Relative Recirculation
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».