New Software for Preoperative Diagnostics of Meningeal Tumor Histological Types

Abstract Objective Meningeal tumors are neoplasms with different histological manifestations of both benign and malignant types that determines the prognosis of tumor recurrence and its consistency. The risk of surgical treatment depends on the location, size, and consistency of the tumor. MRI sequences could be used to identify the features of tumors, but these MRI characteristics are not well understood yet. The present study describes an advanced mathematical algorithm to analyze of MRI data and distinguish histological types of meningeal tumors before surgery. Methods 48 patients underwent surgical removal of meningeal brain tumor. All patients had preoperative MR imaging with a 1.5-T scanner. One radiologist and two neurosurgeons evaluated MRI histogram peaks of the whole tumor volume using the advanced computer algorithm. Results Three specialists received the following mean value of histogram peaks: 15.99 ± 0.23 (± m) for meningoteliomatous meningiomas; 21.24 ± 0.3 (±SEM) for fibroplastic meningiomas; 19.0 ± 0.28 (±SEM) for transitional meningiomas; 10.7 ± 0.27 (±SEM) for anatypical, anaplastic meningiomas, 11.03± 0.51 (±SEM) for PIFs and 25.72 ± 0.29 (±SEM) for HPC. One-way ANOVA test proved the difference between group means: F = 70.138, p