Pancreatic cancer stromal characterization using diffusion tensor imaging and collagen 1 fibers in xenograft model
Samata Kakkad1, Desmond Jacob1, Marie-France Penet1,2, Jiangyang Zhang 1, Kristine Glunde1,2, and Zaver M. Bhujwalla1,2

1JHU ICMIC program, Division of Cancer Imaging Research, The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States, 2Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, United States

Synopsis

The dense desmoplastic stroma present in pancreatic ductal adenocarcinoma (PDAC) limits the delivery of diagnostic imaging probes and therapeutic agents leading to poor prognosis of PDAC from a combination of late-stage diagnosis and limited response to chemotherapy. Collagen 1 (Col1) fibers form a major component of this desmoplastic stroma. By combining noninvasive diffusion MRI with optical imaging we characterized the relationship between Col1 fibers and diffusion MRI in PDAC. A good correlation was observed between Col1 fibers and diffusion MRI parameters providing a rationale for detecting PDAC with diffusion MRI, and characterizing the relationship between Col1 fibers and diffusion MRI.

Introduction

Pancreatic ductal adenocarcinoma (PDAC) develops silently and is often detected in the late stages with only ~10-15% operable when diagnosed. The dense desmoplastic stroma in PDAC limits delivery of imaging probes for detection and drug delivery. Chronic pancreatitis has similar clinical behavior and imaging features as PDAC, making it harder to detect PDAC1. Survival outcomes could be significantly improved by early detection. Diffusion MRI is a noninvasive imaging technique that is being increasingly used for breast and brain cancer detection and has been explored in the detection of PDAC, to improve the confidence level of detecting PDAC with MRI2. The underlying changes in water diffusion in PDAC are not defined and their characterization would provide a strong rationale to incorporate this external label-free modality in PDAC detection. Diffusion tensor imaging (DTI) has been extensively used to examine tissue microstructure in neurological diseases3, such as white matter tracks, and we have recently observed heterogeneous DTI parameters in breast cancer. These DTI parameter patterns were seen to follow the underlying Collagen 1 (Col1) fiber distributions. We observed in regions with low Col1 fiber content that the apparent diffusion coefficient (ADC) and fractional anisotropy (FA) values decreased significantly as compared to regions containing dense Col1 fibers. Col1 fibers are a major structural component of the tumor extracellular matrix (ECM) and play an important role in cancer dissemination and molecular transport through the tumor interstitium. Col1 fibers are detected using second harmonic generation (SHG) microscopy ex vivo on tumor sections. Here, we have combined DTI and optical imaging to characterize diffusion parameters in a PDAC xenograft model to understand the relationship between Col1 fibers and diffusion in PDAC. We observed that regions containing fewer Col1 fibers were characterized by lower ADC and FA compared to dense fiber regions. Results here support the use of ADC and FA in detecting and characterizing PDAC.

Methods

BxPC3 PDAC were implanted orthotopically in SCID mice as previously described4. Tumors were excised from euthanized mice at volumes of ~ 300 mm3 and fixed in 4% paraformaldehyde. A vertical 11.7 Tesla spectrometer was used to acquire three-dimensional DTI with two non-diffusion weighted images and eight diffusion-weighted images (b=1500 s/mm2, resolution 60 x 60 x 60 μm3). Following DTI, the tumors were paraffin-embedded and sectioned at 5 μm thickness. The sections were then stained with hematoxylin and eosin (H&E). These H&E sections were used to acquire tiled scan SHG microscopy to detect the Col1 fibers distributions in 3D (incidence = 860 nm, emission = 430 nm) using a 25× lens on an Olympus FV1000 multiphoton microscope. ADC and FA maps were calculated from the DTI data. Multimodality co-registration was performed using affine transformation to co-register the SHG images to the diffusion images.

Results and Discussion

We found that high Col1 fiber density correlated with increased ADC and FA in the tumors, compared to regions with fewer Col1 fibers (Figure 1). We observed that regions with aligned Col1 fibers had increased diffusion anisotropy (compare Figure 1D with E). The primary diffusion direction in high anisotropy regions mostly followed the underlying Col1 fiber distribution alignment. We simulated water diffusion directionality maps from the maximum intensity projected SHG data and the simulated results (in X-Y direction) displayed in Figure 1F closely matched the actual water diffusion directionality maps. Consistent with our previous observations in human breast cancer tissue, fewer Col1 fibers exhibited lower ADC and FA compared to dense fiber regions. These data suggest that delivery and transport of low molecular weight chemotherapy agents through the tumor ECM may be influenced by the Col1 fiber distribution. The results obtained here support further investigating the use of intrinsic ADC and FA to noninvasively detect PDAC. Diffusion-MRI can be performed on most clinical MRI scanners, providing ease of clinical translation. Our data create much-needed new possibilities for the detection of PDAC and for evaluating cancer architecture using diffusion MRI.

Acknowledgements

This work was supported by P30 CA006973 and NIH P50 CA103175.

References

1. Steer ML, Waxman I, Freedman S. Chronic pancreatitis. N Engl J Med. 1995;332(22):1482-90.

2. Park MJ, Kim YK, Choi SY, Rhim H, Lee WJ, Choi D. Preoperative detection of small pancreatic carcinoma: value of adding diffusion-weighted imaging to conventional MR imaging for improving confidence level. Radiology. 2014;273(2):433-43.

3. Mori S, Zhang JY. Principles of diffusion tensor imaging and its applications to basic neuroscience research. Neuron. 2006;51(5):527-39.

4. Penet M-F, Shah T, Bharti S, Krishnamachary B, Artemov D, Mironchik Y, Wildes F, Maitra A, Bhujwallal ZM. Clin Cancer Res. 2015; 21(2):386-395.

Figures

Representative images of BxPC3 specimen. (A) A representative average diffusion-weighted (aDW) image, (B) corresponding ADC map, (C) corresponding FA map, (D) corresponding water diffusion direction color map, (E) corresponding SHG map of Col1 fiber distribution. (F) 2D water diffusion directionality simulated from SHG Col1 fiber data. Scale bar of 2 mm for all images (A-F).



Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)
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