Background. Gliomas are the most common primary brain tumors in adults, with an annual incidence of approximately 6 cases per 100,000 population and up to 3.2 cases per 100,000 for glioblastoma. Overall, the incidence of gliomas is higher in men than in women. Glioblastoma is the most malignant tumor of the central nervous system and have a poor prognosis, the 5-year overall survival rate is approximately 5–7%. Purpose – to trace the evolution of treatment response assessment criteria for gliomas and to summarize the key principles and practical recommendations of the RANO 2.0 criteria. Materials and Methods. A literature search was conducted using the PubMed and Google Scholar databases with the keywords «glioma», «glioblastoma», «response assessment», «pseudoprogression», «progression» and «RANO» covering the periods 2010–2020, 2021–2026 and 2024–2026. The review included 70 scientific articles that met the criteria for thematic relevance. Results. Assessing the therapeutic response is a key factor influencing the clinical course of the disease. Introduction of the 5th edition (2021) of the World Health Organization (WHO) classification of tumors, based on molecular-genetic criteria, has fundamentally altered the view on the traditional classification of gliomas and necessitated a revision of the criteria for treatment evaluating efficacy. Consequently, updated, unified RANO 2.0 criteria were developed in 2023, they provide a single, standardized algorithm for assessing all gliomas. Key innovations of RANO 2.0 include revised approaches to baseline scanning, the rational use of confirmatory scans, the standardization of MRI protocols, the application of two- and three-dimensional assessment and the elimination of FLAIR-based assessment of the non-contrastenhancing tumor component for glioblastomas. Conclusions. Assessing therapeutic response enables personalized decision-making, the timely discontinuation of ineffective therapy, the optimization of dosages for effective drugs and the minimization of side effects. Refining the criteria for assessing therapeutic response remains one of the priority area of current neuro-radiology and neurooncology.
Background. CT morphometry of the olfactory cleft (OC) reflects structural pre-requisites for olfactory dysfunction; however, its relationship with olfactory function may depend on etiology: a conductive mechanism predominates in mechanical obstruction, whereas a neurosensory mechanism may occur after SARS-CoV-2 infection. Purpose – to assess rhinomanometric, olfactometric, and CT-morphometric para-meters of the olfactory cleft in patients with olfactory dysfunction of mechanical and post-viral (COVID-19) origin and to compare the pattern of concordance of these parameters between the two etiological phenotypes. Materials and Methods. A total of 196 patients (37.4 ± 3.1 years) were examined: group 1 (n = 53) – mechanical nasal obstruction for 3–5 years; group 2 (n = 48) – up to 6 months; group 3 (n = 44) – up to 1 month; group 4 (n = 51) – post-viral rhino-sinusitis within 3 months. Rhinomanometry, Sniffin’ Sticks olfactometry, and CT using a Vatech PaX-i3D system were performed. ANOVA (η2) and the χ2 test with Cramer’s V were applied. Results. Aerodynamic resistance was 3.1 ± 0.4, 2.2 ± 0.5, 3.6 ± 0.4, and 1.3 ± 0.5 kPa·s/L, respectively (F(3,192) = 243.3; p < 0.001; η2 = 0.792). OC area was 86.5 ± 0.4, 111.1 ± 0.5, 78.8 ± 0.5, and 164.4 ± 0.8 mm2, respectively (all p < 0.001). In groups 1–3, structural and functional parameters changed concordantly. In group 4, despite the largest OC area and lowest resistance, T was 3.0 ± 1.8 points and I was 6.9 ± 2.5 points; anosmia by T occurred in 27.5% and hyposmia in 72.5%. Keros type distribution differed significantly between groups (χ2(6) = 28.09; p < 0.001; V = 0.268), with type III predominating in group 4 (50.9%). Conclusions. In mechanical nasal obstruction, morphometric and aerodynamic changes are consistent with the severity of olfactory dysfunction. After COVID-19, this relationship is absent, supporting a predominant neurosensory mechanism.
Background. Gastrointestinal stromal tumours (GISTs) are the most common mesenchymal tumours of the gastrointestinal tract and are frequently associated with mutations in the KIT and PDGFRA genes. The introduction of targeted therapy, particularly imatinib, has significantly improved outcomes in patients with unresectable, metastatic, and high-risk GISTs. However, further evaluation of treatment efficacy, molecular predictors of response, resistance mechanisms, and safety remains clinically relevant. Purpose – to evaluate the clinical efficacy and safety of imatinib-based targeted therapy in patients with GISTs, focusing on treatment response, adverse effects, progression-free survival (PFS), and the impact of tumour molecular characteristics on therapeutic outcomes. Materials and Methods. A prospective single-centre study was conducted at the National Centre of Oncology and Haematology of the Kyrgyz Republic. The study included 70 patients aged 30–75 years with histologically confirmed GISTs treated from 1 June 2020 to 1 June 2025. All patients received imatinib at a standard dose of 400 mg/day. Clinical response, adverse events, PFS, and survival outcomes were assessed. Molecular analysis of KIT and PDGFRA mutations and immunohisto-chemical evaluation of CD117 expression were performed. Results. Clinical response to imatinib was achieved in 90% of patients, including partial remission in 75% and disease stabilisation in 15%; progression occurred in 10% of cases. Grade 3–4 adverse effects were observed in 20% of patients. Five-year survival after R0 resection reached 89%, compared with 63% and 38% after R1 and R2 resections, respectively. The longest PFS was observed in patients with exon 11 KIT mutations (78 months), while the shortest was associated with the PDGFRA D842V mutation (12 months). CD117 expression was detected in 98% of cases, and secondary resistance developed in 12% of patients. Conclusions. Imatinib demonstrated high efficacy and acceptable safety as first-line targeted therapy for GISTs. Molecular profiling and individualised treatment strategies may improve therapeutic optimisation and patient outcomes.
Background. This study considers the response system to wartime radiological incidents not as a collection of autonomous departmental structures but as an integrated system in which the coordination of interagency information interfaces is considered one of the factors supporting continuity of clinically relevant information exchange. A scenario-adaptive model of interagency information interfaces (Scenario-Adaptive Interagency Information Model, SAIIM) is proposed, in which the primary object of analysis is not the individual functions of participating agencies but standardized points of interagency interaction intended to support the transfer of the minimum information required for medical decision-making under time-constrained conditions. Purpose – to develop a formal scenario-adaptive model of interagency information exchange aimed at ensuring the continuity of the treatment and evacuation process through the standardization of information interfaces among response stakeholders across different radiological emergency scenarios. Materials and Methods. The study was conducted using the methodology of systems analysis, information flow theory, and conceptual modeling of complex organizational and technical systems. The object of the study was interagency interaction during the response to radiological emergencies, whereas the subject was the information interfaces between response stakeholders that determine the continuity of the treatment and evacuation process. Results. Scenario-based modeling demonstrated differences in the structure of clinically relevant information needs and interagency information interfaces across radiological emergency scenarios. For each scenario, a representative Critical Information Interface and a potential Interface Failure Point (IFP) were identified. Loss or delay of clinically relevant information at such a point may create conditions for errors in medical triage, inappropriate routing, or delays in specialized care; however, the clincal consequences of such information failures require separate empirical assessment. Conclusions. The proposed SAIIM formalizes interagency information exchange as a system of scenario-dependent information interfaces and defines a Minimum Clinical Information Set (MCIS) required to support subsequent stages of the treatment and evacuation process. The model is conceptual and provides a methodological basis for further expert validation, quantitative assessment of interface criticality, and simulation-based evaluation of its practical applicability.
Background. Postoperative monitoring of midline shift (MLS) and intracranial complications is critical for patients after decompressive craniectomy (DC). Routine computed tomography (CT) monitoring is associated with the risks of intrahospital transport of critically ill patients. Bedside transcranial sonography (TCS) through the trepanation window is a promising alternative; however, the limits of its absolute clinical agreement with CT for safe decision-making based on static thresholds (e.g., MLS > 5 mm) remain insufficiently studied. Purpose – to determine the diagnostic accuracy and absolute clinical agreement of bedside TCS compared to CT for quantifying MLS and detecting intracranial hematomas in patients following DC in the intensive care unit. Materials and methods. This prospective cohort observational study analyzed data from 25 patients with severe traumatic brain injury who underwent DC. Bedside TCS via the trepanation acoustic window was performed within 60 minutes of the refe-rence CT scan, maintaining blinding of the imaging results. The absolute agreement for MLS quantification was evaluated using Bland–Altman mathematical and graphical analysis, along with the intraclass correlation coefficient (ICC). Hematoma detection was assessed using the prevalence- and biasadjusted kappa index (PABAK). Results. The agreement evaluation for MLS measurements between CT and TCS demonstrated a moderate level of concordance (ICC = 0.736). The mean systematic bias was 0.84 mm (with TCS marginally underestimating the shift); however, the calculated 95% limits of agreement exhibited a substantial range (from –2.96 mm to 4.63 mm). The diagnostic accuracy of TCS for detecting intracerebral hematomas reached a sensitivity of 91.7% and a specificity of 92.3% (PABAK = 0.840). Furthermore, the method showed 100% accuracy in visualizing external ventricular drains and 100% specificity for detecting extra-axial hemorrhages. Conclusions. TCS is a highly effective, safe, and radiation-free bedside modality for identifying massive cerebral midline shifts, intracerebral hematomas, and verifying ventricular drain placement, entirely eliminating the risks associated with intra-hospital transport. Nevertheless, given the wide limits of agreement utilizing TCS for the absolute evaluation of static MLS thresholds is not recommended. The optimal clinical paradigm entails deploying TCS for dynamic trend monitoring relative to an individual’s baseline post-operative metrics.
