Assker Mohamad M, Youssef Ahmed M, Mohammed Saeed A S, Akar Noor M, Hashim Mohammed A, Kadhim Narjis, Al-Saadi Noor, Algabri Mostafa H, Shukur Mustafa J, Ismail Mustafa, Muthana Ahmed, Hoz Samer S
Department of Radiology, Sheikh Khalifa Medical City, Abu Dhabi, United Arab Emirates.
Department of Education, Al Qassimi Hospital, Sharjah, United Arab Emirates.
Surg Neurol Int. 2025 May 9;16:173. doi: 10.25259/SNI_140_2025. eCollection 2025.
Arteriovenous malformations (AVMs) are complex vascular anomalies requiring classification systems to guide treatment and predict outcomes. This review evaluates multiple AVM classification systems, including the widely used Spetzler-Martin Grading System (SMGS), emphasizing their importance in neurosurgery for improving clinical decision-making and communication.
We conducted a literature search using Google Scholar, PubMed, and Scopus to gather information on AVM classification systems. Our inclusion criteria involved articles that referenced a well-established classification system with at least two components. Radiological, surgical, and clinical outcomes systematically categorized nine distinct AVM grading systems. The review focuses on comparing the advantages and limitations of different AVM classification systems to the SMGS.
A review of 33 articles highlights the evolution of AVM classification systems, with the SMGS as a foundation for surgical outcomes. Systems such as the Pollock-Flickinger and Pittsburgh AVM scale improve radiosurgery predictions, while Lawton-Young adds factors for surgical precision. Specialized scores refine grading for specific cases, and simplified systems like Spetzler-Ponce enhance usability in unique contexts.
AVM classification systems, including Spetzler-Martin, Pollock-Flickinger, and Lawton-Young, provide critical insights into treatment and prognosis. While Spetzler-Martin effectively predicts surgical outcomes, systems like Lawton-Young enhance accuracy by incorporating additional factors but may face challenges in clinical application due to complexity. Continued refinement and validation are essential to improve predictive accuracy, optimize patient care, and connect research with clinical practice.
动静脉畸形（AVM）是复杂的血管异常，需要分类系统来指导治疗并预测预后。本综述评估了多种AVM分类系统，包括广泛使用的斯佩茨勒-马丁分级系统（SMGS），强调了它们在神经外科手术中对改善临床决策和沟通的重要性。
我们使用谷歌学术、PubMed和Scopus进行文献检索，以收集有关AVM分类系统的信息。我们的纳入标准包括引用了一个成熟的、至少有两个组成部分的分类系统的文章。放射学、手术和临床结果系统地对九个不同的AVM分级系统进行了分类。本综述重点比较了不同AVM分类系统与SMGS的优缺点。
对33篇文章的综述突出了AVM分类系统的演变，其中SMGS是手术结果的基础。波洛克-弗利金格和匹兹堡AVM量表等系统改善了放射外科手术的预测，而劳顿-杨增加了手术精度的因素。专门的评分细化了特定病例的分级，斯佩茨勒-庞塞等简化系统在特定情况下提高了可用性。
包括斯佩茨勒-马丁、波洛克-弗利金格和劳顿-杨在内的AVM分类系统为治疗和预后提供了关键见解。虽然斯佩茨勒-马丁有效地预测了手术结果，但劳顿-杨等系统通过纳入其他因素提高了准确性，但由于复杂性，在临床应用中可能面临挑战。持续的改进和验证对于提高预测准确性、优化患者护理以及将研究与临床实践联系起来至关重要。
