Cervical dystonia is focal dystonia characterized by involuntary movement of the neck muscle, which leads to abnormal head posture. It can be accompanied with pain and tremor. In this study, we evaluated the presence of depression and anxiety in patients with cervical dystonia and the influence of dystonia symptoms on the quality of life. Psychiatric symptoms were evaluated by use of the Beck Depression Inventory (BDI-II) and Beck Anxiety Inventory. Toronto Western Spasmodic Torticollis Rating Scale (TWSTRS) was used to evaluate the cervical dystonia symptoms. Quality of life was assessed by the craniocervical dystonia questionnaire (CDQ-24) and short form 36 health survey (SF-36). Nineteen patients were analyzed. Most of the patients had mild cervical dystonia (mean TWSTRS 23.89). Depression was present in 42.1 % and anxiety in 57.9 % of the patients. Disability due to cervical dystonia correlated with the occurrence of depression (ρ = 0.534) and anxiety (r = 0.652). Disability was found to significantly influence the stigma, emotional state, pain, daily activity, social life, physical function, and physical and mental disability. Pain influenced some aspects of body pain, physical function, and physical and mental disability. Being associated with disability and pain, cervical dystonia decreases the quality of life in many aspects. Disability also influenced depression and anxiety, which were present in half of study patients. In addition to follow up for cervical dystonia symptoms, patients with cervical dystonia should also be assessed for psychiatric symptoms on routine clinical check-ups. In addition to botulinum toxin, psychopharmaceuticals should be considered as a treatment option in these patients.

SUMMARY – Objectives of the study were to observe supraspinatus muscle thickness in patients with supraspinatus tendon pathology using ultrasound (US) and examining inter- and intra-rater reliability, and to compare muscle thickness with cross-sectional area (CSA) and occupation ratio measured by both US and magnetic resonance imaging (MRI). The investigation was designed as a prospective cohort study. Two groups of patients were included in the study: 43 patients with tendon rupture and 44 patients without tendon rupture as a control group. A written consent was obtained from all patients. In both groups, muscle thickness, CSA and occupation ratio were measured with US, and CSA and occupation ratio with MRI. Study results showed statistically significant between-group differences. The mean supraspinatus muscle thickness measured by US was 14.01 mm and 19.83 mm in patients with and without tendon rupture, respectively. CSA and occupation ratio measured by US and MRI also showed statistically significant between-group differences. Pearson correlation coefficient between supraspinatus thickness and occupation ratio and CSA measured by US and MRI showed strong to moderate correlation. US measurements showed moderate to strong intra- and inter-rater reliability. In conclusion, supraspinatus muscle thickness measurement by US is a reliable method for muscle atrophy evaluation and strongly correlates with other acknowledged methods.

The aim of the study was to assess diagnostic value and utility of selected morphological features in predicting lymph node (LN) malignancy using B-mode, Doppler ultrasonography and multivariate settings in a tertiary radiological referral center. The study included 123 patients having undergone ultrasound-guided fine-needle aspiration and cytologic analysis (FNAC) of cervical, axillary and inguinal LNs. Each LN was characterized by long/L and short/T-axis, shape, margins, echogenicity, cortical thickness, vascularization, and examiner's subjective impression. Within the limitations of FNAC, altered shape and vascularization had relatively high specificity and positive predictive value (>80%), whereas subjective impression had high sensitivity and negative predictive value (100%) for malignancy. The cut-off levels for different features of LN by ROC analysis were as follows: long-axis 23 mm, short-axis 11 mm, L/T ratio 2.19, and maximal cortical thickness 5.1 mm. On multivariate analysis (adaptive regression splines, n=108), the addition of long-axis, L/T ratio, age and sex considerably improved diagnostic accuracy (88%), sensitivity (margins + vascularization) and specificity (subjective impression) of the diagnostic model. The combination of morphological and demographic features could improve diagnostic accuracy, usually with a trade-off between the sensitivity and specificity of the predictive model. The performance may depend on the level of expertise and institutional settings.

Glioblastoma (GBM) is the most aggressive glial tumor of the central nervous system. Despite intense scientific efforts, patients diagnosed with GBM and treated with the current standard of care have a median survival of only 15 months. Patients are initially treated by a neurosurgeon with the goal of maximal safe resection of the tumor. Obtaining tissue samples during surgery is indispensable for the diagnosis of GBM. Technological improvements, such as navigation systems and intraoperative monitoring, significantly advanced the possibility of safe gross tumor resection. Usually within six weeks after the surgery, concomitant radiotherapy and chemotherapy with temozolomide are initiated. However, current radiotherapy regimens are based on population-level studies and could also be improved. Implementing artificial intelligence in radiotherapy planning might be used to individualize treatment plans. Furthermore, detailed genetic and molecular markers of the tumor could provide patient-tailored immunochemotherapy. In this article, we review current standard of care and possibilities of personalizing these treatments. Additionally, we discuss novel individualized therapeutic options with encouraging results. Due to inherent heterogeneity of GBM, applying patient-tailored treatment could significantly prolong survival of these patients.

Glioblastoma (GBM) is the most common malignancy of the brain with a relatively short median survival and high mortality. Advanced age, high socioeconomic status, exposure to ionizing radiation, and other factors have been correlated with an increased incidence of GBM, while female sex hormones, history of allergies, and frequent use of specific drugs might exert protective effects against this disease. However, none of these explain the pathogenesis of GBM. The most recent WHO classification of CNS tumors classifies neoplasms based on their histopathological and molecular characteristics. Modern laboratory techniques, such as matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry, enable the comprehensive metabolic analysis of the tissue sample. MALDI imaging is able to characterize the spatial distribution of a wide array of biomolecules in a sample, in combination with histological features, without sacrificing the tissue integrity. In this review, we first provide an overview of GBM epidemiology, risk, and protective factors, as well as the recent WHO classification of CNS tumors. We then provide an overview of mass spectrometry workflow, with a focus on MALDI imaging, and recent advances in cancer research. Finally, we conclude the review with studies of GBM that utilized MALDI imaging and offer our perspective on future research.