Summary

A Dorsal Skinfold Window Chamber Tumor Mouse Model for Combined Intravital Microscopy and Magnetic Resonance Imaging in Translational Cancer Research

Published: April 12, 2024
doi:

Summary

Translation of Intravital microscopy findings is challenged by its shallow depth penetration into tissue. Here we describe a dorsal window chamber mouse model that enables co-registration of intravital microscopy and clinically applicable imaging modalities (e.g., CT, MRI) for direct spatial correlation, potentially streamlining clinical translation of intravital microscopy findings.

Abstract

Preclinical intravital imaging such as microscopy and optical coherence tomography have proven to be valuable tools in cancer research for visualizing the tumor microenvironment and its response to therapy. These imaging modalities have micron-scale resolution but have limited use in the clinic due to their shallow penetration depth into tissue. More clinically applicable imaging modalities such as CT, MRI, and PET have much greater penetration depth but have comparatively lower spatial resolution (mm scale).

To translate preclinical intravital imaging findings into the clinic, new methods must be developed to bridge this micro-to-macro resolution gap. Here we describe a dorsal skinfold window chamber tumor mouse model designed to enable preclinical intravital and clinically applicable (CT and MR) imaging in the same animal, and the image analysis platform that links these two disparate visualization methods. Importantly, the described window chamber approach enables the different imaging modalities to be co-registered in 3D using fiducial markers on the window chamber for direct spatial concordance. This model can be used for validation of existing clinical imaging methods, as well as for the development of new ones through direct correlation with “ground truth” high-resolution intravital findings.

Finally, the tumor response to various treatments-chemotherapy, radiotherapy, photodynamic therapy-can be monitored longitudinally with this methodology using preclinical and clinically applicable imaging modalities. The dorsal skinfold window chamber tumor mouse model and imaging platforms described here can thus be used in a variety of cancer research studies, for example, in translating preclinical intravital microscopy findings to more clinically applicable imaging modalities such as CT or MRI.

Introduction

Tumor microvasculature is an important component of the tumor microenvironment that can be a target for therapy and a determinant of treatment response. In the preclinical setting, the microvasculature is typically studied using intravital microscopy in orthotopic or heterotopic window chamber animal models1,2. This has several advantages over histological studies since the imaging is done in live tissues and the tumor can be monitored longitudinally over several weeks or even months2,3. These studies can leverage the high-resolution imaging capabilities of intravital microscopy to study the delivery of therapeutics to the tumor4,5, the causes of treatment resistance6, and the response of the micro vessels to therapies such as antiangiogenic treatment7,8 and radiotherapy2,9.

Intravital microscopy clearly plays an important role in preclinical cancer research; however, how can tumor microenvironmental features be measured in the clinic? Microvascular information would be useful in the clinic for measuring blood supply and tumor cell hypoxia, which is important for determining treatment resistance in radiotherapy10, as well as the ability of the microvasculature to deliver chemotherapeutic agents to the surrounding tumor cells11. For example, in radiotherapy, spatial information on the structure and function of the tumor microvasculature may help personalize a patient's treatment plan by adjusting the fractionation schedule or by preferentially boosting the dose to avascular and likely hypoxic regions12.

Intravital microscopy can measure these important microvascular features since it has a very high resolution (μm scale); however, its depth penetration into tissue is limited to several hundred microns or a few millimeters, at most making clinical implementation challenging. Indeed, there are some novel applications of intravital microscopy in the clinic13; however, these are still limited to examinations of near-surface level tissue such as the skin14 or mucosal/endothelial linings of various body cavities via flexible catheters/endoscopes15,16.

More commonly, the microvasculature is studied using imaging modalities such as CT17 or MRI18. These clinical imaging modalities can image to any depth within the body, but they have a much lower spatial resolution (mm scale). Thus, there is a need to bridge this resolution gap between preclinical intravital microscopy and clinical imaging modalities to bring high-resolution and detailed microvascular information into the clinic19. Several functional imaging methods have been developed to improve the microvascular imaging capabilities of clinical imaging modalities such as dynamic contrast-enhanced (DCE) MRI and CT20, and Intravoxel incoherent motion (IVIM) MRI21. However, these are model-based methods that provide indirect measurements of the microvasculature and thus, must be validated with appropriate "ground truth" measurements of the microvasculature19,22.

We have developed a dorsal skinfold window chamber (DSFC) tumor mouse model to bridge this gap between preclinical intravital microscopy and clinically applicable imaging modalities such as CT and MRI. The DSFC provides direct access to the tumor for high-resolution, intravital microscopy imaging through a glass window but also clinically applicable imaging such as MRI as it is made of MR-compatible materials (plastic and glass). Furthermore, an included MATLAB code performs multimodality 3D co-registration for direct spatial correlations between preclinical intravital microscopy and clinically applicable imaging modalities. Here we will describe the design and surgery to install the DSFC as well as the procedure to co-register intravital microscopy and clinically applicable imaging modalities.

Protocol

All animal procedures were performed in accordance with the Guide to the Care and Use of Experimental Animals which is set forth by the Canadian Council on Animal Care. Experiments were performed according to a protocol approved by the University Health Network Institutional Animal Care and Use Committee in Toronto, Canada. 1. Tumor inoculation landmarking NOTE: "Landmarking" refers to the process of marking the skin of the mouse to indicate w…

Representative Results

Speckle variance optical coherence tomography (svOCT) was performed to obtain large field-of-view (FOV) 3D microvascular images (6 x 6 mm2 lateral x 1 mm depth). To obtain these images, a previously described swept source OCT system based on a quadrature interferometer was used23. OCT images were acquired by stitching together two laterally adjacent 3 x 6 mm2 FOV scans. Each B-scan consisted of 400 A-scans and was performed 24x per location (25 ms apart) to enable accurate sp…

Discussion

In this work, we have developed a workflow to perform both intravital microscopy and clinically applicable imaging (CT, MRI, and PET) in the same animal. This was done with the goal of translating preclinical microscopy findings to the clinic by direct correlation of intravital microscopy with clinical imaging modalities such as MRI. Although conventional DSFC designs are made of metal2,3, we have adapted the DSFC to be MR-compatible by using 3D-printed window ch…

Disclosures

The authors have nothing to disclose.

Acknowledgements

We thank Dr. Carla Calçada (Postdoctoral Fellow, Princess Margaret Cancer Centre) and Dr. Timothy Samuel (Ph.D. Student, Princess Margaret Cancer Centre) for help with tumor cell culturing and inoculation protocol development. Dr. Kathleen Ma, Dr. Anna Pietraszek, and Dr. Alyssa Goldstein (Animal Research Centre, Princess Margaret Cancer Centre) helped with surgery protocol development. Jacob Broske (Medical Engineering Technologist, Princess Margaret Cancer Centre) and Wayne Keller (Hardware Client Executive, Javelin Technologies – A TriMech Group Company) 3D printed the window chambers. James Jonkman (Advanced Optical Microscopy Facility, University Health Network) provided valuable guidance for brightfield and fluorescence microscopy image acquisition.

Materials

Cell Culture Materials
BxPC-3 Human Pancreatic Cancer Cells ATCC (American Type Culture Collection) CRL-1687
Corning Matrigel Basement Membrane Matrix, LDEV-free, 10 mL Corning 354234
Corning Stripettor Ultra Pipet Controller Corning 07-202-350
Dulbecco Phospphate buffered saline without Calcium, Magnesium, or phenol red, 500 mL Gibco 14190144
Fetal Bovine Serum (Canada), 500 mL Sigma-Aldrich F1051-500ML
Penicillin-Streptomycin 100x (liquid,stabilized, sterile-filtered, cell culture tested) Sigma-Aldrich P4333-100ML
RPMI Medium 1640 (1x), liquid; with L-Glutamine, 500 mL Gibco 11875093
TrypLE Express Enzyme, 500 mL Gibco 12605028
Window Chamber Materials
12 mm Glass Coverslip Harvard Apparatus   CS-12R No. 1.5
Connex 500 3D Printer Stratasys N/A
Biocompatible clear MED610 resin Stratasys  RGD810
Loctite AA 3105 UV curable glue Loctite LCT1214249
Window chamber back frame Trimech Inc N/A
Window chamber fiducial marker Trimech Inc N/A
Window Chamber front frame Trimech Inc N/A
Window chamber support clip Trimech Inc N/A
inoculation and Surgery Materials
BD SafetyGlide Insulin Syringes with Permanently Attached Needles, 0.5 mL, 29 G x 1/2" BD CABD305932
Betadine Solution Betadine AP-B002C2R98U
Cidex OPA 14 Day Solution 3.8 L ASP JOH20394
Disposable Surgical Underpads 23 inch x 24 inch Kendall 7134
Eye lubricant   Optixcare 50-218-8442
Hair removal cream Nair ‎061700222611
Halstead Hemostatic Forceps Almedic 7742-A12-150
Heating pad Sunbeam  B086MCN59R
Iris Scissors Almedic 7601-A8-690
Isoflurane Sigma 792632
Metacam  Boehringer Ingelheim Animal Health USA Inc NDC 0010-6015-03
NOD.Cg-Rag1tm1Mom Il2rgtm1Wjl/SzJ mouse the Jackson laboratory 7799
Peanut Clipper & Trimmer Wahl 8655-200
 SOFSILK Nonabsorbable Surgical Suture #5-0 with 3/8" Taper point needle (17 mm) (Wax Coated,Braided Black Silk, Sterile)   Syneture   VS880
Splinter Forceps Almedic 7725-A10-634
MR Imaging
3D printed window chamber immobilization device. custom 3D printed, refer to figure 3 for details.
Convection heating device 3M Bair Hugger 70200791401
Drug injection system Harvard Apparatus   PY2 70-2131 PHD 22/2200 MRI compatible Syringe Pump
Gadovist 1.0 Bayer 2241089
Respiratory monitoring system SAII Model 1030 MR-compatible monitoring and gating system for small animals.
Tail vein catheter (27 G 0.5" ) Terumo Medical Corp 15253
Optical Imaging
3D printed imaging stage Custom 3D printed, refer to supplementary figure 3 for details.
12 V 7 W Flexible Polyimide Heater Plate Thin Adhesive PI Heating Film 25 mm x 50 mm BANRIA  B09X16XCVS Heating element used for mouse body temeprature regulation.
DC power supply BK Precission 1761 Used to power the heating element.
Leica MZ FLIII Leica Microsystems 15209
svOCT imaging system In-house made imaging system. Details can be found in reference 23.
Software
MATLAB Software MathWorks R2020A

References

  1. Fukumura, D., Duda, D. G., Munn, L. L., Jain, R. K. Tumor microvasculature and microenvironment: Novel insights through intravital imaging in pre-clinical models. Microcirculation. 17 (3), 206-225 (2010).
  2. Demidov, V., et al. Preclinical longitudinal imaging of tumor microvascular radiobiological response with functional optical coherence tomography. Sci Rep. 8 (1), 38 (2018).
  3. Alieva, M., Ritsma, L., Giedt, R. J., Weissleder, R., van Rheenen, J. Imaging windows for long-term intravital imaging. IntraVital. 3 (2), e29917 (2014).
  4. Dreher, M. R., et al. Tumor vascular permeability, accumulation, and penetration of macromolecular drug carriers. J Natl Cancer Inst. 98 (5), 335-344 (2006).
  5. Momiyama, M., et al. Subcellular real-time imaging of the efficacy of temozolomide on cancer cells in the brain of live mice. Anticancer Res. 33 (1), 103-106 (2013).
  6. Dadgar, S., Rajaram, N. Optical imaging approaches to investigating radiation resistance. Front Oncol. 9, 1152 (2019).
  7. Fukumura, D., Jain, R. K. Tumor microvasculature and microenvironment: Targets for anti-angiogenesis and normalization. Microvasc Res. 74 (2-3), 72-84 (2007).
  8. Dirkx, A. E. M., et al. Anti-angiogenesis therapy can overcome endothelial cell anergy and promote leukocyte-endothelium interactions and infiltration in tumors. FASEB J. 20 (6), 621-630 (2006).
  9. Allam, N., et al. Longitudinal in-vivo quantification of tumour microvascular heterogeneity by optical coherence angiography in pre-clinical radiation therapy. Sci Rep. 12, 6140 (2022).
  10. Stadlbauer, A., et al. Tissue hypoxia and alterations in microvascular architecture predict glioblastoma recurrence in humans. Clin Cancer Res. 27 (6), 1641-1649 (2021).
  11. Danquah, M. K., Zhang, X. A., Mahato, R. I. Extravasation of polymeric nanomedicines across tumor vasculature. Adv Drug Deliv Rev. 63 (8), 623-639 (2011).
  12. Bentzen, S. M., Gregoire, V. Molecular imaging-based dose painting: a novel paradigm for radiation therapy prescription. Semin Radiat Oncol. 21 (2), 101-110 (2011).
  13. Gabriel, E. M., Fisher, D. T., Evans, S., Takabe, K., Skitzki, J. J. Intravital microscopy in the study of the tumor microenvironment: from bench to human application. Oncotarget. 9 (28), 20165-20178 (2018).
  14. Demidov, V., et al. Preclinical quantitative in-vivo assessment of skin tissue vascularity in radiation-induced fibrosis with optical coherence tomography. J Biomed Opt. 23 (10), 1-9 (2018).
  15. Wallace, M. B., et al. The safety of intravenous fluorescein for confocal laser endomicroscopy in the gastrointestinal tract. Aliment Pharmacol Ther. 31 (5), 548-552 (2010).
  16. Standish, B. A., et al. In vivo endoscopic multi-beam optical coherence tomography. Phys Med Biol. 55 (3), 615-622 (2010).
  17. Wang, J. H., et al. Dynamic CT evaluation of tumor vascularity in renal cell carcinoma. AJR Am J Roentgenol. 186 (5), 1423-1430 (2006).
  18. Tropres, I., et al. Imaging the microvessel caliber and density: Principles and applications of microvascular MRI. Magn Reson Med. 73 (1), 325-341 (2014).
  19. McDonald, D. M., Choyke, P. L. Imaging of angiogenesis: from microscope to clinic. Nat Med. 9, 713-725 (2003).
  20. O’Connor, J. P. B., et al. Dynamic contrast-enhanced imaging techniques: CT and MRI. Brit J Radiol. 84, S112-S120 (2011).
  21. Lima, M., Le Bihan, D. Clinical intravoxel incoherent motion and diffusion MR imaging: past, present, and future. Radiology. 278 (1), 13-32 (2015).
  22. Zabel, W. J., et al. Bridging the macro to micro resolution gap with angiographic optical coherence tomography and dynamic contrast enhanced MRI. Sci Rep. 12 (1), 3159 (2022).
  23. Mao, Y., Flueraru, C., Chang, S., Popescu, D. P., Sowa, M. G. High-quality tissue imaging using a catheter-based swept-source optical coherence tomography systems with an integrated semiconductor optical amplifier. IEEE Trans Instrum Meas. 60 (10), 3376-3383 (2011).
  24. Mariampillai, A., et al. Optimized speckle variance OCT imaging of microvasculature. Opt Lett. 35 (8), 1257-1259 (2010).
  25. Tofts, P. S., et al. Estimating kinetic parameters from dynamic contrast-enhanced T1-weighted MRI of a diffusible tracer: standardized quantities and symbols. J Magn Res Imaging. 10 (3), 223-232 (1999).
  26. Khalifa, F., et al. Models and methods for analyzing DCE-MRI: a review. Med Phys. 41 (12), 124301 (2014).
  27. Reitan, N. K., Thuen, M., Goa, P. E., de Lange Davies, C. Characterization of tumor microvascular structure and permeability: comparison between magnetic resonance imaging and intravital confocal imaging. J Biomed Opt. 15 (3), 036004 (2010).
  28. Dhani, N. C., et al. Analysis of the intra- and intertumoral heterogeneity of hypoxia in pancreatic cancer patients receiving the nitroimidazole tracer pimonidazole. Br J Cancer. 113 (6), 864-871 (2015).
  29. Gaustad, J. V., Brurberg, K. G., Simonsen, T. G., Mollatt, C. S., Rofstad, E. K. Tumor vascularity assessed by magnetic resonance imaging and intravital microscopy imaging. Neoplasia. 10 (4), 354-362 (2008).
  30. Rouffiac, V., et al. Multimodal imaging for tumour characterization from micro to macroscopic level using a newly developed dorsal chamber designed for long-term follow-up. J Biophotonics. 13 (1), 201900217 (2020).
  31. Leung, H. M., Schafer, R., Pagel, M. M., Robey, I. F., Gmitro, A. F. Multimodality pH imaging in a mouse dorsal skin fold window chamber model. Proc SPIE Int Soc Opt Eng. 8574, 85740L (2013).
  32. Erten, A., et al. Magnetic resonance and fluorescence imaging of doxorubicin-loaded nanoparticles using a novel in vivo model. Nanomed. 6 (6), 797-807 (2010).
  33. Maeda, A., DaCosta, R. S. Optimization of the dorsal skinfold window chamber model and multi-parametric characterization of tumor-associated vasculature. Intravital. 3 (1), e27935 (2014).
  34. Allam, N., Taylor, E., Vitkin, I. A. Low-cost 3D-printed tools towards robust longitudinal multi-modal pre-clinical imaging. bioRxiv. , (2023).
  35. Alexander, S., Weigelin, B., Winkler, F., Friedl, P. Preclinical intravital microscopy of the tumour-stroma interface: invasion, metastasis, and therapy response. Curr Opin Cell Biol. 25 (5), 659-671 (2013).
  36. Steven, A. J., Zhuo, J., Melhem, E. R. Diffusion kurtosis imaging: an emerging technique for evaluating the microstructural environment of the brain.Am. J Roentgenol. 202 (1), W26-W33 (2014).
  37. Mayer, P., et al. Diffusion kurtosis imaging-a superior approach to assess tumor-stroma ratio in pancreatic ductal adenocarcinoma. Cancers (Basel). 12 (6), 1656 (2020).
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Cite This Article
Zabel, W. J., Allam, N., Contreras Sanchez, H. A., Foltz, W., Flueraru, C., Taylor, E., Vitkin, A. A Dorsal Skinfold Window Chamber Tumor Mouse Model for Combined Intravital Microscopy and Magnetic Resonance Imaging in Translational Cancer Research. J. Vis. Exp. (206), e66383, doi:10.3791/66383 (2024).

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