Spontaneous Regression of Vestibular Schwannomas: A Clinical And Radiographic Assessment
Notice bibliographique
Résumé
Background: Vestibular schwannomas (VSs) are benign nerve sheath tumors that arise from the vestibulocochlear nerve within the internal auditory canal (IAC) and extend into the cerebellopontine angle (CPA). It is the most common tumor of the CPA with an annual incidence of 17.4/1 million. They typically demonstrate slow growth over time and as such, observation is a reasonable approach to management. A portion of these tumor remains static and approximately 5 to 10% of these tumors will demonstrate spontaneous regression while under observation, including those associated with neurofibromatosis type 2. The standard treatment for symptomatic or growing lesions is surgical resection followed by radiation for residual tumor or reoccurrence; however, management recommendations encourage tailoring care to each patient and tumor individually. Several previous case series have attempted to identify predictive factors for tumor growth and regression, but few have reached significance or demonstrated reproducible findings. If factors were identified that could predict tumor growth one could intervene at an earlier stage of the disease. One meta-analysis conducted on growing tumors identified that size at diagnosis was the only predictive factor that reached significance. In a similar vein, defining factors that reliably predict spontaneous regression could prevent unnecessary intervention. As per our review of the literature, no patient characteristics have yet predicted spontaneous regression to date. Imaging characteristics including a festooned aspect of the tumor and the presence of cerebrospinal fluid in the IAC have been identified as predictive for tumor regression in small case series ( N = 13–14). Methods: Using a clinical database of VS treated by one team at our institution, we identified 40 patients who have demonstrated significant spontaneous regression or complete resolution of their VS. All patients received a survey by mail and telephone. For all patients who consented to participate, radiographic and clinical data was collected from patient charts in addition to survey responses. Medical comorbidities and medications provided through patient questionnaire were corroborated with patient charts. Tumor volume was approximated using the formula V = 4/3 × π × length/2 × width/2 × height/2 and nominal logistic regression was completed using JMPv17 with 50% tumor reduction as the reference value. Results: Ten patients were included in the final descriptive summary of this patient population. Tumors were generally small, left sided (8/10), with a fungated shape (6/10) and at least partial preservation of CSF in the IAC (8/10). Significant decrease in tumor volume was an inclusion criterion; however, no patient factors or radio graphic factors appeared to predict the degree of tumor regression. Conclusion: In conclusion, this is the first study to consider patient lifestyle factors obtained through patient survey in addition to clinical and radiographic findings to describe spontaneous regression of VS. Although there was perhaps a higher-than-average rate of herpes/varicella in this population, no clinical factors were found to be predictive on analysis. Additionally, no radiographic factors appear to be protective including those previously demonstrated to be protective, such as CSF preservation in the IAC and IAC extension. Publication History Article published online: 07 February 2025 © 2025. Thieme. All rights reserved. Georg Thieme Verlag KG Oswald-Hesse-Straße 50, 70469 Stuttgart, Germany
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 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».