Predicting the consistency of intracranial meningiomas using apparent diffusion coefficient maps derived from...

Area of Science:

• Neurosurgery
• Radiology
• Medical Imaging

Background:

• Meningioma consistency impacts surgical difficulty, complications, and duration.
• Apparent diffusion coefficient (ADC) from diffusion-weighted imaging (DWI) is a quantitative imaging biomarker.
• Previous studies show varied correlations between standard ADC and meningioma consistency, with shifted ADC showing promise.

Purpose of the Study:

• To investigate if preoperative standard and shifted ADC maps can predict the consistency of intracranial meningiomas.
• To evaluate the diagnostic performance of ADC maps in differentiating hard from soft meningiomas.

Main Methods:

• Prospective cohort study involving patients undergoing meningioma resection.
• Calculation of standard (b=0, 1000) and shifted (b=200, 1500) ADC maps from preoperative DWI.
• Measurement of tumor stiffness using a durometer and correlation with ADC values and receiver operating characteristic (ROC) curve analysis.

Main Results:

• Significant negative correlations found between tumor stiffness and both standard (ρ = -0.465) and shifted (ρ = -0.490) ADC values (p < 0.01).
• Areas under the ROC curve for detecting hard tumors were comparable for standard (0.820) and shifted (0.847) ADC.
• High positive predictive values were achieved for detecting hard (89%) and soft (81%) tumors using combined ADC map analysis.

Conclusions:

• Preoperative standard and shifted ADC maps are valuable tools for predicting intracranial meningioma consistency.
• Combining standard and shifted ADC information enhances the prediction of tumor stiffness.
• This non-invasive method can aid in surgical planning and risk assessment for meningioma resection.