MedElevator Войти в исследования
← Поиск публикаций

DOI 10.1016/j.wneu.2022.07.149

Медицинская библиотека · World neurosurgery · 2022

Surgical Resection of a Sylvian Arteriovenous Malformation.

Dellaretti Marcos, Ronconi Daniel, Melo Matheus

Video-Audio MediaСтатьяПеревод в очереди

Аннотация

Sylvian arteriovenous malformations (sAVMs) are rare and account for approximately 8%-11% of all intracranial arteriovenous malformations (AVMs).1 Because of their proximity to eloquent structures such as the motor speech center, insular cortex, and internal capsule, microsurgical resection of sAVMs remains a challenge. Several classifications have already been suggested for sAVMs, such as Sugita and Yasargil.1,2 It is well established that for low-grade AVMs, results of the microsurgical resection are excellent and tend to favor surgery,1-3 but in high-grade AVM, a multimodal assessment is necessary for formulating treatment strategies.1 In Video 1, we demonstrate the surgical resection of a ruptured sylvian temporal AVM. This AVM was localized in the superior surface of the temporal lobe, and its nidus was just beneath the cortical surface of this lobe. Because it was 5.1 cm at its largest diameter, had a deep drainage vein, and was localized adjacent to the Wernicke area, we classified it as a Spetzler-Martin grade IV AVM.4 Despite the high-grade AVM, microsurgical treatment was the choice in this ruptured AVM and there was no increase in morbidity.

Для цитирования: Dellaretti Marcos, Ronconi Daniel, Melo Matheus. Surgical Resection of a Sylvian Arteriovenous Malformation.. World neurosurgery. 2022. DOI: 10.1016/j.wneu.2022.07.149.

Предметные рубрики MeSH

Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…

История · было → стало

Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.

Тип публикации указан по данным источника. Уровень доказательности автоматически не присваивается.