Preoperative flow analysis of arteriovenous malformations and obliteration response after stereotactic radiosurgery.

Gamma Knife radiosurgery angioarchitecture digital subtraction angiography intracranial arteriovenous malformations obliteration rate stereotactic radiosurgery vascular disorders

Journal

Journal of neurosurgery
ISSN: 1933-0693
Titre abrégé: J Neurosurg
Pays: United States
ID NLM: 0253357

Informations de publication

Date de publication:
01 04 2023
Historique:
received: 29 04 2022
accepted: 11 07 2022
medline: 4 4 2023
pubmed: 4 9 2022
entrez: 3 9 2022
Statut: epublish

Résumé

Morphological and angioarchitectural features of cerebral arteriovenous malformations (AVMs) have been widely described and associated with outcomes; however, few studies have conducted a quantitative analysis of AVM flow. The authors examined brain AVM flow and transit time on angiograms using direct visual analysis and a computer-based method and correlated these factors with the obliteration response after Gamma Knife radiosurgery. A retrospective analysis was conducted at a single institution using a prospective registry of patients managed from January 2013 to December 2019: 71 patients were analyzed using a visual method of flow determination and 38 were analyzed using a computer-based method. After comparison and validation of the two methods, obliteration response was correlated to flow analysis, demographic, angioarchitectural, and dosimetric data. The mean AVM volume was 3.84 cm3 (range 0.64-19.8 cm3), 32 AVMs (45%) were in critical functional locations, and the mean margin radiosurgical dose was 18.8 Gy (range 16-22 Gy). Twenty-seven AVMs (38%) were classified as high flow, 37 (52%) as moderate flow, and 7 (10%) as low flow. Complete obliteration was achieved in 44 patients (62%) at the time of the study; the mean time to obliteration was 28 months for low-flow, 34 months for moderate-flow, and 47 months for high-flow AVMs. Univariate and multivariate analyses of factors predicting obliteration included AVM nidus volume, age, and flow. Adverse radiation effects were identified in 5 patients (7%), and 67 patients (94%) remained free of any functional deterioration during follow-up. AVM flow analysis and categorization in terms of transit time are useful predictors of the probability of and the time to obliteration. The authors believe that a more quantitative understanding of flow can help to guide stereotactic radiosurgery treatment and set accurate outcome expectations.

Identifiants

pubmed: 36057117
doi: 10.3171/2022.7.JNS221008
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

944-954

Commentaires et corrections

Type : CommentIn

Auteurs

Juan Diego Alzate (JD)

Departments of1Neurological Surgery.

Assaf Berger (A)

Departments of1Neurological Surgery.

Kenneth Bernstein (K)

Departments of1Neurological Surgery.

Reed Mullen (R)

Departments of1Neurological Surgery.

Tanxia Qu (T)

Departments of1Neurological Surgery.

Joshua S Silverman (JS)

2Radiation Oncology, and.

Maksim Shapiro (M)

3Interventional Neuroradiology, NYU Langone Health, New York University, New York, New York.

Peter K Nelson (PK)

3Interventional Neuroradiology, NYU Langone Health, New York University, New York, New York.

Eytan Raz (E)

3Interventional Neuroradiology, NYU Langone Health, New York University, New York, New York.

Jafar J Jafar (JJ)

Departments of1Neurological Surgery.

Howard A Riina (HA)

Departments of1Neurological Surgery.

Douglas Kondziolka (D)

Departments of1Neurological Surgery.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH