Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy.
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy.
Neuroimage Clin. 2022;34:102972. doi: 10.1016/j.nicl.2022.102972. Epub 2022 Feb 25.
There is an increasing need of sharing harmonized data from large, cooperative studies as this is essential to develop new diagnostic and prognostic biomarkers. In the field of multiple sclerosis (MS), the issue has become of paramount importance due to the need to translate into the clinical setting some of the most recent MRI achievements. However, differences in MRI acquisition parameters, image analysis and data storage across sites, with their potential bias, represent a substantial constraint. This review focuses on the state of the art, recent technical advances, and desirable future developments of the harmonization of acquisition, analysis and storage of large-scale multicentre MRI data of MS cohorts. Huge efforts are currently being made to achieve all the requirements needed to provide harmonized MRI datasets in the MS field, as proper management of large imaging datasets is one of our greatest opportunities and challenges in the coming years. Recommendations based on these achievements will be provided here. Despite the advances that have been made, the complexity of these tasks requires further research by specialized academical centres, with dedicated technical and human resources. Such collective efforts involving different professional figures are of crucial importance to offer to MS patients a personalised management while minimizing consumption of resources.
由于需要将最近的一些 MRI 成果转化为临床应用,多发性硬化症 (MS) 领域对共享大型合作研究中协调一致的数据的需求日益增加,而这一点至关重要。然而,由于各研究中心之间在 MRI 采集参数、图像分析和数据存储方面存在差异,以及由此带来的潜在偏差,这成为了一个重大的限制因素。这篇综述重点介绍了在 MS 队列的大型多中心 MRI 数据的采集、分析和存储方面实现协调的最新技术进展和未来发展方向。目前正在做出巨大努力,以满足在 MS 领域提供协调一致的 MRI 数据集所需的所有要求,因为妥善管理大型成像数据集是我们未来几年面临的最大机遇和挑战之一。在此提供基于这些成果的建议。尽管已经取得了进展,但这些任务的复杂性仍需要由专业学术中心进一步研究,需要配备专门的技术和人力资源。这种涉及不同专业人士的集体努力对于为 MS 患者提供个性化管理,同时最大限度地减少资源消耗至关重要。