Reproducibility of Radiomic Features in Glial Brain Tumors.

In our recent research, we have effectively demonstrated the feasibility of classifying magnetic resonance images (MRI) of glial tumors into four histological types utilizing standardized volume of interest (VOI), radiomics and machine learning. This research aims to determine the reproducibility of our approach when the locations of VOI are changed. We were able to demonstrate high reproducibility of ML results when the same feature selection methodology was employed across different VOIs.

Non-invasive diagnosis of brain gliomas by histological type using neuroradiomics in standardized regions of interest: towards digital biopsy.

Unlabelled: The future of contemporary neuroimaging does not solely lie in novel image-capturing technologies, but also in better methods for extraction of useful information from these images. Scientists see great promise in radiomics, i.e.

Optical Differentiation of Brain Tumors Based on Raman Spectroscopy and Cluster Analysis Methods.

In the present study, various combinations of dimensionality reduction methods with data clustering methods for the analysis of biopsy samples of intracranial tumors were investigated. Fresh biopsies of intracranial tumors were studied in the Laboratory of Neurosurgical Anatomy and Preservation of Biological Materials of N.N.

Metastatic brain lesion following gastrointestinal stromal tumor of the stomach complicated by coma.( A case report and literature review).

The authors present an extremely rare case of metastatic brain lesion in a patient with gastrointestinal stromal tumor of the stomach. There are literature data on 23 cases of metastatic lesions of the brain, skull and soft tissues of the head in similar patients. Atypical localization of metastases can lead to some diagnostic difficulties, unreasonable cancellation of chemotherapy and delayed surgical treatment.