MONITORING OF CEMENT DISTRIBUTION IN VERTEBRAL BODIES DURING VERTEBROPLASTY
Notice bibliographique
Résumé
Summary Time-lapsed CT offers new opportunities to predict the risk of cement leakage and to evaluate the mechanical effects on a vertebral body by monitoring each incremental injection step in an in-vitro vertebroplasty procedure. Introduction Vertebroplasty has been shown to reinforce weak vertebral bodies and to prophylactically reduce fracture risks. However, bone cement leakage is a major vertebroplasty related problem which can cause severe complications. Leakage risk can be minimised by injecting less cement into the vertebral body, inevitably compromising the mechanical properties of the augmented bone, as a proper endplate-to-endplate connection of the injected cement is needed to obtain a mechanical benefit. Thus the cement flow in a vertebroplasty procedure requires a better understanding. This study aimed at developing a method to monitor the cement flow in a vertebral body and its mechanical effect. Materials and Methods Eight fresh frozen human cadaveric vertebrae were prepared for augmentation by performing a bitrans- or bipedicular approach. Following they were XTremeCT-scanned (Scanco, Switzerland) at a nominal resolution of 82µm. A custom made setup enabled to fix the vertebrae in the CT bore (Siemens Emotion6) centrically. Bone cement (Vertecem V+, Synthes GmbH, Switzerland) was injected monopedicularly via a syringe driver (Harvard Apparatus, USA). Injection forces were recorded through a load cell (Type 9211, Kistler Instrumente AG, Switzerland) placed on the driver. Either a custom PEEK cannula or a trocar was inserted into each pedicle of a vertebra to allow artifact-free CT scanning. After each milliliter of injection a CT scan of the vertebra was performed at a nominal resolution of 0.63mm. Subsequently, the CT images were resampled to the original XTremeCT image and the cement cloud was segmented. The image data were then further processed for micro finite element (microFE) modeling (FAIM, Numerics88, Canada). The models were then solved for axial stiffness and Von Mises Stress (VMS) distribution. Finally, the vertebrae underwent a biomechanical quasistatic axial compression test (Mini Bionix II 858, MTS Systems Corp., USA). Results Endplate-to-endplate connection of the cement was reached in 4 vertebrae. The average volume needed to reach the connection was 5.0±1.2 ml. Cement leakage occurred in all vertebrae, whereby in 4 cases the cement leaked into the spine channel. Each successive cement injection step was characterised with an increase of peak injection forces (16.5±12.7N at 1ml to 70.82±21.14N at 6ml). With respect to axial stiffness the mechanical tests and the microFE models correlated well (R 2 = 0.778). Analyzing the top 100 VMS an elevated stress concentration between the endplate and the cement was observed unless the endplate was in direct contact with the cement. Conclusion Cement flow can be monitored precisely at each injection step using the time-lapsed CT approach. Combined with microFE modeling the mechanical properties of the augmented bone can be evaluated for different incremental cement volumes injected. Our results suggest augmenting the bone until an endplate-to-endplate connection is established as otherwise partial filling would increase the risk of failure in the trabecular bone structure. This is in close agreement to other studies.
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 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) | 0,001 | 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 ».