Differences between Tuberous Sclerosis Complex Patients with and without Epilepsy: The Results of a Quantitative Diffusion Tensor Imaging Study.

INTRODUCTION: Tuberous sclerosis complex (TSC) is a neurocutaneous disease with a high incidence of epilepsy and damaging effects on cognitive development. To understand the mechanisms leading to abnormal cognitive development, diffusion tensor imaging (DTI) techniques have begun to be used in recent years. The present study is the first to investigate differences in the microstructure and integrity of white matter tracts in adult patients with TSC and with and without epilepsy. METHOD: A total of 37 patients with TSC (18 with epilepsy, median age 36 years; 19 without epilepsy, median age 35 years) without intellectual disability and autism spectrum disorder were included in the study. The control group (median age 34 years) comprised 37 individuals without psychiatric or neurodevelopmental disorders and neurological and cardiovascular diseases, diabetes, or addictions. A magnetic resonance imaging (MRI) DTI sequence was applied. RESULTS: There were differences in the average values of DTI parameters between patients with TSC and epilepsy and patients with TSC but without epilepsy in five white matter bands. When comparing the average values of DTI parameters between patients with TSC and epilepsy and healthy controls, we found differences in 15 of 20 analysed white matter fibres. White matter tracts in patients with TSC and epilepsy had more abnormalities than in patients with TSC but without epilepsy. The former group presented abnormalities in longer white matter fibres, especially in the left hemisphere. However, the latter group presented abnormalities in more medial and shorter white matter fibres. CONCLUSION: This DTI study documents the changes in the brain white matter of patients with TSC associated with the presence of epilepsy.

Emphysema and lung cancer risk.

Background: With increasing significance of lung cancer screening programs, it is essential to determine the group of participants, who would benefit the most from screening. In our study, we aimed to establish the correlation between lung emphysema and lung cancer risk. Methods: The study design was cross-sectional. Low-dose computed tomography (LDCT) scans of 896 subjects from MOLTEST-BIS lung cancer screening program, including 100 subjects with detected lung cancer, were visually evaluated for the presence, type and severity of emphysema. Quantitative emphysema evaluation was performed with Siemens syngo.via Pulmo 3D application. Results: Visually detected presence of centrilobular emphysema (CLE) correlated with male gender (P=0.02), age (P<0.001) and pack-years of smoking (P=0.004), as well as with quantitative assessment of Emphysema Index (EI) (P=0.008), and with emphysema clusters of given size (Clas 1-4) Clas 1, Clas 3 and Clas 4 (P<0.001). Visually assessed severity grade of emphysema correlated with age (P<0.001), pack-years of smoking history (P=0.002) and EI (P<0.001). There was a correlation between lung cancer occurrence and pack-years (P<0.001), age (P<0.001), and presence of CLE (P<0.001) but no correlation with gender (P=0.88) and EI (P=0.32) was found. In the logistic regression model pack-years, age, qualitative severity of CLE and Clas 1 were significant factors correlated with lung cancer occurrence (P<0.001). Conclusions: Qualitative and quantitative emphysema evaluation correlate with each other. Both, presence and severity of CLE correlate with higher incidence of lung cancer. Severity of visually assessed emphysema, age and pack-years of smoking are significant predictors of lung cancer occurrence.

Segmentation-based BI-RADS ensemble classification of breast tumours in ultrasound images.

BACKGROUND: The development of computer-aided diagnosis systems in breast cancer imaging is exponential. Since 2016, 81 papers have described the automated segmentation of breast lesions in ultrasound images using artificial intelligence. However, only two papers have dealt with complex BI-RADS classifications. PURPOSE: This study addresses the automatic classification of breast lesions into binary classes (benign vs. malignant) and multiple BI-RADS classes based on a single ultrasonographic image. Achieving this task should reduce the subjectivity of an individual operator's assessment. MATERIALS AND METHODS: Automatic image segmentation methods (PraNet, CaraNet and FCBFormer) adapted to the specific segmentation task were investigated using the U-Net model as a reference. A new classification method was developed using an ensemble of selected segmentation approaches. All experiments were performed on publicly available BUS B, OASBUD, BUSI and private datasets. RESULTS: FCBFormer achieved the best outcomes for the segmentation task with intersection over union metric values of 0.81, 0.80 and 0.73 and Dice values of 0.89, 0.87 and 0.82, respectively, for the BUS B, BUSI and OASBUD datasets. Through a series of experiments, we determined that adding an extra 30-pixel margin to the segmentation mask counteracts the potential errors introduced by the segmentation algorithm. An assembly of the full image classifier, bounding box classifier and masked image classifier was the most accurate for binary classification and had the best accuracy (ACC; 0.908), F1 (0.846) and area under the receiver operating characteristics curve (AUROC; 0.871) in the BUS B and ACC (0.982), F1 (0.984) and AUROC (0.998) in the UCC BUS datasets, outperforming each classifier used separately. It was also the most effective for BI-RADS classification, with ACC of 0.953, F1 of 0.920 and AUROC of 0.986 in UCC BUS. Hard voting was the most effective method for dichotomous classification. For the multi-class BI-RADS classification, the soft voting approach was employed. CONCLUSIONS: The proposed new classification approach with an ensemble of segmentation and classification approaches proved more accurate than most published results for binary and multi-class BI-RADS classifications.

Lung ultrasound in a nutshell. Lines, signs, some applications, and misconceptions from a radiologist's point of view. Part 2.

In recent years, lung ultrasound (LUS) has developed rapidly, and it is gaining growing popularity in various scenarios. There are constant attempts to introduce it to new fields. In addition, knowledge regarding lung and LUS has been augmented by the recent COVID-19 pandemics. In the first part of this review we discuss lines, signs and pheno-mena, profiles, some applications, and misconceptions. An aim of the second part of the review is mainly to discuss some advanced applications of LUS, including lung elastography, lung spectroscopy, colour and spectral Doppler, contrast-enhanced ultrasound of lung, speckled tracking of pleura, quantification of pulmonary oedema, predicting success of talc pleurodesis, asthma exacerbations, detecting chest wall invasion by tumours, lung biopsy, estimating pleural effusion volume, and predicting mechanical ventilatory weaning outcome. For this purpose, we reviewed literature concerning LUS.

The use of intravascular contrast media in patients with impaired kidney function - joint clinical practice position statement of the Polish Society of Nephrology and the Polish Medical Society of Radiology.

Radiological procedures utilising intravascular contrast media (ICM) are fundamental to modern medicine, enhancing diagnostics and treatment in diverse medical fields. However, the application of ICM has been constrained in patients with compromised kidney function due to perceived nephrotoxic risks, called contrast-induced nephropathy or contrastinduced acute kidney injury. Historical evidence marked ICM as a possible contributor to kidney damage. This led to restrictive guidelines advocating limited ICM use in patients with impaired renal function, preventing crucial radiographic interventions in patients with acute kidney injury (AKI) and chronic kidney disease. Recent advances challenge these traditional views. In particular, no direct causal relationship has been confirmed between contrast admi-nistration and elevated serum creatinine concentrations in humans. Furthermore, contemporary research models and meta-analyses do not associate AKI with contrast usage. This paper, prepared by a cross-disciplinary team of nephrologists and radiologists, presents updated guidelines for ICM application amid renal function impairments, emphasising the reduced nephrotoxic risks currently understood and loosening the previous restrictive approach in patients with renal dysfunction.

The Complex Network of Cytokines and Chemokines in Pediatric Patients with Long-Standing Type 1 Diabetes.

Type 1 diabetes (T1D) is a progressive disorder leading to the development of microangiopathies and macroangiopathies. Numerous cytokines and chemokines are involved in the pathogenesis of T1D complications. The study aimed to assess the presence of complications in patients with long-standing T1D and its relationship with serum biomarker concentrations. We examined 52 T1D subjects, with a disease duration ≥4 years and 39 healthy controls. The group of T1D patients was further divided into subgroups based on the duration of the disease (<7 years and ≥7 years) and the metabolic control assessed by the HbAlc level (<8% and ≥8%). We used Luminex Technology to assess a wide range of biomarker concentrations. A 24 h urine test was done to evaluate the rate of albuminuria. Optical coherence tomography (OCT) was conducted to detect early retinopathic changes. Subclinical atherosclerosis was assessed by measuring the carotid intima-media thickness (IMT). T1D patients showed remarkably higher concentrations of EGF, eotaxin/CCL11, MDC/CCL22, sCD40L, TGF-α, and TNF-α. Moreover, we reported statistically significant correlations between cytokines and IMT. Biomarker concentrations depend on numerous factors such as disease duration, metabolic control, and the presence of complications. Although the majority of pediatric T1D patients do not present signs of overt complications, it is indispensable to conduct the screening for angiopathies already in childhood, as its early recognition may attenuate the further progression of complications.

Evaluation of Conventional Cardiovascular Risk Factors and Ordinal Coronary Artery Calcium Scoring in a Lung Cancer Screening Cohort.

(1) Background: Lung cancer screening (LCS) consists of low-dose computed tomography (LDCT) results to reduce lung cancer-related mortality. The LCS program has a unique opportunity to impact CVD mortality by providing tools for CVD risk assessment and implementing preventative strategies. In this study, we estimated standardized CVD risk (SCORE) and assessed the prevalence of coronary artery calcium (CAC) in a Polish LCS cohort. (2) Methods: In this observational study, 494 LCS participants aged 50-79 years with a cigarette smoking history of at least 30 pack-years were included. Medical history, anthropometric measurements, blood pressure measurements, serum glucose, and cholesterol levels were assessed in one visit. CVD risk assessment using SCORE tables was performed. The results were compared to the general population (NATPOL 2011 study). On LDCT scans, CAC was classified using an Ordinal Score ranging from 0 to 12. (3) Results: The prevalence of classic cardiovascular risk factors was very high. Among study participants, 83.7% of men and 40.7% of women were classified with a very high CVD SCORE risk (>10%). CAC was reported in 190 (47%) participants. Calcification was categorized as severe (CAC ≥ 4) in 84 (21%) participants. (4) Conclusions: Due to the high cardiovascular risk, intensive preventive strategies are recommended for LCS participants.

To assess the quantitative features of focal liver lesions in gadoxetic acid enhanced MRI and to determine whether these features can accurately differentiate benign form malignant lesions.

PURPOSE: The study aims at assessing the quantitative features which distinguish focal liver lesions (FLLs) in gadoxetic acid (GA) enhanced liver MRI and at determining whether these features can accurately differentiate benign from malignant lesions. MATERIAL AND METHODS: 107 patients with 180 unequivocal FLLs in previous examinations were included in a single-center retrospective study. All patients underwent a MRI test of the liver with GA. 99 benign and 74 malignant lesions were included. The group of benign lesions consisted of 60 focal nodular hyperplasias (FNH), 22 hemangiomas (HMG), 6 hepatic adenomas (HA), and 11 other benign lesions (1 angiomyolipioma, 6 lesions histopathology diagnoses as benign without further specification, or ones lacking features of malignancy, and 4 lesions radiologically diagnosed as benign which remained stable in the follow-up studies). The group of malignant lesions consisted of primary 51 hepatocellular carcinomas, 12 metastases, and 11 metastases from melanoma malignum (MM meta). 7 FLLs were excluded (4 cases of uncertain histopathological diagnosis, 2 cholangiocarcinomas, and 1 regenerative nodule). For the included lesions ROI (region of interest) measurements were taken by two observers in the T2-w, ADC (apparent diffusion coefficient) and in the T1-w sequence in the hepatobiliary phase (HBP). The interobserver agreement was evaluated with the Wilcoxon test. The Kruskal - Wallis, Mann - Whitney U and post hoc Dunn's tests were applied to assess if there were any significant differences in the ROI values between individual lesions. The variables with the p values of < 0.05 were considered statistically significant. RESULTS: We found significant differences in the ROI values between lesions with p < 0.0001. Strikingly high ROI values in the T2-w sequence were found for HMG. The lowest ADC values were encountered for metastases and MM metastases. The highest ROI values in the HBP were found for FNH, and the lowest for metastases. We also found statistically significant differences in the ROI values between benign and malignant lesions with benign lesions presenting statistically higher ROI values compared to malignant lesions. CONCLUSIONS: There were significant differences in the ROI values among different types of FLLs. The predominant quantitative feature in the T2-w sequence was a strikingly high ROI value for HMG. Benign lesions presented statistically higher ROI values in the T2-w, ADC, and HBP sequences compared to malignant lesions. This was true for all lesions except for HA.

Choroid Plexus Volume Change-A Candidate for a New Radiological Marker of MS Progression.

(1) Background: Multiple sclerosis (MS) is an auto-immune, chronic, neuroinflammatory, demyelinating disease that affects mainly young patients. This progressive inflammatory process causes the chronic loss of brain tissue and results in a deterioration in quality of life. To monitor neuroinflammatory process activity and predict the further development of disease, it is necessary to find a suitable biomarker that could easily be used. In this research, we verify the usability of choroid plexus (CP) volume, a new MS biomarker, in the monitoring of the progression of multiple sclerosis disease. (2) Methods: A single-center, prospective study with three groups of patients was conducted based on the following groups: MS patients who received experimental cellular therapy (Treg), treatment-naïve MS patients and healthy controls. (3) Results: This study concludes that there is a correlation between the CPV/TIV (choroid plexus/total intracranial volume) ratio and the progress of multiple sclerosis disease-patients with MS (MS + Treg) had larger volumes of choroid plexuses. CPV/TIV ratios in MS groups were constantly and significantly growing. In the Treg group, patients with relapses had larger plexuses in comparison to the group with no relapses of MS. A similar correlation was observed for the GD+ group (patients with postcontrast enhancing plaques) compared against the non-GD group (patients without postcontrast enhancing plaques). (4) Conclusion: Choroid plexus volume, due to its immunological function, correlates with the inflammatory process in the central nervous system. We consider it to become a valuable radiological biomarker of MS activity.

Lung ultrasound in a nutshell. Lines, signs, some applications, and misconceptions from a radiologist's point of view.

In recent years, lung ultrasound (LUS) has developed rapidly, and it is growing in popularity in various scenarios. It has become especially popular among clinicians. There are constant attempts to introduce it in new fields, with quite a strong resistance in the radiological community. In addition, knowledge regarding lung and LUS has been augmented by the recent COVID-19 pandemic. Unfortunately, this has led to many misconceptions. The aim of this review is to discuss lines, signs, and phenomena that can be seen in LUS in order to create a single, easily available compendium for radiologists and promote consistency in LUS nomenclature. Some simplified suggestions are presented.

Cardiac Magnetic Resonance Relaxometry Parameters, Late Gadolinium Enhancement, and Feature-Tracking Myocardial Longitudinal Strain in Patients Recovered from COVID-19.

COVID-19 infection is associated with myocarditis, and cardiovascular magnetic resonance (CMR) is the reference non-invasive imaging modality for myocardial tissue characterization. Quantitative CMR techniques, such as feature tracking (FT) and left ventricular global longitudinal strain (GLS) analysis, have been introduced as promising diagnostic tools to improve the diagnostic accuracy of suspected myocarditis. The aim of this study was to analyze the left ventricular global longitudinal strain (GLS) and the influence of T1 and T2 relaxation times, ECV, and LGE appearance on GLS parameters in a multiparametric imaging protocol in patients who recovered from COVID-19. The 86 consecutive patients enrolled in the study had all recovered from mild or moderate COVID-19 infections; none required hospitalization. Their persistent symptoms and suspected myocarditis led to cardiac magnetic resonance imaging within 3 months of the diagnosis of the SARS-CoV-2 infection. Results: Patients with GLS less negative than -15% had significantly lower LVEF (53.6% ± 8.9 vs. 61.6% ± 4.8; <0.001) and were significantly more likely to have prolonged T1 (28.6% vs. 7.5%; p = 0.019). Left ventricular GLS correlated significantly with T1 (r = 0.303; p = 0.006) and LVEF (r = -0.732; p < 0.001). Left ventricular GLS less negative than -15% was 7.5 times more likely in patients with prolonged T1 (HR 7.62; 95% CI 1.25-46.64). The reduced basal inferolateral longitudinal strain had a significant impact on the global left ventricular longitudinal strain. ROC results suggested that a GLS of 14.5% predicted prolonged T1 relaxation time with the best sensitivity and specificity. Conclusions: CMR abnormalities, including a myocarditis pattern, are common in patients who have recovered from COVID-19. The CMR feature-tracking left ventricular GLS is related to T1 relaxation time and may serve as a novel parameter to detect global and regional myocardial injury and dysfunction in patients with suspected myocardial involvement after recovery from COVID-19.

Prostate Cancer and Its Mimics-A Pictorial Review.

BACKGROUND: Multiparametric prostate MRI (mpMRI) is gaining wider recommendations for diagnosing and following up on prostate cancer. However, despite the high accuracy of mpMRI, false positive and false negative results are reported. Some of these may be related to normal anatomic structures, benign lesions that may mimic cancer, or poor-quality images that hamper interpretation. The aim of this review is to discuss common potential pitfalls in the interpretation of mpMRI. METHODS: mpMRI of the prostates was performed on 3T MRI scanners (Philips Achieva or Siemens Magnetom Vida) according to European Society of Urogenital Radiology (ESUR) guidelines and technical requirements. RESULTS: This pictorial review discusses normal anatomical structures such as the anterior fibromuscular stroma, periprostatic venous plexus, central zone, and benign conditions such as benign prostate hyperplasia (BPH), post-biopsy hemorrhage, prostatitis, and abscess that may imitate prostate cancer, as well as the appearance of prostate cancer occurring in these locations. Furthermore, suggestions on how to avoid these pitfalls are provided, and the impact of image quality is also discussed. CONCLUSIONS: In an era of accelerating prostate mpMRI and high demand for high-quality interpretation of the scans, radiologists should be aware of these potential pitfalls to improve their diagnostic accuracy.

Physical activity and the brain myelin content in humans.

New imaging sequences and biophysical models allow adopting magnetic resonance imaging (MRI) for in vivo myelin mapping in humans. Understanding myelination and remyelination processes in the brain is fundamental from the perspective of proper design of physical exercise and rehabilitation schemes that aim to slow down demyelination in the aging population and to induce remyelination in patients with neurodegenerative diseases. Therefore, in this review we strive to provide a state-of-the art summary of the existing MRI studies in humans focused on the effects of physical activity on myelination/remyelination. We present and discuss four cross-sectional and four longitudinal studies and one case report. Physical activity and an active lifestyle have a beneficial effect on the myelin content in humans. Myelin expansion can be induced in humans throughout the entire lifespan by intensive aerobic exercise. Additional research is needed to determine (1) what exercise intensity (and cognitive novelty, which is embedded in the exercise scheme) is the most beneficial for patients with neurodegenerative diseases, (2) the relationship between cardiorespiratory fitness and myelination, and (3) how exercise-induced myelination affect cognitive abilities.

Attention-Based Deep Learning System for Classification of Breast Lesions-Multimodal, Weakly Supervised Approach.

Breast cancer is the most frequent female cancer, with a considerable disease burden and high mortality. Early diagnosis with screening mammography might be facilitated by automated systems supported by deep learning artificial intelligence. We propose a model based on a weakly supervised Clustering-constrained Attention Multiple Instance Learning (CLAM) classifier able to train under data scarcity effectively. We used a private dataset with 1174 non-cancer and 794 cancer images labelled at the image level with pathological ground truth confirmation. We used feature extractors (ResNet-18, ResNet-34, ResNet-50 and EfficientNet-B0) pre-trained on ImageNet. The best results were achieved with multimodal-view classification using both CC and MLO images simultaneously, resized by half, with a patch size of 224 px and an overlap of 0.25. It resulted in AUC-ROC = 0.896 ± 0.017, F1-score 81.8 ± 3.2, accuracy 81.6 ± 3.2, precision 82.4 ± 3.3, and recall 81.6 ± 3.2. Evaluation with the Chinese Mammography Database, with 5-fold cross-validation, patient-wise breakdowns, and transfer learning, resulted in AUC-ROC 0.848 ± 0.015, F1-score 78.6 ± 2.0, accuracy 78.4 ± 1.9, precision 78.8 ± 2.0, and recall 78.4 ± 1.9. The CLAM algorithm's attentional maps indicate the features most relevant to the algorithm in the images. Our approach was more effective than in many other studies, allowing for some explainability and identifying erroneous predictions based on the wrong premises.

Pathological changes or technical artefacts? The problem of the heterogenous databases in COVID-19 CXR image analysis.

BACKGROUND: When the COVID-19 pandemic commenced in 2020, scientists assisted medical specialists with diagnostic algorithm development. One scientific research area related to COVID-19 diagnosis was medical imaging and its potential to support molecular tests. Unfortunately, several systems reported high accuracy in development but did not fare well in clinical application. The reason was poor generalization, a long-standing issue in AI development. Researchers found many causes of this issue and decided to refer to them as confounders, meaning a set of artefacts and methodological errors associated with the method. We aim to contribute to this steed by highlighting an undiscussed confounder related to image resolution. METHODS: 20 216 chest X-ray images (CXR) from worldwide centres were analyzed. The CXRs were bijectively projected into the 2D domain by performing Uniform Manifold Approximation and Projection (UMAP) embedding on the radiomic features (rUMAP) or CNN-based neural features (nUMAP) from the pre-last layer of the pre-trained classification neural network. Additional 44 339 thorax CXRs were used for validation. The comprehensive analysis of the multimodality of the density distribution in rUMAP/nUMAP domains and its relation to the original image properties was used to identify the main confounders. RESULTS: nUMAP revealed a hidden bias of neural networks towards the image resolution, which the regular up-sampling procedure cannot compensate for. The issue appears regardless of the network architecture and is not observed in a high-resolution dataset. The impact of the resolution heterogeneity can be partially diminished by applying advanced deep-learning-based super-resolution networks. CONCLUSIONS: rUMAP and nUMAP are great tools for image homogeneity analysis and bias discovery, as demonstrated by applying them to COVID-19 image data. Nonetheless, nUMAP could be applied to any type of data for which a deep neural network could be constructed. Advanced image super-resolution solutions are needed to reduce the impact of the resolution diversity on the classification network decision.

POLCOVID: a multicenter multiclass chest X-ray database (Poland, 2020-2021).

The outbreak of the SARS-CoV-2 pandemic has put healthcare systems worldwide to their limits, resulting in increased waiting time for diagnosis and required medical assistance. With chest radiographs (CXR) being one of the most common COVID-19 diagnosis methods, many artificial intelligence tools for image-based COVID-19 detection have been developed, often trained on a small number of images from COVID-19-positive patients. Thus, the need for high-quality and well-annotated CXR image databases increased. This paper introduces POLCOVID dataset, containing chest X-ray (CXR) images of patients with COVID-19 or other-type pneumonia, and healthy individuals gathered from 15 Polish hospitals. The original radiographs are accompanied by the preprocessed images limited to the lung area and the corresponding lung masks obtained with the segmentation model. Moreover, the manually created lung masks are provided for a part of POLCOVID dataset and the other four publicly available CXR image collections. POLCOVID dataset can help in pneumonia or COVID-19 diagnosis, while the set of matched images and lung masks may serve for the development of lung segmentation solutions.

Assessment of the corpus callosum size in male individuals with high intelligence quotient (members of Mensa International).

OBJECTIVES: The aim of this study was to assess the size of the corpus callosum in members of Mensa International, which is the world's largest and oldest high-intelligence quotient (IQ) society. METHODS: We performed T2-weighted magnetic resonance imaging (Repetition Time, TR = 3200 ms, Time of Echo, TE = 409 ms) to examine the brain of members of Mensa International (Polish national group) in order to assess the size of the corpus callosum. Results from 113 male MENSA members and 96 controls in the age range of 21-40 years were analyzed. RESULTS: The comparative analysis showed that the mean length of the corpus callosum and the thickness of the isthmus were significantly greater in the Mensa members compared to the control groups. A statistically significant difference was also identified in the largest linear dimension of the brain from the frontal lobe to the occipital lobe. The mean corpus callosum cross-sectional area and its ratio to the brain area were significantly greater in the Mensa members. CONCLUSIONS: The results show that the dimensions (linear measures and midsagittal cross-sectional surface area) of the corpus callosum were significantly greater in the group of Mensa members than in the controls.

Polish recommendations for diagnosis and therapy of paediatric stroke.

Stroke remains one of the greatest health challenges worldwide, due to a high mortality rate and, despite great progress in its treatment, the significant disability that it causes. Studies conducted around the world show that the diagnosis of stroke in children is often significantly delayed. Paediatric ischaemic arterial stroke (PAIS) is not only a problem that varies greatly in frequency compared to the adult population, it is also completely different in terms of its risk factors, clinical course and outcome. The main reason for the lack of a rapid diagnosis of PAIS is a lack of access to neuroimaging under general anaesthesia. The insufficient knowledge regarding PAIS in society as a whole is also of great importance. Parents and carers of children should always bear in mind that paediatric age is not a factor that excludes a diagnosis of stroke. The aim of this article was to develop recommendations for the management of children with acute neurological symptoms suspected of ischaemic stroke and further treatment after confirmation of the ischaemic aetiology of the problem. These recommendations are based on current global recommendations for the management of children with stroke, but our goal was also to match them as closely as possible to the needs and technical diagnostic and therapeutic possibilities encountered in Poland. Due to the multifactorial problem of stroke in children, not only paediatric neurologists but also a neurologist, a paediatric cardiologist, a paediatric haematologist and a radiologist took part in the preparation of these recommendations.

The association between white matter tract structural connectivity and information processing speed in relapsing-remitting multiple sclerosis.

BACKGROUND: Information processing speed (IPS) deterioration is common in relapsing-remitting multiple sclerosis (RRMS) patients [1] and might severely affect quality of life and occupational activity. However, understanding of its neural substrate is not fully elucidated. We aimed to investigate the associations between MRI-derived metrics of neuroanatomical structures, including the tracts, and IPS. METHODS: Symbol Digit Modalities Test (SDMT), Paced Auditory Serial Addition Test (PASAT), and Color Trails Test (CTT) were used to evaluate IPS in 73 RRMS consecutive patients, all undergoing only interferon beta (IFN-ß) therapy during the study. At the same time, 1.5T MRI including diffusion tensor imaging (DTI) data was acquired for each recruited subject. We analyzed volumetric and diffusion MRI measures (FreeSurfer 6.0) including normalized brain volume (NBV), cortical thickness (thk), white matter hypointensities (WMH), volume (vol), diffusion parameters: mean (MD), radial (RD), axial (AD) diffusivities, and fractional anisotropy (FA) of 18 major white-matter (WM) tracts. Multiple linear regression model with interaction resulted in distinguishing the neural substrate of IPS deficit in the IPS impaired subgroup of patients. RESULTS: The most significant tract abnormalities contributing to IPS deficit were right inferior longitudinal fasciculus (R ILF) FA, forceps major (FMAJ) FA, forceps minor (FMIN) FA, R uncinate fasciculus (UNC) AD, R corticospinal tract (CST) FA, and left superior longitudinal fasciculus FA (L SLFT). Among volumetric MRI metrics, IPS deficit was associated with L and R thalamic vol. and cortical thickness of insular regions. CONCLUSION: In this study, we showed that disconnection of the selected WM tracts, in addition to cortical and deep gray matter (GM) atrophy, might underlie IPS deficit in RRMS patients but more extensive studies are needed for precise associations.