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Tumor cell percentage (TCP) is an essential characteristic of biopsy samples that directly affects the sensitivity of molecular testing in clinical practice. Apart from clarifying diagnoses, rapid evaluation of TCP combined with various neuronavigation systems can be used to support decision making in neurosurgery. It is known that ambient mass spectrometry makes it possible to rapidly distinguish healthy from malignant tissues. In connection with this, here we demonstrate the possibility of using non-imaging ambient mass spectrometry to evaluate TCP in glial tumor tissues with a high degree of confidence. Molecular profiles of histologically annotated human glioblastoma tissue samples were obtained using the inline cartridge extraction ambient mass spectrometry approach. XGBoost regressors were trained to evaluate tumor cell percentage. Using cross-validation, it was estimated that the TCP was determined by the regressors with a precision of approximately 90% using only low-resolution data. This result demonstrates that ambient mass spectrometry provides an accurate method todetermine TCP in dissected tissues even without implementing mass spectrometry imaging. The application of such techniques offers the possibility to automate routine tissue screening and TCP evaluation to boost the throughput of pathology laboratories. Rapid estimation of tumor cell percentage during neurosurgery.

Recently, mass-spectrometry methods show its utility in tumor boundary location. The effect of differences between research and clinical protocols such as low- and high-resolution measurements and sample storage have to be understood and taken into account to transfer methods from bench to bedside. In this study, we demonstrate a simple way to compare mass spectra obtained by different experimental protocols, assess its quality, and check for the presence of outliers and batch effect in the dataset. We compare the mass spectra of both fresh and frozen-thawed astrocytic brain tumor samples obtained with the inline cartridge extraction prior to electrospray ionization. Our results reveal the importance of both positive and negative ion mode mass spectrometry for getting reliable information about sample diversity. We show that positive mode highlights the difference between protocols of mass spectra measurement, such as fresh and frozen-thawed samples, whereas negative mode better characterizes the histological difference between samples. We also show how the use of similarity spectrum matrix helps to identify the proper choice of the measurement parameters, so data collection would be kept reliable, and analysis would be correct and meaningful., (© 2020 John Wiley & Sons, Ltd.)

Significant metabolism alteration is accompanying the cell malignization process. Energy metabolism disturbance leads to the activation of de novo synthesis and beta-oxidation processes of lipids and fatty acids in a cancer cell, which becomes an indicator of pathological processes inside the cell. The majority of studies dealing with lipid metabolism alterations in glial tumors are performed using the cell lines in vitro or animal models. However, such conditions do not entirely represent the physiological conditions of cell growth or possible cells natural variability. This work presents the results of the data obtained by applying ambient mass spectrometry to human glioblastoma multiform tissues. By analyzing a relatively large cohort of primary and secondary glioblastoma samples, we identify the alterations in cells lipid composition, which accompanied the development of grade IV brain tumors. We demonstrate that primary glioblastomas, as well as ones developed from astrocytomas, are enriched with mono- and diunsaturated phosphatidylcholines (PC 26:1, 30:2, 32:1, 32:2, 34:1, 34:2). Simultaneously, the saturated and polyunsaturated phosphatidylcholines and phosphatidylethanolamines decrease. These alterations are obviously linked to the availability of the polyunsaturated fatty acids and activation of the de novo lipid synthesis and beta-oxidation pathways under the anaerobic conditions in the tumor core.

Express MS identification of biological tissues has become a much more accessible research method due to the application of direct specimen ionization at atmospheric pressure. In contrast to traditional methods of analysis employing GC-MS methods for determining the molecular composition of the analyzed objects it eliminates the influence of mutual ion suppression. Despite significant progress in the field of direct MS of biological tissues, the question of mass spectrometric profile attribution to a certain type of tissue still remains open. The use of modern machine learning methods and protocols (e.g., "random forests") enables us to trace possible relationships between the components of the sample MS profile and the result of brain tumor tissue classification (astrocytoma or glioblastoma). It has been shown that the most pronounced differences in the mass spectrometric profiles of these tumors are due to their lipid composition. Detection of statistically significant differences in lipid profiles of astrocytoma and glioblastoma may be used to perform an express test during surgery and inform the neurosurgeon what type of malignant tissue he is working with. The ability to accurately determine the boundaries of the neoplastic growth significantly improves the quality of both surgical intervention and postoperative rehabilitation, as well as the duration and quality of life of patients.

The development of perspective diagnostic techniques in medicine requires efficient high-throughput biological sample analysis methods. Here, we present an inline cartridge extraction that facilitates the screening rate of mass spectrometry shotgun lipidomic analysis of tissue samples. We illustrate the method by its application to tumor tissue identification in neurosurgery. In perspective, this high-performance method provides new possibilities for the investigation of cancer pathogenesis and metabolic disorders.

The majority of research in the biomedical sciences is carried out with the highest resolution accessible to the scientist, but, in the clinic, cost constraints necessitate the use of low-resolution devices. Here, we compare high- and low-resolution direct mass spectrometry profiling data and propose a simple pre-processing technique that makes high-resolution data suitable for the development of classification and regression techniques applicable to low-resolution data, while retaining high accuracy of analysis. This work demonstrates an approach to de-noising spectra to make the same representation for both high- and low-resolution spectra. This approach uses noise threshold detection based on the Tversky index, which compares spectra with different resolutions, and minimizes the percentage of resolution-specific peaks. The presented method provides an avenue for the development of analytical algorithms using high-resolution mass spectrometry data, while applying these algorithms in the clinic using low-resolution mass spectrometers., (© 2019 Published by Elsevier B.V. on behalf of The Association for Mass Spectrometry: Applications to the Clinical Lab (MSACL).)

In this work, we demonstrate a new approach for assessing the stability and reproducibility of mass spectra obtained via ambient ionization methods. This method is suitable for both comparing experiments during which only one mass spectrum is measured and for evaluating the internal homogeneity of mass spectra collected over a period of time. The approach uses Pearson's r coefficient and the cosine measure to compare the spectra. It is based on the visualization of dissimilarities between measurements, thus leading to the analysis of dissimilarity patterns. The cosine measure and correlations are compared to obtain better metrics for spectra homogeneity. The method filters out unreliable scans to prevent the analyzed sample from being wrongly characterized. The applicability of the method is demonstrated on a set of brain tumor samples. The developed method could be employed in neurosurgical applications, where mass spectrometry is used to monitor the intraoperative tumor border.

The relationship between molecular genetic and metabolic disorders is one of the challenges of modern oncology. In this review, we consider lipid metabolism and its changes as one of the factors of oncogenesis of glial tumors. Also, we demonstrate that the genome and the metabolome are interconnected by a large number of links, and the metabolic pathways, during their reorganization, are able to drastically affect the genetic structure of the cell and, in particular, cause its tumor transformation. Our own observations and analysis of the literature data allow us to conclude that mass spectrometry is a highly accurate current method for assessing metabolic disorders at the cellular level. The use of mass spectrometry during surgery allows the neurosurgeon to obtain real-time data on the level of specific molecular markers in the resected tissue, thereby bringing intraoperative navigation techniques to the molecular level. The generation of molecular fingerprints for each tumor significantly complements the available neuroimaging, molecular genetic, and immunohistochemical data.

The median overall survival of glioblastoma patients is about 15 months. Only a small number of patients survive 3 years. The factors of a favorable prognosis for the 'longevity phenomenon' in glioblastoma patients are not fully understood., Objective: to determine the occurrence rate of long-living patients with glioblastomas, identify clinical predictors of a favorable prognosis, and identify the presence and prognostic significance of an IDH1 mutation., Material and Methods: Among 1494 patients operated on for glioblastoma at the Burdenko Neurosurgical Institute from 2007 to 2012, there were 84 (5.6%) patients who lived more than 3 years after primary surgery. In all the cases, histological specimens were reviewed, and immunohistochemical detection of a mutant IDH1 protein was performed. Overall survival was calculated from the time of first surgery to the date of the last consultation or death, and the recurrence-free period was calculated from the time of first surgery to MRI-verified tumor progression., Results: The median age of long-living patients with glioblastoma was 45 years (19-65 years). All tumors were located supratentorially. The median Karnofsky performance status score at the time of surgery was 80 (range, 70-100). All patients underwent microsurgical resection of the tumor, followed by chemoradiotherapy. The median recurrence-free period was 36 months (5-98 months). Overall survival of 48, 60, and 84 months was achieved in 23, 15 and 6% of patients, respectively. Among 49 specimens available for the IDH1 analysis, 14 (28.6%) specimens had a mutant protein. There was no significant difference in survival rates in patients with positive and negative results for IDH1 (44.1 vs. 40.8 months; p>0.05)., Conclusion: The significance of various factors that may be predictors of a favorable course of the disease is discussed in the literature. This work is the first part of analysis of prognostically significant factors positively affecting overall survival of glioblastoma patients. In our series, the predictors of a favorable prognosis for long-living patients with the verified diagnosis of glioblastoma were as follows: young age, the supratentorial location of the tumor, a high Karnofsky score before surgery, and tumor resection. In our series, we used immunohistochemical tests and found no prognostic significance of the IDH1 gene mutation; further analysis will require application of direct sequencing. We plan to study other morphological and molecular genetic features of tumors, which explain prolonged survival of glioblastoma patients, as well as the role of various types of combined chemoradiation treatment.

The paper summarizes the experience in using a system of electromagnetic intraoperative frameless navigation in various neurosurgical pathologies of the brain. The electromagnetic navigation technique was used for 102 operations in 98 patients, including 36 transnasal endoscopic interventions. There were no intraoprtative and postoperative complications associated with the use of the system. In the process of using the system, factors influencing the accuracy of navigation and requiring additional control by the surgeon were identified., Purpose: The study purpose was to evaluate the use of electromagnetic navigation in surgical treatment of patients with various brain lesions., Material and Methods: The system of electromagnetic navigation was used for 102 operations in 98 patients (42 males and 56 females, including 18 children; median age, 34.8 years (min, 2.2 years; max, 69 years)) in the period from December 2012 to December 2016. In 36 patients, the system was used for endoscopic interventions. In 19 patients, electromagnetic navigation was used in combination with neurophysiological monitoring., Results: In our series of cases, the frameless electromagnetic navigation system was used in 66 transcranial operations. The mean error of navigation was 1.9±0.5 mm. In 5 cases, we used the data of preoperative functional MRI (fMRI) and tractography for navigation. At the same time, in all 7 operations with simultaneous direct stimulation of the cortex, there was interference and significant high-frequency noise, which distorted the electrophysiological data. A navigation error of more than 3 mm was associated with the use of neuroimaging data with an increment of more than 3 mm, image artifacts from the head locks, high rate of patient registration, inconsequence of touching points on the patient's head, and unsatisfactory fixation to the skin or subsequent displacement of a non-invasive localizer of the patient. In none of the cases, there was a significant effect of standard metal surgical tools (clamps, tweezers, aspirators) located near the patient's head on the navigation system. In two cases, the use of massive retractors located near the patient's localizer caused noise in the localizer and navigation errors of more than 10 mm due to significant distortions of the electromagnetic field. Thirty-six transnasal endoscopic interventions were performed using the electromagnetic frameless navigation system. The mean navigation error was 2.5±0.8 mm., Conclusion: In general, electromagnetic navigation is an accurate, safe, and effective technique that can be used in surgical treatment of patients with various brain lesions. The mean navigation error in our series of cases was 1.9±0.5 mm for transcranial surgery and 2.5±0.8 mm for endoscopic surgery. Electromagnetic navigation can be used for different, both transcranial and endoscopic, neurosurgical interventions. Electromagnetic navigation is most convenient for interventions that do not require fixation of the patient's head, in particular for CSF shunting procedures, drainage of various space-occupying lesions (cysts, hematomas, and abscesses), and optimization of the size and selection of options for craniotomy. In repeated interventions, disruption of the normal anatomical relationships and landmarks necessitates application of neuronavigation systems in almost mandatory manner. The use of electromagnetic navigation does not limit application of the entire range of necessary intraoperative neurophysiological examinations at appropriate surgical stages. Succession in application of neuronavigation should be used to get adequate test results.

When preparing the review, we analyzed publications available at the Medline database; a total of 1,083 publications related to the review's subject were analyzed. After more careful analysis, we selected 117 publications devoted to the development of neuronavigation in craniocerebral surgery, historical prerequisites of neuronavigation emergence, current trends, and future perspectives of the technique.

It was only 40 years ago that the first PC appeared. Over this period, rather short in historical terms, we have witnessed the revolutionary changes in lives of individuals and the entire society. Computer technologies are tightly connected with any field, either directly or indirectly. We can currently claim that computers are manifold superior to a human mind in terms of a number of parameters; however, machines lack the key feature: they are incapable of independent thinking (like a human). However, the key to successful development of humankind is collaboration between the brain and the computer rather than competition. Such collaboration when a computer broadens, supplements, or replaces some brain functions is known as the brain-computer interface. Our review focuses on real-life implementation of this collaboration.