Defining non-contrast CT markers of the ischaemic penumbra in acute stroke
Notice bibliographique
Résumé
Background and purpose: Isodense swelling is a known early ischaemic change, and it is most likely to represent penumbra tissue on acute non-contrast computed tomography (NCCT) scan. However, in general, its detection by observers showed very poor interobserver agreement, which has been attributed to a lack of defining criteria that differentiate it from hypodensity. The aim of this study is to assess the reliability of detecting isodense swelling within the first six hours post stroke onset. Methods: A three-stage study was designed to test the effect of defining criteria and training on the reliability of detection of isodense swelling on acute NCCT. NCCT and perfusion computed tomography (PCT) scans of patients with acute stroke of less than six hours’ duration were reviewed retrospectively. A web-based tool was used to present NCCT scans to readers of different backgrounds (expert and trainee stroke neurologists and neuroradiologists), who evaluated the scans independently by the Alberta Stroke Program Early CT Score (ASPECTS). In the pre-training stage, nine readers assessed 19 repeated scans (a total of 40 scans) obtained at different slice thicknesses (0.9 mm and 5 mm) and both with and without clinical information. In the consensus stage, definitions for isodense swelling and hypodensity were extracted from simultaneous analysis of NCCT and PCT scans used in the pre-training stage, and potential definitions were circulated to participants for agreement. In the post-training stage, 11 readers assessed 32 scans (5 mm slice thickness) with clinical data after training using the consensus definitions and reviewing examples. Cerebral blood volume (CBV), cerebral blood flow (CBF) and mean transient time (MTT) in each ASPECTS region on all PCT scans were calculated and compared across the three NCCT appearances (normal, hypodense or isodense swelling, and the fate of each ASPECTS region was determined on follow-up NCCT scans. Results: Training increased detection of isodense swelling from 29.4% to 46.8%; significantly (P = 0.0001) improved interobserver agreement from very poor (k = 0.09) to fair (k = 0.30); and ameliorated the predictive power of isodense swelling for penumbra as classified by ASPECTS regions of interest (ROIs) from [sensitivity 9% (confidence interval (CI): 1.9%–24.3%); likelihood ratios positive and negative, 2.5 (CI: 0.6–10) and 0.95 (CI: 0.84–1.06), respectively] to [sensitivity 41% (CI: 30.3%–52.8%); likelihood ratios positive and negative, 5.5 (CI: 3.3–11) and 0.64 (CI: 0.53–0.77), respectively]. Detection of hypodensity did not change significantly with training. Exclusion of outliers improved interobserver agreement for isodense swelling to moderate (k = 0.50). Experience, speciality and clinical information had no significant effect on agreement; however, 5 mm slices increased interobserver agreement on hypodensity significantly (k = 0.34 to k = 0.46, P = 0.01). Intraobserver agreement on both hypodensity and isodense swelling was almost perfect. Hypodensity had low sensitivity for core (41.6% (CI: 33% - 50.7%)) but good likelihood ratios positive and negative (13.7 (CI: 7.5–24.8) and 0.6 (CI: 0.50–0.70), respectively). Both isodense swelling and hypodensity were highly specific (93.8% and 96.9% for penumbra and core, respectively). CBV was increased significantly in isodense swollen areas compared with hypodense areas (P < 0.05). Only 38.3% of isodense swollen ROIs ended in infarction and absence of recanalisation increased odds of infarction four-fold, whereas 90% of hypodense ROIs infarcted with odds of infarction 11 times greater than those of ROIs with isodense swelling. Conclusion: Penumbral tissue in acute stroke patients appears on NCCT as isodense swollen areas that are distinguishable from hypodense regions’ appearance. The detection of penumbral tissue can be improved significantly by training. Isodense swelling most frequently returns normal, particularly in evident recanalisation, and its prognostic value might differ from that of hypodensity.
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 | 0,006 | 0,025 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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 ».