Critical reviews in biomedical engineering最新文献

We review the state of the practice for the development of medical imaging (MI) software based on data available in open-source repositories. We selected 29 projects from 48 candidates and assessed nine software qualities by answering 108 questions for each. Using the analytic hierarchy process (AHP) on the quantitative data, we ranked the MI software. The top five are 3D Slicer, ImageJ, Fiji, OHIF Viewer, and ParaView. This is consistent with the community's view, with four of these also appearing in the top five using GitHub metrics (stars per year). The quality and quantity of documentation present in a project correlate quite well with its popularity. Generally, MI software is in a healthy state: in the repositories, we observed 88% of the documentation artifacts recommended by research software development guidelines, and 100% of MI projects use version control tools. However, the current state of the practice deviates from existing guidelines as some recommended artifacts are rarely present (such as a test plan, requirements' specification, and code style guidelines), low usage of continuous integration (17% of the projects), low use of unit testing (~ 50% of projects), and room for improvement with documentation. From developer interviews, we identified seven concerns: lack of development time, lack of funding, technology hurdles, correctness, usability, maintainability, and reproducibility. We recommend increasing effort on documentation, increasing testing by enriching datasets, increasing continuous integration, moving to web applications, employing linters, using peer reviews, and designing for change.

Oral administration of drugs is patient-preferred due to ease of administration, less invasive procedures, and overall simplicity. However, traditional oral administration of drugs can lead to ineffective treatment and adverse side effects due to the physiological barriers of the gastrointestinal tract. Because of this, colon-specific drug delivery vehicles synthesized from polymeric, porous materials are being designed to control drug release to the colon. Specifically, these porous matrices include hydrogels, microgels/microparticles, and nanoparticle drug delivery systems. Furthermore, these formulations have been studied on their survivability and efficacy in delivery of the drugs to the colon. This review paper is focused on diffusion models for diffusion and drug release and how the choice of matrix material determines what drug release profiles are possible. Our goal is to provide a resource for identifying, applying, and advancing models for drug diffusion to the colon to help guide experimental design of drug delivery vehicles for intestinal pathologies.

In the past decade, microwave imaging (MWI), employing advanced antenna-based systems, has emerged as a cutting-edge, non-invasive approach for pathological diagnosis. Multiple experimental studies suggest that MWI proposes promising results for early-stage tumor diagnosis. Recent studies on MWI show the importance of antenna types and configuration. However, it is observed that a very limited research has focused on exploring the large classes of antennas used in detail. In this review, a systematic study and firsthand classification of the antennas used, as the most important aspect of an MWI system, is proposed. The classification includes fundamental antennas, microstrip antennas, metamaterial/metastructure antennas, specialized antennas, and 3D antennas. A cross-sectional study is performed to depict the potential relationship between antenna type and efficiency of the MWI systems. This goal is achieved by quantitatively analyzing the gain and operating bandwidth, antenna configuration, and application models. Further, a critical analysis is presented on different signal processing and imaging algorithms for synthetic image generation. This review presents a modular analysis of MWI systems and draws several conclusions on the effectiveness of each essential module for a reliable MWI system. It also addresses the challenges, scope of improvement in the MWI systems, and prospects for the technology's integration into clinical practice.

A detailed review is presented on research contributions in peristaltic transport in the human ureter in the presence of microliths. The studies reviewed are differentiated based on methodologies deployed, namely analytical, numerical and CFD simulation techniques and also experimental (clinical) investigations. Various 2D and 3D models are discussed along with more advanced fluid structure interaction (FSI) studies. The propagation of the incompressible urine flow results in reflux nephropathy. As such, the peristaltic waves spread near the outlet of the tube which manifests in a depletion in the flow rate. Due to the maximum pressure gradient, urine backflow occurs. A full understanding of ureter reflux has however not yet been achieved. This review surveys approximately 101 journals addressing the obstruction inside the ureter and the associated hydrodynamics. As such it consolidates many different efforts in the field in a single source which will serve as a guide to both clinical researchers (e.g., physicians) and also mathematical and engineering research groups and is hoped that it will assist in the development of new integrated approaches for robust treatments. The extensive survey of the scientific literature in this review article confirms that stones (monoliths) detected in the proximal part of the nephron are generally larger than those identified in distal parts. These papers defined the position and shapes of microliths. Due to bolus transport inside the ureter flow, varying pressure and velocity balances are also appraised. The more advanced FSI simulations provide much-needed insight into visualizing actual ureteral transport. Some future pathways for collaborative efforts in improving healthcare for patients are also suggested.

Breast cancer diagnosis using implantable biomedical antennas offers a promising alternative to conventional imaging techniques due to their potential for continuous monitoring and minimal invasiveness. This paper presents a miniaturized antenna with dimensions of 3 ȕ 3 ȕ 1.27 mm3, specifically designed for implantation in breast tissue to detect the presence of tumors. The objective is to evaluate the antenna's ability to detect breast tumors by first analyzing its reflection behavior (S11) in implanted conditions, both with and without tumors. Subsequently, a second external antenna is introduced in free space to assess transmission performance at varying distances. To further assess transmission performance, a second external antenna is introduced, and the system is tested at varying distances and orientations (face-to-face and side-by-side). The antenna operates at 2.45 GHz and is tested in both skin and breast tissue phantoms with embedded tumors of different sizes and positions. Key performance metrics such as S-parameters, gain, transmission coefficient, and group delay are analyzed. Simulation results show gain values of -31.28 dB in skin and -17.78 dB in breast tissue. Patient safety is confirmed through specific absorption rate (SAR) analysis, with a maximum input power of 2.3 mW. The proposed design shows strong potential for breast cancer detection due to its small size, consistent performance in various antenna positions, and compliance with SAR safety standards.

The current article discusses several innovative and intriguing aspects of the Caputo and modified Atangana-Baleanu derivative in the Caputo sense (MABC) based on a fractional blood alcohol model. The initial concentration of alcohol in the stomach after consumption, the rate at which alcohol is absorbed into the circulation, and the rate at which the liver metabolizes alcohol are the three factors that determine the model's resolution. Utilizing the Laplace transform method and the generalized Mittag-Leffler function method (GMLFM), the analytical results of stomach alcohol concentration and blood alcohol concentration are examined. Additionally, the study comprehensively analyzes the relationship between blood and stomach alcohol concentrations through an extended series representation. Graphical representations of the impact of fractional parameters on blood and stomach alcohol concentrations are provided. The comparison analysis for both concentrations reveals novel aspects of the studied model's entire fractional derivatives. The fractional blood alcohol models presented provide significant and beneficial outcomes that may be used to forecast future information forthe medical community.

Speckle noise in ultrasound images compromises image quality and hinders diagnostic accuracy. Traditional ultrasound denoising methods often struggle to preserve anatomical details while effectively reducing noise, especially under high-noise conditions. In this study, we propose an innovative approach that integrates a lightweight channel attention mechanism (LCAM) within a convolutional variational autoencoder (CVAE) framework to enhance ultrasound image denoising. The proposed approach efficiently reduces speckle noise while maintaining essential anatomical features. Comprehensive evaluations across six diverse ultrasound datasets demonstrate that the LCAM-CVAE outperforms conventional denoising techniques in both subjective image quality and objective performance metrics, including peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), standard deviation in PSNR (SD-PSNR), standard deviation in SSIM (SD-SSIM), PSNR statistical relevance tests, and computational efficiency (CE). The LCAM-CVAE approach demonstrates exceptional performance, particularly under high-noise conditions, ensuring the preservation of key anatomical structures for accurate diagnosis. These results highlight the LCAM-CVAE approach as a robust and promising solution for ultrasound image denoising, with significant clinical potential to improve diagnostic quality in noisy environments.

The global burden of cancer is rising, causing significant strain on individuals, families, and healthcare systems. Traditional treatments, such as chemotherapy and radiation, are effective but harm healthy cells and lead to side effects. In contrast, virotherapy specifically targets cancer cells, leaving healthy cells unharmed. This study presents a mathematical model of cancer treatment with viral therapy and the immune system. We show the non-negative and boundedness of the model's solution. Our findings identify five equilibrium points: free equilibrium point, two immune response-free equilibrium points, and two coexisting equilibrium points. The local and global stability of the equilibrium point is established. We show the tumor size reduction from 0.55 to 0.05 as an increase in the burst size from 0.8 to 9.0, respectively. We also explore that the proposed methodology reduces tumor size from 0.59 to 0.21 as the stimulation rate of immune response increases from 0.29 to 0.90. Thus, numerical simulations indicate that high immune response and viruses reduce tumor size. This study emphasizes the effectiveness of combining viral therapy with high immune responses in cancer patients. This study is helpful for oncologists and immunologists to understand the behavior of virotherapy and immune response to control the proliferation of different kinds of tumors.

In this study, an epidemic model with a constant recruitment rate of susceptible individuals with a bilinear transmission rate of infection is considered. Vaccination-type treatment is inspected to minimize the impact of the disease. The asymptomatic infected and the vaccinated compartments are taken with regard to the circumstances of the coronavirus disease (COVID-19) pandemic 2020-2025. The impact of these two compartments is examined specifically to shed light on the behavioral dynamics. Local as well as the global stability of the disease-free equilibrium point and the endemic equilibrium point are examined by constructing Lyapunov functions. Hence, we prove that if the basic reproduction number is < 1, then there will be no disease in the system, and if the basic reproduction number is > 1, then the disease will persist. Sensitivity analysis is performed to identify the influential model parameters that have the greatest impact on the original reproduction number of the proposed model. The model is validated by fitting it to real data. Furthermore, we carried out numerical simulations of the model parameters and their accompanying theoretical results. To control or eliminate the effect of emerging diseases, we made several suggestions to control the most sensitive model parameters while using necessary preventive measures.

Brachial plexus injuries during childbirth can be devastating injuries with lifelong consequences. Here we review the biomechanical literature related to this injury and integrate it with recent epidemiological and clinical literature to better understand how intrinsic and extrinsic factors contribute to this injury. Brachial plexus palsy is caused by excessive stretching, tearing, or avulsion of the nerve fibers of the brachial plexus and can lead to temporary or permanent injury to the motor and sensory functions of the upper extremity. Compared to other maternal and fetal factors, the highest risk factor for brachial plexus palsy is shoulder dystocia. The continuum of brachial plexus injuries, from temporary impairments of the C5 and C6 nerve roots to the permanent disruption of the entire brachial plexus, is consistent with a dose-response relationship whereby higher applied birthing forces cause greater degrees of injury. The current biomechanical models of shoulder dystocia and brachial plexus strain have not been validated against experimental data and their results should be treated cautiously. Endogenous forces (e.g., uterine contractions and maternal pushing) and exogenous forces (e.g., clinician-applied traction) generate strain in the brachial plexus, but the rarity of permanent, severe injuries and the reduction of these injuries after clinician training suggest that clinician-applied forces during shoulder dystocia increase the risk of permanent, severe brachial plexus injury. There are currently no reliable biomechanical methods for determining if maternal forces or clinician-applied forces are responsible for less severe types of brachial plexus injury.