Progress in biomedical engineering (Bristol, England)最新文献

Computational models of the heart are now being used to assess the effectiveness and feasibility of interventions through in-silico clinical trials (ISCTs). As the adoption and acceptance of ISCTs increases, best practices for reporting the methodology and analysing the results will emerge. Focusing in the area of cardiology, we aim to evaluate the types of ISCTs, their analysis methods and their reporting standards. To this end, we conducted a systematic review of cardiac ISCTs over the period of 1 January 2012-1 January 2022, following the preferred reporting items for systematic reviews and meta-analysis (PRISMA). We considered cardiac ISCTs of human patient cohorts, and excluded studies of single individuals and those in which models were used to guide a procedure without comparing against a control group. We identified 36 publications that described cardiac ISCTs, with most of the studies coming from the US and the UK. In $75\%$ of the studies, a validation step was performed, although the specific type of validation varied between the studies. ANSYS FLUENT was the most commonly used software in $19\%$ of ISCTs. The specific software used was not reported in $14\%$ of the studies. Unlike clinical trials, we found a lack of consistent reporting of patient demographics, with $28\%$ of the studies not reporting them. Uncertainty quantification was limited, with sensitivity analysis performed in only $19\%$ of the studies. In $97\%$ of the ISCTs, no link was provided to provide easy access to the data or models used in the study. There was no consistent naming of study types with a wide range of studies that could potentially be considered ISCTs. There is a clear need for community agreement on minimal reporting standards on patient demographics, accepted standards for ISCT cohort quality control, uncertainty quantification, and increased model and data sharing.

In this review, we provide a summary of the state-of-the-art in the in silico modelling of cerebral blood flow (CBF) and its application in in silico clinical trials. CBF plays a key role in the transport of nutrients, including oxygen and glucose, to brain cells, and the cerebral vasculature is a highly complex, multi-scale, dynamic system that acts to ensure that supply and demand of these nutrients are continuously balanced. It also plays a key role in the transport of other substances, such as recombinant tissue-plasminogen activator, to brain tissue. Any dysfunction in CBF can rapidly lead to cell death and permanent damage to brain regions, leading to loss of bodily functions and death. The complexity of the cerebral vasculature and the difficulty in obtaining accurate anatomical information combine to make mathematical models of CBF key in understanding brain supply, diagnosis of cerebrovascular disease, quantification of the effects of thrombi, selection of the optimum intervention, and neurosurgical planning. Similar in silico models have now been widely applied in a variety of body organs (most notably in the heart), but models of CBF are still far behind. The increased availability of experimental data in the last 15 years however has enabled these models to develop more rapidly and this progress is the focus of this review. We thus present a brief review of the cerebral vasculature and the mathematical foundations that underpin CBF in both the microvasculature and the macrovasculature. We also demonstrate how such models can be applied in the context of cerebral diseases and show how this work has recently been expanded to in silico trials for the first time. Most work to date in this context has been performed for ischaemic stroke or cerebral aneurysms, but these in-silico models have many other applications in neurodegenerative diseases where mathematical models have a vital role to play in testing hypotheses and providing test beds for clinical interventions.

Significant advances have been made to improve control and to provide sensory functions for bionic hands. However, great challenges remain, limiting wide acceptance of bionic hands due to inadequate bidirectional neural compatibility with human users. Recent research has brought to light the necessity for matching neuromechanical behaviors between the prosthesis and the sensorimotor system of amputees. A novel approach to achieving greater neural compatibility leverages the technology of biorealistic modeling with real-time computation. These studies have demonstrated a promising outlook that this unique approach may transform the performance of hand prostheses. Simultaneously, a noninvasive technique of somatotopic sensory feedback has been developed based on evoked tactile sensation (ETS) for conveying natural, intuitive, and digit-specific tactile information to users. This paper reports the recent work on these two important aspects of sensorimotor functions in prosthetic research. A background review is presented first on the state of the art of bionic hand and the various techniques to deliver tactile sensory information to users. Progress in developing the novel biorealistic hand prosthesis and the technique of noninvasive ETS feedback is then highlighted. Finally, challenges to future development of the biorealistic hand prosthesis and implementing the ETS feedback are discussed with respect to shaping a next-generation hand prosthesis.