Rietberg Max T, Gröhl Janek, Else Thomas R, Bohndiek Sarah E, Manohar Srirang, Cox Benjamin T
Multi-Modality Medical Imaging, TechMed Centre, University of Twente, Drienerlolaan 5, Enschede, 7522 NB, Overijssel, The Netherlands.
Cancer Research UK, Cambridge Institute, University of Cambridge, Robinson Way, Cambridge, CB2 0RE, United Kingdom.
Photoacoustics. 2025 Jul 5;45:100745. doi: 10.1016/j.pacs.2025.100745. eCollection 2025 Oct.
Photoacoustic imaging (PAI) is rapidly moving from the laboratory to the clinic, increasing the need to understand confounders which might adversely affect patient care. Over the past five years, landmark studies have shown the clinical utility of PAI, leading to regulatory approval of several devices. In this article, we describe the various causes of artifacts in PAI, providing schematic overviews and practical examples, simulated as well as experimental. This work serves two purposes: (1) educating clinical users to identify artifacts, understand their causes, and assess their impact, and (2) providing a reference of the limitations of current systems for those working to improve them. We explain how two aspects of PAI systems lead to artifacts: their inability to measure complete data sets, and embedded assumptions during reconstruction. We describe the physics underlying PAI, and propose a classification of the artifacts. The paper concludes by discussing possible advanced mitigation strategies.
光声成像(PAI)正迅速从实验室走向临床,这增加了人们对了解可能对患者护理产生不利影响的混杂因素的需求。在过去五年中,具有里程碑意义的研究已经证明了PAI的临床实用性,促使多款设备获得监管批准。在本文中,我们描述了PAI中伪像的各种成因,并提供了示意图概述以及实际示例,包括模拟和实验示例。这项工作有两个目的:(1)教育临床用户识别伪像、理解其成因并评估其影响;(2)为致力于改进当前系统的人员提供有关当前系统局限性的参考。我们解释了PAI系统的两个方面如何导致伪像:它们无法测量完整数据集以及重建过程中固有的假设。我们描述了PAI背后的物理原理,并提出了伪像的分类。本文最后讨论了可能的先进缓解策略。