A brain tumor is one of the foremost reasons for the rise in mortality among children and adults. A brain tumor is a mass of tissue that propagates out of control of the normal forces that regulate growth inside the brain. A brain tumor appears when one type of cell changes from its normal characteristics and grows and multiplies abnormally. The unusual growth of cells within the brain or inside the skull, which can be cancerous or non-cancerous has been the reason for the death of adults in developed countries and children in under developing countries like Ethiopia. The studies have shown that the region growing algorithm initializes the seed point either manually or semi-manually which as a result affects the segmentation result. However, in this paper, we proposed an enhanced region-growing algorithm for the automatic seed point initialization. The proposed approach’s performance was compared with the state-of-the-art deep learning algorithms using the common dataset, BRATS2015. In the proposed approach, we applied a thresholding technique to strip the skull from each input brain image. After the skull is stripped the brain image is divided into 8 blocks. Then, for each block, we computed the mean intensities and from which the five blocks with maximum mean intensities were selected out of the eight blocks. Next, the five maximum mean intensities were used as a seed point for the region growing algorithm separately and obtained five different regions of interest (ROIs) for each skull stripped input brain image. The five ROIs generated using the proposed approach were evaluated using dice similarity score (DSS), intersection over union (IoU), and accuracy (Acc) against the ground truth (GT), and the best region of interest is selected as a final ROI. Finally, the final ROI was compared with different state-of-the-art deep learning algorithms and region-based segmentation algorithms in terms of DSS. Our proposed approach was validated in three different experimental setups. In the first experimental setup where 15 randomly selected brain images were used for testing and achieved a DSS value of 0.89. In the second and third experimental setups, the proposed approach scored a DSS value of 0.90 and 0.80 for 12 randomly selected and 800 brain images respectively. The average DSS value for the three experimental setups was 0.86.

Background: Etiologies of neural tube defects (NTDs) are multifactorial. Genetic, epigenetic and environmental factors may contribute to their reported variation in prevalence across the globe. Ethiopia has among the highest reported NTD prevalence globally, making investigation of genetic determinants in this high-risk population particularly important for advancing the understanding of NTD etiology. Genes involved in folate metabolism, such as the reduced folate carrier 1 (RFC1), have been investigated for the potential associations with NTDs, but findings throughout the literature remain inconsistent and inconclusive. Objective: The aim of this study was to determine an association of RFC-1 polymorphism at rs1131596 and rs1051266 loci (functional variants previously implicated in folate transport efficiency and NTD susceptibility) among mothers with the occurrence of NTDs in their offspring in Ethiopia. Methods: A case–control study involving 250 mothers (187 controls and 63 cases) of children with or without NTDs was conducted in Addis Ababa, Ethiopia from April 2022, to September 2024. A total of 250 maternal whole blood samples were systematically collected and subjected to genetic analysis at loci rs1131596 and rs1051266 by polymerase chain reaction (PCR) and Sanger sequencing. Results: Detection of heterozygous (TC) and homozygous (CC) genotypes for SNP rs1131596 (−43T>C) in the RFC1 gene was 27.2%, with heterozygous (TC) comprising 10.4% and homozygous (CC) 16.8%. In contrast, for the rs1051266 (80A>G), the prevalence of the AG polymorphism was 28% while the GG polymorphism was 16.4%, resulting in a cumulative prevalence of 44.4%. The presence of maternal RFC-1 polymorphism at these two locations were not associated with significantly (p = 0.601 & p = 0.225 respectively) higher odds for NTD births. Conclusions: This study did not reveal significant association between maternal RFC1 gene polymorphisms and NTD-affected births. Comprehensive whole-genome sequencing of affected off-spring is essential to identify specific mutations or polymorphisms that may individually or collaboratively affect the risk of NTDs in the Ethiopian context.

Background: Etiologies of neural tube defects (NTDs) are multifactorial. Genetic, epigenetic and environmental factors may contribute to their reported variation in prevalence across the globe. Ethiopia has among the highest reported NTD prevalence globally, making investigation of genetic determinants in this high-risk population particularly important for advancing understanding of NTD etiology. Genes involved in folate metabolism, such as the reduced folate carrier 1 (RFC1), have been investigated for the potential associations with NTDs, but findings throughout the literature remain inconsistent and inconclusive. Objective: The aim of this study was to determine an association of RFC-1 polymorphism at rs1131596 and rs1051266 loci (functional variants previously implicated in folate transport efficiency and NTD susceptibility) among mothers with the occurrence of NTDs in their offspring in Ethiopia. Methods: A case-control study involving 250 mothers (187 controls and 63 cases) of children with or without NTDs was conducted in Addis Ababa, Ethiopia between April, 2022, to September, 2024. A total of 250 maternal whole blood samples were systematically collected and subjected to genetic analysis at loci rs1131596 and rs1051266 by PCR (polymerase chain reaction) and Sanger sequencing. Results: Detection of heterozygous (TC) and homozygous (CC) genotypes for SNP rs1131596 (-43T>C) in the RFC1 gene was 27.2%, with heterozygous (TC) comprising 10.4% and homozygous (CC) 16.8 %. In contrast, for the rs1051266 (80A>G), the prevalence of the AG polymorphism was 28% while the GG polymorphism was 16.4%, resulting in a cumulative prevalence of 44.4%. The presence of maternal RFC-1 polymorphism at these two locations did not show significant association (p =0.601 & p = 0.225 respectively) with increased risk for NTD births. Conclusion: This study did not reveal significant association between maternal RFC-1 gene polymorphisms and NTD-affected births. Comprehensive whole-genome sequencing of affected off springs is essential to identify specific mutations or polymorphisms that may individually or collaboratively affect the risk of NTDs in the Ethiopian context.