Abadi Ehsan, Barufaldi Bruno, Lago Miguel, Badal Andreu, Mello-Thoms Claudia, Bottenus Nick, Wangerin Kristen A, Goldburgh Mitchell, Tarbox Lawrence, Beaucage-Gauvreau Erica, Frangi Alejandro F, Maidment Andrew, Kinahan Paul E, Bosmans Hilde, Samei Ehsan
Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Departments of Radiology and Electrical & Computer Engineering, Medical Physics Graduate Program, Duke University, Durham, North Carolina, USA.
Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Med Phys. 2024 Dec;51(12):9394-9404. doi: 10.1002/mp.17442. Epub 2024 Oct 6.
The rapid advancement in the field of medical imaging presents a challenge in keeping up to date with the necessary objective evaluations and optimizations for safe and effective use in clinical settings. These evaluations are traditionally done using clinical imaging trials, which while effective, pose several limitations including high costs, ethical considerations for repetitive experiments, time constraints, and lack of ground truth. To tackle these issues, virtual trials (aka in silico trials) have emerged as a promising alternative, using computational models of human subjects and imaging devices, and observer models/analysis to carry out experiments. To facilitate the widespread use of virtual trials within the medical imaging research community, a major need is to establish a common consensus framework that all can use. Based on the ongoing efforts of an AAPM Task Group (TG387), this article provides a comprehensive overview of the requirements for establishing virtual imaging trial frameworks, paving the way toward their widespread use within the medical imaging research community. These requirements include credibility, reproducibility, and accessibility. Credibility assessment involves verification, validation, uncertainty quantification, and sensitivity analysis, ensuring the accuracy and realism of computational models. A proper credibility assessment requires a clear context of use and the questions that the study is intended to objectively answer. For reproducibility and accessibility, this article highlights the need for detailed documentation, user-friendly software packages, and standard input/output formats. Challenges in data and software sharing, including proprietary data and inconsistent file formats, are discussed. Recommended solutions to enhance accessibility include containerized environments and data-sharing hubs, along with following standards such as CDISC (Clinical Data Interchange Standards Consortium). By addressing challenges associated with credibility, reproducibility, and accessibility, virtual imaging trials can be positioned as a powerful and inclusive resource, advancing medical imaging innovation and regulatory science.
医学成像领域的快速发展给紧跟临床环境中安全有效使用所需的客观评估和优化带来了挑战。传统上，这些评估是通过临床成像试验进行的，虽然有效，但存在一些局限性，包括成本高、重复实验的伦理考量、时间限制以及缺乏真实情况。为了解决这些问题，虚拟试验（又称计算机模拟试验）作为一种有前景的替代方法出现了，它使用人体和成像设备的计算模型以及观察者模型/分析来进行实验。为了促进虚拟试验在医学成像研究界的广泛应用，一个主要需求是建立一个所有人都能使用的通用共识框架。基于美国医学物理学家协会任务组（TG387）正在进行的工作，本文全面概述了建立虚拟成像试验框架的要求，为其在医学成像研究界的广泛应用铺平道路。这些要求包括可信度、可重复性和可及性。可信度评估涉及验证、确认、不确定性量化和敏感性分析，以确保计算模型的准确性和现实性。适当的可信度评估需要明确的使用背景以及该研究旨在客观回答的问题。对于可重复性和可及性，本文强调了详细文档、用户友好的软件包以及标准输入/输出格式的必要性。讨论了数据和软件共享方面的挑战，包括专有数据和不一致的文件格式。提高可及性的推荐解决方案包括容器化环境和数据共享中心，以及遵循诸如CDISC（临床数据交换标准协会）等标准。通过应对与可信度、可重复性和可及性相关的挑战，虚拟成像试验可以成为一种强大且包容的资源，推动医学成像创新和监管科学的发展。
