Motion and magnetic field inhomogeneity correction techniques for chemical exchange saturation transfer (CEST) MRI: A contemporary review.

Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) has emerged as a powerful imaging technique sensitive to tissue molecular composition, pH, and metabolic processes in situ. CEST MRI uniquely probes the physical exchange of protons between water and specific molecules within tissues, providing a window into physiological phenomena that remain invisible to standard MRI. However, given the very low concentration (millimolar range) of CEST compounds, the effects measured are generally only on the order of a few percent of the water signal.

Advancements in MR hardware systems and magnetic field control: B shimming, RF coils, and gradient techniques for enhancing magnetic resonance imaging and spectroscopy.

High magnetic field homogeneity is critical for magnetic resonance imaging (MRI), functional MRI, and magnetic resonance spectroscopy (MRS) applications. B inhomogeneity during MR scans is a long-standing problem resulting from magnet imperfections and site conditions, with the main issue being the inhomogeneity across the human body caused by differences in magnetic susceptibilities between tissues, resulting in signal loss, image distortion, and poor spectral resolution. Through a combination of passive and active shim techniques, as well as technological advances employing multi-coil techniques, optimal coil design, motion tracking, and real-time modifications, improved field homogeneity and image quality have been achieved in MRI/MRS.

Comparison of test-retest reproducibility of DESPOT and 3D-QALAS for water and mapping.

Purpose: Relaxometry, specifically and mapping, has become an essential technique for assessing the properties of biological tissues related to various physiological and pathological conditions. Many techniques are being used to estimate and relaxation times, ranging from the traditional inversion or saturation recovery and spin-echo sequences to more advanced methods. Choosing the appropriate method for a specific application is critical since the precision and accuracy of and measurements are influenced by a variety of factors including the pulse sequence and its parameters, the inherent properties of the tissue being examined, the MRI hardware, and the image reconstruction.

Assessment of the Barriers and Enablers of the Use of mHealth Systems in Sub-Saharan Africa According to the Perceptions of Patients, Physicians, and Health Care Executives in Ethiopia: Qualitative Study.

Background: Digital technologies are increasingly being used to deliver health care services and promote public health. Mobile wireless technologies or mobile health (mHealth) technologies are particularly relevant owing to their ease of use, broad reach, and wide acceptance. Unlike developed countries, Sub-Saharan Africa experiences more challenges and obstacles when it comes to deploying, using, and expanding mHealth systems.

Spatiotemporal distribution of climate-sensitive disease incidences in ethiopia: a longitudinal retrospective analysis of Malaria, Meningitis, Cholera, Dysentery, Leishmaniasis and Dengue fever between 2010 and 2022/2023.

Background: Understanding the temporal and geographic distribution of disease incidences is crucial for effective public health planning and intervention strategies. This study presents a comprehensive analysis of the spatiotemporal distribution of disease incidences in Ethiopia, focusing on six major diseases: Malaria, Meningitis, Cholera and Dysentery, over the period from 2010 to 2022, whereas Dengue Fever and Leishmaniasis from 2018 to 2023.

Methods: Using data from Ethiopian public health institute: public health emergency management (PHEM), and Ministry of Health, we examined the occurrence and spread of each disease across different regions of Ethiopia.

Rule-based expert system for the diagnosis of maternal complications during pregnancy: For low resource settings.

Objectives: Maternal complications are health challenges linked to pregnancy, encompassing conditions like gestational diabetes, maternal sepsis, sexually transmitted diseases, obesity, anemia, urinary tract infections, hypertension, and heart disease. The diagnosis of common pregnancy complications is challenging due to the similarity in signs and symptoms with general pregnancy indicators, especially in settings with scarce resources where access to healthcare professionals, diagnostic tools, and patient record management is limited. This paper presents a rule-based expert system tailored for diagnosing three prevalent maternal complications: preeclampsia, gestational diabetes mellitus (GDM), and maternal sepsis.

Development of birth weight estimation model for Ethiopian population from sonographic evaluation.

Background: Fetal birth weight (FBW) estimation involves predicting the weight of a fetus prior to delivery. This prediction serves as a crucial input for ensuring effective, accurate, and appropriate obstetric planning, management, and decision-making. Typically, there are two methods used to estimate FBW: the clinical method (which involves measuring fundal height and performing abdominal palpation) or sonographic evaluation.

mHealth in sub-Saharan Africa and Europe: A systematic review comparing the use and availability of mHealth approaches in sub-Saharan Africa and Europe.

Background: mHealth can help with healthcare service delivery for various health issues, but there's a significant gap in the availability and use of mHealth systems between sub-Saharan Africa and Europe, despite the ongoing digitalization of the global healthcare system.

Objective: This work aims to compare and investigate the use and availability of mHealth systems in sub-Saharan Africa and Europe, and identify gaps in current mHealth development and implementation in both regions.

Methods: The study adhered to the PRISMA 2020 guidelines for article search and selection to ensure an unbiased comparison between sub-Saharan Africa and Europe.

mHealth in Sub-Saharan Africa and Europe: Context of current health, healthcare status, and demographic structure.

Introduction: The advent of digital systems and global mobile phone availability presents an opportunity for better healthcare access and equity. However, the disparity in the usage and availability of mHealth systems between Europe and Sub-Saharan Africa (SSA) has not been explored in relation to current health, healthcare status, and demographics.

Objective: This study aimed to compare mHealth system availability and use in SSA and Europe in the above-mentioned context.

The impact of khat chewing on heart activity and rehabilitation therapy from khat addiction in healthy khat chewers.

Khat is a flowering plant whose leaves and stems are chewed for excitement purposes in most of east African and Arabian countries. Khat can cause mood changes, increased alertness, hyperactivity, anxiety, elevated blood pressure, and heart diseases. However, the effect of khat on the heart has not been studied exclusively.

Cervix Type and Cervical Cancer Classification System Using Deep Learning Techniques.

Purpose: Cervical cancer is the 4th most common cancer among women, worldwide. Incidence and mortality rates are consistently increasing, especially in developing countries, due to the shortage of screening facilities, limited skilled professionals, and lack of awareness. Cervical cancer is screened using visual inspection after application of acetic acid (VIA), papanicolaou (Pap) test, human papillomavirus (HPV) test and histopathology test.

Planning and Budgeting of Medical Devices Among Ethiopian Public Hospitals.

Background: Planning and budgeting of medical devices allow a healthcare institution to properly use funds, acquire quality and efficient medical devices, and improve healthcare service delivery. The lack of proper policy in the procurement and management of medical devices causes inappropriate usage of funds and impedes the quality of a product. This study aimed to identify the current practices and gaps in the planning and budgeting of medical devices in Ethiopian public hospitals.

Machine learning-based automatic sleep apnoea and severity level classification using ECG and SpO signals.

Sleep apnoea is a potentially serious sleep disorder that is characterised by repetitive episodes of breathing interruptions. Traditionally, sleep apnoea is commonly diagnosed in an attended sleep laboratory setting using polysomnography (PSG). The manual diagnosis of sleep apnoea using PSG is, however complex, and time-consuming, as many physiological variables are usually measured overnight using numerous sensors attached to patients.

Treatment device for neonatal birth asphyxia related Hypoxic Ischemic Encephalopathy.

Background: Birth asphyxia is a leading cause of neonatal brain injury, morbidity, and mortality globally. It leads to a multi-organ dysfunction in the neonate and to a neurological dysfunction called Hypoxic Ischemic Encephalopathy (HIE). Cooling therapy is commonly used to slow or stop the damaging effects of birth asphyxia.

Quantitative analysis of blood cells from microscopic images using convolutional neural network.

Blood cell count provides relevant clinical information about different kinds of disorders. Any deviation in the number of blood cells implies the presence of infection, inflammation, edema, bleeding, and other blood-related issues. Current microscopic methods used for blood cell counting are very tedious and are highly prone to different sources of errors.

Digital postpartum hemorrhage management device (DPHMD).

Background: Primary postpartum hemorrhage (PPH) is an obstetric emergency caused by excessive blood loss that occurs most commonly after the placenta is delivered. PPH can lead to volume depletion, hypovolemic shock, anemia, and it is the leading cause of maternal mortality worldwide. With 470 deaths per 100,000 live births, the maternal mortality ratio in Ethiopia is one of the highest in the world.

Repeatability and reproducibility of prospective motion- and shim corrected 2D glycoCEST MRI.

Background: Repeated glycoCEST MRI measurements on the same subject should produce similar results under the same environmental and experimental conditions. However, fluctuations in the static B field, which may occur between and within measurements due to heating of the shim iron or subject motion, may alter results and affect reproducibility. Here we investigate the repeatability and reproducibility of glycoCEST measurements and examine the effectiveness of a real-time shim- and motion navigated chemical exchange saturation transfer (CEST) sequence to improve reproducibility.

Real-time simultaneous shim and motion measurement and correction in glycoCEST MRI using double volumetric navigators (DvNavs).

Purpose: CEST MRI allows for indirect detection of molecules with exchangeable protons, measured as a reduction in water signal because of continuous transfer of saturated protons. CEST requires saturation pulses on the order of a second, as well as repeated acquisitions at different offset frequencies. The resulting extended scan time makes CEST susceptible to subject motion, which introduces field inhomogeneity, shifting offset frequencies and causing distortions in CEST spectra that resemble true CEST effects.