The task of ethical Medical Image Synthesis (MISyn) is to ensure that the MISyn techniques are researched and developed ethically throughout their entire lifecycle, which is essential to prevent the negative impacts of MISyn. To address the ever-increasing needs and requirements for ethical practice of MISyn research and development, we first conduct a theoretical analysis that identifies the key properties of ethical MISyn and intrinsic limits of MISyn. We identify that synthetic images lack inherent grounding in real medical phenomena, cannot fully represent the training medical images, and inevitably introduce new distribution shifts and biases. Ethical risks can arise from not acknowledging the intrinsic limits and weaknesses of synthetic images compared to medical images, with the extreme form manifested as misinformation of MISyn that substitutes synthetic images for medical images without acknowledgment. The resulting ethical harms include eroding trust in the medical imaging dataset environment and causing algorithmic discrimination towards stakeholders and the public. To facilitate collective efforts towards ethical MISyn within and outside the medical image analysis community, we then propose practical supports for ethical practice in MISyn based on the theoretical analysis, including ethical practice recommendations that adapt the existing technical standards, problem formulation, design, and evaluation practice of MISyn to the ethical challenges; and oversight recommendations to facilitate checks and balances from stakeholders and the public. We also present two case studies that demonstrate how to apply the ethical practice recommendations in practice, and identify gaps between existing practice and the ethical practice recommendations.

翻译：伦理医学图像合成（MISyn）的任务是确保MISyn技术在其整个生命周期中得到合乎伦理的研究与开发，这对于防止MISyn的负面影响至关重要。为应对MISyn研发实践中日益增长的伦理需求与要求，我们首先进行了理论分析，明确了伦理MISyn的关键特性以及MISyn的内在局限。我们指出，合成图像缺乏对真实医学现象的内在基础，无法完全代表训练所用的医学图像，并且不可避免地会引入新的分布偏移与偏差。若不承认合成图像相较于医学图像的内在局限与弱点，便可能产生伦理风险，其极端表现形式是MISyn信息误导，即在未予说明的情况下以合成图像替代医学图像。由此导致的伦理危害包括侵蚀医学影像数据集环境的可信度，以及对利益相关方和公众造成算法歧视。为促进医学图像分析社区内外共同致力于实现伦理MISyn，我们随后基于理论分析，提出了支持MISyn伦理实践的实用方案，包括：伦理实践建议——将MISyn现有的技术标准、问题定义、设计与评估实践调整以适应伦理挑战；以及监督建议——以促进利益相关方和公众的制衡。我们还提供了两个案例研究，展示如何在实践中应用这些伦理实践建议，并指出现有实践与伦理实践建议之间存在的差距。