# The Role of Angiographic Imaging in the Treatment of Spinal Vascular Malformations

## TL;DR

This review discusses how angiographic imaging helps diagnose and treat spinal vascular malformations, highlighting the strengths and limitations of various imaging techniques.

## Contribution

The paper provides a comprehensive analysis of angiographic imaging techniques for spinal vascular malformations and outlines future directions for improving diagnostic and therapeutic approaches.

## Key findings

- 2D DSA is the gold standard for intraoperative spinal vascular malformation imaging due to its high resolution and real-time capabilities.
- ICG–VAG serves as a non-ionizing complementary tool for intraoperative visualization but has limitations in field of view and quantitative analysis.
- Emerging technologies like AI-driven imaging and patient-specific modeling are expected to improve outcomes for SVM treatment.

## Abstract

Spinal vascular malformations (SVMs) are rare and heterogeneous lesions that may lead to progressive neurological decline or hemorrhage, posing significant challenges for management due to their complex angioarchitecture and proximity to critical neural structures. This review examines the role of angiographic imaging modalities used intraoperatively and postoperatively in guiding treatment, confirming therapeutic success, and informing follow-up strategies. We summarize evidence on two-dimensional digital subtraction angiography (2D DSA), indocyanine green videoangiography (ICG–VAG), and emerging adjunctive techniques. 2D DSA remains the reference standard, offering superior temporal and spatial resolution for real-time visualization of vascular anatomy, catheter navigation, and embolic delivery, though its invasive nature, radiation exposure, and two-dimensional projection limit long-term applicability. ICG–VAG provides a complementary, non-ionizing method for intraoperative fluorescence imaging, aiding in shunt localization and venous preservation, although its restricted field of view and limited capacity for quantitative analysis reduce its standalone value. Advances in quantitative angiographic metrics, patient-specific hemodynamic modeling, and artificial intelligence-driven image analysis are anticipated to enhance diagnostic accuracy and reproducibility. The development of standardized multimodal protocols will be crucial for optimizing patient-centered treatment of these complex and rare lesions.