Meningioma Consistency: Correlation Between Magnetic Resonance Imaging Characteristics, Operative Findings, and

Mahmoud Alyamany1, Mohammad M Alshardan2, Abdullah Abu Jamea3

  • 1Department of Neurosurgery, National Neuroscience Institute, King Saud Bin Abdulaziz University for Health Sciences, King Fahad Medical City, Riyadh, Saudi Arabia.

Abstract

Insights

This study introduces an objective MRI-based method to measure intracranial meningioma consistency. Findings correlate MRI signal characteristics with intraoperative measurements, aiding surgical planning and tumor resectability assessment.

Area of Science:

  • Neurosurgery
  • Radiology
  • Oncology

Background:

  • Intracranial meningiomas represent 30% of primary brain tumors.
  • Surgical resection is the primary treatment modality.
  • Differentiating meningioma characteristics via MRI remains challenging.

Purpose of the Study:

  • To establish an objective relationship between MRI signal characteristics and intracranial meningioma consistency.
  • To develop a quantifiable method for assessing tumor consistency preoperatively.

Main Methods:

  • Prospective study of 70 patients undergoing surgery for suspected meningioma.
  • Correlation of MRI signal intensities (T2, FLAIR, DWI) with intraoperative consistency (CUSA levels).
  • Normalized MRI signal ratios (lesion vs. cortex) analyzed using Pearson's correlation and linear regression.

Main Results:

  • Significant correlation found between CUSA levels and FLAIR/T2 MRI signal differences (P=0.046, P=0.003).
  • Inverse relationship observed between CUSA and FLAIR/T2 MRI signal differences.
  • Weak linear relationships identified between MRI signal differences and CUSA values.

Conclusions:

  • A novel, objective MRI-based method for measuring meningioma consistency is presented.
  • This quantitative approach can assist in surgical planning and resectability assessment.
  • This study provides the first objective measurement of meningioma consistency using integrated MRI and intraoperative data.

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