain barrier permeability (KPS). MATERIALS AND METHODS: Data obtained from 26 patients (age: 27-89 years) with a working diagnosis of AIS were examined retrospectively. Patients were examined within a mean of 3.5 hours of symptom onset. Eleven patients received intravenous recombinant tissue-plasminogen activator (rt-PA). HT was determined by follow-up computed tomography and/or magnetic resonance imaging 24 to 72 hours after initial imaging. Permeability (DCE) always preceded DSC imaging and consisted of a 3D gradient-recalled echo scan acquired in 4 minutes 48 s. DSC imaging consisted of a T2*-weighted single shot EPI scan acquired in 43 to 86 seconds. Gadodiamide (0.1 mmol/kg) was injected as a bolus for each scan. Permeability (KPS) and rR were calculated offline for regions of interest (ROI) defined within the core of the infarct, as well as within the homologous location in the contralateral hemisphere. The relationship between KPS and rR was investigated using linear regression and receiver operating characteristic (ROC) curves were computed for predicting HT from either rR or KPS. RESULTS: Eleven patients proceeded to HT (including 5 treated with rt-PA). Mean KPS values were significantly elevated in infarct relative to contralateral areas (0.84 +/- 0.57 vs. 0.42 +/- 0.34 mL/100 g/min; P = 0.0003). For infarct ROIs, KPS values were significantly greater in patients with HT compared with non-HT patients (1.25 +/- 0.63 vs. 0.53 +/- 0.23 mL/100 g/min; P = 0.0015). KPS values were higher in patients who received rt-PA than in untreated patients (1.09 +/- 0.61 vs. 0.65 +/- 0.47 mL/100 g/min; P = 0.0497). ROC analysis indicated a KPS threshold value of 0.67 mL/100 g/min for providing an optimal sensitivity and specificity for predicting HT of 91% and 80%, respectively. Mean rR values for infarct ROIs were significantly higher than those determined for contralateral regions (0.17 +/- 0.06 vs. 0.09 +/- 0.03; P < 0.0001). The mean rR for the HT group was significantly greater than for the non-HT group (0.22 +/- 0.05 vs. 0.14 +/- 0.05; P = 0.0002). As with KPS, the mean rR for patients who were treated with rt-PA was significantly greater than for untreated patients (0.21 +/- 0.07 vs. 0.15 +/- 0.05; P = 0.0112). ROC analysis indicated a threshold value of 0.17 for providing optimal sensitivity and specificity for predicting HT of 91% and 87%, respectively. There was a significant correlation between rR and KPS for infarct ROIs (r = 0.67; P < 0.001). CONCLUSIONS: Both KPS and rR are significantly elevated in infarcted, relative to uninfarcted tissue in the same AIS patient. Both parameters were also significantly elevated in HT, relative to non-HT infarcts. The strong correlation between rR and KPS, coupled with the high sensitivity and specificity of rR for the prediction of HT suggest that rR is related to blood-brain barrier integrity in AIS and may prove valuable in the prediction of HT.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".