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Artificial intelligence (AI) stands at the threshold of revolutionizing clinical oncology, with considerable potential to improve early cancer detection and risk assessment, and to enable more accurate personalized treatment recommendations. However, a notable imbalance exists in the distribution of the benefits of AI, which disproportionately favour those living in specific geographical locations and in specific populations. In this Perspective, we discuss the need to foster the development of equitable AI tools that are both accurate in and accessible to a diverse range of patient populations, including those in low-income to middle-income countries. We also discuss some of the challenges and potential solutions in attaining equitable AI, including addressing the historically limited representation of diverse populations in existing clinical datasets and the use of inadequate clinical validation methods. Additionally, we focus on extant sources of inequity including the type of model approach (such as deep learning, and feature engineering-based methods), the implications of dataset curation strategies, the need for rigorous validation across a variety of populations and settings, and the risk of introducing contextual bias that comes with developing tools predominantly in high-income countries., (© 2024. Springer Nature Limited.)

The global disparity of magnetic resonance imaging (MRI) is a major challenge, with many low- and middle-income countries (LMICs) experiencing limited access to MRI. The reasons for limited access are technological, economic and social. With the advancement of MRI technology, we explore why these challenges still prevail, highlighting the importance of MRI as the epidemiology of disease changes in LMICs. In this paper, we establish a framework to develop MRI with these challenges in mind and discuss the different aspects of MRI development, including maximising image quality using cost-effective components, integrating local technology and infrastructure and implementing sustainable practices. We also highlight the current solutions-including teleradiology, artificial intelligence and doctor and patient education strategies-and how these might be further improved to achieve greater access to MRI., (© 2023 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.)

Objective: This study aims to assess the statistical significance of training parameters in 240 dense UNets (DUNets) used for enhancing low Signal-to-Noise Ratio (SNR) and undersampled MRI in various acquisition protocols. The objective is to determine the validity of differences between different DUNet configurations and their impact on image quality metrics., Materials and Methods: To achieve this, we trained all DUNets using the same learning rate and number of epochs, with variations in 5 acquisition protocols, 24 loss function weightings, and 2 ground truths. We calculated evaluation metrics for two metric regions of interest (ROI). We employed both Analysis of Variance (ANOVA) and Mixed Effects Model (MEM) to assess the statistical significance of the independent parameters, aiming to compare their efficacy in revealing differences and interactions among fixed parameters., Results: ANOVA analysis showed that, except for the acquisition protocol, fixed variables were statistically insignificant. In contrast, MEM analysis revealed that all fixed parameters and their interactions held statistical significance. This emphasizes the need for advanced statistical analysis in comparative studies, where MEM can uncover finer distinctions often overlooked by ANOVA., Discussion: These findings highlight the importance of utilizing appropriate statistical analysis when comparing different deep learning models. Additionally, the surprising effectiveness of the UNet architecture in enhancing various acquisition protocols underscores the potential for developing improved methods for characterizing and training deep learning models. This study serves as a stepping stone toward enhancing the transparency and comparability of deep learning techniques for medical imaging applications., (© 2023. The Author(s), under exclusive licence to European Society for Magnetic Resonance in Medicine and Biology (ESMRMB).)

Traumatic brain injury (TBI) is a leading cause of disability worldwide. Traumatic axonal injury (TAI) is a subtype of TBI resulting from high-impact forces that cause shearing and/or stretching of the axonal fibers in white matter tracts. It is present in almost half of cases of severe TBI and frequently associated with poor functional outcomes. Axonal injury results from axonotomy due to mechanical forces and the activation of a biochemical cascade that induces the activation of proteases. It occurs at a cellular level; hence, conventional imaging modalities often fail to display TAI lesions. However, the advent of novel imaging modalities, such as functional magnetic resonance imaging and fiber tractography, has significantly improved the detection and characteristics of TAI. Furthermore, the significance of several fluid and structural biomarkers has also been researched, while the contribution of omics in the detection of novel biomarkers is currently under investigation. In the present review, we discuss the role of imaging modalities and potential biomarkers in diagnosing, classifying, and predicting the outcome in patients with TAI. [ABSTRACT FROM AUTHOR]

Background: Parkinson’s disease (PD) is a chronic neurodegenerative disorder complicated by cognitive dysfunctions which are associated with increased caregiver burden, pressure on community health facilities, and mortality in affected patients. Most of the data concerning cognitive dysfunctions in PD are from studies conducted in Europe and North America, but there is paucity of data from Sub-Saharan Africa. Objective: The objective of this study is to determine the frequency, pattern and predictors of cognitive impairments amongst patients with Parkinson’s disease. Materials and methods: This was a cross sectional case control study carried out at a tertiary health facility in South-south Nigeria. Participants with PD were consecutively recruited from the neurology outpatient clinics. Demographic and disease-specific data were obtained with the use of a pre-tested questionnaire. Cognitive performance of thirty patients with PD were compared with thirty demographically matched controls using the Community Screening Instrument for Dementia (CSID). CSID was already validated among Nigerians. Results: The frequency of cognitive impairment using the CSID was 50% for PD patients (3.3% for controls). Poor cognitive performance was observed across several cognitive domains including language, executive dysfunction, psychomotor speed, and constructional apraxia among PD patients. The independent predictors of the overall cognitive impairment in patients with PD determined by logistic regression analysis include recall deficiency (p = 0.007), impairment with naming (p = 0.044), apraxia (p = 0.003), Hoen&Yahr staging (p = 0.046), UPDRS score (p = 0.015) and age at presentation (p = 0.014). Conclusion: Cognitive impairments occur more frequently in patients with PD compared to controls. This study also demonstrated the predictive role of severity of disease based on Hoehn &Yahr staging and UPDRS score, and presence of recall deficiency, poor naming ability and apraxia. [ABSTRACT FROM AUTHOR]

Objective: Diagnostic-quality neuroimaging methods are vital for widespread clinical adoption of low field MRI. Spiral imaging is an efficient acquisition method that can mitigate the reduced signal-to-noise ratio at lower field strengths. As concomitant field artifacts are worse at lower field, we propose a generalizable quadratic gradient-field nulling as an echo-to-echo compensation and apply it to spiral TSE at 0.55 T. Materials and methods: A spiral in–out TSE acquisition was developed with a compensation for concomitant field variation between spiral interleaves, by adding bipolar gradients around each readout to minimize phase differences at each refocusing pulse. Simulations were performed to characterize concomitant field compensation approaches. We demonstrate our proposed compensation method in phantoms and (n = 8) healthy volunteers at 0.55 T. Results: Spiral read-outs with integrated spoiling demonstrated strong concomitant field artifacts but were mitigated using the echo-to-echo compensation. Simulations predicted a decrease of concomitant field phase RMSE between echoes of 42% using the proposed compensation. Spiral TSE improved SNR by 17.2 ± 2.3% compared to reference Cartesian acquisition. Discussion: We demonstrated a generalizable approach to mitigate concomitant field artifacts for spiral TSE acquisitions via the addition of quadratic-nulling gradients, which can potentially improve neuroimaging at low-field through increased acquisition efficiency. [ABSTRACT FROM AUTHOR]

While women have greater incidence of dementia, men have higher prevalence of vascular risk factors. This study examined sex differences in risk of screening positive for cognitive impairment after stroke. Ischemic stroke/TIA patients (N = 5969) participated in this prospective, multi-centered study, which screened for cognitive impairment using a validated brief screen. Men showed a higher risk of screening positive for cognitive impairment after adjusting for age, education, stroke severity, and vascular risk factors, suggesting that other factors may be contributing to increased risk among men (OR = 1.34, CI 95% [1.16, 1.55], p < 0.001). The effect of sex on cognitive impairment after stroke warrants further attention. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is a neurological ailment that primarily affects the elderly and necessitates an efficient treatment regimen backed up by extensive care. Despite advancement in the in vivo imaging techniques focussing on early diagnosis of reliable biomarkers using novel magnetic resonance imaging (MRI) and positron emission topography (PET) scans, AD remains largely unexplained and effective preventative and treatment strategies are still lacking. Consequently, research groups are constantly attempting to improve its early detection, using both invasive and non‐invasive techniques with established core markers like Aβ and Tau (t‐tau and p‐tau) proteins. Unfortunately, African American and other black races are facing an increasing burden of closely associated risk factors, and only a few attempts have been made to find effective complementary and alternative therapies for AD cure and management. A greater epidemiology and natural product research are required to deal with the concurrent rise of dementia among quickly ageing African population, which so far have largely been ignored in addition to a disparity in the AD risk factors. We have tried to bring attention to the issue by reviewing up on this predisposition while generating a perspective on how race may affect AD risk and expression. This article also puts emphasis on finding new research leads from African phytodiversity while presenting several of the important species along with their biological agents found helpful in dementia related symptoms. [ABSTRACT FROM AUTHOR]

Background: In Kenya, there is lack of evidence on existing dementia care pathways, with minimal or no presentation for dementia-related symptoms in health care settings. Understanding the services available for people with dementia as well as how communities access the services could offer a practical pattern for policy makers to identify strategies that encourage early detection, care and support for people with dementia and their families. Objectives: To elucidate initial responses of individuals and their families to dementia and challenges encountered in help seeking through care pathways to inform dementia care-related policies and practice. Methods: The Strengthening Responses to dementia in Developing Countries (STRiDE) Kenya team adapted case vignettes (brief hypothetical stories meant to elicit responses on how the characters would behave) developed by the entire STRiDE team. A total of 29 stakeholders were then asked to provide feedback on the completed vignettes and summarize a common pathway to dementia care in Kenya while using the proposed case vignettes. Findings: We found four initial responses to dementia suspicion in Kenya where individuals:(i) Perceive symptoms as normal part of ageing, (ii) Consult a spiritual or traditional healer, (iii) Visit a private clinic or primary health care facilities, or (iv) No action taken. These were the first points within the care pathways which determined the care trajectory the person with dementia would follow. Conclusions: Identification of dementia care pathways could form a basis for improving the way communities perceive dementia etiology and establish standard pathways to care whilst ensuring that some pathways do not further pose an impediment to care and treatment for dementia. [ABSTRACT FROM AUTHOR]

Background: Post-stroke cognitive impairment (PSCI) is a major complication of stroke that affects more than one-third of stroke survivors, threatening their quality of life and increasing the risk of disability and death. Although various studies have described the etiology, epidemiology, and risk factors of PSCI, there are a limited number of comprehensive and accurate reports on research trends and hotspots in this field. Therefore, this review aimed to evaluate research trends, hotspots, and frontiers in PSCI using bibliometric analysis. Methods: We screened the literature spanning 20 years in the Web of Science Core Collection: Science Citation Index Expanded (SCI-Expanded) database from 1 January 2003 to 31 December 2022. We included all eligible literature reports based on our comprehensive search strategy, inclusion criteria, and exclusion criteria. The analysis of annual publications, countries/regions, institutions, journals, co-cited references, and keywords was conducted using CiteSpace and VOSviewer, and the hotspots and major findings of PSCI were summarized. Results: A total of 1,024 publications were included in this review. We found that the number of publications on PSCI increased annually. These publications were published in 75 countries or regions by over 400 institutions. Although Chinese institutions had the highest number of publications, their international influence was limited. The United States showed a strong influence in the field. The journal "Stroke" published the most publications (57) with a high impact factor and was considered the most co-cited journal. The most frequently cited references focused on the prevalence, incidence, neuropsychological assessment scales, criteria, and guidelines of PSCI. The strongest citation burst keywords for PSCI were "neurotrophic factor" and "synaptic plasticity", which were regarded as research focuses and research hotspots, respectively. Conclusion: This review provided a comprehensive summary of the literature of PSCI, identified the authoritative and frequently cited literature and journals, clarified the trends in PSCI research, and highlighted the hotspots in this field. Currently, studies on the mechanisms and treatment of PSCI are limited, and we hope that this review has effectively highlighted the research trajectory of PSCI and will lay the foundation for more innovative research in the future. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is a progressive, neurodegenerative disorder that affects memory, thinking, behavior, and other cognitive functions. Although there is no cure, detecting AD early is important for the development of a therapeutic plan and a care plan that may preserve cognitive function and prevent irreversible damage. Neuroimaging, such as magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomography (PET), has served as a critical tool in establishing diagnostic indicators of AD during the preclinical stage. However, as neuroimaging technology quickly advances, there is a challenge in analyzing and interpreting vast amounts of brain imaging data. Given these limitations, there is great interest in using artificial Intelligence (AI) to assist in this process. AI introduces limitless possibilities in the future diagnosis of AD, yet there is still resistance from the healthcare community to incorporate AI in the clinical setting. The goal of this review is to answer the question of whether AI should be used in conjunction with neuroimaging in the diagnosis of AD. To answer the question, the possible benefits and disadvantages of AI are discussed. The main advantages of AI are its potential to improve diagnostic accuracy, improve the efficiency in analyzing radiographic data, reduce physician burnout, and advance precision medicine. The disadvantages include generalization and data shortage, lack of in vivo gold standard, skepticism in the medical community, potential for physician bias, and concerns over patient information, privacy, and safety. Although the challenges present fundamental concerns and must be addressed when the time comes, it would be unethical not to use AI if it can improve patient health and outcome. [ABSTRACT FROM AUTHOR]

Background: Stroke is a major cause of disability and mortality world-wide. Ischemic stroke is reversible when patients present early. With the current treatment guideline in Nigeria, most ischemic stroke patients present after the 4.5 hours treatment “time window” and are ineligible for intravenous thrombolysis (IVT). However, studies with computed tomography and magnetic resonance imaging have shown variability in the duration of tissue viability, with some remaining viable up to 24 hours and beyond. These advanced imaging are not readily available in the sub-Saharan Africa but the X-ray attenuation ratio of hypoattenuating lesions on the easily accessible nonenhanced computed tomography (NECT), have recently shown to be a valuable alternative. In late presentation, IVT and endovascular thrombectomy (EVT) have proven to have reasonable degree of success in recanalization. Hence, the need for the study. Materials and method: This was a retrospective cross-sectional study of ischemic stroke patients who presented between 4.5 and 24 hours for NECT. The extent of the ischemia was determined using the Alberta stroke programme early CT score (ASPECTS), while the Hounsfield unit ratio of the hypodense lesions was used to determine tissue viability. Results: Fifty-five patients met the inclusion criteria and had a mean age of 58.8 years. Four (7.27%) patients clearly had ASPECTS and Hounsfield unit ratio (HUr) scores suggestive of salvageable penumbral tissue, while another four (7.27%) had the probability of being reversible. Conclusion: Some patients were still eligible for treatment after the current guideline’s 4.5 hours treatment “time window” using the ASPECTS and HUr scores on NECT. [ABSTRACT FROM AUTHOR]

Introduction: Neurocognitive deficits after stroke are a common manifestation and pose a significant impact on the quality of life for patients and families; however, little attention is given to the burden and associated impact of cognitive impairment following stroke. The study aims to determine the prevalence and predictors of post-stroke cognitive impairment (PSCI) among adult stroke patients admitted to tertiary hospitals in Dodoma, Tanzania. Methodology: A prospective longitudinal study is conducted at tertiary hospitals in the Dodoma region, central Tanzania. Participants with the first stroke confirmed by CT/MRI brain aged ≥ 18 years who meet the inclusion criteria are enrolled and followed up. Baseline socio-demographic and clinical factors are identified during admission, while other clinical variables are determined during the three-month follow-up period. Descriptive statistics are used to summarize data; continuous data will be reported as Mean (SD) or Median (IQR), and categorical data will be summarized using proportions and frequencies. Univariate and multivariate logistic regression analysis will be used to determine predictors of PSCI. [ABSTRACT FROM AUTHOR]

This study presents evidence of validity and reliability of the results obtained with the Cognitive Screening (TRIACOG) to evaluate post-stroke adults. The TRIACOG assesses orientation memory, language, arithmetic, praxis, information processing speed, and executive functions. A total of 126 post-stroke adults (M = 63.50; SD = 13.28 years old) and 126 neurologically healthy adults (M = 61.97; SD = 11.48 years old) participated in the study. Performance on the TRIACOG was positively correlated with scores on the Montreal Cognitive Assessment-Basic (MoCA-B), schooling, and reading and writing habits, and negatively correlated with the NIHSS and Rankin scales. Post-stroke adults scored lower and took longer to complete the instrument than neurologically healthy adults. Inter-rater agreement was achieved in scoring the TRIACOG. The TRIACOG presents evidence of validity based on its relationships to other variables (criterion and convergent) and on response processes, in addition to presenting reliability evidence established by inter-rater agreement. We expect that the TRIACOG will be employed by health workers in hospital settings, health units, and medical offices. [ABSTRACT FROM AUTHOR]

Magnetic resonance imaging (MRI) provides excellent soft-tissue contrast for clinical diagnoses and research which underpin many recent breakthroughs in medicine and biology. The post-processing of reconstructed MR images is often automated for incorporation into MRI scanners by the manufacturers and increasingly plays a critical role in the final image quality for clinical reporting and interpretation. For image enhancement and correction, the post-processing steps include noise reduction, image artefact correction, and image resolution improvements. With the recent success of deep learning in many research fields, there is great potential to apply deep learning for MR image enhancement, and recent publications have demonstrated promising results. Motivated by the rapidly growing literature in this area, in this review paper, we provide a comprehensive overview of deep learning-based methods for post-processing MR images to enhance image quality and correct image artefacts. We aim to provide researchers in MRI or other research fields, including computer vision and image processing, a literature survey of deep learning approaches for MR image enhancement. We discuss the current limitations of the application of artificial intelligence in MRI and highlight possible directions for future developments. In the era of deep learning, we highlight the importance of a critical appraisal of the explanatory information provided and the generalizability of deep learning algorithms in medical imaging. [ABSTRACT FROM AUTHOR]

Introduction: Stroke is a significant health problem and is considered one of the leading causes of mortality and permanent disability worldwide. Hypertension is a primary risk factor for stroke. Thus, hypertensive patients' knowledge, attitudes, and practices (KAP) are essential in preventing stroke. Objective: To examine hypertensive patients' KAP towards stroke prevention among rural population in Saudi Arabia. Methods: The study utilized a cross-sectional design. The data were collected using a convenience sampling technique from hypertensive patients in the northwestern rural areas of Riyadh Province. A self-administered questionnaire was adapted from the Stroke Recognition Questionnaire (SRQ) and utilized to assess KAP towards stroke prevention among rural hypertensive patients. The STrengthening of the Reporting of OBservational studies in Epidemiology (STROBE) checklist was used to report the study. Results: A total of 196 hypertensive patients participated in the study. The total mean scores categorization into three quartiles showed that most respondents had poor levels of KAP towards stroke prevention. Weak positive correlations were found between KAP of patients. There were statistically significant differences between respondents' attitudes and practices with their age, education, marital status, and occupational status. Discussion: This study denoted poor levels of KAP towards stroke prevention among hypertensive patients living in rural areas. This study showed the importance of further considering rural population by which improving their health and quality of life. Extending health educational programs and behavior-changing strategies to rural areas is essential to increase hypertensive patients and general public awareness about their stroke prevention and other health-related concerns. [ABSTRACT FROM AUTHOR]

Purpose: To describe the current properties and capabilities of an open‐source hardware and software package that is being developed by many sites internationally with the aim of providing an inexpensive yet flexible platform for low‐cost MRI. Methods: This article describes three different setups from 50 to 360 mT in different settings, all of which used the MaRCoS console for acquiring data, and different types of software interface (custom‐built GUI or Pulseq overlay) to acquire it. Results: Images are presented both from phantoms and in vivo from healthy volunteers to demonstrate the image quality that can be obtained from the MaRCoS hardware/software interfaced to different low‐field magnets. Conclusions: The results presented here show that a number of different sequences commonly used in the clinic can be programmed into an open‐source system relatively quickly and easily, and can produce good quality images even at this early stage of development. Both the hardware and software will continue to develop, and it is an aim of this article to encourage other groups to join this international consortium. [ABSTRACT FROM AUTHOR]

Background: Cerebral small vessel disease (cSVD) is a major cause of stroke and dementia. Previous studies on the prevalence of cSVD are mostly based on single geographically defined cohorts in high-income countries. Studies investigating the prevalence of cSVD in low- and middle-income countries (LMICs) are expanding but have not been systematically assessed. Aim: This study aims to systematically review the prevalence of cSVD in LMICs. Results: Articles were searched from the Ovid MEDLINE and EMBASE databases from 1 January 2000 to 31 March 2022, without language restrictions. Title/abstract screening, full-text review, and data extraction were performed by two to seven independent reviewers. The prevalence of cSVD and study sample size were extracted by pre-defined world regions and health status. The Risk of Bias for Non-randomized Studies tool was used. The protocol was registered on PROSPERO (CRD42022311133). A meta-analysis of proportion was performed to assess the prevalence of different magnetic resonance imaging markers of cSVD, and a meta-regression was performed to investigate associations between cSVD prevalence and type of study, age, and male: female ratio. Of 2743 studies identified, 42 studies spanning 12 global regions were included in the systematic review. Most of the identified studies were from China (n = 23). The median prevalence of moderate-to-severe white matter hyperintensities (WMHs) was 20.5%, 40.5%, and 58.4% in the community, stroke, and dementia groups, respectively. The median prevalence of lacunes was 0.8% and 33.5% in the community and stroke groups. The median prevalence of cerebral microbleeds (CMBs) was 10.7% and 22.4% in the community and stroke groups. The median prevalence of moderate-to-severe perivascular spaces was 25.0% in the community. Meta-regression analyses showed that the weighted median age (51.4 ± 0.0 years old; range: 36.3–80.2) was a significant predictor of the prevalence of moderate-to-severe WMH and lacunes, while the type of study was a significant predictor of the prevalence of CMB. The heterogeneity of studies was high (>95%). Male participants were overrepresented. Conclusions: This systematic review and meta-analysis provide data on cSVD prevalence in LMICs and demonstrated the high prevalence of the condition. cSVD research in LMICs is being published at an increasing rate, especially between 2010 and 2022. More data are particularly needed from Sub-Saharan Africa and Central Europe, Eastern Europe, and Central Asia. [ABSTRACT FROM AUTHOR]

Modern MRI scanners have trended toward higher field strengths to maximize signal and resolution while minimizing scan time. However, high‐field devices remain expensive to install and operate, making them scarce outside of high‐income countries and major population centers. Low‐field strength scanners have drawn renewed academic, industry, and philanthropic interest due to advantages that could dramatically increase imaging access, including lower cost and portability. Nevertheless, low‐field MRI still faces inherent limitations in image quality that come with decreased signal. In this article, we review advantages and disadvantages of low‐field MRI scanners, describe hardware and software innovations that accentuate advantages and mitigate disadvantages, and consider clinical applications for a new generation of low‐field devices. In our review, we explore how these devices are being or could be used for high acuity brain imaging, outpatient neuroimaging, MRI‐guided procedures, pediatric imaging, and musculoskeletal imaging. Challenges for their successful clinical translation include selecting and validating appropriate use cases, integrating with standards of care in high resource settings, expanding options with actionable information in low resource settings, and facilitating health care providers and clinical practice in new ways. By embracing both the promise and challenges of low‐field MRI, clinicians and researchers have an opportunity to transform medical care for patients around the world. Level of Evidence: 5 Technical Efficacy: Stage 6 [ABSTRACT FROM AUTHOR]

Genetic discoveries related to Alzheimer's disease and other dementias have been performed using either large cohorts of affected subjects or multiple individuals from the same pedigree, therefore disregarding mutations in the context of healthy groups. Moreover, a large portion of studies so far have been performed on individuals of European ancestry, with a remarkable lack of epidemiological and genomic data from underrepresented populations. In the present study, 70 single-point mutations on the APP gene in a publicly available genetic dataset that included 2504 healthy individuals from 26 populations were scanned, and their distribution was analyzed. Furthermore, after gametic phase reconstruction, a pairwise comparison of the segments surrounding the mutations was performed to reveal patterns of haplotype sharing that could point to specific cross-population and cross-ancestry admixture events. Eight mutations were detected in the worldwide dataset, with several of them being specific for a single individual, population, or macroarea. Patterns of segment sharing reflected recent historical events of migration and admixture possibly linked to colonization campaigns. These observations reveal the population dynamics of the considered APP mutations in worldwide human groups and support the development of ancestry-informed screening practices for the improvement of precision and personalized approaches to neurodegeneration and dementia. [ABSTRACT FROM AUTHOR]

We compared the trajectory of activities of daily living (ADL) in a nationally representative sample of older Nigerians with their Spanish peers and identified factors to explain country-specific growth models. Data from two household multistage probability samples were used, comprising older adults from Spain (n = 2,011) and Nigeria (n = 1,704). All participants underwent assessment for ADL. Risk factors including sex, household income, urbanicity, years of education, depression, alcohol consumption and smoking were assessed using validated methods. State-space model in continuous time (SSM-CT) methods were used for trajectory comparison. Compared with Nigerians (µADL80=0.44, SE = 0.015, p < 0.001), Spanish older adults had higher disability scores (µADL80=1.23, SE = 0.021, p < 0.001). In SSM-CT models, the rate of increase in disability was faster in Nigerians (Nigeria: β = 0.061, p<.01; Spain: β = 0.028, p < 0.010). An increasing course of disability in the Spanish sample was predicted by female sex, lower education and depression diagnosis. The rate of increase in disability was faster in older Nigerians living in an economically disadvantaged context. [ABSTRACT FROM AUTHOR]

Stroke constitutes a major cause of functional disability with increasing prevalence among adult individuals. Thus, it is of great importance for both clinicians and stroke survivors to be provided with a timely and accurate prognostication of functional outcome. A great number of biomarkers capable of yielding useful information regarding stroke patients' recovery propensity have been evaluated so far with leukoaraiosis being among them. Literature research of two databases (MEDLINE and Scopus) was conducted to identify all relevant studies published between 1 January 2012 and 25 June 2022 that dealt with the clinical utility of a current leukoaraiosis as a prognostic indicator following stroke. Only full-text articles published in English language were included. Forty-nine articles have been traced and are included in the present review. Our findings highlight the prognostic value of leukoaraiosis in an acute stroke setting. The assessment of leukoaraiosis with visual rating scales in CT/MRI imaging appears to be able to reliably provide important insight into the recovery potential of stroke survivors, thus significantly enhancing stroke management. Yielding additional information regarding both short- and long-term functional outcome, motor recovery capacity, hemorrhagic transformation, as well as early neurological deterioration following stroke, leukoaraiosis may serve as a valuable prognostic marker poststroke. Thus, leukoaraiosis represents a powerful prognostic tool, the clinical implementation of which is expected to significantly facilitate the individualized management of stroke patients. [ABSTRACT FROM AUTHOR]

Congenital pulmonary airway malformation (CPAM) is because of excessive and disordered proliferation of bronchial tubular structures of the lung. CPAM is slightly infrequent with the unknown etiology and incidence. The diagnosis of these cases is most of the time performed prenatally by routine ultrasonography scanning. Examination of the resection specimen is mandatory for determining occult malignancy. Complication of untreated congenital cystic adenomatous malformation of lung includes pulmonary hypertension; pulmonary hypoplasia; respiratory distress because of hydrops, pneumothorax, or prematurity; recurrent respiratory tract infection; recurrent pneumonia; hemothorax; pleural effusion; and pneumatocoele. A correct prenatal diagnosis and a clinical assessment of the congenital cystic lung diseases authorize an advanced and successful surgical timing. Surgery is the only definitive treatment and should be undertaken as early as possible to prevent infection and other complications. [ABSTRACT FROM AUTHOR]

MR scans of low-gamma X-nuclei, low-concentration metabolites, or standard imaging at very low field entail a challenging tradeoff between resolution, signal-to-noise, and acquisition duration. Deep learning (DL) techniques, such as UNets, can potentially be used to improve such "low-quality" (LQ) images. We investigate three UNets for upscaling LQ MRI: dense (DUNet), robust (RUNet), and anisotropic (AUNet). These were evaluated for two acquisition scenarios. In the same-subject High-Quality Complementary Priors (HQCP) scenario, an LQ and a high quality (HQ) image are collected and both LQ and HQ were inputs to the UNets. In the No Complementary Priors (NoCP) scenario, only the LQ images are collected and used as the sole input to the UNets. To address the lack of same-subject LQ and HQ images, we added data from the OASIS-1 database. The UNets were tested in upscaling 1/8, 1/4, and 1/2 undersampled images for both scenarios. As manifested by non-statically significant differences of matrices, also supported by subjective observation, the three UNets upscaled images equally well. This was in contrast to mixed effects statistics that clearly illustrated significant differences. Observations suggest that the detailed architecture of these UNets may not play a critical role. As expected, HQCP substantially improves upscaling with any of the UNets. The outcomes support the notion that DL methods may have merit as an integral part of integrated holistic approaches in advancing special MRI acquisitions; however, primary attention should be paid to the foundational step of such approaches, i.e., the actual data collected. [ABSTRACT FROM AUTHOR]

Background: The sphenoid sinus (SS) is located close to vital structures, such as the pituitary gland, and it has significant clinical relevance. This study aimed to clarify the growth pattern of the SS in Japanese children using three-dimensional computed tomography (CT). Methods: Seventy-eight participants with congenital, acquired, or external auditory canal cholesteatoma were recruited and underwent CT more than twice during their treatment. Using the volume-rendered images, the size and volume of the SS were measured. Furthermore, on the scout image, the morphological measurements of the cranial base were determined. Results: The size and volume of the SS increased with age, and peaked at the mean age of 15 years. For males, the volume of the SS was smaller than that of females aged <5 years. The growth rate of the SS was significantly higher in males than in females. The maximum growth rate was detected at the age of 12 years for males and 10 years for females. For females, the increase in the length of the anterior cranial base ceased at approximately 10 years of age and remained constant thereafter. In contrast, for males, the length of the anterior cranial base increased gradually until 15 years of age. Conclusions: Considering the similarity of the periods between the adolescent growth spurt and the maximum growth rate of the SS, changes in the size of the SS may be used as an indicator of the physical growth spurt. [ABSTRACT FROM AUTHOR]

Background. Contrast medium (CM) administration during computed tomography (CT) enhances the accuracy in the detection and interpretation of abnormalities. Evidence from literature also validate the essence of CM in imaging studies. CT, by virtue of its ubiquity, ease of use, speed, and lower financial footprint, is usually the first investigation in cases of headache. Through a multicenter retrospective analysis, we compared findings of contrast-enhanced CT (CECT) to noncontrast-enhanced CT (NCECT) head examinations among patients presenting with headache. Methods. A multicenter retrospective analysis of four years' CT head examination data at two radiology centers located in Central and Western Regions of Ghana were reviewed. Records of patients who presented with headache as principal complaint between January 2017 and December 2020 were reviewed. A total of 477 records of patients with headache were identified, retrieved and evaluated. A Chi-square test and Fisher exact test were used to compare the CECT and NCECT groups. Binary logistic regression analysis was computed to assess association between CECT and each CT findings. Statistical significance was considered at p < 0.05 with a 95% confidence interval. Results. A significant proportion of the patients was females (51.8% in CECT and 60% in NCECT). The NCECT group (40.06 ± 14.76 years) was relatively older than the CECT group (38.43 ± 17.64 years). There was a significant difference between the CECT and NCECT in terms of age (p = 0.002) and facility CT was performed (p < 0.0001). The rate of abnormalities was higher in CECT (43.5%, 166/382) compared NCECT (37.9%, 36/95). There was no significant association between CT head findings and contrast enhancement. Conclusion. CECT examination accounted for 5.6% increase in the detection of head abnormalities. Efforts required to establish local standard operation procedures (SOPs) for contrast medium use especially in CT head examinations. Further studies to improve the knowledge of agents, mechanism of action, and safety of contrast media used among practitioners in Ghana is recommended. [ABSTRACT FROM AUTHOR]

Clinical challenges in pediatrics dose estimation by the displayed computed tomography (CT) dose indices may lead to inaccuracy, and thus size-specific dose estimate (SSDE) is introduced for better-personalized dose estimation. This study aims to estimate pediatric dose adapted to specific size. This retrospective study involved pediatric population aged 0–12 y. SSDE was derived from scanner reported volume CT dose index (CTDIvol), based on individual effective diameter (Deff) with corresponding size correction factors. The correlations of Deff with other associated factors such as age, exposure setting, CTDIvol and SSDE were also studied. The average Deff of Malaysian pediatric was smaller than reference phantom size (confidence interval, CI = 0.28, mean = 14.79) and (CI = 0.51, mean = 16.33) for head and abdomen, respectively. These have led to underestimation of pediatric dose as SSDE was higher than displayed CTDIvol. The percentage differences were statistically significant (p  < .001) ranged from 0 to 17% and 37 to 60% for head and abdominal CT, respectively. In conclusion, the clinical implementation of SSDE in pediatric CT imaging is highly relevant to reduce radiation risk. [ABSTRACT FROM AUTHOR]

Radiomics, a quantitative approach to extracting features from medical images, represents a new frontier in skull base oncology. Novel image analysis approaches have enabled us to capture patterns from images imperceptible by the human eye. This rich source of data can be combined with a range of clinical features, holding the potential to be a noninvasive source of biomarkers. Applications of radiomics in skull base pathologies have centered around three common tumor classes: meningioma, sellar/parasellar tumors, and vestibular schwannomas. Radiomic investigations can be categorized into five domains: tumor detection/segmentation, classification between tumor types, tumor grading, detection of tumor features, and prognostication. Various computational architectures have been employed across these domains, with deep-learning methods becoming more common versus machine learning. Across radiomic applications, contrast-enhanced T1-weighted MRI images remain the most utilized sequence for model development. Efforts to standardize and connect radiomic features to tumor biology have facilitated more clinically applicable radiomic models. Despite the advancement in model performance, several challenges continue to hinder translatability, including small sample sizes and model training on homogenous single institution data. To recognize the potential of radiomics for skull base oncology, prospective, multi-institutional collaboration will be the cornerstone for a validated radiomic technology., (© 2024. The Author(s), under exclusive license to Springer Nature Switzerland AG.)

HDAC9 is a histone deacetylase enzyme belonging to the class IIa of HDACs which catalyses histone deacetylation. HDAC9 inhibit cell proliferation by repairing DNA, arresting the cell cycle, inducing apoptosis, and altering genetic expression. HDAC9 plays a significant part in human physiological system and are involved in various type of diseases like cancer, diabetes, atherosclerosis and CVD, autoimmune response, inflammatory disease, osteoporosis and liver fibrosis. This review discusses the role of HDAC9 in different diseases and structure-activity relationships (SARs) of various hydroxamate and non-hydroxamate-based inhibitors. SAR of compounds containing several scaffolds have been discussed in detail. Moreover, structural requirements regarding the various components of HDAC9 inhibitor (cap group, linker and zinc-binding group) has been highlighted in this review. Though, HDAC9 is a promising target for the treatment of a number of diseases including cancer, a very few research are available. Thus, this review may provide useful information for designing novel HDAC9 inhibitors to fight against different diseases in the future., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Magnetic resonance imaging (MRI) of the brain has benefited from deep learning (DL) to alleviate the burden on radiologists and MR technologists, and improve throughput. The easy accessibility of DL tools has resulted in a rapid increase of DL models and subsequent peer-reviewed publications. However, the rate of deployment in clinical settings is low. Therefore, this review attempts to bring together the ideas from data collection to deployment in the clinic, building on the guidelines and principles that accreditation agencies have espoused. We introduce the need for and the role of DL to deliver accessible MRI. This is followed by a brief review of DL examples in the context of neuropathologies. Based on these studies and others, we collate the prerequisites to develop and deploy DL models for brain MRI. We then delve into the guiding principles to develop good machine learning practices in the context of neuroimaging, with a focus on explainability. A checklist based on the United States Food and Drug Administration's good machine learning practices is provided as a summary of these guidelines. Finally, we review the current challenges and future opportunities in DL for brain MRI., (© 2023 John Wiley & Sons Ltd.)

BACKGROUND Race and geographic differences in the prevalence and predictors of hypertension in stroke survivors have been reported, but apparent treatment-resistant hypertension (aTRH) among stroke survivors by race (African ancestry vs. non-Hispanic Caucasians) and by geography (continental Africa vs. the United States) are under studied. METHODS This is a cross-sectional study using ethically approved stroke registries from the University of Florida and the Kwame Nkrumah University of Science and Technology, Kumasi, Ghana. Univariate and multivariate regression was used to evaluate for differences in prevalence of aTRH and associations with clinical covariates. RESULTS Harmonized data were available for 3,365 stroke survivors of which 943 (28.0%) were indigenous Africans, 558 (16.6%) African Americans, and 1,864 (55.4%) non-Hispanic Caucasians with median ages (interquartile range) of 59 (49–68), 61 (55–72), and 70 (62–78) years, P < 0.0001. The overall frequency of aTRH was 18.5% (95% confidence interval [CI]: 17.2%–19.8%) with 42.7% (95% CI: 39.6%–46.0%) among indigenous Africans, 16.1% (95% CI: 13.2%–19.5%) among African Americans, and 6.9% (95% CI: 5.8%–8.2%) among non-Hispanic Caucasians, P < 0.0001. Five factors associated with aTRH: age, adjusted odds ratio (95% CI) of 0.99 (0.98–0.99), female sex 0.70 (0.56–0.87), cigarette smoking 1.98 (1.36–2.90), intracerebral hemorrhage 1.98 (1.57–2.48), and Black race namely indigenous Africans 4.42 (3.41–5.73) and African Americans 2.44 (1.81–3.29). CONCLUSIONS Future studies are needed to investigate the contribution of socioeconomic disparities in the prevalence aTRH in those with African Ancestry to explore the long-term impact, and evaluate effective therapeutic interventions in this subpopulation. [ABSTRACT FROM AUTHOR]

High-field magnetic resonance (MR) images are desired for precise medical diagnosis and analysis. The financial constraints restrict the deployment of high-field MR scanners worldwide and thus limit the availability of high-field (HF) MR images. The information in HF MR images (7T) can be approximated from low-field MR images (3T) and has been addressed by several learning-based methods in supervised framework. The existing approaches require example of 3T and 7T paired MR images which are not generally available in real scenarios. This article proposes, for the first time in the literature, the unsupervised single-image-based method to estimate 7T-like MR images from the given 3T MR images such that the extra requirement of example 3T and/or 7T MR images can be avoided. The intensity transformation A between 7T-like and 3T MR images is estimated along with the 7T-like MR image in an alternative minimization framework. This framework is regularized with a novel mean correction constraint and a l 1 , 2 norm constraint on columns of matrix A , in multiple dictionary-based sparse representation framework. The significance of the proposed constraints and sparse representation framework is emphasized by the ablation study. In comparison with the existing supervised approaches, the proposed unsupervised approach provides comparable performance. [ABSTRACT FROM AUTHOR]

Purpose: To compare the morphological features of the bony nasolacrimal canal (NLC) in Caucasian adults with and without primary acquired nasolacrimal duct obstruction (PANDO). Methods: The study included one eye each from 38 patients with PANDO and 38 age- and gender-matched controls without PANDO, all of whom underwent multidetector computed tomography. In tomographic images, length, and orientation angles of the NLC, transverse canal diameters at the duct entrance and lower end, and minimum (narrowest) transverse and anterior–posterior canal diameters were measured. Results: The two groups were similar for NLC length and angulations. The transverse entrance diameter was significantly narrower in the PANDO group (mean, 4.6 mm vs. 5.1 mm) (p = 0.09). The narrowest site was most frequently in the middle duct or slightly above the middle in both groups (p > 0.05). The minimum canal diameters were significantly smaller in the PANDO group (p = 0.010 and p = 0.003). When gender subgroups were compared, the significant differences continued for the transverse entrance and minimum diameters in females with PANDO (p = 0.006) and for the minimum anterior–posterior diameter in males with PANDO (p = 0.02). Conclusion: Narrowness of the upper and/or middle part of the bony nasolacrimal duct may play a role in the development of PANDO in the adult Caucasian population. [ABSTRACT FROM AUTHOR]

Objectives: Ischemic stroke is a leading cause of mortality and acquired disability worldwide and thus plays an enormous health-economic role. Imaging of choice is computed-tomographic (CT) or magnetic resonance imaging (MRI), especially diffusion-weighted (DW) sequences. However, MR imaging is associated with high costs and therefore has a limited availability leading to low-field-MRI techniques increasingly coming into focus. Thus, the aim of our study was to assess the potential of stroke imaging with low-field MRI. Material and Methods: A scanner comparison was performed including 27 patients (17 stroke cohort, 10 control group). For each patient, a brain scan was performed first with a 1.5T scanner and afterwards with a 0.55T scanner. Scan protocols were as identical as possible and optimized. Data analysis was performed in three steps: All DWI/ADC (apparent diffusion coefficient) and FLAIR (fluid attenuated inversion recovery) sequences underwent Likert rating with respect to image impression, resolution, noise, contrast, and diagnostic quality and were evaluated by two radiologists regarding number and localization of DWI and FLAIR lesions in a blinded fashion. Then segmentation of lesion volumes was performed by two other radiologists on DWI/ADC and FLAIR. Results: DWI/ADC lesions could be diagnosed with the same reliability by the most experienced reader in the 0.55T and 1.5T sequences (specificity 100% and sensitivity 92.9%, respectively). False positive findings did not occur. Detection of number/location of FLAIR lesions was mostly equivalent between 0.55T and 1.5T sequences. No significant difference (p = 0.789–0.104) for FLAIR resolution and contrast was observed regarding Likert scaling. For DWI/ADC noise, the 0.55T sequences were significantly superior (p < 0.026). Otherwise, the 1.5T sequences were significantly superior (p < 0.029). There was no significant difference in infarct volume and volume of infarct demarcation between the 0.55T and 1.5T sequences, when detectable. Conclusions: Low-field MRI stroke imaging at 0.55T may not be inferior to scanners with higher field strengths and thus has great potential as a low-cost alternative in future stroke diagnostics. However, there are limitations in the detection of very small infarcts. Further technical developments with follow-up studies must show whether this problem can be solved. [ABSTRACT FROM AUTHOR]

Campylobacter is a leading cause of bacterial gastroenteritis worldwide. This study determined the phenotypic characteristics of Campylobacter from ruminants slaughtered in two major abattoirs in Ilorin metropolis of Kwara state, Nigeria. In total, 350 fecal samples were collected from beef cattle (n = 200) and goat (n = 150). Campylobacter was isolated and phenotypically characterized using standard bacteriological methods. Seventy (20%) of the samples were positive for Campylobacter. The isolation rate of Campylobacter from female animals (11.71%) was higher than that of males (8.28%), albeit there was no significant difference (P > 0.05). Similarly, the rate of isolation of Campylobacter from bovine (12.86%) was not statistically significant (P > 0.05) from that of caprine (7.14%) species. Only five (7.14%) of the total isolates were Campylobacter jejuni. All isolates were resistant to nalidixic acid and pan-susceptible to gentamicin, but there were different rates of antimicrobial resistance to other tested antibiotics. There was also high rate of resistance to cefotaxime (83%) and ampicillin (76%), and 53% of the isolates displayed multidrug resistance phenotypes. The study established 20% Campylobacter contamination of ruminants slaughtered in the two major abattoirs in Ilorin, and most of the isolates were multidrug resistant. Further study is recommended to molecularly characterize the species of Campylobacter circulating in the study area. [ABSTRACT FROM AUTHOR]

Background. Stroke is a cardiovascular disorder causing mortality globally and long-lasting harm worldwide. The disease occurs when the blood flow to the brain is either interrupted or blocked. This disruption leads to the increase in reactive oxygen species (ROS), especially superoxide free radicals, resulting in oxidative stress. The superoxide radicals are removed by superoxide dismutase (SOD), a key antioxidant enzyme. In this work, we investigated haematological indices and superoxide dismutase enzyme activity in Ghanaian patients with stroke and healthy control participants. Materials and Methods. Thirty stroke patients attending a stroke clinic and thirty apparently healthy control participants were recruited into the study. Blood samples were collected to determine haematological indices and SOD enzyme activity in red blood cells. Results. The stroke patients had significantly high blood parameters such as white blood cell (p < 0.001), neutrophil (p < 0.001), lymphocyte (p = 0.003), and eosinophil (p < 0.001) comparing with study participants without stroke, who were the control group in the study. Other blood parameters such as red blood cell, (p < 0.001), haemoglobin (p < 0.001), and haematocrit (p < 0.001) levels and mean cell haemoglobin concentration (p = 0.030), platelet (p = 0.010), and plateletcrit (p = 0.027) were high in stroke patients comparing with study control participants and statistically significant. Blood lymphocyte levels observed in stroke patients correlated negatively and significantly with SOD activity levels. SOD activity levels were significantly lower in stroke patients compared with the control group (p < 0.001). Low values of the antioxidant enzyme SOD activity levels, lymphocytes, and high values of plateletcrit were significant predictors of stroke. Conclusion. Haematological parameters such as WBC, lymphocyte, platelet levels, and red cell indices were significantly different in the stroke patients being studied. There was negative correlation between lymphocyte significantly with SOD activity and high oxidative stress in stroke patients compared with the control group. Lymphocytes and plateletcrit levels were also good predictors of the occurrence of stroke. [ABSTRACT FROM AUTHOR]

Purpose: The goals of this study include: (a) generating tailored magnetic resonance fingerprinting (TMRF) based non‐synthetic imaging; (b) assessing the repeatability of TMRF and deep learning‐based mapping of in vitro ISMRM/NIST phantom and in vivo brain data of healthy human subjects. Methods: We have acquired qualitative images obtained from the vendor‐supplied gold standard (GS), MRF (synthetic), and TMRF (non‐synthetic) on one representative healthy human brain. We also acquired 30 datasets on the ISMRM/NIST phantom for the in vitro repeatability study on a GE Discovery 3T MR750w scanner using the TMRF sequence. We compared T1 and T2 maps generated from 30 ISMRM/NIST phantom datasets to the spin‐echo (SE) based GS method as part of the in vitro repeatability study. R‐squared coefficient of determination in a simple linear regression and Bland–Altman analysis were computed for 30 datasets of ISMRM/NIST phantom to assess the accuracy of in vitro quantitative TMRF data. The repeatability of T1 and T2 estimates by TMRF was evaluated by calculating the standard deviation (SD) divided by the average of 30 datasets for each sphere, respectively. We acquired 10 volunteers for the in vivo repeatability study on the same scanner using the same TMRF sequence. These volunteers were imaged five times with two runs per repetition, resulting in 100 in vivo datasets. Five contrasts, T1 and T2 maps of 10 human volunteers acquired over five repetitions, were evaluated in the in vivo repeatability study. We computed the intraclass correlation coefficient (ICC) of the signal‐to‐noise ratio (SNR), signal intensities, T1 and T2 relaxation times in white matter (WM), and gray matter (GM). Results: The synthetic images generated from MRF show partial volume and flow artifacts compared to non‐synthetic images obtained from TMRF images and the GS. In vitro studies show that TMRF estimates have less than 5% variations except sphere 14 in the T2 array (6.36%). TMRF and SE relaxometry measurements were strongly correlated; R2 values were 0.9958 and 0.9789 for T1 and T2 estimates, respectively. Based on the ICC values, SNR, mean intensity values, and relaxation times of WM and GM for the in vivo studies were consistent. T1 and T2 values of WM and GM were similar to previously published values. The mean ± SD of T1 and T2 for WM for ten subjects and five repeats are 992 ± 41 ms and 99 ± 6 ms, while the corresponding values for T1 and T2 for GM are 1598 ± 73 ms and 152 ± 14 ms. Conclusion: TMRF and deep learning‐based reconstruction produce repeatable, non‐synthetic multi‐contrast images, and parametric maps simultaneously. [ABSTRACT FROM AUTHOR]

Background. The rising incidence of hypertension and diabetes calls for a global response. Hypertension and diabetes will rise in Ghana as the population ages, urbanization increases, and people lead unhealthy lives. Our goal was to create a time series algorithm that effectively predicts future increases to help preventative medicine and health care intervention strategies by preparing health care practitioners to control health problems. Methods. Data on hypertension and diabetes from January 2016 to December 2020 were obtained from three health facilities. To detect patterns and predict data from a particular time series, three forecasting algorithms (SARIMAX (seasonal autoregressive integrated moving average with exogenous components), ARIMA (autoregressive integrated moving average), and LSTM (long short-term memory networks)) were implemented. We assessed the model's ability to perform by calculating the root mean square error (RMSE), mean absolute error (MAE), mean square error (MSE), and mean absolute percentage error (MAPE). Results. The RMSE, MSE, MAE, and MAPE for ARIMA (5, 2, 4), SARIMAX 1 , 1 , 1 × 1 , 1 , 1 , 7 , and LSTM was 28, 769.02, 22, and 7%, 67, 4473, 56, and 14%, and 36, 1307, 27, and 8.6%, respectively. We chose ARIMA (5, 2, 4) as a more suitable model due to its lower error metrics when compared to the others. Conclusion. All models had promising predictability and predicted a rise in the number of cases in the future, and this was essential for administrative and management planning. For appropriate and efficient strategic planning and control, the prognosis was useful enough than would have been possible without it. [ABSTRACT FROM AUTHOR]

Despite projections of stroke being a leading cause of mortality in Africa, reliable estimates of stroke burden on the continent using rigorous methods are not available. We aimed to implement a mobile-Health community-based interactive Stroke Information and Surveillance System to sustainably measure stroke burden and improve stroke health literacy and outcomes in urban and rural sites in Nigeria. African Rigorous Innovative Stroke Epidemiological Surveillance (ARISES) is an observational cohort study, which will be conducted in urban (Ibadan North LGA Ward 3) and rural (Ibarapa Central LGA) sites with a combined base population of over 80,000 people. The study will use a consultative approach to establish an mHealth-based Stroke Information and Surveillance System comprising a Stroke Alert System and a Stroke Finding System. These systems will enable the community to report stroke events and the research team/health workers find stroke cases using phone calls, short message service, and Voice Over Internet Protocols (VoIP). We will update community household data and geo-locate all households. Over the 5 years of the study, the system will collect information on stroke events and educate the community about this disease. Reported stroke cases will be clinically adjudicated at home and in prespecified health facilities. Baseline and endline community surveys will be conducted to assess stroke occurrence and other important study variables. The proportion of strokes alerted and found will be determined over the study period. Focus group discussions and key informant interviews will be conducted to understand community stroke literacy and perspectives. The study will also assess any impact of these efforts on time from stroke onset to referral, community uptake of orthodox health services for stroke patients. ARISES is anticipated to establish proof of concept about using mHealth for stroke surveillance in Africa. The potential impact of the SISS on improving patient outcomes will also be determined. [ABSTRACT FROM AUTHOR]

BACKGROUND: The variant pneumatization patterns of the sphenoid sinus have significant surgical implications due to their associated inconsistent neurovascular relations. This study aimed at evaluating the pneumatization patterns of the sphenoid sinus in adult Nigerians. METHODS: This was a retrospective study conducted at the Radiology Department of a Tertiary Hospital in Nigeria after obtaining institutional ethical approval. Brain Computed Tomography images of 336 patients (137 females, 199 males) aged ≥20 years were studied for the variant pneumatization patterns of the sphenoid sinus. Statistical Package for Social Sciences version 23 was used for data analysis. Chi-square test was used to assess for the association of the variants with gender and side. Pvalue was considered significant at <0.05. RESULTS: The predominant pneumatization pattern in relation to the seller turcica was the sellar type (181;53.9%) followed by the presellar type (65;19.3%), post-sellar (62;18.5%), and lastly the conchal type (28;8.3%). The most prevalent clival recess was the subdorsal type (25;7.4%) followed by the dorsal (18;5.4%), combined (7;2.1%), and lastly occipital (3;0.9%). The frequency of pneumatized anterior clinoid process, greater wing of sphenoid and pterygoid process was 76;22.6%, 60;17.9% and 141;42% respectively and these showed significant side difference (P=0.001 each). None of the pneumatization patterns showed a significant gender difference. Sphenoid sinus agenesis was not observed. CONCLUSION: The pneumatization patterns in our study varied from the findings in previous Nigerian studies and other populations. There is therefore the need for preoperative evaluation before endoscopic transsphenoidal surgical procedures. [ABSTRACT FROM AUTHOR]

Background: Cerebral small vessel disease (cSVD) and neurodegeneration are the two main causes of dementia and are considered distinct pathological processes, while studies have shown overlaps and interactions between the two pathological pathways. Medial temporal atrophy (MTA) is considered a classic marker of neurodegeneration. We aimed to investigate the relationship of total cSVD burden and MTA on MRI using a total cSVD score and to explore the impact of the two MRI features on cognition. Methods: Patients in a memory clinic were enrolled, who underwent brain MRI scan and cognitive evaluation within 7 days after the first visit. MTA and total cSVD score were rated using validated visual scales. Cognitive function was assessed by using Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scales. Spearman's correlation and regression models were used to test (i) the association between MTA and total cSVD score as well as each cSVD marker and (ii) the correlation of the MRI features and cognitive status. Results: A total of 312 patients were finally enrolled, with a median age of 75.0 (66.0–80.0) years and 40.7% (127/312) males. All of them finished MRI and MMSE, and 293 subjects finished MoCA. Of note, 71.8% (224/312) of the patients had at least one of the cSVD markers, and 48.7% (152/312) of them had moderate–severe MTA. The total cSVD score was independently associated with MTA levels, after adjusting for age, gender, years of education, and other vascular risk factors (OR 1.191, 95% CI 1.071–1.324, P = 0.001). In regard to individual markers, a significant association existed only between white matter hyperintensities and MTA after adjusting for the factors mentioned above (OR 1.338, 95% CI 1.050–1.704, P = 0.018). Both MTA and total cSVD score were independent risk factors for MMSE ≤ 26 (MTA: OR 1.877, 95% CI 1.407–2.503, P < 0.001; total cSVD score: OR 1.474, 95% CI 1.132–1.921, P = 0.004), and MoCA < 26 (MTA: OR 1.629, 95% CI 1.112–2.388, P = 0.012; total cSVD score: OR 1.520, 95% CI 1.068–2.162, P = 0.020). Among all the cSVD markers, microbleed was found significantly associated with MMSE ≤ 26, while no marker was demonstrated a relationship with MoCA < 26. Conclusion: Cerebral small vessel disease was related to MTA in patients of a memory clinic, and both the MRI features had a significant association with cognitive impairment. [ABSTRACT FROM AUTHOR]