Bone Matan, Malik Maham, Crilly Siobhan
School of Medical Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre and The University of Manchester, Manchester, UK.
Division of Neuroscience, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre and The University of Manchester, Manchester, UK.
Brain Neurosci Adv. 2023 Jun 21;7:23982128231182506. doi: 10.1177/23982128231182506. eCollection 2023 Jan-Dec.
As a leading cause of mortality and morbidity, stroke and its management have been studied extensively. Despite numerous pre-clinical studies identifying therapeutic targets, development of effective, specific pharmacotherapeutics remain limited. One significant limitation is a break in the translational pipeline - promising pre-clinical results have not always proven replicable in the clinic. Recent developments in virtual reality technology might help generate a better understanding of injury and recovery across the whole research pipeline in search of optimal stroke management. Here, we review the technologies that can be applied both clinically and pre-clinically to stroke research. We discuss how virtual reality technology is used to quantify clinical outcomes in other neurological conditions that have potential to be applied in stroke research. We also review current uses in stroke rehabilitation and suggest how immersive programmes would better facilitate the quantification of stroke injury severity and patient recovery comparable to pre-clinical study design. By generating continuous, standardised and quantifiable data from injury onset to rehabilitation, we propose that by paralleling pre-clinical outcomes, we can apply a better reverse-translational strategy and apply this understanding to animal studies. We hypothesise this combination of translational research strategies may improve the reliability of pre-clinical research outcomes and culminate in real-life translation of stroke management regimens and medications.
作为导致死亡和发病的主要原因,中风及其治疗方法已得到广泛研究。尽管众多临床前研究确定了治疗靶点,但有效的特异性药物治疗的开发仍然有限。一个显著的限制是转化流程的中断——有前景的临床前结果在临床上并不总是能够得到重复验证。虚拟现实技术的最新发展可能有助于在整个研究流程中更好地理解损伤和恢复情况,以寻找最佳的中风治疗方法。在此,我们综述了可在临床和临床前应用于中风研究的技术。我们讨论了虚拟现实技术如何用于量化其他神经系统疾病的临床结果,这些结果有可能应用于中风研究。我们还综述了其在中风康复中的当前应用,并提出沉浸式方案如何能更好地促进中风损伤严重程度和患者恢复情况的量化,使其与临床前研究设计相当。通过从损伤发生到康复生成连续、标准化和可量化的数据,我们建议通过与临床前结果并行,我们可以应用更好的反向转化策略,并将这种理解应用于动物研究。我们假设这种转化研究策略的结合可能会提高临床前研究结果的可靠性,并最终实现中风治疗方案和药物在现实生活中的转化。