The evolution in our understanding of tumor angiogenesis has been the result of pioneering imaging and computational modeling studies spanning the endothelial cell, microvasculature and tissue levels. Many of these primary data on the tumor vasculature are in the form of images from pre-clinical tumor models that provide a wealth of qualitative and quantitative information in many dimensions and across different spatial scales. However, until recently, the visualization of changes in the tumor vasculature across spatial scales remained a challenge due to a lack of techniques for integrating micro- and macroscopic imaging data. Furthermore, the paucity of three-dimensional (3-D) tumor vascular data in conjunction with the challenges in obtaining such data from patients presents a serious hurdle for the development and validation of predictive, multiscale computational models of tumor angiogenesis. In this review, we discuss the development of multiscale models of tumor angiogenesis, new imaging techniques capable of reproducing the 3-D tumor vascular architecture with high fidelity, and the emergence of “image-based models”of tumor blood flow and molecular transport. Collectively, these developments are helping us gain a fundamental understanding of the cellular and molecular regulation of tumor angiogenesis that will benefit the development of new cancer therapies. Eventually, we expect this exciting integration of multiscale imaging and mathematical modeling to have widespread application beyond the tumor vasculature to other diseases involving a pathological vasculature, such as stroke and spinal cord injury.
Angiogenesis; Tumor; Vasculature; Multiscale; Imaging; Mathematical modeling; Computational modeling; Cancer; Tumor microenvironment; Systems biology
Induction of tumor angiogenesis is among the hallmarks of cancer and a driver of metastatic cascade initiation. Recent advances in high-resolution imaging enable highly detailed three-dimensional geometrical representation of the whole-tumor microvascular architecture. This enormous increase in complexity of image-based data necessitates the application of informatics methods for the analysis, mining and reconstruction of these spatial graph data structures. We present a novel methodology that combines ex-vivo high-resolution micro-computed tomography imaging data with a bioimage informatics algorithm to track and reconstruct the whole-tumor vasculature of a human breast cancer model. The reconstructed tumor vascular network is used as an input of a computational model that estimates blood flow in each segment of the tumor microvascular network. This formulation involves a well-established biophysical model and an optimization algorithm that ensures mass balance and detailed monitoring of all the vessels that feed and drain blood from the tumor microvascular network. Perfusion maps for the whole-tumor microvascular network are computed. Morphological and hemodynamic indices from different regions are compared to infer their role in overall tumor perfusion.
Hypoxic tumor microenvironments result in an aggressive phenotype and resistance to therapy that lead to tumor progression, recurrence, and metastasis. While poor vascularization and the resultant inadequate drug delivery are known to contribute to drug resistance, the effect of hypoxia on molecular transport through the interstitium, and the role of the extracellular matrix (ECM) in mediating this transport are unexplored. The dense mesh of fibers present in the ECM can especially influence the movement of macromolecules. Collagen 1 (Col1) fibers form a key component of the ECM in breast cancers. Here we characterized the influence of hypoxia on macromolecular transport in tumors, and the role of Col1 fibers in mediating this transport using an MDA-MB-231 breast cancer xenograft model engineered to express red fluorescent protein under hypoxia. Magnetic resonance imaging of macromolecular transport was combined with second harmonic generation microscopy of Col1 fibers. Hypoxic tumor regions displayed significantly decreased Col1 fiber density and volume, as well as significantly lower macromolecular draining and pooling rates, than normoxic regions. Regions adjacent to severely hypoxic areas revealed higher deposition of Col1 fibers and increased macromolecular transport. These data suggest that Col1 fibers may facilitate macromolecular transport in tumors, and their reduction in hypoxic regions may reduce this transport. Decreased macromolecular transport in hypoxic regions may also contribute to poor drug delivery and tumor recurrence in hypoxic regions. High Col1 fiber density observed around hypoxic regions may facilitate the escape of aggressive cancer cells from hypoxic regions.
Abnormal vascular phenotypes have been implicated in neuropathologies ranging from Alzheimer's disease to brain tumors. The development of transgenic mouse models of such diseases has created a crucial need for characterizing the murine neurovasculature. Although histologic techniques are excellent for imaging the microvasculature at submicron resolutions, they offer only limited coverage. It is also challenging to reconstruct the three-dimensional (3D) vasculature and other structures, such as white matter tracts, after tissue sectioning. Here, we describe a novel method for 3D whole-brain mapping of the murine vasculature using magnetic resonance microscopy (μMRI), and its application to a preclinical brain tumor model. The 3D vascular architecture was characterized by six morphologic parameters: vessel length, vessel radius, microvessel density, length per unit volume, fractional blood volume, and tortuosity. Region-of-interest analysis showed significant differences in the vascular phenotype between the tumor and the contralateral brain, as well as between postinoculation day 12 and day 17 tumors. These results unequivocally show the feasibility of using μMRI to characterize the vascular phenotype of brain tumors. Finally, we show that combining these vascular data with coregistered images acquired with diffusion-weighted MRI provides a new tool for investigating the relationship between angiogenesis and concomitant changes in the brain tumor microenvironment.
angiogenesis; brain tumor microenvironment; diffusion tensor imaging; magnetic resonance microscopy; vasculature
Knowledge of the three-dimensional (3D) architecture of blood vessels in the brain is crucial because the progression of various neuropathologies ranging from Alzheimer's disease to brain tumors involves anomalous blood vessels. The challenges in obtaining such data from patients, in conjunction with development of mouse models of neuropathology, have made the murine brain indispensable for investigating disease induced neurovascular changes. Here we describe a novel method for “whole brain” 3D mapping of murine neurovasculature using magnetic resonance microscopy (μMRI). This approach preserves the vascular and white matter tract architecture, and can be combined with complementary MRI contrast mechanisms such as diffusion tensor imaging (DTI) to examine the interplay between the vasculature and white matter reorganization that often characterizes neuropathologies. Following validation with micro computed tomography (μCT) and optical microscopy, we demonstrate the utility of this method by: (i) combined 3D imaging of angiogenesis and white matter reorganization in both, invasive and non-invasive brain tumor models; (ii) characterizing the morphological heterogeneity of the vascular phenotype in the murine brain; and (iii) conducting “multi-scale” imaging of brain tumor angiogenesis, wherein we directly compared in vivo MRI blood volume measurements with ex vivo vasculature data.
Some of the most exciting advances in molecular-functional imaging of cancer are occurring at the interface between chemistry and imaging. Several of these advances have occurred through the development of novel imaging probes that report on molecular pathways, the tumor micro-environment and the response of tumors to treatment; as well as through novel image-guided platforms such as nanoparticles and nanovesicles that deliver therapeutic agents against specific targets and pathways. Cancer cells have a remarkable ability to evade destruction despite the armamentarium of drugs currently available. While these drugs can destroy cancer cells, normal tissue toxicity is a major limiting factor, a problem further compounded by poor drug delivery. One major challenge for chemistry continues to be to eliminate cancer cells without damaging normal tissues. Here we have selected examples of MRI and optical imaging, to demonstrate how integrating imaging with novel probes can facilitate the successful treatment of this multifaceted disease.
Metastasis continues to be one of the major causes of mortality from prostate cancer. Since human malignant cell lines metastasize more readily from orthotopic sites than from heterotopic sites, to identify metastasis-permissive tumor microenvironments, we used noninvasive imaging to compare the in vivo vascular, metabolic and physiological characteristics of a human prostate cancer xenograft implanted orthotopically in the prostate or subcutaneously in the flank. Hypoxia was detected in these xenografts by placing an enhanced green fluorescent protein (EGFP) optical reporter under the control of a hypoxia response element (HRE). A multi-parametric analysis of hypoxia, extracellular pH (pHe), vascularization and metabolism provided a characterization of environments that are permissive for metastasis to occur. We found that orthotopic tumors, which metastasized more easily, were characterized by higher vascular volume, permeability, and total choline, and a more acidic pHe. Interestingly, metastatic deposits in the lymph nodes as well as cancer cells in ascites fluid were found to be hypoxic, explaining in part, the refractory nature of metastatic disease. These results also provide the basis for clinically translatable noninvasive imaging markers for predicting metastatic risk in prostate cancer.
prostate cancer; hypoxia; vascularization; choline metabolism; pHe; magnetic resonance spectroscopy and imaging; metastasis
Cancer is a complex disease exhibiting a host of phenotypic diversities. Noninvasive multinuclear magnetic resonance imaging (MRI) and spectroscopic imaging (MRSI) provide an array of capabilities to characterize and understand several of the vascular, metabolic, and physiological characteristics unique to cancer. The availability of targeted contrast agents has widened the scope of MR techniques to include the detection of receptor and gene expression. In this paper, we have highlighted the application of several MR techniques in imaging and understanding cancer.
Cancer; metabolism; molecular imaging; magnetic resonance imaging (MRI); magnetic resonance spectroscopic imaging (MRSI); receptor expression; vascular imaging
Recently, we demonstrated that vessel geometry is a significant determinant of susceptibility-induced contrast in MRI. This is especially relevant for susceptibility-contrast enhanced MRI of tumors with their characteristically abnormal vessel morphology. In order to better understand the biophysics of this contrast mechanism, it is of interest to model how various factors, including microvessel morphology contribute to the measured MR signal, and was the primary motivation for developing a novel computer modeling approach called the Finite Perturber Method (FPM). The FPM circumvents the limitations of traditional fixed-geometry approaches, and enables us to study susceptibility-induced contrast arising from arbitrary microvascular morphologies in 3D, such as those typically observed with brain tumor angiogenesis. Here we describe this new modeling methodology and some of its applications. The excellent agreement of the FPM with theory and the extant susceptibility modeling data, coupled with its computational efficiency demonstrates its potential to transform our understanding of the factors that engender susceptibility contrast in MRI.
Dynamic susceptibility; contrast; arbitrary geometry; microvasculature; tumor angiogenesis; BOLD fMRI
Depending on dose, dexamethasone has been shown to inhibit or stimulate growth of rat 9L gliosarcoma and decrease the expression of vascular endothelial growth factor (VEGF), an important mediator of tumor-associated angiogenesis. We demonstrate, by constructing relative cerebral blood volume (rCBV) maps with MRI, that dexamethasone also decreases total blood volume while increasing microvascular blood volume in Fischer rats bearing intracranial 9L gliosarcoma. Animals were inoculated with 1 x 10(5) 9L gliosarcoma tumor cells. On days 10-14 after tumor cell inoculation, animals were intra-peritoneally injected with dexamethasone (3 mg/kg) over 5 days. MRI-derived gradient echo (GE) and spin-echo (SE) rCBV maps were created to demonstrate total vasculature (GE) and microvasculature (SE). After MRI studies were performed, the rat's vasculature was perfused with a latex compound. Total vessel volume and diameters were assessed by microscopy. Dexamethasone decreased the tumor-enhancing area of postcontrast T1-weighted images (P < 0.0001) and total tumor volume(P = 0.0085). In addition, there was a greater than 50% decrease in GE rCBV (total vasculature) (P = 0.007) as well as a significant decrease in total fractional blood volume, as validated by histology (P = 0.0007). Conversely, there was an increase in SE rCBV signal (microvasculature) in animals treated with dexamethasone (P = 0.05), which was consistent with microscopy (P < 0.0001). These data demonstrate that (1) dexamethasone selectively treats tumor vasculature, suggesting a vessel-size selective effect and (2) MRI-derived rCBV is a noninvasive technique that can be used to evaluate changes in blood volume and vascular morphology.
Cancer cells invade by secreting degradative enzymes, which are sequestered in lysosomal vesicles. In this study, the impact of an acidic extracellular environment on lysosome size, number, and distance from the nucleus in human mammary epithelial cells (HMECs) and breast cancer cells of different degrees of malignancy was characterized because the physiological microenvironment of tumors is frequently characterized by extracellular acidity. An acidic extracellular pH (pHe) resulted in a distinct shift of lysosomes from the perinuclear region to the cell periphery irrespective of the HMECs' degree of malignancy. With decreasing pH, larger lysosomal vesicles were observed more frequently in highly metastatic breast cancer cells, whereas smaller lysosomes were observed in poorly metastatic breast cancer cells and HMECs. The number of lysosomes decreased with acidic pH values. The displacement of lysosomes to the cell periphery driven by extracellular acidosis may facilitate exocytosis of these lysosomes and increase secretion of degradative enzymes. Filopodia formations, which were observed more frequently in highly metastatic breast cancer cells maintained at acidic pHe, may also contribute to invasion.
Breast cancer; metastasis; fluorescence microscopy; lysosome; trafficking