Computed Tomography in the Assessment of Periacetabular Osteolysis
Notice bibliographique
Résumé
BACKGROUND: Computed tomography recently has been proposed as an accurate method for diagnosing periacetabular osteolytic lesions. Several investigators have attempted to validate the accuracy of this technique, but they employed cadaveric and animal models, which cannot replicate the adaptive changes that occur over time in vivo. This study was performed to determine the accuracy of computed tomography in identifying and measuring periacetabular osteolytic lesions in hemipelves retrieved at autopsies of individuals with a previously well-functioning total hip prosthesis. METHODS: We evaluated nine hemipelves, retrieved at autopsy, that contained a cementless porous-coated acetabular component. The fresh specimens were examined with conventional radiographs and computed tomography and then were embedded and sectioned into 1.5-mm slices for evaluation with slab radiographs. Anteroposterior and iliac oblique plain radiographs as well as axial, coronal, and sagittal computed tomography scans were reviewed to determine the presence and location of any periacetabular osteolytic lesions. These results were then compared with those identified on the slab radiographs. Lesion volume was calculated from computed tomography scans with use of post-processing software. RESULTS: A total of twenty-three periacetabular osteolytic lesions were identified on the slab radiographs of the nine hemipelves. The plain radiographs identified twelve (52%) of the twenty-three lesions, and the computed tomography scans identified twenty (87%) of the twenty-three lesions. Three medial wall perforations were identified on the computed tomography scans but were not detected on the plain radiographs. Computed tomography was accurate in measuring the volume of the osteolytic lesions (r(2) = 0.997) but tended to overestimate the volumes measured on the slab radiographs. Periacetabular osteolytic lesions appeared on the computed tomography scans and slab radiographs as areas devoid of trabecular bone that were delineated by a sclerotic border and communicated with the joint space. CONCLUSIONS: In this autopsy model, computed tomography was an accurate method for detecting the location and measuring the volume of periacetabular osteolytic lesions.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».