Challenges and opportunities of integrating imaging and mathematical modelling to interrogate biological processes.
Challenges and opportunities of integrating imaging and mathematical modelling to interrogate biological processes.
复制标题
DOI：
10.1016/j.biocel.2022.106195
复制
发表时间：
2022-05
期刊：
影响因子：
--
通讯作者：
中科院分区：
文献类型：
--
作者：
生物成像的进步加速了我们对健康和疾病方面的人体生理学的理解。随着这些进步的发展，通过与尖端数学模型集成所获得的机会已经变得明显，但仍然具有挑战性。结合成像建模方法提供了前所未有的机会，可以跨长度和时间尺度将组织结构和功能的数据关联起来，以更好地了解基础生物学的机制，并为临床决策提供信息。在这里，我们讨论了这些方法的机遇和挑战，提供了一系列器官系统的文献例子。鉴于该领域的广度，我们专注于连续建模和应用于脉管系统和血流的体内成像的交叉点，尽管我们的理论基础和结论广泛延伸。我们提出了三个关键的研究支柱（图像采集，图像处理，数学建模），并通过更好的整合，提出各自的进步以及未来的机会。同时开发成像和建模工具的多学科努力，并与研究界开源共享，为推进这些领域提供了令人兴奋的机会。
Advances in biological imaging have accelerated our understanding of human physiology in both health and disease. As these advances have developed, the opportunities gained by integrating with cutting-edge mathematical models have become apparent yet remain challenging. Combined imaging-modelling approaches provide unprecedented opportunity to correlate data on tissue architecture and function, across length and time scales, to better understand the mechanisms that underpin fundamental biology and also to inform clinical decisions. Here we discuss the opportunities and challenges of such approaches, providing literature examples across a range of organ systems. Given the breadth of the field we focus on the intersection of continuum modelling and in vivo imaging applied to the vasculature and blood flow, though our rationale and conclusions extend widely. We propose three key research pillars (image acquisition, image processing, mathematical modelling) and present their respective advances as well as future opportunity via better integration. Multidisciplinary efforts that develop imaging and modelling tools concurrently, and share them open-source with the research community, provide exciting opportunity for advancing these fields.
登录
查看更多内容
影响因子：
3.7
作者：
Pearce P;Brownbill P;Janáček J;Jirkovská M;Kubínová L;Chernyavsky IL;Jensen OE
通讯作者：
Jensen OE
影响因子：
4
作者：
Epp R;Schmid F;Weber B;Jenny P
通讯作者：
Jenny P
影响因子：
4.3
作者：
Coy R;Berg M;Phillips JB;Shipley RJ
通讯作者：
Shipley RJ
影响因子：
48
作者：
Gomez-de-Mariscal, Estibaliz;Garcia-Lopez-de-Haro, Carlos;Sage, Daniel
通讯作者：
Sage, Daniel
影响因子：
3.3
作者：
Slator PJ;Hutter J;McCabe L;Gomes ADS;Price AN;Panagiotaki E;Rutherford MA;Hajnal JV;Alexander DC
通讯作者：
Alexander DC