Medical image processing and COVID-19: A literature review and bibliometric analysis.

COVID-19 crisis has placed medical systems over the world under unprecedented and growing pressure. Medical imaging processing can help in the diagnosis, treatment, and early detection of diseases. It has been considered as one of the modern technologies applied to fight against the COVID-19 crisis. Although several artificial intelligence, machine learning, and deep learning techniques have been deployed in medical image processing in the context of COVID-19 disease, there is a lack of research considering systematic literature review and categorization of published studies in this field. A systematic review locates, assesses, and interprets research outcomes to address a predetermined research goal to present evidence-based practical and theoretical insights. The main goal of this study is to present a literature review of the deployed methods of medical image processing in the context of the COVID-19 crisis. With this in mind, the studies available in reliable databases were retrieved, studied, evaluated, and synthesized. Based on the in-depth review of literature, this study structured a conceptual map that outlined three multi-layered folds: data gathering and description, main steps of image processing, and evaluation metrics. The main research themes were elaborated in each fold, allowing the authors to recommend upcoming research paths for scholars. The outcomes of this review highlighted that several methods have been adopted to classify the images related to the diagnosis and detection of COVID-19. The adopted methods have presented promising outcomes in terms of accuracy, cost, and detection speed.

Optimizing Gentamicin Dosing in Pediatrics Using Monte Carlo Simulations.

Gentamicin is known to have concentration-dependent bactericidal activity, and its nephrotoxic effect is well described. We developed a population pharmacokinetic/pharmacodynamic model to optimize gentamicin dosing in pediatrics. Data were retrospectively collected for pediatric patients 1 month to 12 years of age, admitted to general pediatric wards or intensive care units and received gentamicin for suspected or proven Gram-negative infections at King Saud University Medical City, Riyadh, Saudi Arabia. A total of 306 gentamicin peak and trough concentrations sets from 107 patients were analyzed with mean (±standard deviation) patient age and weight of 4.5 ± 3.5 years and 16.7 ± 10.8 kg, respectively. Gentamicin pharmacokinetics were adequately described with a one compartment system (R = 0.82, bias = 1.75% and precision = 88% for population predictions and R = 0.94, bias = 5% and precision = 29% for individual predictions). The gentamicin pharmacokinetic parameters were as follows: volume of distribution = 8.9 L, total body clearance = 2.8 L/h for a 20-kg patient. Monte Carlo simulations showed that doses of 5-6 mg/kg/dose once daily are adequate only to treat infections with Gram-negative organisms having minimal inhibitory concentration less than 1 µg/mL. While, at minimal inhibitory concentration of 1 µg/mL, higher doses (7-8 mg/kg/dose once daily) are needed to maximize the efficacy of gentamicin. However, at minimal inhibitory concentration of 2 µg/mL, even a 10 mg/kg dose showed poor target attainment (52%). The finding of this study highlights the need to reevaluate the current breakpoints of gentamicin and also to assess the safety of higher doses of gentamicin in pediatrics.

Optimizing Amikacin Dosage in Pediatrics Based on Population Pharmacokinetic/Pharmacodynamic Modeling.

OBJECTIVE: Our objective was to determine the population pharmacokinetic parameters of amikacin in pediatric patients to contribute to the future development of a revised optimum dose and population-specific dosing regimens. METHODS: We performed a retrospective chart review in non-critical pediatric patients (aged 1-12 years) who received amikacin for suspected or proven Gram-negative infection at a university hospital. The population pharmacokinetic models were developed using Monolix 4.4. Pharmacokinetic/pharmacodynamic (PK/PD) simulations were performed to explore the ability of different dosage regimens to achieve the pharmacodynamic targets. RESULTS: The analysis included 134 amikacin plasma concentrations from 67 patients with a mean ± standard deviation age of 4.1 ± 3.9 years and bodyweight of 15 ± 8.4 kg. The patients received an amikacin total daily dose (TDD) of 23 ± 7.3 mg/kg, which resulted in peak and trough concentrations of 20.65 ± 7.6 and 2.4 ± 1.7 mg/l, respectively. The estimated pharmacokinetic parameters for amikacin were 1.2 l/h and 6.5 l for total body clearance (CL) and the volume of distribution (V), respectively. Dosing simulations showed that the standard dosing regimen (15 mg/kg/day) of amikacin achieved the PK/PD target of peak serum concentration (Cpeak)/minimum inhibitory concentration (MIC) ≥ 8 for an MIC of 2 mg/l; higher doses were required to achieve higher MIC values. CONCLUSION: The simulation results indicated that amikacin 20 mg/kg once daily provided a higher probability of target attainment with lower toxicity than dosing three times daily. In addition, combination therapy is recommended for pathogens with an MIC of ≥ 8 mg/l.