Macholl Sven, Finucane Ciara M, Hesterman Jacob, Mather Stephen J, Pauplis Rachel, Scully Deirdre, Sosabowski Jane K, Jouannot Erwan
inviCRO Ltd, Charterhouse Square, London, EC1M 6BQ, UK.
Centre for Molecular Oncology, Barts Cancer Institute, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK.
EJNMMI Res. 2017 Dec;7(1):33. doi: 10.1186/s13550-017-0281-4. Epub 2017 Apr 7.
Preclinical single-photon emission computed tomography (SPECT)/CT imaging studies are hampered by low throughput, hence are found typically within small volume feasibility studies. Here, imaging and image analysis procedures are presented that allow profiling of a large volume of radiolabelled compounds within a reasonably short total study time. Particular emphasis was put on quality control (QC) and on fast and unbiased image analysis.
2-3 His-tagged proteins were simultaneously radiolabelled by Tc-tricarbonyl methodology and injected intravenously (20 nmol/kg; 100 MBq; n = 3) into patient-derived xenograft (PDX) mouse models. Whole-body SPECT/CT images of 3 mice simultaneously were acquired 1, 4, and 24 h post-injection, extended to 48 h and/or by 0-2 h dynamic SPECT for pre-selected compounds. Organ uptake was quantified by automated multi-atlas and manual segmentations. Data were plotted automatically, quality controlled and stored on a collaborative image management platform. Ex vivo uptake data were collected semi-automatically and analysis performed as for imaging data.
500 single animal SPECT images were acquired for 25 proteins over 5 weeks, eventually generating >3500 ROI and >1000 items of tissue data. SPECT/CT images clearly visualized uptake in tumour and other tissues even at 48 h post-injection. Intersubject uptake variability was typically 13% (coefficient of variation, COV). Imaging results correlated well with ex vivo data.
The large data set of tumour, background and systemic uptake/clearance data from 75 mice for 25 compounds allows identification of compounds of interest. The number of animals required was reduced considerably by longitudinal imaging compared to dissection experiments. All experimental work and analyses were accomplished within 3 months expected to be compatible with drug development programmes. QC along all workflow steps, blinding of the imaging contract research organization to compound properties and automation provide confidence in the data set. Additional ex vivo data were useful as a control but could be omitted from future studies in the same centre. For even larger compound libraries, radiolabelling could be expedited and the number of imaging time points adapted to increase weekly throughput. Multi-atlas segmentation could be expanded via SPECT/MRI; however, this would require an MRI-compatible mouse hotel. Finally, analysis of nuclear images of radiopharmaceuticals in clinical trials may benefit from the automated analysis procedures developed.
临床前单光子发射计算机断层扫描（SPECT）/计算机断层扫描（CT）成像研究因通量低而受到阻碍，因此通常在小容量可行性研究中进行。本文介绍了成像和图像分析程序，可在合理的短总研究时间内对大量放射性标记化合物进行分析。特别强调了质量控制（QC）以及快速且无偏差的图像分析。
采用三羰基锝方法同时对2 - 3种带有组氨酸标签的蛋白质进行放射性标记，并静脉注射（20 nmol/kg；100 MBq；n = 3）到患者来源的异种移植（PDX）小鼠模型中。在注射后1、4和24小时同时采集3只小鼠的全身SPECT/CT图像，对于预先选定的化合物，可延长至48小时和/或进行0 - 2小时的动态SPECT。通过自动多图谱和手动分割对器官摄取进行定量。数据自动绘制、进行质量控制并存储在协作图像管理平台上。半自动收集离体摄取数据，并按照成像数据的分析方法进行分析。
在5周内对25种蛋白质采集了>500张单只动物的SPECT图像，最终生成>3500个感兴趣区域（ROI）和>1000项组织数据。即使在注射后48小时，SPECT/CT图像也能清晰显示肿瘤和其他组织中的摄取情况。个体间摄取变异性通常为13%（变异系数，COV）。成像结果与离体数据相关性良好。
来自75只小鼠、针对25种化合物的肿瘤、背景及全身摄取/清除的大数据集，有助于识别感兴趣的化合物。与解剖实验相比，纵向成像显著减少了所需动物的数量。所有实验工作和分析均在3个月内完成，预计与药物开发计划兼容。所有工作流程步骤的质量控制、成像合同研究组织对化合物特性的盲法处理以及自动化操作，为数据集提供了可信度。额外的离体数据作为对照很有用，但在同一中心的未来研究中可以省略。对于更大的化合物库，可以加快放射性标记速度，并调整成像时间点的数量以提高每周通量。可通过SPECT/磁共振成像（MRI）扩展多图谱分割；然而，这需要一个与MRI兼容的小鼠饲养笼。最后，临床试验中放射性药物的核图像分析可能会受益于所开发的自动分析程序。
