Computer simulation of glioma growth and morphology.

Despite major advances in the study of glioma, the quantitative links between intra-tumor molecular/cellular properties, clinically observable properties such as morphology, and critical tumor behaviors such as growth and invasiveness remain unclear, hampering more effective coupling of tumor physical characteristics with implications for prognosis and therapy. Although molecular biology, histopathology, and radiological imaging are employed in this endeavor, studies are severely challenged by the multitude of different physical scales involved in tumor growth, i.e., from molecular nanoscale to cell microscale and finally to tissue centimeter scale. Consequently, it is often difficult to determine the underlying dynamics across dimensions. New techniques are needed to tackle these issues. Here, we address this multi-scalar problem by employing a novel predictive three-dimensional mathematical and computational model based on first-principle equations (conservation laws of physics) that describe mathematically the diffusion of cell substrates and other processes determining tumor mass growth and invasion. The model uses conserved variables to represent known determinants of glioma behavior, e.g., cell density and oxygen concentration, as well as biological functional relationships and parameters linking phenomena at different scales whose specific forms and values are hypothesized and calculated based on in vitro and in vivo experiments and from histopathology of tissue specimens from human gliomas. This model enables correlation of glioma morphology to tumor growth by quantifying interdependence of tumor mass on the microenvironment (e.g., hypoxia, tissue disruption) and on the cellular phenotypes (e.g., mitosis and apoptosis rates, cell adhesion strength). Once functional relationships between variables and associated parameter values have been informed, e.g., from histopathology or intra-operative analysis, this model can be used for disease diagnosis/prognosis, hypothesis testing, and to guide surgery and therapy. In particular, this tool identifies and quantifies the effects of vascularization and other cell-scale glioma morphological characteristics as predictors of tumor-scale growth and invasion.

Computer simulation of glioma growth and morphology.

Despite major advances in the study of glioma, the quantitative links between intra-tumor molecular/cellular properties, clinically observable properties such as morphology, and critical tumor behaviors such as growth and invasiveness remain unclear, hampering more effective coupling of tumor physical characteristics with implications for prognosis and therapy. Although molecular biology, histopathology, and radiological imaging are employed in this endeavor, studies are severely challenged by the multitude of different physical scales involved in tumor growth, i.e., from molecular nanoscale to cell microscale and finally to tissue centimeter scale. Consequently, it is often difficult to determine the underlying dynamics across dimensions. New techniques are needed to tackle these issues. Here, we address this multi-scalar problem by employing a novel predictive three-dimensional mathematical and computational model based on first-principle equations (conservation laws of physics) that describe mathematically the diffusion of cell substrates and other processes determining tumor mass growth and invasion. The model uses conserved variables to represent known determinants of glioma behavior, e.g., cell density and oxygen concentration, as well as biological functional relationships and parameters linking phenomena at different scales whose specific forms and values are hypothesized and calculated based on in vitro and in vivo experiments and from histopathology of tissue specimens from human gliomas. This model enables correlation of glioma morphology to tumor growth by quantifying interdependence of tumor mass on the microenvironment (e.g., hypoxia, tissue disruption) and on the cellular phenotypes (e.g., mitosis and apoptosis rates, cell adhesion strength). Once functional relationships between variables and associated parameter values have been informed, e.g., from histopathology or intra-operative analysis, this model can be used for disease diagnosis/prognosis, hypothesis testing, and to guide surgery and therapy. In particular, this tool identifies and quantifies the effects of vascularization and other cell-scale glioma morphological characteristics as predictors of tumor-scale growth and invasion.

Predictive oncology: a review of multidisciplinary, multiscale in silico modeling linking phenotype, morphology and growth.

Empirical evidence and theoretical studies suggest that the phenotype, i.e., cellular- and molecular-scale dynamics, including proliferation rate and adhesiveness due to microenvironmental factors and gene expression that govern tumor growth and invasiveness, also determine gross tumor-scale morphology. It has been difficult to quantify the relative effect of these links on disease progression and prognosis using conventional clinical and experimental methods and observables. As a result, successful individualized treatment of highly malignant and invasive cancers, such as glioblastoma, via surgical resection and chemotherapy cannot be offered and outcomes are generally poor. What is needed is a deterministic, quantifiable method to enable understanding of the connections between phenotype and tumor morphology. Here, we critically assess advantages and disadvantages of recent computational modeling efforts (e.g., continuum, discrete, and cellular automata models) that have pursued this understanding. Based on this assessment, we review a multiscale, i.e., from the molecular to the gross tumor scale, mathematical and computational "first-principle" approach based on mass conservation and other physical laws, such as employed in reaction-diffusion systems. Model variables describe known characteristics of tumor behavior, and parameters and functional relationships across scales are informed from in vitro, in vivo and ex vivo biology. We review the feasibility of this methodology that, once coupled to tumor imaging and tumor biopsy or cell culture data, should enable prediction of tumor growth and therapy outcome through quantification of the relation between the underlying dynamics and morphological characteristics. In particular, morphologic stability analysis of this mathematical model reveals that tumor cell patterning at the tumor-host interface is regulated by cell proliferation, adhesion and other phenotypic characteristics: histopathology information of tumor boundary can be inputted to the mathematical model and used as a phenotype-diagnostic tool to predict collective and individual tumor cell invasion of surrounding tissue. This approach further provides a means to deterministically test effects of novel and hypothetical therapy strategies on tumor behavior.

Brain fiber tract plasticity in experimental spinal cord injury: diffusion tensor imaging.

Diffusion tensor imaging (DTI) and immunohistochemistry were performed in spinal cord injured rats to understand the basis for activation of multiple regions in the brain observed in functional magnetic resonance imaging (fMRI) studies. The measured fractional anisotropy (FA), a scalar measure of diffusion anisotropy, along the region encompassing corticospinal tracts (CST) indicates significant differences between control and injured groups in the 3 to 4 mm area posterior to bregma that correspond to internal capsule and cerebral peduncle. Additionally, DTI-based tractography in injured animals showed increased number of fibers that extend towards the cortex terminating in the regions that were activated in fMRI. Both the internal capsule and cerebral peduncle demonstrated an increase in GFAP-immunoreactivity compared to control animals. GAP-43 expression also indicates plasticity in the internal capsule. These studies suggest that the previously observed multiple regions of activation in spinal cord injury are, at least in part, due to the formation of new fibers.

Outcomes of safety and effectiveness in a multicenter randomized, controlled trial of whole-body hypothermia for neonatal hypoxic-ischemic encephalopathy.

BACKGROUND: Whole-body hypothermia reduced the frequency of death or moderate/severe disabilities in neonates with hypoxic-ischemic encephalopathy in a randomized, controlled multicenter trial. OBJECTIVE: Our goal was to evaluate outcomes of safety and effectiveness of hypothermia in infants up to 18 to 22 months of age. DESIGN/METHODS: A priori outcomes were evaluated between hypothermia (n = 102) and control (n = 106) groups. RESULTS: Encephalopathy attributable to causes other than hypoxia-ischemia at birth was not noted. Inotropic support (hypothermia, 59% of infants; control, 56% of infants) was similar during the 72-hour study intervention period in both groups. Need for blood transfusions (hypothermia, 24%; control, 24%), platelet transfusions (hypothermia, 20%; control, 12%), and volume expanders (hypothermia, 54%; control, 49%) was similar in the 2 groups. Among infants with persistent pulmonary hypertension (hypothermia, 25%; control, 22%), nitric-oxide use (hypothermia, 68%; control, 57%) and placement on extracorporeal membrane oxygenation (hypothermia, 4%; control, 9%) was similar between the 2 groups. Non-central nervous system organ dysfunctions occurred with similar frequency in the hypothermia (74%) and control (73%) groups. Rehospitalization occurred among 27% of the infants in the hypothermia group and 42% of infants in the control group. At 18 months, the hypothermia group had 24 deaths, 19 severe disabilities, and 2 moderate disabilities, whereas the control group had 38 deaths, 25 severe disabilities, and 1 moderate disability. Growth parameters were similar between survivors. No adverse outcomes were noted among infants receiving hypothermia with transient reduction of temperature below a target of 33.5 degrees C at initiation of cooling. There was a trend in reduction of frequency of all outcomes in the hypothermia group compared with the control group in both moderate and severe encephalopathy categories. CONCLUSIONS: Although not powered to test these secondary outcomes, whole-body hypothermia in infants with encephalopathy was safe and was associated with a consistent trend for decreasing frequency of each of the components of disability.

Diffusion tensor imaging of rat spinal cord in vivo

Magnetic resonance imaging, with its exquisite soft tissue contrast, is an ideal modality for investigating spinal cord pathology. While conventional MRI techniques are very sensitive for spinal cord pathology, their specificity is somewhat limited. Diffusion MRI is an advanced technique which is a very sensitive and specific indicator of the integrity of white matter tracts. Diffusion imaging has been shown to detect early ischemic changes in white matter, while conventional imaging demonstrates no change. By acquiring the complete apparent diffusion tensor (ADT), tissue diffusion properties can be expressed in terms of quantitative and rotationally invariant parameters. ^ Systematic study of SCI in vivo requires controlled animal models such as the popular rat model. To date, studies of spinal cord using ADT imaging have been performed exclusively in fixed, excised spinal cords, introducing inevitable artifacts and losing the benefits of MRI's noninvasive nature. In vivo imaging reflects the actual in vivo tissue properties, and allows each animal to be imaged at multiple time points, greatly reducing the number of animals required to achieve statistical significance. Because the spinal cord is very small, the available signal-to-noise ratio (SNR) is very low. Prior spin-echo based ADT studies of rat spinal cord have relied on high magnetic field strengths and long imaging times—on the order of 10 hours—for adequate SNR. Such long imaging times are incompatible with in vivo imaging, and are not relevant for imaging the early phases following SCI. Echo planar imaging (EPI) is one of the fastest imaging methods, and is popular for diffusion imaging. However, EPI further lowers the image SNR, and is very sensitive to small imperfections in the magnetic field, such as those introduced by the bony spine. Additionally, The small field-of-view (FOV) needed for spinal cord imaging requires large imaging gradients which generate EPI artifacts. The addition of diffusion gradients introduces yet further artifacts. ^ This work develops a method for rapid EPI-based in vivo diffusion imaging of rat spinal cord. The method involves improving the SNR using an implantable coil; reducing magnetic field inhomogeneities by means of an autoshim, and correcting EPI artifacts by post-processing. New EPI artifacts due to diffusion gradients described, and post-processing correction techniques are developed. ^ These techniques were used to obtain rotationally invariant diffusion parameters from 9 animals in vivo, and were validated using the gold-standard, but slow, spinecho based diffusion sequence. These are the first reported measurements of the ADT in spinal cord in vivo . ^ Many of the techniques described are equally applicable toward imaging of human spinal cord. We anticipate that these techniques will aid in evaluating and optimizing potential therapies, and will lead to improved patient care. ^

The heparan sulfate-fibroblast growth factor signaling system in liver growth and function

The heparan sulfate (HS)-fibroblast growth factor (FGF) signaling system is a ubiquitous regulator that senses local environmental changes and mediates cell-to-cell communication. This system consists of three mutually interactive components. These are regulatory polypeptides (FGF), FGF receptor (FGFR) and heparan sulfate proteoglycans (FGFRHS). All four FGFR genes are expressed in the adult liver. Expression of the FGFR1–3 genes is generally associated with non-parenchymal cells while expression of the FGFR4 gene is associated with parenchymal hepatocytes. We showed that livers of mice lacking FGFR4 exhibited normal morphology and regenerated normally in response to partial hepatectomy. However, the FGFR4 (−/−) mice exhibited depleted gallbladders, an elevated bile acid pool and elevated excretion of bile acids. Cholesterol- and bile acid-controlled liver cholesterol 7α-hydroxylase (Cyp7a), the limiting enzyme for bile acid synthesis, was elevated, unresponsive to dietary cholesterol, but repressed normally by dietary cholate. These results indicated that FGFR4 was not directly involved in liver growth but exerted negative control on liver bile acid synthesis. This was confirmed in transgenic mice overexpressing the constitutively active human FGFR4 in livers. The transgenic mice exhibited decreased fecal bile acid excretion, bile acid pool size, and expression of Cyp7a. Introduction of this constitutively active human FGFR4 into FGFR4 (−/−) mice restored the inhibition of bile acid synthesis. Activation of the c-Jun N-terminal Kinase (JNK) pathway by FGFR4 correlated with the repressive effect on bile acid synthesis. ^ To determine whether FGFR4 played a broader role in liver-specific metabolic function, we examined the impact of both acute and chronic exposure to CCl 4 in FGFR4 (−/−) mice. Following acute CCl4 exposure, the FGFR4 (−/−) mice exhibited accelerated liver injury, a significant increase in liver mass and delayed hepatolobular repair, with no apparent effect on liver cell proliferation and restoration of cellularity. Chronic CCl4 exposure resulted in severe fibrosis in livers of FGFR4 (−/−) mice compared to normal mice. Analysis at both mRNA and protein levels indicated an 8 hr delay in FGFR4-deficient mice in the down-regulation of cytochrome P450 2E1 (CYP2E1) protein, the major enzyme whose products underlie CCl 4-induced injury. These results show that hepatocyte FGFR4 protects against acute and chronic insult to the liver and prevents accompanying fibrosis. ^ Of the 23 FGF polypeptides, FGF1 and FGF2 are present at significant levels in the liver. To determine whether FGF1 and FGF2 played a role in CCl 4-induced liver injury and fibrosis, we examined the impact of both acute and chronic exposure to CCl4 in both wild-type and FGF1-FGF2 double-knockout mice. Following acute CCl4 exposure, FGF1(−/−)FGF2(−/−) mice exhibited accelerated liver injury, overall normal liver growth and repair, and decreased liver collagen α1(I) induction. Liver fibrosis resulting from chronic CCl4 exposure was markedly decreased in livers of FGF1(−/−)FGF2(−/−) mice compared to wild-type mice. This study suggests a role for FGF1 and FGF2 in hepatic fibrogenesis. ^ In summary, our three part study shows that specific components of the ubiquitous HS-FGF signaling family in the liver context interfaces with metabolite- and xenobiotic-controlled networks to regulate liver function, but has no apparent direct effect on liver cell growth. ^