Technique for targeting arteriovenous malformations using frameless image-guided robotic radiosurgery.

Area of Science:

• Neurosurgery
• Medical Imaging
• Radiation Oncology

Background:

• Arteriovenous malformations (AVMs) require precise targeting for effective radiosurgery.
• Integrating advanced imaging techniques can enhance treatment accuracy and patient outcomes.
• Current methods may have limitations in precise AVM nidus localization.

Purpose of the Study:

• To develop and validate a novel targeting methodology for robotic radiosurgery of AVMs.
• To integrate three-dimensional (3D) digital rotation angiography (DRA) with two-dimensional (2D) digital subtraction angiography (DSA).
• To enable comprehensive image-guided robotic radiosurgery for AVMs.

Main Methods:

• Evaluated DRA geometric integrity using a phantom with embedded markers.
• Configured dedicated DSA acquisition modes and determined the geometric reproducibility of C-arm presets.
• Developed software for 2D-3D image registration to correct for C-arm misalignments and patient motion.

Main Results:

• DRA spatial distortions were consistently below 0.3 mm within the imaging volume.
• 2D-3D image registration reduced localization uncertainties to approximately 0.2 mm.
• Achieved an overall system-related localization uncertainty of 0.4 mm in the DRA coordinate space.

Conclusions:

• Integrating DRA and DSA enhances confidence in image-guided radiosurgical ablation of AVMs.
• This approach can improve patient comfort and reduce procedural time pressures.
• The technique may potentially decrease the number of cerebral angiograms required per patient.