Reference region-based pharmacokinetic modeling in quantitative dynamic contract-enhanced MRI allows robust treatment monitoring in a rat liver tumor model despite cardiovascular changes

Functional biomarkers derived from computed tomography and magnetic resonance imaging differentiate PDAC subgroups and reveal gemcitabine-induced hypo-vascularization

PURPOSE

Pancreatic ductal adenocarcinoma (PDAC) is a molecularly heterogeneous tumor entity with no clinically established imaging biomarkers. We hypothesize that tumor morphology and physiology, including vascularity and perfusion, show variations that can be detected by differences in contrast agent (CA) accumulation measured non-invasively. This work seeks to establish imaging biomarkers for tumor stratification and therapy response monitoring in PDAC, based on this hypothesis.

METHODS AND MATERIALS

Regional CA accumulation in PDAC was correlated with tumor vascularization, stroma content, and tumor cellularity in murine and human subjects. Changes in CA distribution in response to gemcitabine (GEM) were monitored longitudinally with computed tomography (CT) Hounsfield Units ratio (HUr) of tumor to the aorta or with magnetic resonance imaging (MRI) ΔR₁ area under the curve at 60 s tumor-to-muscle ratio (AUC60r). Tissue analyses were performed on co-registered samples, including endothelial cell proliferation and cisplatin tissue deposition as a surrogate of chemotherapy delivery.

RESULTS

Tumor cell poor, stroma-rich regions exhibited high CA accumulation both in human (meanHUr 0.64 vs. 0.34, p < 0.001) and mouse PDAC (meanAUC60r 2.0 vs. 1.1, p < 0.001). Compared to the baseline, in vivo CA accumulation decreased specifically in response to GEM treatment in a subset of human (HUr -18%) and mouse (AUC60r -36%) tumors. Ex vivo analyses of mPDAC showed reduced cisplatin delivery (GEM: 0.92 ± 0.5 mg/g, vs. vehicle: 3.1 ± 1.5 mg/g, p = 0.004) and diminished endothelial cell proliferation (GEM: 22.3% vs. vehicle: 30.9%, p = 0.002) upon GEM administration.

CONCLUSION

In PDAC, CA accumulation, which is related to tumor vascularization and perfusion, inversely correlates with tumor cellularity. The standard of care GEM treatment results in decreased CA accumulation, which impedes drug delivery. Further investigation is warranted into potentially detrimental effects of GEM in combinatorial therapy regimens.

Tumor Uptake of Anti-CD20 Fabs Depends on Tumor Perfusion

Antibodies have become an established treatment modality in cancer therapy during the last decade. However, these treatments often suffer from an insufficient and heterogeneous response despite validated antigen or target receptor expression in the tumor. In fact, therapeutic success depends on both the presence of the tumor antigen and its accessibility by the antibody. In search of a suitable preclinical animal model to evaluate the mechanisms of tumor heterogeneity and hemodynamics, we characterized two exemplary non-Hodgkin lymphoma subtypes with comparable CD20 expression and metabolism, SUDHL-4 and Granta-519, using multimodal imaging techniques.

METHODS

To investigate in vivo biodistribution, two differently modified αCD20 antigen-binding fragments (Fab), prepared by PASylation with a 200-residue polypeptide tag comprising Pro, Ala, and Ser (PAS₂₀₀) and by fusion with an albumin-binding domain (ABD), were radiolabeled with ¹²⁵I and intravenously injected into immunocompromised mice bearing corresponding xenografts.

RESULTS

Validation with ¹⁸F-FDG revealed a similar distribution in vital tumor tissue 1 h after injection. However, large differences in tumor uptake were observed when the CD20-specific radiotracers ¹²⁵I-Fab-ABD and ¹²⁵I-Fab-PAS₂₀₀ were applied (respective percentages injected dose per gram at 24 h after injection: 12.3 and 2.4 for Granta-519 vs. 5.8 and 1.2 for SUDHL-4). Three-dimensional light-sheet fluorescence microscopy with Cy5-Fab-PAS₂₀₀ confirmed better tracer extravasation in the Granta-519 tumors. Moreover, dynamic contrast-enhanced (DCE) MRI revealed significantly reduced perfusion in the SUDHL-4 tumors.

CONCLUSION

Tracer uptake was highly dependent on local tumor perfusion and Fab permeation in the SUDHL-4 and Granta-519 tumors. Thus, the SUDHL-4 xenograft offers an excellent model for investigating the influence of therapies affecting tumor angiogenesis.

Multiparametric human hepatocellular carcinoma characterization and therapy response evaluation by hyperpolarized (13) C MRSI

Individual tumor characterization and treatment response monitoring based on current medical imaging methods remain challenging. This work investigates hyperpolarized (13) C compounds in an orthotopic rat hepatocellular carcinoma (HCC) model system before and after transcatheter arterial embolization (TAE). HCC ranks amongst the top six most common cancer types in humans and accounts for one-third of cancer-related deaths worldwide. Early therapy response monitoring could aid in the development of personalized therapy approaches and novel therapeutic concepts. Measurements with selectively (13) C-labeled and hyperpolarized urea, pyruvate and fumarate were performed in tumor-bearing rats before and after TAE. Two-dimensional, slice-selective MRSI was used to obtain spatially resolved maps of tumor perfusion, cell energy metabolic conversion rates and necrosis, which were additionally correlated with immunohistochemistry. All three injected compounds, taken together with their respective metabolites, exhibited similar signal distributions. TAE induced a decrease in blood flow into the tumor and thus a decrease in tumor to muscle and tumor to liver ratios of urea, pyruvate and its metabolites, alanine and lactate, whereas conversion rates remained stable or increased on TAE in tumor, muscle and liver tissue. Conversion from fumarate to malate successfully indicated individual levels of necrosis, and global malate signals after TAE suggested the washout of fumarase or malate itself on necrosis. This study presents a combination of three (13) C compounds as novel candidate biomarkers for a comprehensive characterization of genetically and molecularly diverse HCC using hyperpolarized MRSI, enabling the simultaneous detection of differences in tumor perfusion, metabolism and necrosis. If, as in this study, bolus dynamics are not required and qualitative perfusion information is sufficient, the desired information could be extracted from hyperpolarized fumarate and pyruvate alone, acquired at higher fields with better spectral separation. Copyright © 2016 John Wiley & Sons, Ltd.

Models and methods for analyzing DCE-MRI: a review

PURPOSE

To present a review of most commonly used techniques to analyze dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), discusses their strengths and weaknesses, and outlines recent clinical applications of findings from these approaches.

METHODS

DCE-MRI allows for noninvasive quantitative analysis of contrast agent (CA) transient in soft tissues. Thus, it is an important and well-established tool to reveal microvasculature and perfusion in various clinical applications. In the last three decades, a host of nonparametric and parametric models and methods have been developed in order to quantify the CA's perfusion into tissue and estimate perfusion-related parameters (indexes) from signal- or concentration-time curves. These indexes are widely used in various clinical applications for the detection, characterization, and therapy monitoring of different diseases.

RESULTS

Promising theoretical findings and experimental results for the reviewed models and techniques in a variety of clinical applications suggest that DCE-MRI is a clinically relevant imaging modality, which can be used for early diagnosis of different diseases, such as breast and prostate cancer, renal rejection, and liver tumors.

CONCLUSIONS

Both nonparametric and parametric approaches for DCE-MRI analysis possess the ability to quantify tissue perfusion.

Multimodality multiparametric imaging of early tumor response to a novel antiangiogenic therapy based on anticalins

Anticalins are a novel class of targeted protein therapeutics. The PEGylated Anticalin Angiocal (PRS-050-PEG40) is directed against VEGF-A. The purpose of our study was to compare the performance of diffusion weighted imaging (DWI), dynamic contrast enhanced magnetic resonance imaging (DCE)-MRI and positron emission tomography with the tracer [18F]fluorodeoxyglucose (FDG-PET) for monitoring early response to antiangiogenic therapy with PRS-050-PEG40. 31 mice were implanted subcutaneously with A673 rhabdomyosarcoma xenografts and underwent DWI, DCE-MRI and FDG-PET before and 2 days after i.p. injection of PRS-050-PEG40 (n = 13), Avastin (n = 6) or PBS (n = 12). Tumor size was measured manually with a caliper. Imaging results were correlated with histopathology. In the results, the tumor size was not significantly different in the treatment groups when compared to the control group on day 2 after therapy onset (P = 0.09). In contrast the imaging modalities DWI, DCE-MRI and FDG-PET showed significant differences between the therapeutic compared to the control group as early as 2 days after therapy onset (P<0.001). There was a strong correlation of the early changes in DWI, DCE-MRI and FDG-PET at day 2 after therapy onset and the change in tumor size at the end of therapy (r = -0.58, 0.71 and 0.67 respectively). The imaging results were confirmed by histopathology, showing early necrosis and necroptosis in the tumors. Thus multimodality multiparametric imaging was able to predict therapeutic success of PRS-050-PEG40 and Avastin as early as 2 days after onset of therapy and thus promising for monitoring early response of antiangiogenic therapy.

A comparison of individual and population-derived vascular input functions for quantitative DCE-MRI in rats

Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) can quantitatively and qualitatively assess physiological characteristics of tissue. Quantitative DCE-MRI requires an estimate of the time rate of change of the concentration of the contrast agent in the blood plasma, the vascular input function (VIF). Measuring the VIF in small animals is notoriously difficult as it requires high temporal resolution images limiting the achievable number of slices, field-of-view, spatial resolution, and signal-to-noise. Alternatively, a population-averaged VIF could be used to mitigate the acquisition demands in studies aimed to investigate, for example, tumor vascular characteristics. Thus, the overall goal of this manuscript is to determine how the kinetic parameters estimated by a population based VIF differ from those estimated by an individual VIF. Eight rats bearing gliomas were imaged before, during, and after an injection of Gd-DTPA. K(trans), ve, and vp were extracted from signal-time curves of tumor tissue using both individual and population-averaged VIFs. Extended model voxel estimates of K(trans) and ve in all animals had concordance correlation coefficients (CCC) ranging from 0.69 to 0.98 and Pearson correlation coefficients (PCC) ranging from 0.70 to 0.99. Additionally, standard model estimates resulted in CCCs ranging from 0.81 to 0.99 and PCCs ranging from 0.98 to 1.00, supporting the use of a population based VIF if an individual VIF is not available.

Validation of preclinical multiparametric imaging for prediction of necrosis in hepatocellular carcinoma after embolization

BACKGROUND & AIMS

The hepatocellular carcinoma (HCC) exhibits varying degrees of vascularization with more poorly differentiated carcinoma commonly exhibiting high amounts of vascularization. Transcatheter arterial embolization (TAE) of HCC tumor nodules results in varying amounts of tumor necrosis. Reliable quantification of necrosis after TAE, would aid in treatment planning and testing of novel combinatorial treatment regimen. The aim of this work was to validate different imaging parameters as individual or combined predictors of tumor necrosis after TAE in an orthotopic rat HCC tumor model.

METHODS

Unifocal rat HCC was imaged by T(2)-weighted MRI, quantitative dynamic contrast enhanced (DCE) MRI, diffusion weighted MRI (DWI) and [(18)F]-FDG PET imaging before (day-1) and after (days 1 and 3) TAE. Univariate and multivariate regression analyses were carried out to analyze the ability of each imaging parameter to predict the percent residual vital tumor (vtu) and vital tissue (vti) as determined by quantitative histopathology.

RESULTS

TAE induced a wide range of tumor necrosis. Tumor volume was the only parameter showing a correlation with vti (r(2) = 0.63) before TAE. After TAE, moderate correlations were found for FDG tracer uptake (r(2) = 0.56) and plasma tissue transfer constant (r(2) = 0.55). Correlations were higher for the extravascular extracellular volume fraction (v(e), r(2) = 0.68) and highest for the apparent diffusion coefficient (ADC, r(2) = 0.86). Multivariate analyses confirmed highest correlation of ADC and v(e) with vtu and vti.

CONCLUSIONS

DWI and DCE-MRI with the respective parameters ADC (day 3) and v(e) (day 1) were identified as the most promising imaging techniques for the prediction of necrosis. This study validates a preclinical platform allowing for the improved tumor stratification after TAE and thus the testing of novel combinatorial therapy approaches in HCC.

Assessing antiangiogenic therapy response by DCE-MRI: development of a physiology driven multi-compartment model using population pharmacometrics

Dynamic contrast enhanced (DCE-) MRI is commonly applied for the monitoring of antiangiogenic therapy in oncology. Established pharmacokinetic (PK) analysis methods of DCE-MRI data do not sufficiently reflect the complex anatomical and physiological constituents of the analyzed tissue. Hence, accepted endpoints such as Ktrans reflect an unknown multitude of local and global physiological effects often rendering an understanding of specific local drug effects impossible. In this work a novel multi-compartment PK model is presented, which for the first time allows the separation of local and systemic physiological effects. DCE-MRI data sets from multiple, simultaneously acquired tissues, i.e. spinal muscle, liver and tumor tissue, of hepatocellular carcinoma (HCC) bearing rats were applied for model development. The full Markov chain Monte Carlo (MCMC) Bayesian analysis method was applied for model parameter estimation and model selection was based on histological and anatomical considerations and numerical criteria. A population PK model (MTL3 model) consisting of 3 measured and 6 latent (unobserved) compartments was selected based on Bayesian chain plots, conditional weighted residuals, objective function values, standard errors of model parameters and the deviance information criterion. Covariate model building, which was based on the histology of tumor tissue, demonstrated that the MTL3 model was able to identify and separate tumor specific, i.e. local, and systemic, i.e. global, effects in the DCE-MRI data. The findings confirm the feasibility to develop physiology driven multi-compartment PK models from DCE-MRI data. The presented MTL3 model allowed the separation of a local, tumor specific therapy effect and thus has the potential for identification and specification of effectors of vascular and tissue physiology in antiangiogenic therapy monitoring.