Lack of functional normalisation of tumour vessels following anti-angiogenic therapy in glioblastoma.

Neo-angiogenesis represents an important factor for the delivery of oxygen and nutrients to a growing tumour, and is considered to be one of the main pathodiagnostic features of glioblastomas (GBM). Anti-angiogenic therapy by vascular endothelial growth factor (VEGF) blocking agents has been shown to lead to morphological vascular normalisation resulting in a reduction of contrast enhancement as seen by magnetic resonance imaging (MRI). Yet the functional consequences of this normalisation and its potential for improved delivery of cytotoxic agents to the tumour are not known. The presented study aimed at determining the early physiologic changes following bevacizumab treatment. A time series of perfusion MRI and hypoxia positron emission tomography (PET) scans were acquired during the first week of treatment, in two human GBM xenograft models treated with either high or low doses of bevacizumab. We show that vascular morphology was normalised over the time period investigated, but vascular function was not improved, resulting in poor tumoural blood flow and increased hypoxia.

EGFRvIII mutations can emerge as late and heterogenous events in glioblastoma development and promote angiogenesis through Src activation.

BACKGROUND: Amplification of the epidermal growth factor receptor (EGFR) and its mutant EGFRvIII are among the most common genetic alterations in glioblastoma (GBM), the most frequent and most aggressive primary brain tumor. METHODS: In the present work, we analyzed the clonal evolution of these major EGFR aberrations in a small cohort of GBM patients using a unique surgical multisampling technique. Furthermore, we overexpressed both receptors separately and together in 2 patient-derived GBM stem cell lines (GSCs) to analyze their functions in vivo in orthotopic xenograft models. RESULTS: In human GBM biopsies, we identified EGFR amplification as an early event because EGFRvIII mutations emerge from intratumoral heterogeneity later in tumor development. To investigate the biological relevance of this distinct developmental pattern, we established experimental model systems. In these models, EGFR+ tumor cells showed activation of classical downstream signaling pathways upon EGF stimulation and displayed enhanced invasive growth without evidence of angiogenesis in vivo. In contrast, EGFRvIII+ tumors were driven by activation of the prototypical Src family kinase c-Src that promoted VEGF secretion leading to angiogenic tumor growth. CONCLUSIONS: The presented work shows that sequential EGFR amplification and EGFRvIII mutations might represent concerted evolutionary events that drive the aggressive nature of GBM by promoting invasion and angiogenesis via distinct signaling pathways. In particular, c-SRC may be an attractive therapeutic target for tumors harboring EGFRvIII as we identified this protein specifically mediating angiogenic tumor growth downstream of EGFRvIII.

Distributed capillary adiabatic tissue homogeneity model in parametric multi-channel blind AIF estimation using DCE-MRI.

PURPOSE: One of the main challenges in quantitative dynamic contrast-enhanced (DCE) MRI is estimation of the arterial input function (AIF). Usually, the signal from a single artery (ignoring contrast dispersion, partial volume effects and flow artifacts) or a population average of such signals (also ignoring variability between patients) is used. METHODS: Multi-channel blind deconvolution is an alternative approach avoiding most of these problems. The AIF is estimated directly from the measured tracer concentration curves in several tissues. This contribution extends the published methods of multi-channel blind deconvolution by applying a more realistic model of the impulse residue function, the distributed capillary adiabatic tissue homogeneity model (DCATH). In addition, an alternative AIF model is used and several AIF-scaling methods are tested. RESULTS: The proposed method is evaluated on synthetic data with respect to the number of tissue regions and to the signal-to-noise ratio. Evaluation on clinical data (renal cell carcinoma patients before and after the beginning of the treatment) gave consistent results. An initial evaluation on clinical data indicates more reliable and less noise sensitive perfusion parameter estimates. CONCLUSION: Blind multi-channel deconvolution using the DCATH model might be a method of choice for AIF estimation in a clinical setup.

Multimodal imaging of gliomas in the context of evolving cellular and molecular therapies.

The vast majority of malignant gliomas relapse after surgery and standard radio-chemotherapy. Novel molecular and cellular therapies are thus being developed, targeting specific aspects of tumor growth. While histopathology remains the gold standard for tumor classification, neuroimaging has over the years taken a central role in the diagnosis and treatment follow up of brain tumors. It is used to detect and localize lesions, define the target area for biopsies, plan surgical and radiation interventions and assess tumor progression and treatment outcome. In recent years the application of novel drugs including anti-angiogenic agents that affect the tumor vasculature, has drastically modulated the outcome of brain tumor imaging. To properly evaluate the effects of emerging experimental therapies and successfully support treatment decisions, neuroimaging will have to evolve. Multi-modal imaging systems with existing and new contrast agents, molecular tracers, technological advances and advanced data analysis can all contribute to the establishment of disease relevant biomarkers that will improve disease management and patient care. In this review, we address the challenges of glioma imaging in the context of novel molecular and cellular therapies, and take a prospective look at emerging experimental and pre-clinical imaging techniques that bear the promise of meeting these challenges.

The precision of DCE-MRI using the tissue homogeneity model with continuous formulation of the perfusion parameters.

The present trend in dynamic contrast-enhanced MRI is to increase the number of estimated perfusion parameters using complex pharmacokinetic models. However, less attention is given to the precision analysis of the parameter estimates. In this paper, the distributed capillary adiabatic tissue homogeneity pharmacokinetic model is extended by the bolus arrival time formulated as a free continuous parameter. With the continuous formulation of all perfusion parameters, it is possible to use standard gradient-based optimization algorithms in the approximation of the tissue concentration time sequences. This new six-parameter model is investigated by comparing Monte-Carlo simulations with theoretically derived covariance matrices. The covariance-matrix approach is extended from the usual analysis of the primary perfusion parameters of the pharmacokinetic model to the analysis of the perfusion parameters derived from the primary ones. The results indicate that the precision of the estimated perfusion parameters can be described by the covariance matrix for signal-to-noise ratio higher than~20dB. The application of the new analysis model on a real DCE-MRI data set is also presented.

Blind deconvolution in dynamic contrast-enhanced MRI and ultrasound.

This paper is focused on quantitative perfusion analysis using MRI and ultrasound. In both MRI and ultrasound, most approaches allow estimation of rate constants (Ktrans, kep for MRI) and indices (AUC, TTP) that are only related to the physiological perfusion parameters of a tissue (e.g. blood flow, vessel permeability) but do not allow their absolute quantification. Recent methods for quantification of these physiological perfusion parameters are shortly reviewed. The main problem of these methods is estimation of the arterial input function (AIF). This paper summarizes and extends the current blind-deconvolution approaches to AIF estimation. The feasibility of these methods is shown on a small preclinical study using both MRI and ultrasound.

Dynamic contrast-enhanced MRI in endometrial carcinoma identifies patients at increased risk of recurrence.

OBJECTIVES: To study the feasibility of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for assessment of tumour microvasculature in endometrial carcinoma patients, and to explore correlations with histological subtype, clinical course and microstructural characteristics based on apparent diffusion coefficient (ADC) values. METHODS: Diffusion-weighted imaging (DWI) and three-dimensional DCE-MRI (1.5 T) with high temporal resolution (2.49 s) were acquired preoperatively in 55 patients. Quantitative modelling allowed the calculation of four independent parameters describing microvasculature: blood flow (Fb), extraction fraction (E), capillary transit time (Tc) and transfer constant from the extravascular extracellular space [EES] to blood (Kep); and four derived parameters: blood volume (Vb), volume of EES (Ve), capillary permeability surface area product (PS) and transfer from blood to EES (Ktrans). RESULTS: Endometrial carcinoma tissue exhibited reduced Fb, E, Vb, Ve, PS and Ktrans compared with normal myometrium. Non-endometrioid carcinomas (n = 12) had lower Fb, and E than endometrioid carcinomas (n = 43; P < 0.05). Tumour Ve positively correlated with tumour ADC value (r = 0.29, P = 0.03). Reduced survival was observed in patients with low tumour Fb and high tumour Tc (P < 0.05). CONCLUSIONS: We demonstrate the feasibility of DCE-MRI in reflecting histological subtype and clinical course in primary endometrial carcinomas. DCE-MRI may potentially provide future biomarkers for preoperative risk stratification in endometrial carcinomas. KEY POINTS: • Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) offers new information about endometrial carcinoma. • Pelvic DCE-MRI with subsequent quantitative modelling seems feasible in endometrial carcinoma patients. • Low tumour perfusion is a feature of a more aggressive tumour subtype. • DCE-MRI provides potential biomarkers for preoperative risk stratification in endometrial carcinoma patients.

Quantitative contrast-enhanced ultrasound comparison between inflammatory and fibrotic lesions in patients with Crohn's disease.

The aim of this study was to determine whether there are differences in absolute blood flow between patients with Crohn's disease with inflammation or fibrosis using contrast-enhanced ultrasound. Eighteen patients with fibrotic disease and 19 patients with inflammation were examined. Video sequences of contrast data were analyzed using a pharmacokinetic model to extract the arterial input and tissue residue functions with a custom software, enabling calculation of the absolute values for mean transit time, blood volume and flow. Feasibility of the examination was 89%. The fibrosis group had lower blood volume (0.9 vs. 3.4 mL per 100 mL tissue; p = 0.001) and flow (22.6 vs. 45.3 mL/min per 100 mL tissue; p = 0.003) compared with the inflammation group. There was no significant difference in mean transit time (3.9 vs. 5.5 s). In conclusion, absolute perfusion measurement in the gastrointestinal wall using contrast-enhanced ultrasound is feasible. There seems to be reduced blood volume and blood flow in patients with fibrotic disease.

Ultrasound perfusion analysis combining bolus-tracking and burst-replenishment.

A new signal model and processing method for quantitative ultrasound perfusion analysis is presented, called bolus-and-burst. The method has the potential to provide absolute values of blood flow, blood volume, and mean transit time. Furthermore, it provides an estimate of the local arterial input function which characterizes the arterial tree, allowing accurate estimation of the bolus arrival time. The method combines two approaches to ultrasound perfusion analysis: bolus-tracking and burst-replenishment. A pharmacokinetic model based on the concept of arterial input functions and tissue residue functions is used to model both the bolus and replenishment parts of the recording. The pharmacokinetic model is fitted to the data using blind deconvolution. A preliminary assessment of the new perfusion-analysis method is presented on clinical recordings.

Anti-VEGF treatment reduces blood supply and increases tumor cell invasion in glioblastoma.

Bevacizumab, an antibody against vascular endothelial growth factor (VEGF), is a promising, yet controversial, drug in human glioblastoma treatment (GBM). Its effects on tumor burden, recurrence, and vascular physiology are unclear. We therefore determined the tumor response to bevacizumab at the phenotypic, physiological, and molecular level in a clinically relevant intracranial GBM xenograft model derived from patient tumor spheroids. Using anatomical and physiological magnetic resonance imaging (MRI), we show that bevacizumab causes a strong decrease in contrast enhancement while having only a marginal effect on tumor growth. Interestingly, dynamic contrast-enhanced MRI revealed a significant reduction of the vascular supply, as evidenced by a decrease in intratumoral blood flow and volume and, at the morphological level, by a strong reduction of large- and medium-sized blood vessels. Electron microscopy revealed fewer mitochondria in the treated tumor cells. Importantly, this was accompanied by a 68% increase in infiltrating tumor cells in the brain parenchyma. At the molecular level we observed an increase in lactate and alanine metabolites, together with an induction of hypoxia-inducible factor 1α and an activation of the phosphatidyl-inositol-3-kinase pathway. These data strongly suggest that vascular remodeling induced by anti-VEGF treatment leads to a more hypoxic tumor microenvironment. This favors a metabolic change in the tumor cells toward glycolysis, which leads to enhanced tumor cell invasion into the normal brain. The present work underlines the need to combine anti-angiogenic treatment in GBMs with drugs targeting specific signaling or metabolic pathways linked to the glycolytic phenotype.

Multispectral analysis of multimodal images.

INTRODUCTION: An increasing number of multimodal images represent a valuable increase in available image information, but at the same time it complicates the extraction of diagnostic information across the images. Multispectral analysis (MSA) has the potential to simplify this problem substantially as unlimited number of images can be combined, and tissue properties across the images can be extracted automatically. MATERIALS AND METHODS: We have developed a software solution for MSA containing two algorithms for unsupervised classification, an EM-algorithm finding multinormal class descriptions and the k-means clustering algorithm, and two for supervised classification, a Bayesian classifier using multinormal class descriptions and a kNN-algorithm. The software has an efficient user interface for the creation and manipulation of class descriptions, and it has proper tools for displaying the results. RESULTS: The software has been tested on different sets of images. One application is to segment cross-sectional images of brain tissue (T1- and T2-weighted MR images) into its main normal tissues and brain tumors. Another interesting set of images are the perfusion maps and diffusion maps, derived images from raw MR images. The software returns segmentations that seem to be sensible. DISCUSSION: The MSA software appears to be a valuable tool for image analysis with multimodal images at hand. It readily gives a segmentation of image volumes that visually seems to be sensible. However, to really learn how to use MSA, it will be necessary to gain more insight into what tissues the different segments contain, and the upcoming work will therefore be focused on examining the tissues through for example histological sections.

Pancreatic lipomatosis is a structural marker in nondiabetic children with mutations in carboxyl-ester lipase.

Both pancreatic volume reduction and lipomatosis have been observed in subjects with diabetes. The underlying molecular and pathological mechanisms are, however, poorly known, and it has been speculated that both features are secondary to diabetes. We have recently described pancreatic atrophy and lipomatosis in diabetic subjects of two Norwegian families with a novel syndrome of diabetes and exocrine pancreatic dysfunction caused by heterozygous carboxyl-ester lipase (CEL) mutations. To explore the early pathological events in this syndrome, we performed radiological examinations of the pancreas in nondiabetic mutation carriers with signs of exocrine dysfunction. In a case series study at a tertiary hospital, we evaluated 11 nondiabetic and mutation-positive children with fecal elastase deficiency and 11 age- and sex-matched control subjects using ultrasound and magnetic resonance imaging (MRI) to estimate pancreatic fat content. The pancreata of nondiabetic mutation carriers exhibited increased reflectivity on ultrasound and had MRI findings indicative of lipomatosis. Apparently, carriers of heterozygous CEL mutations accumulate fat in their pancreas before the anticipated development of diabetes. Our findings suggest that lipomatosis of the pancreas reflects early events involved in the pathogenesis of diabetes and exocrine pancreatic dysfunction syndrome.

Iterative blind deconvolution in magnetic resonance brain perfusion imaging.

In first pass magnetic resonance brain perfusion imaging, arterial input functions are used in the deconvolution of the observed contrast concentrations to obtain quantitative hemodynamic parameters. Ideally, arterial input functions should be measured in each imaged voxel to eliminate the effects of delay and dispersion of the contrast agent from the injection site. An approach based on iterative blind deconvolution with the Richardson-Lucy algorithm is proposed for the simultaneous estimation of voxel-specific arterial input functions and voxel-specific tissue residue functions. An extended contrast concentration model was used to separate the first pass bolus from additional recirculation and leakage signals. The extended model was evaluated using in vivo data. Computer simulations examined the feasibility of iterative blind deconvolution in perfusion imaging. Preliminary in vivo results from a patient with fibromuscular dysplasia showed territories with delayed/dispersed arterial input functions that coincided with the location of territories supplied by collateral circulation as described from the complete radiologic examination. Higher flow values and shorter mean transit times compared to conventional methods were obtained in these areas, suggesting that the effects of dispersion were minimized. The in vivo estimated arterial input functions visualized the patient's blood supply patterns as a function of time.