A dosimetric study of radionuclide therapy for bone marrow ablation

In a phase I clinical trial, six multiple myeloma patients, who were non-responsive to conventional therapy and were scheduled for bone marrow transplantation, received Holmium-166 ($\sp{166}$Ho) labeled to a bone seeking agent, DOTMP (1,4,7,10-tetraazacyclododecane-1,4,7,10-tetramethylene-phosphonic acid), for the purpose of bone marrow ablation. The specific aims of my research within this protocol were to evaluate the toxicity and efficacy of $\sp{166}$Ho DOTMP by quantifying the in vivo pharmacokinetics and radiation dosimetry, and by correlating these results to the biologic response observed. The reproducibility of pharmacokinetics from multiple injections of $\sp{166}$Ho DOTMP administered to these myeloma patients was demonstrated from both blood and whole body retention. The skeletal concentration of $\sp{166}$Ho DOTMP was heterogenous in all six patients: high in the ribs, pelvis, and lumbar vertebrae regions, and relatively low in the femurs, arms, and head.^ A novel technique was developed to calculate the radiation dose to the bone marrow in each skeletal ROI, and was applied to all six $\sp{166}$Ho DOTMP patients. Radiation dose estimates for the bone marrow calculated using the standard MIRD "S" factors were compared with the average values derived from the heterogenous distribution of activity in the skeleton (i.e., the regional technique). The results from the two techniques were significantly different; the average of the dose estimates from the regional technique were typically 30% greater. Furthermore, the regional technique provided a range of radiation doses for the entire marrow volume, while the MIRD "S" factors only provided a single value. Dose volume histogram analysis of data from the regional technique indicated a range of dose estimates that varied by a factor of 10 between the high dose and low dose regions. Finally, the observed clinical response of cells and abnormal proteins measured in bone marrow aspirates and peripheral blood samples were compared with radiation dose estimates for the bone marrow calculated from the standard and regional technique. The results showed the regional technique values correlated more closely to several clinical response parameters. (Abstract shortened by UMI.) ^

Differential dynamic properties of scleroderma fibroblasts in response to perturbation of environmental stimuli.

Diseases are believed to arise from dysregulation of biological systems (pathways) perturbed by environmental triggers. Biological systems as a whole are not just the sum of their components, rather ever-changing, complex and dynamic systems over time in response to internal and external perturbation. In the past, biologists have mainly focused on studying either functions of isolated genes or steady-states of small biological pathways. However, it is systems dynamics that play an essential role in giving rise to cellular function/dysfunction which cause diseases, such as growth, differentiation, division and apoptosis. Biological phenomena of the entire organism are not only determined by steady-state characteristics of the biological systems, but also by intrinsic dynamic properties of biological systems, including stability, transient-response, and controllability, which determine how the systems maintain their functions and performance under a broad range of random internal and external perturbations. As a proof of principle, we examine signal transduction pathways and genetic regulatory pathways as biological systems. We employ widely used state-space equations in systems science to model biological systems, and use expectation-maximization (EM) algorithms and Kalman filter to estimate the parameters in the models. We apply the developed state-space models to human fibroblasts obtained from the autoimmune fibrosing disease, scleroderma, and then perform dynamic analysis of partial TGF-beta pathway in both normal and scleroderma fibroblasts stimulated by silica. We find that TGF-beta pathway under perturbation of silica shows significant differences in dynamic properties between normal and scleroderma fibroblasts. Our findings may open a new avenue in exploring the functions of cells and mechanism operative in disease development.

Differential dynamic properties of scleroderma fibroblasts in response to perturbation of environmental stimuli.

Diseases are believed to arise from dysregulation of biological systems (pathways) perturbed by environmental triggers. Biological systems as a whole are not just the sum of their components, rather ever-changing, complex and dynamic systems over time in response to internal and external perturbation. In the past, biologists have mainly focused on studying either functions of isolated genes or steady-states of small biological pathways. However, it is systems dynamics that play an essential role in giving rise to cellular function/dysfunction which cause diseases, such as growth, differentiation, division and apoptosis. Biological phenomena of the entire organism are not only determined by steady-state characteristics of the biological systems, but also by intrinsic dynamic properties of biological systems, including stability, transient-response, and controllability, which determine how the systems maintain their functions and performance under a broad range of random internal and external perturbations. As a proof of principle, we examine signal transduction pathways and genetic regulatory pathways as biological systems. We employ widely used state-space equations in systems science to model biological systems, and use expectation-maximization (EM) algorithms and Kalman filter to estimate the parameters in the models. We apply the developed state-space models to human fibroblasts obtained from the autoimmune fibrosing disease, scleroderma, and then perform dynamic analysis of partial TGF-beta pathway in both normal and scleroderma fibroblasts stimulated by silica. We find that TGF-beta pathway under perturbation of silica shows significant differences in dynamic properties between normal and scleroderma fibroblasts. Our findings may open a new avenue in exploring the functions of cells and mechanism operative in disease development.

Dynamic Chemical Shift Imaging for Image-Guided Thermal Therapy

Magnetic resonance temperature imaging (MRTI) is recognized as a noninvasive means to provide temperature imaging for guidance in thermal therapies. The most common method of estimating temperature changes in the body using MR is by measuring the water proton resonant frequency (PRF) shift. Calculation of the complex phase difference (CPD) is the method of choice for measuring the PRF indirectly since it facilitates temperature mapping with high spatiotemporal resolution. Chemical shift imaging (CSI) techniques can provide the PRF directly with high sensitivity to temperature changes while minimizing artifacts commonly seen in CPD techniques. However, CSI techniques are currently limited by poor spatiotemporal resolution. This research intends to develop and validate a CSI-based MRTI technique with intentional spectral undersampling which allows relaxed parameters to improve spatiotemporal resolution. An algorithm based on autoregressive moving average (ARMA) modeling is developed and validated to help overcome limitations of Fourier-based analysis allowing highly accurate and precise PRF estimates. From the determined acquisition parameters and ARMA modeling, robust maps of temperature using the k-means algorithm are generated and validated in laser treatments in ex vivo tissue. The use of non-PRF based measurements provided by the technique is also investigated to aid in the validation of thermal damage predicted by an Arrhenius rate dose model.

Extended kalman filter for estimation of parameters in nonlinear state-space models of biochemical networks.

It is system dynamics that determines the function of cells, tissues and organisms. To develop mathematical models and estimate their parameters are an essential issue for studying dynamic behaviors of biological systems which include metabolic networks, genetic regulatory networks and signal transduction pathways, under perturbation of external stimuli. In general, biological dynamic systems are partially observed. Therefore, a natural way to model dynamic biological systems is to employ nonlinear state-space equations. Although statistical methods for parameter estimation of linear models in biological dynamic systems have been developed intensively in the recent years, the estimation of both states and parameters of nonlinear dynamic systems remains a challenging task. In this report, we apply extended Kalman Filter (EKF) to the estimation of both states and parameters of nonlinear state-space models. To evaluate the performance of the EKF for parameter estimation, we apply the EKF to a simulation dataset and two real datasets: JAK-STAT signal transduction pathway and Ras/Raf/MEK/ERK signaling transduction pathways datasets. The preliminary results show that EKF can accurately estimate the parameters and predict states in nonlinear state-space equations for modeling dynamic biochemical networks.

Dynamic Remodeling of the Stressed Heart: Role of Protein Degradation Pathways

The heart is a remarkable organ. In order to maintain its function, it remodels in response to a variety of environmental stresses, including pressure overload, volume overload, mechanical or pharmacological unloading and hormonal or metabolic disturbances. All these responses are linked to the inherent capacity of the heart to rebuild itself. Particularly, cardiac pressure overload activates signaling pathways of both protein synthesis and degradation. While much is known about regulators of protein synthesis, little is known about regulators of protein degradation in hypertrophy. The ubiquitin-proteasome system (UPS) selectively degrades unused and abnormal intracellular proteins. I speculated that the UPS may play an important role in both qualitative and quantitative changes in the composition of heart muscle during hypertrophic remodeling. My study hypothesized that cardiac remodeling in response to hypertrophic stimuli is a dynamic process that requires activation of highly regulated mechanisms of protein degradation as much as it requires protein synthesis. My first aim was to adopt a model of left ventricular hypertrophy and determine its gene expression and structural changes. Male Sprague-Dawley rats were submitted to ascending aortic banding and sacrificed at 7 and 14 days after surgery. Sham operated animals served as controls. Effective aortic banding was confirmed by hemodynamic assessment by Doppler flow measurements in vivo. Banded rats showed a four-fold increase in peak stenotic jet velocities. Histomorphometric analysis revealed a significant increase in myocyte size as well as fibrosis in the banded animals. Transcript analysis showed that banded animals had reverted to the fetal gene program. My second aim was to assess if the UPS is increased and transcriptionally regulated in hypertrophic left ventricular remodeling. Protein extracts from the left ventricles of the banded and control animals were used to perform an in vitro peptidase assay to assess the overall catalytic activity of the UPS. The results showed no difference between hypertrophied and control animals. Transcript analysis revealed decreases in transcript levels of candidate UPS genes in the hypertrophied hearts at 7 days post-banding but not at 14 days. However, protein expression analysis showed no difference at either time point compared to controls. These findings indicate that elements of the UPS are downregulated in the early phase of hypertrophic remodeling and normalizes in a later phase. The results provide evidence in support of a dynamic transcriptional regulation of a major pathway of intracellular protein degradation in the heart. The discrepancy between transcript levels on the one hand and protein levels on the other hand supports post-transcriptional regulation of the UPS pathway in the hypertrophied heart. The exact mechanisms and the functional consequences remain to be elucidated.

Design and analysis for three level hierarchical structures with count response

In numerous intervention studies and education field trials, random assignment to treatment occurs in clusters rather than at the level of observation. This departure of random assignment of units may be due to logistics, political feasibility, or ecological validity. Data within the same cluster or grouping are often correlated. Application of traditional regression techniques, which assume independence between observations, to clustered data produce consistent parameter estimates. However such estimators are often inefficient as compared to methods which incorporate the clustered nature of the data into the estimation procedure (Neuhaus 1993).1 Multilevel models, also known as random effects or random components models, can be used to account for the clustering of data by estimating higher level, or group, as well as lower level, or individual variation. Designing a study, in which the unit of observation is nested within higher level groupings, requires the determination of sample sizes at each level. This study investigates the design and analysis of various sampling strategies for a 3-level repeated measures design on the parameter estimates when the outcome variable of interest follows a Poisson distribution. ^ Results study suggest that second order PQL estimation produces the least biased estimates in the 3-level multilevel Poisson model followed by first order PQL and then second and first order MQL. The MQL estimates of both fixed and random parameters are generally satisfactory when the level 2 and level 3 variation is less than 0.10. However, as the higher level error variance increases, the MQL estimates become increasingly biased. If convergence of the estimation algorithm is not obtained by PQL procedure and higher level error variance is large, the estimates may be significantly biased. In this case bias correction techniques such as bootstrapping should be considered as an alternative procedure. For larger sample sizes, those structures with 20 or more units sampled at levels with normally distributed random errors produced more stable estimates with less sampling variance than structures with an increased number of level 1 units. For small sample sizes, sampling fewer units at the level with Poisson variation produces less sampling variation, however this criterion is no longer important when sample sizes are large. ^ 1Neuhaus J (1993). “Estimation efficiency and Tests of Covariate Effects with Clustered Binary Data”. Biometrics , 49, 989–996^

Sequential updating via dynamic hierarchical models: A Bayesian approach to longitudinal data analysis

Most statistical analysis, theory and practice, is concerned with static models; models with a proposed set of parameters whose values are fixed across observational units. Static models implicitly assume that the quantified relationships remain the same across the design space of the data. While this is reasonable under many circumstances this can be a dangerous assumption when dealing with sequentially ordered data. The mere passage of time always brings fresh considerations and the interrelationships among parameters, or subsets of parameters, may need to be continually revised. ^ When data are gathered sequentially dynamic interim monitoring may be useful as new subject-specific parameters are introduced with each new observational unit. Sequential imputation via dynamic hierarchical models is an efficient strategy for handling missing data and analyzing longitudinal studies. Dynamic conditional independence models offers a flexible framework that exploits the Bayesian updating scheme for capturing the evolution of both the population and individual effects over time. While static models often describe aggregate information well they often do not reflect conflicts in the information at the individual level. Dynamic models prove advantageous over static models in capturing both individual and aggregate trends. Computations for such models can be carried out via the Gibbs sampler. An application using a small sample repeated measures normally distributed growth curve data is presented. ^

Dynamic population coding in primary visual cortex

More than a century ago Ramon y Cajal pioneered the description of neural circuits. Currently, new techniques are being developed to streamline the characterization of entire neural circuits. Even if this 'connectome' approach is successful, it will represent only a static description of neural circuits. Thus, a fundamental question in neuroscience is to understand how information is dynamically represented by neural populations. In this thesis, I studied two main aspects of dynamical population codes. ^ First, I studied how the exposure or adaptation, for a fraction of a second to oriented gratings dynamically changes the population response of primary visual cortex neurons. The effects of adaptation to oriented gratings have been extensively explored in psychophysical and electrophysiological experiments. However, whether rapid adaptation might induce a change in the primary visual cortex's functional connectivity to dynamically impact the population coding accuracy is currently unknown. To address this issue, we performed multi-electrode recordings in primary visual cortex, where adaptation has been previously shown to induce changes in the selectivity and response amplitude of individual neurons. We found that adaptation improves the population coding accuracy. The improvement was more prominent for iso- and orthogonal orientation adaptation, consistent with previously reported psychophysical experiments. We propose that selective decorrelation is a metabolically inexpensive mechanism that the visual system employs to dynamically adapt the neural responses to the statistics of the input stimuli to improve coding efficiency. ^ Second, I investigated how ongoing activity modulates orientation coding in single neurons, neural populations and behavior. Cortical networks are never silent even in the absence of external stimulation. The ongoing activity can account for up to 80% of the metabolic energy consumed by the brain. Thus, a fundamental question is to understand the functional role of ongoing activity and its impact on neural computations. I studied how the orientation coding by individual neurons and cell populations in primary visual cortex depend on the spontaneous activity before stimulus presentation. We hypothesized that since the ongoing activity of nearby neurons is strongly correlated, it would influence the ability of the entire population of orientation-selective cells to process orientation depending on the prestimulus spontaneous state. Our findings demonstrate that ongoing activity dynamically filters incoming stimuli to shape the accuracy of orientation coding by individual neurons and cell populations and this interaction affects behavioral performance. In summary, this thesis is a contribution to the study of how dynamic internal states such as rapid adaptation and ongoing activity modulate the population code accuracy. ^

APPLICATION OF THE BRAINSTEM EVOKED RESPONSE (BER) TO NEUROTOXICITY EVALUATION OF THE AUDITORY SYSTEM: ASSESSMENT OF INORGANIC LEAD-INDUCED OTOTOXICITY

An experimental procedure was developed using the Brainstem Evoked Response (BER) electrophysiological technique to assess the effect of neurotoxic substances on the auditory system. The procedure utilizes Sprague-Dawley albino rats who have had dural electrodes implanted in their skulls, allowing neuroelectric evoked potentials to be recorded from their brainstems. Latency and amplitude parameters derived from the evoked potentials help assess the neuroanatomical integrity of the auditory pathway in the brainstem. Moreover, since frequency-specific auditory stimuli are used to evoke the neural responses, additional audiometric information is obtainable. An investigation on non-exposed control animals shows the BER threshold curve obtained by tests at various frequencies very closely approximates that obtained by behavioral audibility tests. Thus, the BER appears to be a valid measure of both functional and neuroanatomical integrity of the afferent auditory neural pathway.^ To determine the usefulness of the BER technique in neurobehavioral toxicology research, a known neurotoxic agent, Pb, was studied. Female Sprague-Dawley rats were dosed for 45 days with low levels of Pb acetate in their drinking water, after which BER recordings were obtained. The Pb dosages were determined from the findings of an earlier pilot study. One group of 6 rats received normal tap water, one group of 7 rats received a solution of 0.1% Pb, and another group of 7 rats received a solution of 0.2% Pb. After 45 days, the three groups exhibited blood Pb levels of 4.5 (+OR-) 0.43 (mu)g/100 ml, 37.8 (+OR-) 4.8 (mu)g/100 ml and 47.3 (+OR-) 2.7 (mu)g/100 ml, respectively.^ The results of the BER recording indicated evoked response waveform latency abnormalities in both the Pb-treated groups when midrange frequency (8 kHz to 32 kHz) stimuli were used. For the most part, waveform amplitudes did not vary significantly from control values. BER recordings obtained after a 30-day recovery period indicated the effects seen in the 0.1% Pb group had disappeared. However, those anomalies exhibited by the 0.2% Pb group either remained or increased in number. This outcome indicates a longer lasting or possibly irreversible effect on the auditory system from the higher dose of Pb. The auditory pathway effect appears to be in the periphery, at the level of the cochlea or the auditory (VIII) nerve. The results of this research indicate the BER technique is a valuable and sensitive indicator of low-level toxic effects on the auditory system.^

RESPIRATORY COMPENSATION MECHANISMS IN THE UPPER AND LOWER RESPIRATORY TRACTS OF AN ANIMAL MODEL AFTER SUBCHRONIC INHALATION EXPOSURE TO FORMALDEHYDE: IMPLICATIONS FOR TOXICOLOGY RISK ASSESSMENT (DEPOSITION, DOSE RECEIVED, RESPONSE)

The potential for significant human populations to experience long-term inhalation of formaldehyde and reports of symptomatology due to this exposure has led to a considerable interest in the toxicologic assessment of risk from subchronic formaldehyde exposures using animal models. Since formaldehyde inhalation depresses certain respiratory parameters in addition to its other forms of toxicity, there is a potential for the alteration of the actual dose received by the exposed individual (and the resulting toxicity) due to this respiratory effect. The respiratory responses to formaldehyde inhalation and the subsequent pattern of deposition were therefore investigated in animals that had received subchronic exposure to the compound, and the potential for changes in the formaldehyde dose received due to long-term inhalation evaluated. Male Sprague-Dawley rats were exposed to either 0, 0.5, 3, or 15 ppm formaldehyde for 6 hours/day, 5 days/week for up to 6 months. The patterns of respiratory response, deposition and the compensation mechanisms involved were then determined in a series of formaldehyde test challenges to both the upper and to the lower respiratory tracts in separate groups of subchronically exposed animals and age-specific controls (four concentration groups, two time points). In both the control and pre-exposed animals, there was a characteristic recovery of respiratory parameters initially depressed by formaldehyde inhalation to at or approaching pre-exposure levels within 10 minutes of the initiation of exposure. Also, formaldehyde deposition was found to remain very high in the upper and lower tracts after long-term exposure. Therefore, there was probably little subsequent effect on the dose received by the exposed individual that was attributable to the repeated exposures. There was a diminished initial minute volume response in test challenges of both the upper and lower tracts of animals that had received at least 16 weeks of exposure to 15 ppm, with compensatory increases in tidal volume in the upper tract and respiratory rate in the lower tract. However, this dose-related effect was probably not relevant to human risk estimation because this formaldehyde dose is in excess of that experienced by human populations. ^

Renal Cryoablation: Investigation of Periprocedural Visualization Tools and Treatment Response Quantification

Cryoablation for small renal tumors has demonstrated sufficient clinical efficacy over the past decade as a non-surgical nephron-sparing approach for treating renal masses for patients who are not surgical candidates. Minimally invasive percutaneous cryoablations have been performed with image guidance from CT, ultrasound, and MRI. During the MRI-guided cryoablation procedure, the interventional radiologist visually compares the iceball size on monitoring images with respect to the original tumor on separate planning images. The comparisons made during the monitoring step are time consuming, inefficient and sometimes lack the precision needed for decision making, requiring the radiologist to make further changes later in the procedure. This study sought to mitigate uncertainty in these visual comparisons by quantifying tissue response to cryoablation and providing visualization of the response during the procedure. Based on retrospective analysis of MR-guided cryoablation patient data, registration and segmentation algorithms were investigated and implemented for periprocedural visualization to deliver iceball position/size with respect to planning images registered within 3.3mm with at least 70% overlap and a quantitative logit model was developed to relate perfusion deficit in renal parenchyma visualized in verification images as a result of iceball size visualized in monitoring images. Through retrospective study of 20 patient cases, the relationship between likelihood of perfusion loss in renal parenchyma and distance within iceball was quantified and iteratively fit to a logit curve. Using the parameters from the logit fit, the margin for 95% perfusion loss likelihood was found to be 4.28 mm within the iceball. The observed margin corresponds well with the clinically accepted margin of 3-5mm within the iceball. In order to display the iceball position and perfusion loss likelihood to the radiologist, algorithms were implemented to create a fast segmentation and registration module which executed in under 2 minutes, within the clinically-relevant 3 minute monitoring period. Using 16 patient cases, the average Hausdorff distance was reduced from 10.1mm to 3.21 mm with average DSC increased from 46.6% to 82.6% before and after registration.

Retinoid -induced regression of human head and neck squamous cell carcinomas is associated with the induction of a pro -inflammatory response

Retinoids are Vitamin A derivatives that are effective chemopreventative and chemotherapeutic agents for head and neck squamous cell carcinomas (HNSCC). Despite the wide application of retinoids in cancer treatment, the mechanism by which retinoids inhibit head and neck squamous cell carcinomas is not completely understood. While in vitro models show that drugs affect cell proliferation and differentiation, in vivo models, such as tumor xenografts in nude mice drugs affect more complex parameters such as extracellular matrix formation, angiogenesis and inflammation. Therefore, we studied the effects of retinoids on the growth of the 22B HNSCC tumors using a xenograft model. In this system, retinoids had no effect on tumor cell differentiation but caused invasion of the tumor by inflammatory cells. Retinoid induced inflammation lead to tumor cell death and tumor regression. Therefore, we hypothesized that retinoids stimulated the 22B HNSCC xenografts to produce a pro-inflammatory signal such as chemokines that in turn activated host inflammatory responses. ^ We used real time quantitative RT-PCR to measure cytokine and chemokine expression in retinoid treated tumors. Treatment of tumors with an RAR-specific retinoid, LGD1550, had no effect on the expression of TNFα, IL-1α, GROα, IP-10, Rantes, MCP-1 and MIP-1α but induced IL-8 mRNA 5-fold. We further characterized the retinoid effect on IL-8 expression on the 22B HNSCC and 1483 HNSCC cells in vitro. Retinoids increased IL-8 expression and enhanced TNFα-dependent IL-8 induction. In addition, retinoids increased the basal and TNFα-dependent expression of MCP-1 but decreased the basal and TNFα dependent expression of IP-10. The effect of retinoids on IL-8 and MCP-1 expression was very rapid with increased levels of mRNA detected within 1–2 hours. This effect did not require new protein synthesis and did not result from mRNA stabilization. Both RAR and RXR ligands increased IL-8 expression whereas only RAR ligands activated MCP-1 expression. ^ We identified a functional retinoid response element in the IL-8 promoter that was located adjacent to the C/EBP-NFkB response element. TNFα treatment of the 22B cells caused rapid, transient and selective acetylation of regions of the IL-8 promoter associated with the NFkB response element. Co-treatment of the cells with retinoids plus TNF increased the acetylation of chromatin in this region without altering the kinetics of acetylation. These results demonstrate that ligand activated retinoid receptors can cooperate with NFkB in histone acetylation and chromatin remodeling. We believe that in certain HNSCC tumors this cooperation and the resulting enhancement of IL-8 expression can induce an inflammatory response that leads to tumor regression. We believe that the induction of inflammation in susceptible tumors, possibly coupled with cytotoxic interventions may be an important component in the use of retinoids to treat human squamous cancers. ^

Dynamic contrast agent -enhanced magnetic resonance imaging assessment of tumor microvasculature

Dynamic contrast agent-enhanced magnetic resonance imaging (DCE MRI) data, when analyzed with the appropriate pharmacokinetic models, have been shown to provide quantitative estimates of microvascular parameters important in characterizing the angiogenic activity of malignant tissue. These parameters consist of the whole blood volume per unit volume of tissue, v b, transport constant from the plasma to the extravascular, extracellular space (EES), k1 and the transport constant from the EES to the plasma, k2. Parameters vb and k1 are expected to correlate with microvascular density (MVD) and vascular permeability, respectively, which have been suggested to serve as surrogate markers for angiogenesis. In addition to being a marker for angiogenesis, vascular permeability is also useful in estimating tumor penetration potential of chemotherapeutic agents. ^ Histological measurements of the intratumoral microvascular environment are limited by their invasiveness and susceptibility to sampling errors. Also, MVD and vascular permeability, while useful for characterizing tumors at a single time point, have shown less utility in longitudinal studies, particularly when used to monitor the efficacy of antiangiogenic and traditional chemotherapeutic agents. These limitations led to a search for a non-invasive means of characterizing the microvascular environment of an entire tumor. ^ The overall goal of this project was to determine the utility of DCE MRI for monitoring the effect of antiangiogenic agents. Further applications of a validated DCE MRI technique include in vivo measurements of tumor microvascular characteristics to aid in determining prognosis at presentation and in estimating drug penetration. DCE MRI data were generated using single- and dual-tracer pharmacokinetic models with different molecular-weight contrast agents. The resulting pharmacokinetic parameters were compared to immunohistochemical measurements. The model and contrast agent combination yielding the best correlation between the pharmacokinetic parameters and histological measures was further evaluated in a longitudinal study to evaluate the efficacy of DCE MRI in monitoring the intratumoral microvascular environment following antiangiogenic treatment. ^