Dynamic contrast-enhanced magnetic resonance imaging of human melanoma xenografts with necrotic regions

Incorporating cross-voxel exchange into the analysis of dynamic contrast-enhanced imaging data: theory, simulations and experimental results

Predictions of tumour perfusion are key determinants of drug delivery and responsiveness to therapy. Pharmacokinetic models allow for the estimation of perfusion properties of tumour tissues but many assume no dispersion associated with tracer transport away from the capillaries and through the tissue. At the level of a voxel, this translates to assuming no cross-voxel tracer exchange, often leading to the misinterpretation of derived perfusion parameters. Tofts model (TM), a compartmental model widely used in oncology, also makes this assumption. A more realistic description is required to quantify kinetic properties of tracers, such as convection and diffusion. We propose a Cross-Voxel Exchange Model (CVXM) for analysing cross-voxel tracer kinetics.In silicodatasets quantifying the roles of convection and diffusion in tracer transport (which TM ignores) were employed to investigate the interpretation of Tofts' perfusion parameters compared to CVXM. TM returned inaccurate values ofKtransandvewhere diffusive and convective mechanisms are pronounced (up to 20% and 300% error respectively). A mathematical equation, developed in this work, predicts and gives the correct physiological interpretation of Tofts've.Finally, transport parameters were derived from dynamic contrast enhanced-magnetic resonance imaging of a TS-415 human cervical carcinoma xenograft by using TM and CVXM. The latter deduced lower values ofKtransandvecompared to TM (lower by up to 63% and 76% respectively). It also allowed the detection of a diffusive flux (mean diffusivity 155μm²s^-1) in the tumour tissue, as well as an increased convective flow at the periphery (mean velocity 2.3μm s^-1detected). The results serve as a proof of concept establishing the feasibility of using CVXM for accurately determining transport metrics that characterize the exchange of tracer between voxels. CVXM needs to be investigated further as its parameters can be linked to the tumour microenvironment properties (permeability, pressure…), potentially leading to enhanced personalized treatment planning.

DCE-MRI of Tumor Hypoxia and Hypoxia-Associated Aggressiveness

Tumor hypoxia is associated with resistance to treatment, aggressive growth, metastatic dissemination, and poor clinical outcome in many cancer types. The potential of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to assess the extent of hypoxia in tumors has been investigated in several studies in our laboratory. Cervical carcinoma, melanoma, and pancreatic ductal adenocarcinoma (PDAC) xenografts have been used as models of human cancer, and the transfer rate constant (K^trans) and the extravascular extracellular volume fraction (v_e) have been derived from DCE-MRI data by using Tofts standard pharmacokinetic model and a population-based arterial input function. K^trans was found to reflect naturally occurring and treatment-induced hypoxia when hypoxia was caused by low blood perfusion, radiation responsiveness when radiation resistance was due to hypoxia, and metastatic potential when metastasis was hypoxia-induced. K^trans was also associated with outcome for patients with locally-advanced cervical carcinoma treated with cisplatin-based chemoradiotherapy. Together, the studies imply that DCE-MRI can provide valuable information on the hypoxic status of cervical carcinoma, melanoma, and PDAC. In this communication, we review and discuss the studies and provide some recommendations as to how DCE-MRI data can be analyzed and interpreted to assess tumor hypoxia.

Differentiation of tumor vasculature heterogeneity levels in small animals based on total hemoglobin concentration using magnetic resonance-guided diffuse optical tomography in vivo

Insight into the vasculature of the tumor in small animals has the potential to impact many areas of cancer research. The heterogeneity of the vasculature of a tumor is directly related to tumor stage and disease progression. In this small scale animal study, we investigated the feasibility of differentiating tumors with different levels of vasculature heterogeneity in vivo using a previously developed hybrid magnetic resonance imaging (MRI) and diffuse optical tomography (DOT) system for small animal imaging. Cross-sectional total hemoglobin concentration maps of 10 Fisher rats bearing R3230 breast tumors are reconstructed using multi-wavelength DOT measurements both with and without magnetic resonance (MR) structural a priori information. Simultaneously acquired MR structural images are used to guide and constrain the DOT reconstruction, while dynamic contrast-enhanced MR functional images are used as the gold standard to classify the vasculature of the tumor into two types: high versus low heterogeneity. These preliminary results show that the stand-alone DOT is unable to differentiate tumors with low and high vascular heterogeneity without structural a priori information provided by a high resolution imaging modality. The mean total hemoglobin concentrations comparing the vasculature of the tumors with low and high heterogeneity are significant (p-value 0.02) only when MR structural a priori information is utilized.

Optimized time-resolved imaging of contrast kinetics (TRICKS) in dynamic contrast-enhanced MRI after peptide receptor radionuclide therapy in small animal tumor models

Anti-tumor efficacy of targeted peptide-receptor radionuclide therapy (PRRT) relies on several factors, including functional tumor vasculature. Little is known about the effect of PRRT on tumor vasculature. With dynamic contrast-enhanced (DCE-) MRI, functional vasculature is imaged and quantified using contrast agents. In small animals DCE-MRI is a challenging application. We optimized a clinical sequence for fast hemodynamic acquisitions, time-resolved imaging of contrast kinetics (TRICKS), to obtain DCE-MRI images at both high spatial and high temporal resolution in mice and rats. Using TRICKS, functional vasculature was measured prior to PRRT and longitudinally to investigate the effect of treatment on tumor vascular characteristics. Nude mice bearing H69 tumor xenografts and rats bearing syngeneic CA20948 tumors were used to study perfusion following PRRT administration with (177) lutetium octreotate. Both semi-quantitative and quantitative parameters were calculated. Treatment efficacy was measured by tumor-size reduction. Optimized TRICKS enabled MRI at 0.032 mm(3) voxel size with a temporal resolution of less than 5 s and large volume coverage, a substantial improvement over routine pre-clinical DCE-MRI studies. Tumor response to therapy was reflected in changes in tumor perfusion/permeability parameters. The H69 tumor model showed pronounced changes in DCE-derived parameters following PRRT. The rat CA20948 tumor model showed more heterogeneity in both treatment outcome and perfusion parameters. TRICKS enabled the acquisition of DCE-MRI at both high temporal resolution (Tres ) and spatial resolutions relevant for small animal tumor models. With the high Tres enabled by TRICKS, accurate pharmacokinetic data modeling was feasible. DCE-MRI parameters revealed changes over time and showed a clear relationship between tumor size and Ktrans .

Assessment of tumor necrotic fraction by dynamic contrast-enhanced MRI: a preclinical study of human tumor xenografts with histopathologic correlation

Contrary to the common notion that tumor necrotic regions are non-enhancing after contrast administration, recent evidence has shown that necrotic regions exhibit delayed and slow uptake of gadolinium tracer on dynamic contrast-enhanced MRI (DCE MRI). The purpose of this study is to explore whether the mapping of tumor voxels with delayed and slow enhancement on DCE MRI can be used to derive estimates of tumor necrotic fraction. Patient-derived tumor xenograft lines of seven human cancers were implanted in 26 mice which were subjected to DCE MRI performed using a spoiled gradient recalled sequence. Gadolinium tracer concentration was estimated using the variable flip angle technique. To identify tumor voxels exhibiting delayed and slow uptake of contrast medium, clustering analysis was performed using a k-means clustering algorithm that classified tumor voxels according to their contrast enhancement patterns. Comparison of the percentage of tumor voxels exhibiting delayed and slow enhancement with the tumor necrotic fraction estimated on histology showed a strong correlation (r = 0.962, p < 0.001). The mapping of tumor regions with delayed and slow contrast uptake on DCE MRI correlated strongly with tumor necrotic fraction, and can potentially serve as a non-invasive imaging surrogate for the in vivo assessment of necrotic fraction.

Regional heterogeneity changes in DCE-MRI as response to isolated limb perfusion in experimental soft-tissue sarcomas

Experimental evidence supports an association between heterogeneity in tumor perfusion and response to chemotherapy/radiotherapy, disease progression and malignancy. Therefore, changes in tumor perfusion may be used to assess early effects of tumor treatment. However, evaluating changes in tumor perfusion during treatment is complicated by extensive changes in tumor type, size, shape and appearance. Therefore, this study assesses the regional heterogeneity of tumors by dynamic contrast-enhanced MRI (DCE-MRI) and evaluates changes in response to isolated limb perfusion (ILP) with tumor necrosis factor alpha and melphalan. Data were acquired in an experimental cancer model, using a macromolecular contrast medium, albumin-(Gd-DTPA)45. Small fragments of BN 175 (a soft-tissue sarcoma) were implanted in eight brown Norway rats. MRI of five drug-treated and three sham-treated rats was performed at baseline and 1 h after ILP intervention. Properly co-registered baseline and follow-up DCE-MRI were used to estimate the volume transfer constant (K(trans) ) pharmacokinetic maps. The regional heterogeneity was estimated in 16 tumor sectors and presented in cumulative map-volume histograms. On average, ILP-treated tumors showed a decrease in regional heterogeneity on the histograms. This study shows that heterogenic changes in regional tumor perfusion, estimated using DCE-MRI pharmacokinetic maps, can be measured and used to assess the short-term effects of a potentially curative treatment on the tumor microvasculature in an experimental soft-tissue sarcoma model.

Three-dimensional whole-liver perfusion magnetic resonance imaging in patients with hepatocellular carcinomas and colorectal hepatic metastases

Background

Three-dimensional (3D) whole-liver perfusion magnetic resonance(MR) imaging with parallel imaging, a novel imaging method to characterize tumor vascularization in vivo, has recently been applied to comprehensively image perfusion changes in large tumors. Coupled with new perfusion software, this technique enables motion correction, registration, and evaluation of perfusion MR parameters. The purpose of this study was to assess the feasibility of 3D whole-liver perfusion MR, for imaging hepatocellular carcinoma (HCC) and colorectal hepatic metastases (CRHM).

Methods

26 patients with hepatic tumors (10 HCC; 16 CRHM) were subjected to 3D whole-liver perfusion MR with a temporal resolution of 3.7 seconds. The following estimated perfusion parameters were measured: the volume transfer constant K^trans (min^-1); the volume (V_e) of extravascular extracellular space (EES) per volume unit of tissue; and the flux rate constant between EES and plasma K_ep (min^-1). Statistical analysis was conducted to investigate inter-observer characteristics and significance of the measured parameters.

Results

Inter-observer agreement analysis (95% limits of agreement) yielded a mean difference of −0.0048 min^-1 (−0.0598 ~ 0.0502) for K^trans , -0.0630 ml (−0.5405 ~ 0.4145) for V_e, and −0.0031 min^-1 (−0.0771 ~ 0.0709) for K_ep respectively. When comparing images from patients with HCC vs. CRHM, significant differences were seen for the mean K^trans (p = 0.017), but not for V_e(p = 0.117) or K_ep(p = 0.595).

Conclusion

Herein we show that 3D whole-liver MR perfusion imaging with semi-automatic data analysis is feasible and enables the reliable quantitative evaluation of the perfusion parameters for HCCs and CRHMs.

Heterogeneity in DCE-MRI parametric maps: a biomarker for treatment response?

This study aims to quantify the heterogeneity of tumour enhancement in dynamic contrast-enhanced MRI (DCE-MRI) using texture analysis methods. The suitability of the coherence and the fractal dimension to monitor tumour response was evaluated in 18 patients with limb sarcomas imaged by DCE-MRI pre- and post-treatment. According to the histopathology, tumours were classified into responders and non-responders. Pharmacokinetic (K(trans)) and heuristic model-based parametric maps (slope, max enhancement, AUC) were computed from the DCE-MRI data. A substantial correlation was found between the pharmacokinetic and heuristic model-based parametric maps: ρ = 0.56 for the slope, ρ = 0.44 for maximum enhancement, and ρ = 0.61 for AUC. From all four parametric maps, the enhancing fraction, and the heterogeneity features (i.e. coherence and fractal dimension) were determined. In terms of monitoring tumour response, using both pre- and post-treatment DCE-MRI, the enhancing fraction and the coherence showed significant differences between the response group and the non-response group (i.e. the highest sensitivity (91%) for K(trans), and the highest specificity (83%) for max enhancement). In terms of treatment prediction, using solely the pre-treatment DCE-MRI, the enhancing fraction and coherence discriminated between responders and non-responders. For prediction, the highest sensitivity (91%) was shared by K(trans), slope and max enhancement, and the highest specificity (71%) was achieved by K(trans). On average, tumours that responded showed a high enhancing fraction and high coherence on the pre-treatment scan. These results suggest that specific heterogeneity features, computed from both pharmacokinetic and heuristic model-based parametric maps, show potential as a biomarker for monitoring tumour response.

Scaling rules for diffusive drug delivery in tumor and normal tissues

Delivery of blood-borne molecules and nanoparticles from the vasculature to cells in the tissue differs dramatically between tumor and normal tissues due to differences in their vascular architectures. Here we show that two simple measures of vascular geometry--δ(max) and λ--readily obtained from vascular images, capture these differences and link vascular structure to delivery in both tissue types. The longest time needed to bring materials to their destination scales with the square of δ(max), the maximum distance in the tissue from the nearest blood vessel, whereas λ, a measure of the shape of the spaces between vessels, determines the rate of delivery for shorter times. Our results are useful for evaluating how new therapeutic agents that inhibit or stimulate vascular growth alter the functional efficiency of the vasculature and more broadly for analysis of diffusion in irregularly shaped domains.

Dynamic contrast-enhanced magnetic resonance imaging of human cervical carcinoma xenografts: pharmacokinetic analysis and correlation to tumor histomorphology

BACKGROUND AND PURPOSE

Biomarkers that can predict the outcome of treatment accurately are needed for treatment individualization in advanced carcinoma of the uterine cervix. The potential of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) was investigated in the present preclinical study.

MATERIALS AND METHODS

CK-160 and TS-415 human cervical carcinoma xenografts were subjected to DCE-MRI at 1.5T using a spatial resolution of 0.23×0.47×2.0mm(3). Parametric images of K(trans) (the volume transfer constant of Gd-DTPA) and v(e) (the extravascular extracellular volume fraction) were produced by pharmacokinetic analysis of the DCE-MRI data and compared with the histomorphology of the imaged tissue.

RESULTS

Analysis of small homogeneous tumor regions showed that K(trans), but not v(e), differed significantly between parenchymal tissue, connective tissue, and necrotic tissue, consistent with the vascularity of these compartments. However, strong correlations between K(trans) and the fractional volume of the compartments could not be detected for larger tumor regions, primarily because the majority of the voxels represented a chaotic mixture of parenchymal, connective, and necrotic tissue.

CONCLUSION

The potential of DCE-MRI in providing detailed information on the histomorphology of cervical carcinoma is limited, mainly because the tumor tissue shows significant morphological heterogeneity at the subvoxel level.

Quantifying spatial heterogeneity in dynamic contrast-enhanced MRI parameter maps

Dynamic contrast-enhanced MRI is becoming a standard tool for imaging-based trials of anti-vascular/angiogenic agents in cancer. So far, however, biomarkers derived from DCE-MRI parameter maps have largely neglected the fact that the maps have spatial structure and instead focussed on distributional summary statistics. Such statistics-e.g., biomarkers based on median values-neglect the spatial arrangement of parameters, which may carry important diagnostic and prognostic information. This article describes two types of heterogeneity biomarker that are sensitive to both parameter values and their spatial arrangement. Methods based on Rényi fractal dimensions and geometrical properties are developed, both of which attempt to describe the complexity of DCE-MRI parameter maps. Experiments using simulated data show that the proposed biomarkers are sensitive to changes that distribution-based summary statistics cannot detect and demonstrate that heterogeneity biomarkers could be applied in the drug trial setting. An experiment using 23 DCE-MRI parameter maps of gliomas-a class of tumour that is graded on the basis of heterogeneity-shows that the proposed heterogeneity biomarkers are able to differentiate between low- and high-grade tumours.

High-resolution longitudinal assessment of flow and permeability in mouse glioma vasculature: Sequential small molecule and SPIO dynamic contrast agent MRI

The poor prognosis associated with malignant glioma is largely attributable to its invasiveness and robust angiogenesis. Angiogenesis involves host-tumor interaction and requires in vivo evaluation. Despite their versatility, few studies have used mouse glioma models with perfusion MRI approaches, and generally lack longitudinal study design. Using a micro-MRI system (8.5 Tesla), a novel dual bolus-tracking perfusion MRI strategy was implemented. Using the small molecule contrast agent Magnevist, dynamic contrast enhanced MRI was implemented in the intracranial 4C8 mouse glioma model to determine K(trans) and v(e), indices of tumor vascular permeability and cellularity, respectively. Dynamic susceptibility contrast MRI was subsequently implemented to assess both cerebral blood flow and volume, using the macromolecular superparamagnetic iron oxide, Feridex, which circumvented tumor bolus susceptibility curve distortions from first-pass extravasation. The high-resolution parametric maps obtained over 4 weeks, indicated a progression of tumor vascularization, permeability, and decreased cellularity with tumor growth. In conclusion, a comprehensive array of key parameters were reliably quantified in a longitudinal mouse glioma study. The syngeneic 4C8 intracerebral mouse tumor model has excellent characteristics for studies of glioma angiogenesis. This approach provides a useful platform for noninvasive and highly diagnostic longitudinal investigations of anti-angiogenesis strategies in a relevant orthotopic animal model.