Imaging in the context of 3R: chances and threats

在之前的资助期间，我们获得了关于成像技术（磁共振成像（MRI），超声（US）和计算机断层扫描（CT））对健康和荷瘤小鼠的动物福利和研究结果的影响的重要见解。根据我们的严重性测试，测试的成像方案耐受良好。然而，CT和造影剂增强US诱导肿瘤生理学变化（特别是肿瘤灌注和免疫反应），通过系统综述对其进行了进一步研究。另一个问题是，最先进的严重性测试是否足够灵敏，可以检测到即使是轻微的负担和组织反应，以及这是否可以通过成像应用进行改进。因此，我们实施了同时检测疼痛（[18 F]氟匹定-PET-CT）和组织损伤（[99 mTc]-Duramycin-SPECT-CT）的成像概念。通过使用这个新的概念，我们已经验证了术后镇痛协议在大鼠模型的部分肝切除术的适用性。结果表明，我们的方法可以显着提高疼痛监测在未来的临床前研究，并为其他严重程度评估工具的参考。目前，我们正在研究这些示踪剂在神经性疼痛模型中的适用性。 第三个资助期将专注于对先前收集的行为和生理福利数据进行深入分析。因此，将对数据进行重新分析，以显著提高相对严重程度评估（RESSASA）工具的通用性和稳健性。此外，我们还计划利用CIMSA工具来设计和发布成像协议的适当评分表。通过将这些数据集与我们联盟内其他工作组的数据集进行比较，并进行进一步的系统评价（例如，CT对肿瘤生理学的影响），我们的目标是为“改进”成像技术（例如，适当的麻醉方案）。在之前的资助期间，我们已经发布了一些成像数据作为CT参考数据库，使科学界能够根据FAIR标准免费访问。在第三个资助期内，我们计划创建一个扩展和全面的成像数据库，包括来自各种成像模式和疾病模型的数据。该数据库将易于访问，并能够重复使用数据，从而促进长期减少实验室动物。最后，我们的目标是制定全面的建议，有效和可靠地使用成像的实验和评估其严重性的改进。我们将通过对已有数据的详细比较来实现这一点，重点是我们的成像协议与传统方法相比的灵敏度。

During the previous funding periods, we gained important insights into the effects of imaging techniques (Magnetic Resonance Imaging (MRI), Ultrasound (US), and Computed Tomography (CT)) on animal welfare and study outcomes in healthy and tumor-bearing mice. The tested imaging protocols were well tolerated according to our severity tests. However, CT and contrast-enhanced US induced changes in tumor physiology (esp. tumor perfusion and immune reactions), which were further investigated through a systematic review. Another question was whether state of the art severity tests are sensitive enough to detect even mild burdens and tissue reactions and whether this can be refined by imaging applications. Therefore, we implemented an imaging concept for the simultaneous detection of pain ([18F]Fluspidine-PET-CT) and tissue damage ([99mTc]-Duramycin-SPECT-CT). By using this new concept, we have already validated the suitability of a postoperative analgesia protocol in a rat model of partial liver resection. The results indicate that our approach can significantly enhance pain monitoring in future preclinical studies and be a reference for other severity assessment tools. Currently, we are investigating the suitability of these tracers in models of neuropathic pain. The 3rd funding period will focus on an in-depth analysis of previously collected behavioral and physiological welfare data. Thereby, the data will be re-analyzed to significantly improve the generalizability and robustness of the RElative Severity Assessment (RELSA) tool. Additionally, we plan to utilize the RELSA tool to design and publish appropriate score sheets for imaging protocols. By comparing these datasets with those from other working groups within our consortium and conducting further systematic reviews (e.g., CT effects on tumor physiology), we aim to develop comprehensive recommendations for “refining” imaging techniques (e.g., appropriate anesthesia protocols). During the previous funding periods, we have already published some of the imaging data as a CT reference database, making it freely accessible to the scientific community in accordance to FAIR criteria. In the 3rd funding period, we plan to create an expanded and comprehensive imaging database comprising data from various imaging modalities and disease models. This database will be easily accessible and enable data reuse, thereby promoting the long-term reduction of laboratory animals. Lastly, we aim to develop comprehensive recommendations for the efficient and reliable use of imaging for the refinement of experiments and the assessment of their severity. We will accomplish this by detailed comparison of our pre-existing data, focusing on the sensitivity of our imaging protocols in contrast to conventional methods.