Monitoring the Growth of an Orthotopic Tumour Xenograft Model: Multi-Modal Imaging Assessment with Benchtop MRI (1T), High-Field MRI (9.4T), Ultrasound and Bioluminescence

RESEARCH ARTICLE Monitoring the Growth of an Orthotopic Tumour Xenograft Model: Multi-Modal Imaging Assessment with Benchtop MRI (1T), High-Field MRI (9.4T), Ultrasound and Bioluminescence a11111 Rajiv Ramasawmy1,2☯*, S. Peter Johnson1,2☯, Thomas A. Roberts1☯, Daniel J. Stuckey1, Anna L. David3, R. Barbara Pedley2, Mark F. Lythgoe1‡, Bernard Siow1‡, Simon WalkerSamuel1‡ 1 UCL Centre for Advanced Biomedical Imaging, Division of Medicine, London, United Kingdom, 2 UCL Cancer Institute, London, United Kingdom, 3 UCL Institute for Women’s Health, London, United Kingdom OPEN ACCESS Citation: Ramasawmy R, Johnson SP, Roberts TA, Stuckey DJ, David AL, Pedley RB, et al. (2016) Monitoring the Growth of an Orthotopic Tumour Xenograft Model: Multi-Modal Imaging Assessment with Benchtop MRI (1T), High-Field MRI (9.4T), Ultrasound and Bioluminescence. PLoS ONE 11(5): e0156162. doi:10.1371/journal.pone.0156162 Editor: Gayle E. Woloschak, Northwestern University Feinberg School of Medicine, UNITED STATES Received: October 7, 2015 Accepted: May 10, 2016 Published: May 25, 2016 Copyright: © 2016 Ramasawmy et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: All relevant data are within the paper and its Supporting Information files. Funding: This work was carried out as part of King’s College London and UCL Comprehensive Cancer Imaging Centre, and The Institute of Cancer Research Cancer Imaging Centre, CR-UK & EPSRC, in association with the Medical Research Council (MRC), Department of Health and British Heart Foundation (England) (C1519/A10331, C1519/ A16463). R. Ramasawmy receives funding from the MRC (MRC 1028351). R. B. Pedley receives funding ☯ These authors contributed equally to this work. ‡ These authors also contributed equally to this work. * Abstract Background Research using orthotopic and transgenic models of cancer requires imaging methods to non-invasively quantify tumour burden. As the choice of appropriate imaging modality is wide-ranging, this study aimed to compare low-field (1T) magnetic resonance imaging (MRI), a novel and relatively low-cost system, against established preclinical techniques: bioluminescence imaging (BLI), ultrasound imaging (US), and high-field (9.4T) MRI. Methods A model of colorectal metastasis to the liver was established in eight mice, which were imaged with each modality over four weeks post-implantation. Tumour burden was assessed from manually segmented regions. Results All four imaging systems provided sufficient contrast to detect tumours in all of the mice after two weeks. No significant difference was detected between tumour doubling times estimated by low-field MRI, ultrasound imaging or high-field MRI. A strong correlation was measured between high-field MRI estimates of tumour burden and all the other modalities (p < 0.001, Pearson). PLOS ONE | DOI:10.1371/journal.pone.0156162 May 25, 2016 1 / 16 Multimodal Imaging Comparison of an Orthotopic Liver Tumour Model from Medical Research Funding DPFS grant (MRC G100149). M. F. Lythgoe receives funding from MRC (MR/J013110/1); the National Centre for the Replacement, Reduction and Refinement of Animal in Research (NC3Rs); UK Regenerative Medicine Platform Safety Hub (MRC: MR/K026739/1). S. Walker-Samuel is a Wellcome Trust Senior Research Fellow (WT100247MA). S. P. Johnson and T. A. Roberts receive funding from the Wellcome Trust (WT100247MA). A. L. David is supported by the University College London/ University College London Hospital National Institute for Health Research Comprehensive Biomedical Research Centre. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. Conclusion These results suggest that both low-field MRI and ultrasound imaging are accurate modalities for characterising the growth of preclinical tumour models. Introduction Translation of research in oncology, from basic biology to therapeutic drug strategies, requires the use of experimental models of disease. Transgenic and orthotopic models are increasingly used to study a tumour microenvironment that more accurately reflects the growth and clinical presentation of the disease [1] than in traditional subcutaneous tumour models [2–4]. Whilst these models have the potential to improve the translation of novel therapeutic strategies, monitoring tumour growth and response to therapy is generally not straightforward. In particular, transgenic models develop tumours spontaneously and over a longer period compared to implanted orthotopic models, hence a screening method is vital. Tumour sites can be inaccessible to traditional calliper measurement of tumour volume [5], and invasive methods used to assess tumour volume require the termination of entire animal groups, which is incompatible with longitudinal studies and greatly increases the number of animals required. Biomedical imaging is key to overcoming this limitation [6], and, additionally, facilitates paired statistical analysis from longitudinal measurements and reduces the required cohort sizes. However, which imaging modality offers the best and most practical solution is often difficult to determine. In recent years, small-animal imaging has rapidly evolved and many dedicated platforms exist [7], including magnetic resonance imaging (MRI), ultrasound imaging (US), x-ray computed tomography (CT), positron emission tomography (PET), single photon emission computed tomography (SPECT), fluorescence imaging (FLI), photoacoustic imaging (PAI) and bioluminescence imaging (BLI). More recently, low-field, ‘benchtop’ MRI scanners have been developed, which offer promise for relative low-cost and precise imaging of pre-clinical models [8–11]. Several of these imaging modalities can also provide functional information on tumour function and microstructure, such as blood flow [12;13], cell density [14], hypoxia [15] and metabolite concentration [16], each of which has been used to assess response to anti-cancer therapy. However, particularly for drug development in cancer, the parameter of greatest interest still tends to be tumour volume. For translational research, measurement of the change in tumour volume allows direct comparison with the clinical assessment via the RECIST criteria [17]. Determining pre-therapy tumour volumes of animal models in therapy trials is essential for group standardisation, alongside the confirmation of successful engraftment. Measuring tumour volume is generally straightforward and fast, although the imaging modality that provides the optimal platform, both in terms of scientific and practical considerations, depends on the requirements of a particular study. The acc (...truncated)