New Software for Preoperative Diagnostics of Meningeal Tumor Histologic Types
| Autor: | A. L. Krivoshapkin, Michael E. Amelin, Vladimir I. Murtazin, Gaytan As, Diana V. Kostromskaya, Sergey M. Pyatov, Leonid E. Kalneus, V.P. Kurbatov, Alexander M. Volkov, Gleb Sergeev, Abdyrakman R. Duishobaev |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Adult
Male Pathology medicine.medical_specialty Brain tumor Sensitivity and Specificity 030218 nuclear medicine & medical imaging Machine Learning 03 medical and health sciences 0302 clinical medicine Surgical removal Image Interpretation Computer-Assisted Preoperative Care Fractional anisotropy Meningeal Neoplasms Histologic type Humans Medicine Surgical treatment Aged Observer Variation medicine.diagnostic_test Brain Neoplasms business.industry Reproducibility of Results Magnetic resonance imaging Middle Aged medicine.disease Magnetic Resonance Imaging Tumor recurrence Magnetic resonance elastography Female Surgery Neurology (clinical) Meningioma business Nuclear medicine Algorithms Software 030217 neurology & neurosurgery |
| Zdroj: | World Neurosurgery. 90:123-132 |
| ISSN: | 1878-8750 |
| Popis: | Meningeal tumors are neoplasms with different histologic manifestations of both benign and malignant types that determine the prognosis of tumor recurrence and its consistency. The risk of surgical treatment depends on the location, size, and consistency of the tumor. Magnetic resonance imaging (MRI) sequences can be used to identify the features of tumors, but these MRI characteristics are not well understood. The present study describes an advanced mathematical algorithm to analyze MRI data and distinguish histologic types of meningeal tumors before surgery.Forty-eight patients underwent surgical removal of meningeal brain tumor. All patients had preoperative MRI with a 1.5-T scanner. One radiologist and 2 neurosurgeons evaluated MRI histogram peaks of the whole tumor volume using the advanced computer algorithm.Three specialists received the following mean value of histogram peaks: 15.99 ± 0.23 (± standard error of the mean [SEM]) 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 primary intracranial fibrosarcomas and 25.72 ± 0.29 (±SEM) for meningeal hemangiopericytomas. A one-way analysis of variance test proved the difference between group means: F = 70.138, P0.01. The Tukey test and the Games-Howell test indicated that the difference between the tumor groups was significant. Mean deviation in agreement index between specialists was 0.98 ± 0.007 (±SEM).The advanced algorithm proved high specificity, sensitivity, and interoperator repeatability. |
| Databáze: | OpenAIRE |
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