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INTRODUCTION

In oncological drug development, animal studies continue to play a central role in which the volume of subcutaneous tumours is monitored to assess the efficacy of new drugs. The tumour volume is estimated by taking the volume to be that of a regular spheroid with the same dimensions. However, this method is subjective, insufficiently traceable, and is subject to error in the accuracy of volume estimates as tumours are frequently irregular.

METHODS & RESULTS: This paper reviews the standard technique for tumour volume assessment, calliper measurements, by conducting a statistical review of a large dataset consisting of 2,500 tumour volume measurements from 1,600 mice by multiple operators across 6 mouse strains and 20 tumour models. Additionally, we explore the impact of six different tumour morphologies on volume estimation and the detection of treatment effects using a computational tumour growth model. Finally, we propose an alternative method to callipers for estimating volume-BioVolumeTM, a 3D scanning technique. BioVolume simultaneously captures both stereo RGB (Red, Green and Blue) images from different light sources and infrared thermal images of the tumour in under a second. It then detects the tumour region automatically and estimates the tumour volume in under a minute. Furthermore, images can be processed in parallel within the cloud and so the time required to process multiple images is similar to that required for a single image. We present data of a pre-production unit test consisting of 297 scans from over 120 mice collected by four different operators.

CONCLUSION

This work demonstrates that it is possible to record tumour measurements in a rapid minimally invasive, morphology-independent way, and with less human-bias compared to callipers, whilst also improving data traceability. Furthermore, the images collected by BioVolume may be useful, for example, as a source of biomarkers for animal welfare and secondary drug toxicity / efficacy.

INTRODUCTION

CONCLUSION

简介

在肿瘤药物开发中，动物研究仍然起着核心作用，其中监测皮下肿瘤的体积以评估新药的疗效。肿瘤体积通过将其估计为具有相同尺寸的规则球体来估计。然而，这种方法是主观的，可追溯性不足，并且由于肿瘤经常不规则，因此在体积估计的准确性方面存在误差。

方法和结果

本文通过对由 6 个品系和 20 个肿瘤模型的 1600 只小鼠的 2500 个肿瘤体积测量值组成的大型数据集进行统计审查，回顾了肿瘤体积评估的标准技术——卡尺测量。此外，我们还探讨了六种不同肿瘤形态对体积估计和治疗效果检测的影响，使用计算肿瘤生长模型。最后，我们提出了一种替代卡尺的方法——BioVolumeTM，这是一种 3D 扫描技术。BioVolume 可以在不到一秒的时间内同时从不同光源捕获立体 RGB（红、绿、蓝）图像和肿瘤的红外热图像。然后它自动检测肿瘤区域，并在不到一分钟的时间内估计肿瘤体积。此外，图像可以在云中并行处理，因此处理多个图像所需的时间与处理单个图像所需的时间相似。我们展示了一个由四个不同操作人员从 120 多只老鼠收集的超过 297 次扫描组成的预生产单元测试的数据。