Assessment and validation of proposed classification tools for brainstem cavernous malformations

Area of Science:

• Neurosurgery
• Neurology
• Medical Imaging

Background:

• Brainstem cavernous malformations (BSCMs) present complex treatment challenges, with surgical indications often debated.
• Existing classification systems aim to identify surgical candidates for BSCMs, but their validation is crucial.
• The Lawton-Garcia (LG) and Dammann-Sure (DS) grading systems have been proposed to stratify BSCM patients.

Purpose of the Study:

• To validate the performance and replicability of the Lawton-Garcia (LG) and Dammann-Sure (DS) grading systems for BSCMs.
• To assess the ability of these systems to predict neurological outcomes following surgical intervention for BSCMs.

Main Methods:

• A cross-sectional study analyzed 67 patients surgically treated for BSCMs between 2003 and 2019.
• Inclusion required complete clinical records, preoperative contrast-enhanced MRI, and ≥ 6 months postoperative follow-up.
• Three independent observers scored each patient using the LG and DS systems; neurological function was assessed using the modified Rankin Scale (mRS).

Main Results:

• Multiple bleedings, lesion diameter > 20 mm, and patient age > 50 years predicted unfavorable outcomes.
• Both LG (AUC = 0.72) and DS (AUC = 0.78) scores demonstrated robust predictive capability for patient outcomes.
• The combined application of LG and DS scores significantly enhanced predictive performance (OR 22.5, p = 0.001).

Conclusions:

• Current classification systems, including LG and DS, are valuable tools for estimating neurological outcomes post-BSCM surgery.
• Further research is warranted to develop an advanced scoring system integrating elements from both LG and DS scales.
• These validated grading systems can aid in surgical decision-making and prognostication for brainstem cavernous malformation patients.