S Simona Turco

Magnetic resonance dispersion imaging for localization of angiogenesis and cancer growth.

PurposeCancer angiogenesis can be imaged by using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Pharmacokinetic modeling can be used to assess vascular perfusion and permeability, but the assessment of angiogenic changes in the microvascular architecture remains challenging. This article presents 2 models enabling the characterization of the microvascular architecture by DCE-MRI. TheoryThe microvascular architecture is reflected in the dispersion coefficient according to the convective dispersion equation. A solution of this equation, combined with the Tofts model, permits defining a dispersion model for magnetic resonance imaging. A reduced dispersion model is also presented. MethodsThe proposed models were evaluated for prostate cancer diagnosis. Dynamic contrast-enhanced magnetic resonance imaging was performed, and concentration-time curves were calculated in each voxel. The simultaneous generation of parametric maps related to permeability and dispersion was obtained through model fitting. A preliminary validation was carried out through comparison with the histology in 15 patients referred for radical prostatectomy. ResultsCancer localization was accurate with both dispersion models, with an area under the receiver operating characteristic curve greater than 0.8. None of the compared parameters, aimed at assessing vascular permeability and perfusion, showed better results. ConclusionsA new DCE-MRI method is proposed to characterize the microvascular architecture through the assessment of intravascular dispersion, without the need for separate arterial-input-function estimation. The results are promising and encourage further research.

Mathematical Models of Contrast Transport Kinetics for Cancer Diagnostic Imaging: A Review

Angiogenesis plays a fundamental role in cancer growth and the formation of metastasis. Novel cancer therapies aimed at inhibiting angiogenic processes and/or disrupting angiogenic tumor vasculature are currently being developed and clinically tested. The need for earlier and improved cancer diagnosis, and for early evaluation and monitoring of therapeutic response to angiogenic treatment, have led to the development of several imaging methods for in vivo noninvasive assessment of angiogenesis. The combination of dynamic contrast-enhanced imaging with mathematical modeling of the contrast agent kinetics enables quantitative assessment of the structural and functional changes in the microvasculature that are associated with tumor angiogenesis. In this paper, we review quantitative imaging of angiogenesis with dynamic contrast-enhanced magnetic resonance imaging, computed tomography, and ultrasound.

Quantitative ultrasound molecular imaging by modeling the binding kinetics of targeted contrast agent

Ultrasound molecular imaging (USMI) is an emerging technique to monitor diseases at the molecular level by the use of novel targeted ultrasound contrast agents (tUCA). These consist of microbubbles functionalized with targeting ligands with high-affinity for molecular markers of specific disease processes, such as cancer-related angiogenesis. Among the molecular markers of angiogenesis, the vascular endothelial growth factor receptor 2 (VEGFR2) is recognized to play a major role. In response, the clinical-grade tUCA BR55 was recently developed, consisting of VEGFR2-targeting microbubbles which can flow through the entire circulation and accumulate where VEGFR2 is over-expressed, thus causing selective enhancement in areas of active angiogenesis. Discrimination between bound and free microbubbles is crucial to assess cancer angiogenesis. Currently, this is done non-quantitatively by looking at the late enhancement, about 10 min after injection, or by calculation of the differential targeted enhancement, requiring the application of a high-pressure ultrasound (US) burst to destroy all the microbubbles in the acoustic field and isolate the signal coming only from bound microbubbles. In this work, we propose a novel method based on mathematical modeling of the binding kinetics during the tUCA first pass, thus reducing the acquisition time and with no need for a destructive US burst. Fitting time-intensity curves measured with USMI by the proposed model enables the assessment of cancer angiogenesis at both the vascular and molecular levels. This is achieved by estimation of quantitative parameters related to the microvascular architecture and microbubble binding. The proposed method was tested in 11 prostate-tumor bearing rats by performing USMI after injection of BR55, and showed good agreement with current USMI methods. The novel information provided by the proposed method, possibly combined with the current non-quantitative methods, may bring deeper insight into cancer angiogenesis, and thus potentially improve cancer diagnosis and management.

Time-efficient estimation of the magnetic resonance dispersion model parameters for quantitative assessment of angiogenesis

The limitations of the available imaging modalities for prostate cancer (PCa) localization result in suboptimal protocols for management of the disease. In response, several dynamic contrast-enhanced imaging modalities have been developed, which aim at cancer detection through the assessment of the changes occurring in the tumor microenvironment due to angiogenesis. In this context, novel magnetic resonance dispersion imaging (MRDI) enables the estimation of parameters related to the microvascular architecture and leakage, by describing the contrast agent kinetics with a dispersion model. Although a preliminary validation of MRDI on PCa has shown promising results, parameter estimation can become burdensome due the convolution integral present in the dispersion model. To overcome this limitation, in this work we provide analytical solutions of the dispersion model in the time and frequency domains, and we implement three numerical methods to increase the time-efficiency of parameter estimation. The proposed solutions are tested for PCa localization. A reduction by about 50% of computation time could be obtained, without significant changes in the estimation performance and in the clinical results. With the continuous development of new technological solutions to boost the spatiotemporal resolution of DCE-MRI, solutions to improve the computational efficiency of parameter estimation are highly required.

Quantitative ultrasound molecular imaging for antiangiogenic therapy monitoring

The link between cancer growth and angiogenesis has led to the development of new techniques for cancer imaging and therapy. Ultrasound molecular imaging permits the visualization of angiogenesis by use of novel targeted ultrasound contrast agents, (tUCA), consisting of ligand-bearing microbubbles designed to specifically bind molecular angiogenic expressions. Discrimination between bound and free microbubbles is crucial to quantify angiogenesis. Currently, the degree of binding is assessed by the differential targeted enhancement, requiring the application of a destructive burst in the late phase (usually 5-10 min after injection) to isolate the signal from bound microbubbles. Recently, we proposed a novel method for quantitative assessment of binding by modeling the microbubble binding kinetics during the tUCA first pass, reducing the acquisition time to 1 min with no need for a destructive burst. The feasibility of the method for angiogenesis imaging was shown in prostate tumor-bearing rats. In this work, we evaluate the proposed method for monitoring the response to angiogenic treatment in human colon cancer xenograft-bearing mice.

Quantification of the binding kinetics of targeted ultrasound contrast agent for molecular imaging of cancer angiogenesis

Cancer growth requires angiogenesis; imaging of angiogenesis holds thus great potential for improved cancer detection and treatment. In this context, ultrasound molecular imaging permits the visualization of cancer angiogenesis by use of novel targeted contrast agents (tUCA). These consist of ligand-bearing microbubbles designed to specifically bind molecular angiogenic expressions, thus providing selective enhancement especially in the late phase after injection. Discrimination between bound and free microbubbles is crucial to assess the degree of binding and thus to quantify angiogenesis. Currently, binding is mainly assessed by the differential targeted enhancement, i.e., the difference in signal intensity in the late phase before and after the application of a high-pressure destructive pulse. However, this method is not quantitative, and it requires long acquisitions and a high-pressure pulse, which may damage the endothelial tissue. To overcome these limitations, here we propose a new method for quantification of the microbubble binding kinetics by fitting a dedicated compartmental model to the tUCA first-pass. We investigated the feasibility of the method in three prostate tumor-bearing rats. The novel information provided by the proposed method may be combined with the late enhancement analysis to gain deeper insight into tumor angionesis, and thus potentially improve cancer diagnosis and management.

On the validity of the first-pass binding model for quantitative ultrasound molecular imaging: Comparison between BR55 and Sonovue

Cancer growth requires angiogenesis; imaging of angiogenesis may thus improve cancer diagnostics and therapy monitoring. Dynamic contrast enhanced ultrasound (DCE-US) permits imaging angiogenesis at the molecular level by using novel targeted ultrasound contrast agents (tUCA). These agents consist of functionalized microbubbles obtained by engineering their shell with targeting ligands able to bind specific biomarkers, over-expressed in tumor angiogenic vasculature. Quantification of binding may thus provide an indirect way of quantifying angiogenesis. Recently, we proposed the first-pass binding (FPB) model to describe the binding kinetics of tUCA. Fitting DCE-US time-intensity curves (TICs) by the FPB model enables quantification of binding by the estimation of the binding rate Kb. After showing the feasibility of the method for angiogenesis imaging in prostate-tumor bearing rats, and performing a preliminary validation for anti-angiogenesis therapy monitoring in colon cancer-bearing mice, in this work we investigated the validity of the proposed model by comparing Kb estimates in rats injected with non-targeted UCAs (Sonovue) and tUCAs (BR55). Significantly lower values of Kb were found for Sonovue compared to BR55, with no significant difference between cancer and healthy prostate for Sonovue.

Effects of perfusion and vascular architecture on contrast dispersion: Validation in ex-vivo porcine liver under machine perfusion

Dynamic contrast enhanced ultrasound (DCE-US) enables imaging of cancer angiogenesis by quantification of perfusion and dispersion. Although increased perfusion may be found in areas of active angiogenesis due to increased demands for blood supply, decreased perfusion may be caused by the decreased efficiency and functionality, typical of cancer angiogenic microvasculature. Contrast dispersion, mainly determined by the flow profile in large vessels and by the multipath trajectories in the microvasculature, may thus represent a suitable alternative to characterize cancer angiogenesis. Based on a model of the contrast transport kinetics as a convective-dispersion process, several DCE-US methods have been proposed estimating dispersion for characterization of cancer angiogenic vasculature. Although dispersion imaging has shown promising in a clinical context, its physical link with variations in flow and vascular architecture has never been shown. The objective of this work is thus to investigate the influence of flow and underlying vascular architecture on the estimation of dispersion in an ex-vivo machine-perfused pig liver.

Closed-form solution of the convolution integral in the magnetic resonance dispersion model for quantitative assessment of angiogenesis

Prostate cancer (PCa) diagnosis and treatment is still limited due to the lack of reliable imaging methods for cancer localization. Based on the fundamental role played by angiogenesis in cancer growth and development, several dynamic contrast enhanced (DCE) imaging methods have been developed to probe tumor angiogenic vasculature. In DCE magnetic resonance imaging (MRI), pharmacokinetic modeling allows estimating quantitative parameters related to the physiology underlying tumor angiogenesis. In particular, novel magnetic resonance dispersion imaging (MRDI) enables quantitative assessment of the microvascular architecture and leakage, by describing the intravascular dispersion kinetics of an extravascular contrast agent with a dispersion model. According to this model, the tissue contrast concentration at each voxel is given by the convolution between the intravascular concentration, described as a Brownian motion process according to the convective-dispersion equation, with the interstitium impulse response, represented by a mono-exponential decay, and describing the contrast leakage in the extravascular space. In this work, an improved formulation of the MRDI method is obtained by providing an analytical solution for the convolution integral present in the dispersion model. The performance of the proposed method was evaluated by means of dedicated simulations in terms of estimation accuracy, precision, and computation time. Moreover, a preliminary clinical validation was carried out in five patients with proven PCa. The proposed method allows for a reduction by about 40% of computation time without any significant change in estimation accuracy and precision, and in the clinical performance.