(1) Purpose: To determine the borders of malignant gliomas with diffusion kurtosis and perfusion MRI biomarkers. (2) Methods: In 50 high-grade glioma patients, diffusion kurtosis and pseudo-continuous arterial spin labeling (pCASL) cerebral blood flow (CBF) values were determined in contrast-enhancing area, in perifocal infiltrative edema zone, in the normal-appearing peritumoral white matter of the affected cerebral hemisphere, and in the unaffected contralateral hemisphere. Neuronavigation-guided biopsy was performed from all affected hemisphere regions. (3) Results: We showed significant differences between the DKI values in normal-appearing peritumoral white matter and unaffected contralateral hemisphere white matter. We also established significant (p < 0.05) correlations of DKI with Ki-67 labeling index and Bcl-2 expression activity in highly perfused enhancing tumor core and in perifocal infiltrative edema zone. CBF correlated with Ki-67 LI in highly perfused enhancing tumor core. One hundred percent of perifocal infiltrative edema tissue samples contained tumor cells. All glioblastoma samples expressed CD133. In the glioblastoma group, several normal-appearing white matter specimens were infiltrated by tumor cells and expressed CD133. (4) Conclusions: DKI parameters reveal changes in brain microstructure invisible on conventional MRI, e.g., possible infiltration of normal-appearing peritumoral white matter by glioma cells. Our results may be useful for plotting individual tumor invasion maps for brain glioma surgery or radiotherapy planning.

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. Burdenko Neurosurgery Medical Center no later than 4 h after surgery. The spectra of Protoporphyrin IX (Pp IX) fluorescence, diffuse reflectance (DR) and Raman scattering (RS) of biopsy samples were recorded. Diffuse reflectance studies were carried out using a white light source in the visible region. Raman scattering spectra were obtained using a 785 nm laser. Patients diagnosed with meningioma, glioblastoma, oligodendroglioma, and astrocytoma were studied. We used the cluster analysis method to detect natural clusters in the data sample presented in the feature space formed based on the spectrum analysis. For data analysis, four clustering algorithms with eight dimensionality reduction algorithms were considered.

Decision support systems based on machine learning (ML) techniques are already empowering neuro-oncologists. These systems provide comprehensive diagnostics, offer a deeper understanding of diseases, predict outcomes, and assist in customizing treatment plans to individual patient needs. Collectively, these elements represent artificial intelligence (AI) in neuro-oncology. This paper reviews recent studies which apply machine learning algorithms to optical spectroscopy data from central nervous system (CNS) tumors, both ex vivo and in vivo. We first cover general issues such as the physical basis of the optical-spectral methods used in neuro-oncology, and the basic algorithms used in spectral signal preprocessing, feature extraction, data clustering, and supervised classification methods. Then, we review in more detail the methodology and results of applying ML techniques to fluorescence, elastic and inelastic scattering, and IR spectroscopy.

The aim of the study was to evaluate the relationship between tumor blood flow (TBF) measured by the pseudo-continuous arterial spin labeling (PCASL) method and IDH1 mutation status of gliomas as well as Ki-67 proliferative index. Methods. The study included 116 patients with newly diagnosed gliomas of various grades. They received no chemotherapy or radiotherapy before MRI. IDH1 status assessment was performed after tumor removal in 106 cases—48 patients were diagnosed with wildtype gliomas (Grade 1–2—6 patients, Grade 3–4—42 patients) and 58 patients were diagnosed with mutant forms of gliomas (Grade 1–2—28 patients, Grade 3–4—30 patients). In 64 cases out of 116 Ki-67 index was measured. Absolute and normalized tumor blood flow values were measured on 3D PCASL maps. Results. TBF and normalized TBF (nTBF) in wildtype gliomas were significantly higher than in IDH1-mutant gliomas (p < 0.001). ASL perfusion showed high values of sensitivity and specificity in the differential diagnosis of gliomas with distinct IDH1 status (for TBF: specificity 75%, sensitivity 77.6%, AUC 0.783, cutoff 80.57 mL/100 g/min, for nTBF: specificity 77.1%, sensitivity 79.3%, AUC 0.791, cutoff 4.7). TBF and nTBF in wildtype high-grade gliomas (HGG) were significantly higher than in mutant forms (p < 0.001). ASL perfusion showed the following values of sensitivity and specificity in the diagnosis of mutant HGG and wildtype HGG (for TBF: specificity 83.3%, sensitivity 60%, AUC 0.719, cutoff 84.18 mL/100 g/min, for nTBF: specificity 88.1%, sensitivity 60%, AUC 0.729, cutoff 4.7). There was a significant positive correlation between tumor blood flow and Ki-67 (for TBF Rs = 0.63, for nTBF Rs = 0.61). Conclusion. ASL perfusion may be an informative factor in determining the IDH1 status in brain gliomas preoperative and tumor proliferative activity.

Менингиомы могут сопровождаться перитуморозным отеком, частота его развития и патогенез окончательно не установлены. Наличие и выраженность отека при сходных по широкому ряду параметров менингиомах значительно варьирует. ЦЕЛЬ ИССЛЕДОВАНИЯ Оценить перитуморозный отек при внутричерепных менингиомах и факторы, влияющие на его возникновение и выраженность. МАТЕРИАЛ И МЕТОДЫ 126 пациентов (из них 69% женщин) в возрасте 19—76 лет (медиана 53 года), у которых диагностированы 142 менингиомы, прошли хирургическое (n=111) и лучевое (n=15) лечение в 2016—2018 гг. Протокол магнитно-резонансных томографий (МРТ) у всех больных включал T1, T2, T2-FLAIR, диффузионно-взвешенные изображения и постконтрастные T1-взвешенные изображения в трех проекциях, диффузионно-тензорную МРТ у 27 и МР-спектроскопию у 21 пациента. РЕЗУЛЬТАТЫ Перитуморозный отек выявлен в 46% (n=66) наблюдений, из них в 31% (n=21) случаев отек был выраженным. Индекс ALPS, используемый для оценки скорости диффузии воды по периваскулярным пространствам вен белого вещества, составил 1,510±0,19 при менингиомах без отека и 1,308±0,19 — с отеком (p=0,014). Выявлены положительная корреляция наличия и выраженности отека с размерами и неровными контурами менингиомы и отрицательная с наличием симптома «ликворной щели». Установлено повышение скорости кровотока в атипических и анапластических менингиомах с отеком (p=0,03). Другие изученные признаки (локализация, гистологический вариант, степень злокачественности, сигнальные МР-характеристики, интегральные значения пиков основных метаболитов, диффузионные и перфузионные параметры опухоли) достоверного влияния на перитуморозный отек мозга при менингиомах не оказывали (p>0,05). ЗАКЛЮЧЕНИЕ Методом диффузионно-тензорной томографии с расчетом индекса ALPS выявлено статистически значимое влияние дисфункции глимфатической системы на развитие перитуморозного отека головного мозга. Большие размеры и неровные контуры менингиомы увеличивали, а наличие ликворной щели уменьшало вероятность развития перитуморозного отека. Другие изученные факторы на отек мозга при менингиомах не влияли.