Quantification of antiangiogenic and antivascular drug activity by kinetic analysis of DCE-MRI data

CEST MRI monitoring of tumor response to vascular disrupting therapy using high molecular weight dextrans

PURPOSE

Vascular disrupting therapy of cancer has become a promising approach not only to regress tumor growth directly but also to boost the delivery of chemotherapeutics in the tumor. An imaging approach to monitor the changes in tumor vascular permeability, therefore, has important applications for monitoring of vascular disrupting therapies.

METHODS

Mice bearing CT26 subcutaneous colon tumors were injected intravenously with 150 kD dextran (Dex150, diameter, d~ 20 nm, 375 mg/kg), tumor necrosis factor-alpha (TNF-α; 1 µg per mouse), or both (n = 3 in each group). The Z-spectra were acquired before and 2 h after the injection, and the chemical exchange saturation transfer (CEST) signals in the tumors as quantified by asymmetric magnetization transfer ratio (MTR_asym ) at 1 ppm were compared.

RESULTS

The results showed a significantly stronger CEST contrast enhancement at 1 ppm (∆MTR_asym = 0.042 ± 0.002) in the TNF-α-treated tumors than those by Dex150 alone (∆MTR_asym = 0.000 ± 0.005, P = 0.0229) or TNF-α alone (∆MTR_asym = 0.002 ± 0.004, P = 0.0264), indicating that the TNF-α treatment strongly augmented the tumor uptake of 150 kD dextran. The MRI findings were verified by fluorescence imaging and immunofluorescence microscopy.

CONCLUSIONS

High molecular weight dextrans can be used as safe and sensitive CEST MRI contrast agents for monitoring tumor response to vascular disrupting therapy and, potentially, for developing dextran-based theranostic drug delivery systems.

Accuracy, repeatability, and interplatform reproducibility of T1 quantification methods used for DCE-MRI: Results from a multicenter phantom study

PURPOSE

To determine the in vitro accuracy, test-retest repeatability, and interplatform reproducibility of T₁ quantification protocols used for dynamic contrast-enhanced MRI at 1.5 and 3 T.

METHODS

A T₁ phantom with 14 samples was imaged at eight centers with a common inversion-recovery spin-echo (IR-SE) protocol and a variable flip angle (VFA) protocol using seven flip angles, as well as site-specific protocols (VFA with different flip angles, variable repetition time, proton density, and Look-Locker inversion recovery). Factors influencing the accuracy (deviation from reference NMR T₁ measurements) and repeatability were assessed using general linear mixed models. Interplatform reproducibility was assessed using coefficients of variation.

RESULTS

For the common IR-SE protocol, accuracy (median error across platforms = 1.4-5.5%) was influenced predominantly by T₁ sample (P < 10^-6 ), whereas test-retest repeatability (median error = 0.2-8.3%) was influenced by the scanner (P < 10^-6 ). For the common VFA protocol, accuracy (median error = 5.7-32.2%) was influenced by field strength (P = 0.006), whereas repeatability (median error = 0.7-25.8%) was influenced by the scanner (P < 0.0001). Interplatform reproducibility with the common VFA was lower at 3 T than 1.5 T (P = 0.004), and lower than that of the common IR-SE protocol (coefficient of variation 1.5T: VFA/IR-SE = 11.13%/8.21%, P = 0.028; 3 T: VFA/IR-SE = 22.87%/5.46%, P = 0.001). Among the site-specific protocols, Look-Locker inversion recovery and VFA (2-3 flip angles) protocols showed the best accuracy and repeatability (errors < 15%).

CONCLUSIONS

The VFA protocols with 2 to 3 flip angles optimized for different applications achieved acceptable balance of extensive spatial coverage, accuracy, and repeatability in T₁ quantification (errors < 15%). Further optimization in terms of flip-angle choice for each tissue application, and the use of B₁ correction, are needed to improve the robustness of VFA protocols for T₁ mapping. Magn Reson Med 79:2564-2575, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Improved Evaluation of Antivascular Cancer Therapy Using Constrained Tracer-Kinetic Modeling for Multiagent Dynamic Contrast-Enhanced MRI

Dynamic contrast-enhanced MRI (DCE-MRI) is a promising technique for assessing the response of tumor vasculature to antivascular therapies. Multiagent DCE-MRI employs a combination of low and high molecular weight contrast agents, which potentially improves the accuracy of estimation of tumor hemodynamic and vascular permeability parameters. In this study, we used multiagent DCE-MRI to assess changes in tumor hemodynamics and vascular permeability after vascular-disrupting therapy. Multiagent DCE-MRI (sequential injection of G5 dendrimer, G2 dendrimer, and Gd-DOTA) was performed in tumor-bearing mice before, 2 and 24 hours after treatment with vascular disrupting agent DMXAA or placebo. Constrained DCE-MRI gamma capillary transit time modeling was used to estimate flow F, blood volume fraction v_b, mean capillary transit time t_c, bolus arrival time t_d, extracellular extravascular fraction v_e, vascular heterogeneity index α^-1 (all identical between agents) and extraction fraction E (reflective of permeability), and transfer constant K^trans (both agent-specific) in perfused pixels. F, v_b, and α^-1 decreased at both time points after DMXAA, whereas t_c increased. E (G2 and G5) showed an initial increase, after which, both parameters restored. K^trans (G2 and Gd-DOTA) decreased at both time points after treatment. In the control, placebo-treated animals, only F, t_c, and K^trans Gd-DOTA showed significant changes. Histologic perfused tumor fraction was significantly lower in DMXAA-treated versus control animals. Our results show how multiagent tracer-kinetic modeling can accurately determine the effects of vascular-disrupting therapy by separating simultaneous changes in tumor hemodynamics and vascular permeability.Significance: These findings describe a new approach to measure separately the effects of antivascular therapy on tumor hemodynamics and vascular permeability, which could help more rapidly and accurately assess the efficacy of experimental therapy of this class. Cancer Res; 78(6); 1561-70. ©2018 AACR.

Dynamic contrast-enhanced magnetic resonance imaging of prostate cancer: A review of current methods and applications

In many areas of oncology, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has proven to be a clinically useful, non-invasive functional imaging technique to quantify tumor vasculature and tumor perfusion characteristics. Tumor angiogenesis is an essential process for tumor growth, proliferation, and metastasis. Malignant lesions demonstrate rapid extravasation of contrast from the intravascular space to the capillary bed due to leaky capillaries associated with tumor neovascularity. DCE-MRI has the potential to provide information regarding blood flow, areas of hypoperfusion, and variations in endothelial permeability and microvessel density to aid treatment selection, enable frequent monitoring during treatment and assess response to targeted therapy following treatment. This review will discuss the current status of DCE-MRI in cancer imaging, with a focus on its use in imaging prostate malignancies as well as weaknesses that limit its widespread clinical use. The latest techniques for quantification of DCE-MRI parameters will be reviewed and compared.

Monitoring Tumor Response to Antivascular Therapy Using Non-Contrast Intravoxel Incoherent Motion Diffusion-Weighted MRI

Antivascular therapy is a promising approach to the treatment of non-small cell lung cancer (NSCLC), where an imaging modality capable of longitudinally monitoring treatment response could provide early prediction of the outcome. In this study, we sought to investigate the feasibility of using intravoxel incoherent motion (IVIM) diffusion MRI to quantitatively assess the efficacy of the treatments of a vascular-disrupting agent CA4P or its combination with bevacizumab on experimental NSCLC tumors. CA4P caused a strong but reversible effect on tumor vasculature; all perfusion-related parameters-D*, f, fD*, and K^trans-initially showed a decrease of 30% to 60% at 2 hours and then fully recovered to baseline on day 2 for CA4P treatment or on days 4 to 8 for CA4P + bevacizumab treatment; the diffusion coefficient in tumors decreased initially at 2 hours and then increased from day 2 to day 8. We observed a good correlation between IVIM parameters and dynamic contrast-enhanced MRI (DCE-MRI; K^trans). We also found that the relative change in f and fD* at 2 hours correlated well with changes in tumor volume on day 8. In conclusion, our results suggest that IVIM is a promising alternative to DCE-MRI for the assessment of the change in tumor perfusion as a result of antivascular agents and can be used to predict the efficacy of antivascular therapies without the need for contrast media injection. Cancer Res; 77(13); 3491-501. ©2017 AACR.

Estimation of contrast agent bolus arrival delays for improved reproducibility of liver DCE MRI

Delays between contrast agent (CA) arrival at the site of vascular input function (VIF) sampling and the tissue of interest affect dynamic contrast enhanced (DCE) MRI pharmacokinetic modelling. We investigate effects of altering VIF CA bolus arrival delays on liver DCE MRI perfusion parameters, propose an alternative approach to estimating delays and evaluate reproducibility.

Thirteen healthy volunteers (28.7  ±  1.9 years, seven males) underwent liver DCE MRI using dual-input single compartment modelling, with reproducibility (n  =  9) measured at 7 days. Effects of VIF CA bolus arrival delays were assessed for arterial and portal venous input functions. Delays were pre-estimated using linear regression, with restricted free modelling around the pre-estimated delay. Perfusion parameters and 7 days reproducibility were compared using this method, freely modelled delays and no delays using one-way ANOVA. Reproducibility was assessed using Bland–Altman analysis of agreement.

Maximum percent change relative to parameters obtained using zero delays, were  −31% for portal venous (PV) perfusion, +43% for total liver blood flow (TLBF), +3247% for hepatic arterial (HA) fraction, +150% for mean transit time and  −10% for distribution volume. Differences were demonstrated between the 3 methods for PV perfusion (p  =  0.0085) and HA fraction (p  <  0.0001), but not other parameters. Improved mean differences and Bland–Altman 95% Limits-of-Agreement for reproducibility of PV perfusion (9.3 ml/min/100 g, ±506.1 ml/min/100 g) and TLBF (43.8 ml/min/100 g, ±586.7 ml/min/100 g) were demonstrated using pre-estimated delays with constrained free modelling.

CA bolus arrival delays cause profound differences in liver DCE MRI quantification. Pre-estimation of delays with constrained free modelling improved 7 days reproducibility of perfusion parameters in volunteers.

Monitoring vascular normalization induced by antiangiogenic treatment with (18)F-fluoromisonidazole-PET

Background: Rationalization of antiangiogenics requires biomarkers. Vascular re‐normalization is one widely accepted mechanism of action for this drug class. The interstitium of tumors with abnormal vasculature is hypoxic. We sought to track vascular normalization with 18F‐misonidazole ([18F]‐FMISO, a probe that detects hypoxia) PET, in response to window‐of‐opportunity (WoO) treatment with the antiangiogenic dovitinib.

Methods: Two patient‐derived pancreas xenografts (PDXs; Panc215 and Panc286) and the spontaneous breast cancer model MMTV‐PyMT were used. Animals were treated during 1 week of WoO treatment with vehicle or dovitinib, preceded and followed by [18F]‐FMISO‐PET, [18F]‐FDG‐PET, and histologic assessment (dextran extravasation, hypoxia and microvessel staining, and necrosis, cleaved caspase‐3 and Ki67 measurements). After WoO treatment, gemcitabine (pancreas)/adriamycin (breast) or vehicle was added and animals were treated until the humane endpoint. Tumor growth inhibition (TGI) and survival were the parameters studied.

Results: [18F]‐FMISO SUV did not change after dovitinib‐WoO treatment compared to vehicle‐WoO (0.54 vs. 0.6) treatment in Panc215, but it decreased significantly in Panc286 (0.58 vs. 1.18; P < 0.05). In parallel, 10‐KDa perivascular dextran extravasation was not reduced with dovitinib or vehicle‐WoO treatment in Panc215, but it was reduced in Panc286. Whereas the addition of dovitinib to gemcitabine was indifferent in Panc215, it increased TGI in Panc286 (TGI switched from −59% to +49%). [18F]‐FMISO SUV changes were accompanied by an almost 100% increase in interstitial gemcitabine delivery (665–1260 ng/mL). The results were validated in the PyMT model.

Conclusions: [18F]‐FMISO accurately monitored vascular re‐normalization and improved interstitial chemotherapy delivery.

We describe a new technique to monitor the efficacy of antiangiogenics.

This drug class currently lacks biomarkers.

Antiangiogenics exert their positive effect by inducing stromal normalization.

18F‐fluoromisonidazole PET is able to monitor stromal normalization.

Tumors showing stromal normalization by PET experience benefit from antiangiogenics.

Radiotherapy planning using MRI

The use of magnetic resonance imaging (MRI) in radiotherapy (RT) planning is rapidly expanding. We review the wide range of image contrast mechanisms available to MRI and the way they are exploited for RT planning. However a number of challenges are also considered: the requirements that MR images are acquired in the RT treatment position, that they are geometrically accurate, that effects of patient motion during the scan are minimized, that tissue markers are clearly demonstrated, that an estimate of electron density can be obtained. These issues are discussed in detail, prior to the consideration of a number of specific clinical applications. This is followed by a brief discussion on the development of real-time MRI-guided RT.

Three-dimensional dynamic contrast-enhanced MRI for the accurate, extensive quantification of microvascular permeability in atherosclerotic plaques

Atherosclerotic plaques that cause stroke and myocardial infarction are characterized by increased microvascular permeability and inflammation. Dynamic contrast-enhanced MRI (DCE-MRI) has been proposed as a method to quantify vessel wall microvascular permeability in vivo. Until now, most DCE-MRI studies of atherosclerosis have been limited to two-dimensional (2D) multi-slice imaging. Although providing the high spatial resolution required to image the arterial vessel wall, these approaches do not allow the quantification of plaque permeability with extensive anatomical coverage, an essential feature when imaging heterogeneous diseases, such as atherosclerosis. To our knowledge, we present the first systematic evaluation of three-dimensional (3D), high-resolution, DCE-MRI for the extensive quantification of plaque permeability along an entire vascular bed, with validation in atherosclerotic rabbits. We compare two acquisitions: 3D turbo field echo (TFE) with motion-sensitized-driven equilibrium (MSDE) preparation and 3D turbo spin echo (TSE). We find 3D TFE DCE-MRI to be superior to 3D TSE DCE-MRI in terms of temporal stability metrics. Both sequences show good intra- and inter-observer reliability, and significant correlation with ex vivo permeability measurements by Evans Blue near-infrared fluorescence (NIRF). In addition, we explore the feasibility of using compressed sensing to accelerate 3D DCE-MRI of atherosclerosis, to improve its temporal resolution and therefore the accuracy of permeability quantification. Using retrospective under-sampling and reconstructions, we show that compressed sensing alone may allow the acceleration of 3D DCE-MRI by up to four-fold. We anticipate that the development of high-spatial-resolution 3D DCE-MRI with prospective compressed sensing acceleration may allow for the more accurate and extensive quantification of atherosclerotic plaque permeability along an entire vascular bed. We foresee that this approach may allow for the comprehensive and accurate evaluation of plaque permeability in patients, and may be a useful tool to assess the therapeutic response to approved and novel drugs for cardiovascular disease.

GPU-accelerated compartmental modeling analysis of DCE-MRI data from glioblastoma patients treated with bevacizumab

The compartment model analysis using medical imaging data is the well-established but extremely time consuming technique for quantifying the changes in microvascular physiology of targeted organs in clinical patients after antivascular therapies. In this paper, we present a first graphics processing unit-accelerated method for compartmental modeling of medical imaging data. Using this approach, we performed the analysis of dynamic contrast-enhanced magnetic resonance imaging data from bevacizumab-treated glioblastoma patients in less than one minute per slice without losing accuracy. This approach reduced the computation time by more than 120-fold comparing to a central processing unit-based method that performed the analogous analysis steps in serial and more than 17-fold comparing to the algorithm that optimized for central processing unit computation. The method developed in this study could be of significant utility in reducing the computational times required to assess tumor physiology from dynamic contrast-enhanced magnetic resonance imaging data in preclinical and clinical development of antivascular therapies and related fields.

Mixed-effects modeling of clinical DCE-MRI data: application to colorectal liver metastases treated with bevacizumab

PURPOSE

Most dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data are evaluated for individual patients with cohorts analyzed to detect significant changes from baseline values, repeating the process at each posttreatment timepoint. Our study aimed to develop a statistically valid model for the complete time course of DCE-MRI data in a patient cohort.

MATERIALS AND METHODS

Data from 10 patients with colorectal cancer liver metastases were analyzed, including two baseline scans and four post-bevacizumab scans. Apparent changes in tumor median K(trans) were adjusted for changes in observed enhancing tumor fraction (EnF) by multiplying K(trans) by EnF (KEnF). A mixed-effects model (MEM) was defined to describe the KEnF time course for all patients simultaneously by assuming a three-parameter indirect response model with model parameters lognormally distributed across patients.

RESULTS

The typical cohort time course showed a KEnF reduction to 59% of baseline at 24 hours, returning to 65% of baseline values by day 12. Interpatient variability of model parameters ranged from 11% to 307%.

CONCLUSION

The MEM approach has potential for comparing responses at a group level in clinical trials with different doses, schedules, or combination regimens. Furthermore, the KEnF biomarker successfully resolved confounds in interpreting K(trans) arising from therapy induced changes in the volume of enhancing tumor.

DCE-MRI of the liver: effect of linear and nonlinear conversions on hepatic perfusion quantification and reproducibility

PURPOSE

To evaluate the effect of different methods to convert magnetic resonance (MR) signal intensity (SI) to gadolinium concentration ([Gd]) on estimation and reproducibility of model-free and modeled hepatic perfusion parameters measured with dynamic contrast-enhanced (DCE)-MRI.

MATERIALS AND METHODS

In this Institutional Review Board (IRB)-approved prospective study, 23 DCE-MRI examinations of the liver were performed on 17 patients. SI was converted to [Gd] using linearity vs. nonlinearity assumptions (using spoiled gradient recalled echo [SPGR] signal equations). The [Gd] vs. time curves were analyzed using model-free parameters and a dual-input single compartment model. Perfusion parameters obtained with the two conversion methods were compared using paired Wilcoxon test. Test-retest and interobserver reproducibility of perfusion parameters were assessed in six patients.

RESULTS

There were significant differences between the two conversion methods for the following parameters: AUC60 (area under the curve at 60 s, P < 0.001), peak gadolinium concentration (Cpeak, P < 0.001), upslope (P < 0.001), Fp (portal flow, P = 0.04), total hepatic flow (Ft, P = 0.007), and MTT (mean transit time, P < 0.001). Our preliminary results showed acceptable to good reproducibility for all model-free parameters for both methods (mean coefficient of variation [CV] range, 11.87-23.7%), except for upslope (CV = 37%). Among modeled parameters, DV (distribution volume) had CV <22% with both methods, PV and MTT showed CV <21% and <29% using SPGR equations, respectively. Other modeled parameters had CV >30% with both methods.

CONCLUSION

Linearity assumption is acceptable for quantification of model-free hepatic perfusion parameters while the use of SPGR equations and T1 mapping may be recommended for the quantification of modeled hepatic perfusion parameters.

Dynamic contrast-enhanced MRI for monitoring antiangiogenic treatment: determination of accurate and reliable perfusion parameters in a longitudinal study of a mouse xenograft model

Objective

To determine the reliable perfusion parameters in dynamic contrast-enhanced MRI (DCE-MRI) for the monitoring antiangiogenic treatment in mice.

Materials and Methods

Mice, with U-118 MG tumor, were treated with either saline (n = 3) or antiangiogenic agent (sunitinib, n = 8). Before (day 0) and after (days 2, 8, 15, 25) treatment, DCE examinations using correlations of perfusion parameters (K_ep, K_el, and A^H from two compartment model; time to peak, initial slope and % enhancement from time-intensity curve analysis) were evaluated.

Results

Tumor growth rate was found to be 129% ± 28 in control group, -33% ± 11 in four mice with sunitinib-treatment (tumor regression) and 47% ± 15 in four with sunitinib-treatment (growth retardation). K_ep (r = 0.80) and initial slope (r = 0.84) showed strong positive correlation to the initial tumor volume (p < 0.05). In control mice, tumor regression group and growth retardation group animals, K_ep (r : 0.75, 0.78, 0.81, 0.69) and initial slope (r : 0.79, 0.65, 0.67, 0.84) showed significant correlation with tumor volume (p < 0.01). In four mice with tumor re-growth, K_ep and initial slope increased 20% or greater at earlier (n = 2) than or same periods (n = 2) to when the tumor started to re-grow with 20% or greater growth rate.

Conclusion

K_ep and initial slope may a reliable parameters for monitoring the response of antiangiogenic treatment.

GPU-accelerated nonparametric kinetic analysis of DCE-MRI data from glioblastoma patients treated with bevacizumab

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is often used to examine vascular function in malignant tumors and noninvasively monitor drug efficacy of antivascular therapies in clinical studies. However, complex numerical methods used to derive tumor physiological properties from DCE-MRI images can be time-consuming and computationally challenging. Recent advancement of computing technology in graphics processing unit (GPU) makes it possible to build an energy-efficient and high-power parallel computing platform for solving complex numerical problems. This study develops the first reported fast GPU-based method for nonparametric kinetic analysis of DCE-MRI data using clinical scans of glioblastoma patients treated with bevacizumab (Avastin®). In the method, contrast agent concentration-time profiles in arterial blood and tumor tissue are smoothed using a robust kernel-based regression algorithm in order to remove artifacts due to patient motion and then deconvolved to produce the impulse response function (IRF). The area under the curve (AUC) and mean residence time (MRT) of the IRF are calculated using statistical moment analysis, and two tumor physiological properties that relate to vascular permeability, volume transfer constant between blood plasma and extravascular extracellular space (K(trans)) and fractional interstitial volume (ve) are estimated using the approximations AUC/MRT and AUC. The most significant feature in this method is the use of GPU-computing to analyze data from more than 60,000 voxels in each DCE-MRI image in parallel fashion. All analysis steps have been automated in a single program script that requires only blood and tumor data as the sole input. The GPU-accelerated method produces K(trans) and ve estimates that are comparable to results from previous studies but reduces computational time by more than 80-fold compared to a previously reported central processing unit-based nonparametric method. Furthermore, it is at least several orders of magnitudes faster than standard parametric methods that perform compartmental modeling. This finding indicates that the GPU-based method can significantly shorten the computational times required to assess tumor physiology from DCE-MRI data in preclinical and clinical development of antivascular therapies.