Improved quantification of tumor adhesion in meningiomas using MR elastography-based slip interface imaging

Area of Science:

• Neurosurgery
• Radiology
• Medical Imaging

Background:

• Meningiomas, common intracranial tumors, often adhere to surrounding tissues, complicating surgical resection and increasing postoperative risks.
• Accurate assessment of tumor-brain adhesion is crucial for surgical planning and predicting outcomes.
• Existing slip interface imaging (SII) techniques using MR elastography (MRE) show potential but require refinement.

Purpose of the Study:

• To develop and validate an improved SII algorithm for precise quantification of meningioma-brain adhesion.
• To assess the correlation between MRE-derived adhesion patterns and meningioma recurrence.
• To enhance clinical decision-making in meningioma management.

Main Methods:

• Developed and tested an improved SII algorithm based on normalized octahedral shear strain (NOSS) patterns from MRE in 52 meningioma patients.
• Quantified tumor interface adhesion degrees (complete, partial, non-adherent).
• Utilized statistical analysis, including Area Under the Curve (AUC), to compare the improved algorithm with previous methods and evaluate recurrence prediction.

Main Results:

• The improved SII technique effectively distinguished degrees of meningioma adhesion, particularly complete adhesion (p = 0.005 for complete vs. partial, p<0.001 for complete vs. non-adherent).
• Demonstrated superior discriminatory ability compared to the previous algorithm (AUC 0.86 vs. 0.72 for complete adhesion).
• Higher adhesion percentages in aggressive tumors correlated with recurrence (p = 0.042).

Conclusions:

• The improved SII technique provides a reliable and objective method for quantifying meningioma-brain adhesion.
• This technique has the potential to aid in predicting meningioma recurrence, especially in aggressive subtypes.
• Findings support the integration of this advanced imaging method into clinical practice for improved treatment strategies.