High-resolution 3D visualization of nanomedicine distribution in tumors.

To improve the clinical translation of anti-cancer nanomedicines, it is necessary to begin building specific insights into the broad concept of the Enhanced Permeability and Retention (EPR) effect, using detailed investigations of the accumulation, distribution and retention of nanomedicines in solid tumors. Nanomedicine accumulation in preclinical tumors has been extensively studied; however, treatment efficacy will be heavily influenced by both the quantity of drug-loaded nanomedicines reaching the tumor as well as their spatial distribution throughout the tumor. It remains a challenge to image the heterogeneity of nanomedicine distribution in 3 dimensions within solid tumors with a high degree of spatial resolution using standard imaging approaches. Methods: To achieve this, an ex vivo micro computed tomography (µCT) imaging approach was developed to visualize the intratumoral distribution of contrast agent-loaded PEGylated liposomes. Using this semi-quantitative method, whole 3-dimensional (3D) tumor liposome distribution was determined with 17 µm resolution in a phenotypically diverse panel of four preclinical xenograft and patient-derived explant (PDX) tumor models. Results: High-resolution ex vivo µCT imaging revealed striking differences in liposome distribution within tumors in four models with different vascular patterns and densities, stromal contents, and microenvironment morphologies. Following intravenous dosing, the model with the highest density of pericyte-supported vessels showed the greatest liposome accumulation, while the model with vessels present in regions of high α-smooth muscle actin (αSMA) content presented with a large proportion of the liposomes at depths beyond the tumor periphery. The two models with an unsupported vascular network demonstrated a more restricted pattern of liposome distribution. Conclusion: Taken together, vessel distribution and support (the latter indicative of functionality) appear to be key factors determining the accumulation and distribution pattern of liposomes in tumors. Our findings demonstrate that high-resolution 3D visualization of nanomedicine distribution is a useful tool for preclinical nanomedicine research, providing valuable insights into the influence of the tumor vasculature and microenvironment on nanomedicine localization.

Evaluation of dynamic contrast-enhanced MRI biomarkers for stratified cancer medicine: How do permeability and perfusion vary between human tumours?

BACKGROUND: Solid tumours exhibit enhanced vessel permeability and fenestrated endothelium to varying degree, but it is unknown how this varies in patients between and within tumour types. Dynamic contrast-enhanced (DCE) MRI provides a measure of perfusion and permeability, the transfer constant Ktrans, which could be employed for such comparisons in patients. AIM: To test the hypothesis that different tumour types exhibit systematically different Ktrans. MATERIALS AND METHODS: DCE-MRI data were retrieved from 342 solid tumours in 230 patients. These data were from 18 previous studies, each of which had had a different analysis protocol. All data were reanalysed using a standardised workflow using an extended Tofts model. A model of the posterior density of median Ktrans was built assuming a log-normal distribution and fitting a simple Bayesian hierarchical model. RESULTS: 12 histological tumour types were included. In glioma, median Ktrans was 0.016min-1 and for non-glioma tumours, median Ktrans ranged from 0.10 (cervical) to 0.21min-1 (prostate metastatic to bone). The geometric mean (95% CI) across all the non-glioma tumours was 0.15 (0.05, 0.45)min-1. There was insufficient separation between the posterior densities to be able to predict the Ktrans value of a tumour given the tumour type, except that the median Ktrans for gliomas was below 0.05min-1 with 80% probability, and median Ktrans measurements for the remaining tumour types were between 0.05 and 0.4min-1 with 80% probability. CONCLUSION: With the exception of glioma, our hypothesis that different tumour types exhibit different Ktrans was not supported. Studies in which tumour permeability is believed to affect outcome should not simply seek tumour types thought to exhibit high permeability. Instead, Ktrans is an idiopathic parameter, and, where permeability is important, Ktrans should be measured in each tumour to personalise that treatment.

The use of 18F-Fluoro-deoxy-glucose positron emission tomography (18F-FDG PET) as a non-invasive pharmacodynamic biomarker to determine the minimally pharmacologically active dose of AZD8835, a novel PI3Kα inhibitor.

BACKGROUND: The phosphatidyl inositol 3 kinase (PI3K), AKT and mammalian target of rapamycin (mTOR) signal transduction pathway is frequently de-regulated and activated in human cancer and is an important therapeutic target. AZD8835 is a PI3K inhibitor, with selectivity against PI3K α and δ isoforms, which is currently in Phase 1 clinical trials. 18F-Fluoro-deoxy-glucose positron emission tomography (18F-FDG PET) is a non-invasive pharmacodynamic imaging biomarker that has become an integral part of drug development. It has been used widely with PI3K inhibitors both clinically and pre-clinically because of the role of the PI3K pathway in glucose metabolism. In this study we investigated the potential of 18F-FDG PET as a non-invasive pharmacodynamic biomarker for AZD8835. We sought to understand if 18F-FDG PET could determine the minimally effective dose of AZD8835 and correlate with other pharmacodynamic biomarkers for validation of its use in clinical development. 18F-FDG PET scans were performed in nude mice in the BT474C breast xenograft model. Mice were fasted prior to imaging and static 18F-FDG PET was performed. Treatment groups received AZD8835 by oral gavage at a dose volume of 10ml/kg. Treatment groups received either 3, 6, 12.5, 25 or 50mg/kg AZD8835. Tumour growth was monitored throughout the study, and at the end of the imaging procedure, tumours were taken and a full pharmacodynamic analysis was performed. RESULTS: Results showed that AZD8835 reduced 18F-FDG uptake at a dose of 12.5, 25 and 50mg/kg with no significant reduction at doses of 3 and 6mg/kg. These results were consistent with other pharmacodynamics biomarkers measured and show 18F-FDG PET as a sensitive biomarker with the ability to determine the minimal effective dose of AZD8835. CONCLUSIONS: Our pre-clinical studies support the use of 18F-FDG PET imaging as a sensitive and non- invasive pharmacodynamic biomarker (understanding the role of PI3K signalling in glucose uptake) for AZD8835 with a decrease in 18F-FDG uptake observed at only two hours post treatment. The decrease in 18F-FDG uptake was dose dependent and data showed excellent PK/PD correlation. This data supports and parallels observations obtained with this class of compounds in patients.

The use of (18)F-fluorodeoxyglucose positron emission tomography ((18)F-FDG PET) as a pathway-specific biomarker with AZD8186, a PI3Kß/δ inhibitor.

BACKGROUND: The phosphatidylinositol 3 kinase (PI3K) signalling pathway is frequently altered in human cancer and a promising therapeutic target. AZD8186 (AstraZeneca) is a PI3Kß/δ inhibitor, currently in phase 1 clinical trials. (18)F-fluorodeoxyglucose positron emission tomography ((18)F-FDG PET) is often used as a biomarker for inhibitors targeting the PI3K axis because of the association of this pathway with glucose metabolism. In this study, we assessed if (18)F-FDG PET could be used as a pharmacodynamic marker to monitor PI3Kß inhibition by AZD8186, and hence have potential as a clinical biomarker of PI3Kß pathway activation, and for patient selection. (18)F-FDG PET scans were performed in nude mice bearing 786-0 renal, U87-MG glioma, and BT474C breast xenograft models. Mice were fasted prior to imaging and static (18)F-FDG PET imaging was performed. Tumour growth was monitored throughout each study, and at the end of the imaging procedure, tumours were taken and a full pharmacodynamic analysis performed. RESULTS: Results showed that in PTEN null tumour xenograft models, 786-0 and U87-MG, the PI3Kß inhibitor AZD8186 reduces (18)F-FDG uptake at a dose of 50 mg/kg, the same dose which causes tumour inhibition, while it has no impact in a PI3Kα mutant tumour xenograft BT474C. Consistent with the change in (18)F-FDG uptake, AZD8186 also modulated AKT and associated glucose pathway biomarkers in the PTEN null tumour xenografts but not in PTEN wild-type tumours. CONCLUSIONS: Our pre-clinical studies support the use of (18)F-FDG PET imaging as a sensitive and non-invasive pharmacodynamic biomarker for use in clinical studies with AZD8186.

The Synergistic Effect of Selumetinib/Docetaxel Combination Therapy Monitored by [(18)F]FDG/[(18)F]FLT PET and Diffusion-Weighted Magnetic Resonance Imaging in a Colorectal Tumor Xenograft Model.

PURPOSE: Positron emission tomography (PET) and diffusion-weighted MRI (DW-MRI) were used to characterize the treatment effects of the MEK1/2 inhibitor selumetinib (AZD6244), docetaxel, and their combination in HCT116 tumor-bearing mice on the molecular level. PROCEDURES: Mice were treated with vehicle, selumetinib (25 mg/kg), docetaxel (15 mg/kg), or a combination of both drugs for 7 days and imaged at four time points with 2-deoxy-2-[(18)F]fluoro-D-glucose ([(18)F]FDG) or 3'-deoxy-3'-[(18)F]fluorothymidine ([(18)F]FLT) followed by DW-MRI to calculate the apparent diffusion coefficient (ADC). Data was cross-validated using the Pearson correlation coefficient (PCC) and compared to histology (IHC). RESULTS: Each drug led to tumor growth inhibition but their combination resulted in regression. Separate analysis of PET or ADC could not provide significant differences between groups. Only PCC combined with IHC analysis revealed the highest therapeutic impact for combination therapy. CONCLUSION: Combination treatment of selumetinib/docetaxel was superior to the respective mono-therapies shown by PCC of PET and ADC in conjunction with histology.

Quantitative correlation at the molecular level of tumor response to docetaxel by multimodal diffusion-weighted magnetic resonance imaging and [¹8F]FDG/[¹8F]FLT positron emission tomography.

We aimed to quantitatively characterize the treatment effects of docetaxel in the HCT116 xenograft mouse model, applying diffusion-weighted magnetic resonance imaging (MRI) and positron emission tomography (PET) using 2-deoxy-2-[¹8F]fluoro-d-glucose ([¹8F]FDG) and 3'-deoxy-3'-[¹8F]-fluorothymidine ([¹8F]FLT). Mice were imaged at four time points over 8 days. Docetaxel (15 mg/kg) was administered after a baseline scan. Voxel-wise scatterplots of PET and apparent diffusion coefficient (ADC) data of tumor volumes were evaluated with a threshold cluster analysis and compared to histology (GLUT1, GLUT3, Ki67, activated caspase 3a). Compared to the extensive tumor growth observed in the vehicle-treated group (from 0.32 ± 0.21 cm³ to 0.69 ± 0.40 cm³), the administration of docetaxel led to tumor growth stasis (from 0.32 ± 0.20 cm³ to 0.45 ± 0.23 cm³). The [¹8F]FDG/ADC cluster analysis and the evaluation of peak histogram values revealed a significant treatment effect matching histology as opposed to [¹8F]FLT/ADC. [¹8F]FLT uptake and the Ki67 index were not in good agreement. Our voxel-based cluster analysis uncovered treatment effects not seen in the separate inspection of PET and MRI data and may be used as an independent analysis tool. [¹8F]FLT/ADC cluster analysis could still point out the treatment effect; however, [¹8F]FDG/ADC reflected the histology findings in higher agreement.

Noninvasive tumor hypoxia measurement using magnetic resonance imaging in murine U87 glioma xenografts and in patients with glioblastoma.

PURPOSE: There is a clinical need for noninvasive, nonionizing imaging biomarkers of tumor hypoxia and oxygenation. We evaluated the relationship of T1 -weighted oxygen-enhanced magnetic resonance imaging (OE-MRI) measurements to histopathology measurements of tumor hypoxia in a murine glioma xenograft and demonstrated technique translation in human glioblastoma multiforme. METHODS: Preclinical evaluation was performed in a subcutaneous murine human glioma xenograft (U87MG). Animals underwent OE-MRI followed by dynamic contrast-enhanced MRI (DCE-MRI) and histological measurement including reduced pimonidazole adducts and CD31 staining. Area under the curve (AUC) was measured for the R1 curve for OE-MRI and the gadolinium concentration curve for DCE-MRI. Clinical evaluation in five patients used analogous imaging protocols and analyses. RESULTS: Changes in AUC of OE-MRI (AUCOE ) signal were regionally heterogeneous across all U87MG tumors. Tumor regions with negative AUCOE typically had low DCE-MRI perfusion, had positive correlation with hypoxic area (P = 0.029), and had negative correlation with vessel density (P = 0.004). DCE-MRI measurements did not relate to either hypoxia or vessel density in U87MG tumors. Clinical data confirmed comparable signal changes in patients with glioblastoma. CONCLUSION: These data support further investigation of T1 -weighted OE-MRI to identify regional tumor hypoxia. The quantification of AUCOE has translational potential as a clinical biomarker of hypoxia.

Longitudinal regional brain volume changes quantified in normal aging and Alzheimer's APP x PS1 mice using MRI.

In humans, mutations of amyloid precursor protein (APP) and presenilins (PS) 1 and 2 are associated with amyloid deposition, brain structural change and cognitive decline, like in Alzheimer's disease (AD). Mice expressing these proteins have illuminated neurodegenerative disease processes but, unlike in humans, quantitative imaging has been little used to systematically determine their effects, or those of normal aging, on brain structure in vivo. Accordingly, we investigated wildtype (WT) and TASTPM mice (expressing human APP(695(K595N, M596L)) x PS1(M146V)) longitudinally using MRI. Automated global and local image registration, allied to a standard digital atlas, provided pairwise segmentation of 13 brain regions. We found the mature mouse brain, unlike in humans, enlarges significantly from 6-14 months old (WT 3.8+/-1.7%, mean+/-SD, P<0.0001). Significant changes were also seen in other WT brain regions, providing an anatomical benchmark for comparing other mouse strains and models of brain disorder. In TASTPM, progressive amyloidosis and astrogliosis, detected immunohistochemically, reflected even larger whole brain changes (5.1+/-1.4%, P<0.0001, transgenexage interaction P=0.0311). Normalising regional volumes to whole brain measurements revealed significant, prolonged, WT-TASTPM volume differences, suggesting transgene effects establish at <6 months old of age in most regions. As in humans, gray matter-rich regions decline with age (e.g. thalamus, cerebral cortex and caudoputamen); ventricles and white matter (corpus callosum, corticospinal tract, fornix system) increase; in TASTPMs such trends often varied significantly from WT (especially hippocampus). The pervasive, age-related structural changes between WT and AD transgenic mice (and mouse and human) suggest subtle but fundamental species differences and AD transgene effects.

Analysis of serial magnetic resonance images of mouse brains using image registration.

The aim of this paper is to investigate techniques that can identify and quantify cross-sectional differences and longitudinal changes in vivo from magnetic resonance images of murine models of brain disease. Two different approaches have been compared. The first approach is a segmentation-based approach: Each subject at each time point is automatically segmented into a number of anatomical structures using atlas-based segmentation. This allows cross-sectional and longitudinal analyses of group differences on a structure-by-structure basis. The second approach is a deformation-based approach: Longitudinal changes are quantified by the registration of each subject's follow-up images to that subject's baseline image. In addition the baseline images can be registered to an atlas allowing voxel-wise analysis of cross-sectional differences between groups. Both approaches have been tested on two groups of mice: A transgenic model of Alzheimer's disease and a wild-type background strain, using serial imaging performed over the age range from 6-14 months. We show that both approaches are able to identify longitudinal and cross-sectional differences. However, atlas-based segmentation suffers from the inability to detect differences across populations and across time in regions which are much smaller than the anatomical regions. In contrast to this, the deformation-based approach can detect statistically significant differences in highly localized areas.

Pharmacological fMRI--challenges in analysing drug-induced single-event BOLD responses.

The interest in BOLD contrast based phMRI is likely to increase in the coming years, but detecting a direct modulation of regional brain activity by drugs presents a challenging problem. Based on in-vivo MRI and simulations we highlight some of the issues in detecting especially small BOLD signals in rat phMRI experiments.

Wavelet-based cluster analysis: data-driven grouping of voxel time courses with application to perfusion-weighted and pharmacological MRI of the rat brain.

MRI time series experiments produce a wealth of information contained in two or three spatial dimensions that evolve over time. Such experiments can, for example, localize brain response to pharmacological stimuli, but frequently the spatiotemporal characteristics of the cerebral response are unknown a priori and variable, and thus difficult to evaluate using hypothesis-based methods alone. Here we used features in the temporal dimension to group voxels with similar time courses based on a nonparametric discrete wavelet transform (DWT) representation of each time course. Applying the DWT to each voxel decomposes its temporal information into coefficients associated with both time and scale. Discarding scales in the DWT that are associated with high-frequency oscillations (noise) provided a straight-forward data reduction step and decreased the computational burden. Optimization-based clustering was then applied to the remaining wavelet coefficients in order to produce a finite number of voxel clusters. This wavelet-based cluster analysis (WCA) was evaluated using two representative classes of MRI neuroimaging experiments. In perfusion-weighted MRI, following occlusion of the middle cerebral artery (MCAO), WCA differentiated healthy tissue and different regions within the ischemic hemisphere. Following an acute cocaine challenge, WCA localized subtle differences in the pharmacokinetic profile of the cerebral response. We conclude that WCA provides a robust method for blind analysis of time series image data.