Post-Treatment Imaging Appearances Following Skull Base Therapy
Notice bibliographique
Résumé
Background and Purpose: Skull base tumors are notoriously difficult to treat due to the inherent high risk of complications from a large number of neurovascular structures within an anatomically dense area. In the management of skull base lesions, craniofacial and endonasal approaches have become viable options either in conjunction or in isolation. However, accurate postoperative imaging remains an issue due to changes in anatomy from surgical defects, reconstructions, or any grafts. Hence a solid fundamental understanding of anticipated postoperative imaging features and expected deviations become crucial for subsequent imaging surveillance. Materials and Methods: We present a review of the imaging features involved in diagnosis and treatment surveillance for skull base tumors. Results: Each imaging modality has a unique range of practical applications. CT is often utilized for good soft tissue resolution, excellent assessment of bone, detection of cervical adenopathy, and rapid image acquisition for patients who are medically unstable or unable to maintain a still supine position. Similarly, magnetic resonance imaging (MRI) provides greater soft tissue resolution and is the modality of choice when investigating dural invasion or perineural spread. Diffusion weighted imaging (DWI) MRI is an adjunct to CT and/or MRI in the early post-treatment period to elucidate tumor recurrence from normal expected changes. FDG PET/CT has limited utility in the immediate 12 week post-treatment phase due to the higher likelihood of false positive and negatives from inflammation and vascular compromise respectively. The ability to detect asymptomatic recurrence is illustrated by frontal lobe edema and differentiation of recurrent or residual tumors from retained secretions for MRI of craniofacial resections, defect obliteration and gliosis in the adjacent cerebellar brain parenchymal from MRI of transpetrous approaches, and hypointense facial nerve visualization on T2-weighted MRI. On CT imaging, the tumor presents with similar attenuation to skeletal muscle and differentiation from granulation tissue is difficult. Thus any mass originating in the primary tumor bed, particularly those with progressive enlargement from serial imaging, should raise suspicion of recurrence. Following skull base reconstruction, the majority of postoperative complications occur acutely in the immediate period, including seroma/fluid retention, fistula formation, infection/abscess and flap necrosis. For fluid collections CSF leaks and chylous fistulas are the primary concern. On CT and MR imaging, particularly in the inferior lower left neck, a peripherally enhancing fluid collection may represent a chylous leak, a hematoma, an abscess or a seroma. MR is indicated in situations where fluid or soft tissue is subjacent to a bony defect it cannot be reliably distinguished or identified on CT, thus T2 weighted imaging complimented by fast imaging employing steady-state acquisition (FIESTA) sequence allows differentiation of herniation contents. Conclusion: Knowledge of the expected appearance following open and endoscopic surgical reconstruction, as well as radiation therapy, is necessary to successfully delineate complications and recurrences. An understanding of the latencies involving tumor recurrence and early versus late complications can be aligned with the clinical context to formulate a logical approach to equivocal findings.
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 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,002 |
| 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 ».