Keywords: Tumors (Pre-Treatment), Quantitative Imaging
Motivation: The consistency of intracranial meningiomas is essential for determining the necessary surgical instruments and influencing the outcome of surgery. However, no specific feature of conventional MRI is reliable in predicting the meningiomas consistency.
Goal(s): To evaluate and compare the potential of various MRI perfusion and diffusion metrics in predicting the meningiomas consistency.
Approach: Histogram parameters of metrics obtained from DKI, DTI, ASL and DSC were included in logistic regression models to predict meningiomas consistency.
Results: DTI, ASL, and DSC metrics could significantly differentiate between soft and hard meningiomas. The DSC combined model yielded the highest AUC of 0.858.
Impact: The differentiation of soft and hard meningiomas was feasible by combining histogram parameters of DSC and DTI metrics.
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