What does the water inside the brain tell us? Diffusion tensor imaging

The brain consist of about 75 percent water. Diffusion tensor imaging (DTI) is an advanced magnetic resonance (MR) technique imaging that has been developed for diagnostic and research in medicine. It can be use DTI tractography to better understand degenerating axons of white matter lesions in some neurological diseases such as MS, AD, trauma, cerebral ischemia, epilepsy, brain tumors and metabolic disorders

Quantitative Susceptibility Mapping in Identification of Intracranial Hemorrhage: A Case Report

Differentiation of intracranial hemorrhage andcalcification on conventional MR images is often challenging. Both pathologiesshow varying signal intensities on T1- and T2-weighted images. Phase imagesobtained in Susceptibility Weighted Imaging[1] and Quantitative SusceptibilityMapping[2] were utilized in identification of hemorrhage and calcification.This study explores the benefits of QSM on a case with hemorrhages and compareits findings with SWI phase images.&nbsp; &nbsp;QSM provides a map of tissue magnetic susceptibility.The voxel intensity in QSM is linearly proportional to the underlying tissueapparent magnetic susceptibility, which is useful for chemical identificationand quantification of specific biomarkers including iron and calcium[2]. Case: MR images of 10-year-old patient with diagnosis ofhemorrhage and microhemorrhages were analyzed. Images consisted of conventionalMRI, SWI and multi-echo gradient echo (GE) sequence. QSM images werereconstructed from multi-echo GE images[3]. Both QSM images and SWI phaseimages were found successful in identifying microhemorrhages. The hemorrhagewas observed to have heterogeneous appearance on SWI in contrast to QSM. The comparativeresults of SWI and QSM will be discussed in the poster.</p

Alzheimer Disease Associated Loci: <em>APOE</em> Single Nucleotide Polymorphisms in Marmara Region

Alzheimer’s disease (AD) is a major global health challenge, especially among individuals aged 65 or older. According to population health studies, Turkey has the highest AD prevalence in the Middle East and Europe. To accurately determine the frequencies of common and rare APOE single nucleotide polymorphisms (SNPs) in the Turkish population residing in the Marmara Region, we conducted a retrospective study analyzing APOE variants in 588 individuals referred to the Bursa Uludag University Genetic Diseases Evaluation Center. Molecular genotyping, clinical exome sequencing, bioinformatics analysis, and statistical evaluation were employed to identify APOE polymorphisms and assess their distribution. The study revealed the frequencies of APOE alleles as follows: ε4 at 9.94%, ε2 at 9.18%, and ε3 at 80.68%. The gender-based analysis in our study uncovered a tendency for females to exhibit a higher prevalence of mutant genotypes across various SNPs. The most prevalent haplotype observed was ε3/ε3, while rare APOE SNPs were also identified. These findings align with global observations, underscoring the significance of genetic diversity and gender-specific characteristics in comprehending health disparities and formulating preventive strategies

BRCA Variations Risk Assessment in Breast Cancers Using Different Artificial Intelligence Models

Artificial intelligence provides modelling on machines by simulating the human brain using learning and decision-making abilities. Early diagnosis is highly effective in reducing mortality in cancer. This study aimed to combine cancer-associated risk factors including genetic variations and design an artificial intelligence system for risk assessment. Data from a total of 268 breast cancer patients have been analysed for 16 different risk factors including genetic variant classifications. In total, 61 BRCA1, 128 BRCA2 and 11 both BRCA1 and BRCA2 genes associated breast cancer patients' data were used to train the system using Mamdani's Fuzzy Inference Method and Feed-Forward Neural Network Method as the model softwares on MATLAB. Sixteen different tests were performed on twelve different subjects who had not been introduced to the system before. The rates for neural network were 99.9% for training success, 99.6% for validation success and 99.7% for test success. Despite neural network's overall success was slightly higher than fuzzy logic accuracy, the results from developed systems were similar (99.9% and 95.5%, respectively). The developed models make predictions from a wider perspective using more risk factors including genetic variation data compared with similar studies in the literature. Overall, this artificial intelligence models present promising results for BRCA variations' risk assessment in breast cancers as well as a unique tool for personalized medicine software

Re-examining the characteristics of pediatric multiple sclerosis in the era of antibody-associated demyelinating syndromes.

Background: The discovery of anti-myelin oligodendrocyte glycoprotein (MOG)-IgG and anti-aquaporin 4 (AQP4)-IgG and the observation on certain patients previously diagnosed with multiple sclerosis (MS) actually have an antibody-mediated disease mandated re-evaluation of pediatric MS series. Aim: To describe the characteristics of recent pediatric MS cases by age groups and compare with the cohort established before 2015. Method: Data of pediatric MS patients diagnosed between 2015 and 2021 were collected from 44 pediatric neurology centers across Turkiye. Clinical and paraclinical features were compared between patients with dis-ease onset before 12 years (earlier onset) and >= 12 years (later onset) as well as between our current (2015-2021) and previous (< 2015) cohorts. Results: A total of 634 children (456 girls) were enrolled, 89 (14%) were of earlier onset. The earlier-onset group had lower female/male ratio, more frequent initial diagnosis of acute disseminated encephalomyelitis (ADEM), more frequent brainstem symptoms, longer interval between the first two attacks, less frequent spinal cord involvement on magnetic resonance imaging (MRI), and lower prevalence of cerebrospinal fluid (CSF)-restricted oligoclonal bands (OCBs). The earlier-onset group was less likely to respond to initial disease-modifying treatments. Compared to our previous cohort, the current series had fewer patients with onset < 12 years, initial presentation with ADEM-like features, brainstem or cerebellar symptoms, seizures, and spinal lesions on MRI. The female/male ratio, the frequency of sensorial symptoms, and CSF-restricted OCBs were higher than reported in our previous cohort. Conclusion: Pediatric MS starting before 12 years was less common than reported previously, likely due to exclusion of patients with antibody-mediated diseases. The results underline the importance of antibody testing and indicate pediatric MS may be a more homogeneous disorder and more similar to adult-onset MS than previously thought

Clinical and molecular evaluation of MEFV gene variants in the Turkish population: a study by the National Genetics Consortium

Familial Mediterranean fever (FMF) is a monogenic autoinflammatory disorder with recurrent fever, abdominal pain, serositis, articular manifestations, erysipelas-like erythema, and renal complications as its main features. Caused by the mutations in the MEditerranean FeVer (MEFV) gene, it mainly affects people of Mediterranean descent with a higher incidence in the Turkish, Jewish, Arabic, and Armenian populations. As our understanding of FMF improves, it becomes clearer that we are facing with a more complex picture of FMF with respect to its pathogenesis, penetrance, variant type (gain-of-function vs. loss-of-function), and inheritance. In this study, MEFV gene analysis results and clinical findings of 27,504 patients from 35 universities and institutions in Turkey and Northern Cyprus are combined in an effort to provide a better insight into the genotype-phenotype correlation and how a specific variant contributes to certain clinical findings in FMF patients. Our results may help better understand this complex disease and how the genotype may sometimes contribute to phenotype. Unlike many studies in the literature, our study investigated a broader symptomatic spectrum and the relationship between the genotype and phenotype data. In this sense, we aimed to guide all clinicians and academicians who work in this field to better establish a comprehensive data set for the patients. One of the biggest messages of our study is that lack of uniformity in some clinical and demographic data of participants may become an obstacle in approaching FMF patients and understanding this complex disease