Introduction to the National Cancer Imaging Translational Accelerator (NCITA): a UK-wide infrastructure for multicentre clinical translation of cancer imaging biomarkers.

The National Cancer Imaging Translational Accelerator (NCITA) is creating a UK national coordinated infrastructure for accelerated translation of imaging biomarkers for clinical use. Through the development of standardised protocols, data integration tools and ongoing training programmes, NCITA provides a unique scalable infrastructure for imaging biomarker qualification using multicentre clinical studies.

A reformulation of pLSA for uncertainty estimation and hypothesis testing in bio-imaging.

MOTIVATION: Probabilistic latent semantic analysis (pLSA) is commonly applied to describe mass spectra (MS) images. However, the method does not provide certain outputs necessary for the quantitative scientific interpretation of data. In particular, it lacks assessment of statistical uncertainty and the ability to perform hypothesis testing. We show how linear Poisson modelling advances pLSA, giving covariances on model parameters and supporting χ2 testing for the presence/absence of MS signal components. As an example, this is useful for the identification of pathology in MALDI biological samples. We also show potential wider applicability, beyond MS, using magnetic resonance imaging (MRI) data from colorectal xenograft models. RESULTS: Simulations and MALDI spectra of a stroke-damaged rat brain show MS signals from pathological tissue can be quantified. MRI diffusion data of control and radiotherapy-treated tumours further show high sensitivity hypothesis testing for treatment effects. Successful χ2 and degrees-of-freedom are computed, allowing null-hypothesis thresholding at high levels of confidence. AVAILABILITY AND IMPLEMENTATION: Open-source image analysis software available from TINA Vision, www.tina-vision.net. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A new method for the high-precision assessment of tumor changes in response to treatment.

Motivation: Imaging demonstrates that preclinical and human tumors are heterogeneous, i.e. a single tumor can exhibit multiple regions that behave differently during both development and also in response to treatment. The large variations observed in control group, tumors can obscure detection of significant therapeutic effects due to the ambiguity in attributing causes of change. This can hinder development of effective therapies due to limitations in experimental design rather than due to therapeutic failure. An improved method to model biological variation and heterogeneity in imaging signals is described. Specifically, linear Poisson modeling (LPM) evaluates changes in apparent diffusion co-efficient between baseline and 72 h after radiotherapy, in two xenograft models of colorectal cancer. The statistical significance of measured changes is compared to those attainable using a conventional t-test analysis on basic apparent diffusion co-efficient distribution parameters. Results: When LPMs were applied to treated tumors, the LPMs detected highly significant changes. The analyses were significant for all tumors, equating to a gain in power of 4-fold (i.e. equivalent to having a sample size 16 times larger), compared with the conventional approach. In contrast, highly significant changes are only detected at a cohort level using t-tests, restricting their potential use within personalized medicine and increasing the number of animals required during testing. Furthermore, LPM enabled the relative volumes of responding and non-responding tissue to be estimated for each xenograft model. Leave-one-out analysis of the treated xenografts provided quality control and identified potential outliers, raising confidence in LPM data at clinically relevant sample sizes. Availability and implementation: TINA Vision open source software is available from www.tina-vision.net. Supplementary information: Supplementary data are available at Bioinformatics online.

Assessment of circulating biomarkers for potential pharmacodynamic utility in patients with lymphoma.

PURPOSE: Treatment efficacy and toxicity are difficult to predict in lymphoma patients. In this study, the utility of circulating biomarkers in predicting and/or monitoring treatment efficacy/toxicity were investigated. PATIENTS AND METHODS: Circulating biomarkers of cell death (nucleosomal DNA (nDNA) and cytokeratin 18 (CK18)), and circulating FLT3 ligand, a potential biomarker of myelosuppression, were assessed before and serially after standard chemotherapy in 49 patients with Hodgkin and non-Hodgkin lymphoma. Cytokeratin 18 is not expressed in lymphoma cells so is a potential biomarker of epithelial toxicity in this setting. Tumour response was assessed before and after completion of chemotherapy by 2D and 3D computed tomography radiological response. RESULTS: Baseline nDNA level was significantly higher in all lymphoma subtypes compared with 61 healthy controls and was prognostic for progression-free survival in diffuse large B-cell lymphoma (DLBCL). Decreases in nDNA levels were observed in the first week after chemotherapy; in FL, early falls in nDNA predicted for long remission following therapy. In DLBCL, elevations in nDNA occurred in cases with progressive disease. Circulating CK18 increased within 48 h of chemotherapy and was significantly higher in patients experiencing epithelial toxicity graded >3 by Common Terminology for Classification of Adverse Events criteria. FLT3 ligand was elevated within 3-8 days of chemotherapy initiation and predicted those patients who subsequently developed neutropenic sepsis. CONCLUSION: These data suggest circulating biomarkers contribute useful information regarding tumour response and toxicity in patients receiving standard chemotherapy and have potential utility in the development of individualised treatment approaches in lymphoma. These biomarkers are now being tested within multicentre phase III trials to progress their qualification.

DCE-MRI biomarkers of tumour heterogeneity predict CRC liver metastasis shrinkage following bevacizumab and FOLFOX-6.

BACKGROUND: There is limited evidence that imaging biomarkers can predict subsequent response to therapy. Such prognostic and/or predictive biomarkers would facilitate development of personalised medicine. We hypothesised that pre-treatment measurement of the heterogeneity of tumour vascular enhancement could predict clinical outcome following combination anti-angiogenic and cytotoxic chemotherapy in colorectal cancer (CRC) liver metastases. METHODS: Ten patients with 26 CRC liver metastases had two dynamic contrast-enhanced MRI (DCE-MRI) examinations before starting first-line bevacizumab and FOLFOX-6. Pre-treatment biomarkers of tumour microvasculature were computed and a regression analysis was performed against the post-treatment change in tumour volume after five cycles of therapy. The ability of the resulting linear model to predict tumour shrinkage was evaluated using leave-one-out validation. Robustness to inter-visit variation was investigated using data from a second baseline scan. RESULTS: In all, 86% of the variance in post-treatment tumour shrinkage was explained by the median extravascular extracellular volume (v(e)), tumour enhancing fraction (E(F)), and microvascular uniformity (assessed with the fractal measure box dimension, d(0)) (R(2)=0.86, P<0.00005). Other variables, including baseline volume were not statistically significant. Median prediction error was 12%. Equivalent results were obtained from the second scan. CONCLUSION: Traditional image analyses may over-simplify tumour biology. Measuring microvascular heterogeneity may yield important prognostic and/or predictive biomarkers.

Identification of early predictive imaging biomarkers and their relationship to serological angiogenic markers in patients with ovarian cancer with residual disease following cytotoxic therapy.

BACKGROUND: Patients with recurrent ovarian cancer often achieve partial response following chemotherapy, resulting in persistent small volume disease. After completion of treatment, the dilemma of when to initiate subsequent chemotherapy arises. Identification of biomarkers that could be used to predict when subsequent treatment is needed would be of significant benefit. DESIGN: Twenty-three patients with advanced ovarian cancer and residual asymptomatic disease following chemotherapy underwent dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) at study entry, 4, 8, 12, 18 and 26 weeks or disease progression. A subgroup of patients provided plasma samples within which a panel of angiogenic biomarkers was quantified. RESULTS: By 4 weeks, significant differences in whole tumour volume, enhancing fraction and Ca125 were observed between patients whose disease progressed by 26 weeks and those who remained stable. Significant correlations between plasma soluble vascular endothelial growth factor receptor-1 (sVEGFR-1) and sVEGFR-2 concentrations, and blood volume and tumour endothelial permeability surface area product measured by DCE-MRI were observed. CONCLUSIONS: Imaging markers have a potential role in early prediction of disease progression in patients with residual ovarian cancer and may supplement current measures of progression. The correlation of DCE-MRI and serological biomarkers suggests that tumour angiogenesis affects these markers through common biological means and warrants further investigation.

Delivering Functional Imaging on the MRI-Linac: Current Challenges and Potential Solutions.

Magnetic resonance imaging (MRI) is a highly versatile imaging modality that can be used to measure features of the tumour microenvironment including cell death, proliferation, metabolism, angiogenesis, and hypoxia. Mapping and quantifying these pathophysiological features has the potential to alter the use of adaptive radiotherapy planning. Although these methods are available for use on diagnostic machines, several challenges exist for implementing these functional MRI methods on the MRI-linear accelerators (linacs). This review considers these challenges and potential solutions.

The meaning, measurement and modification of hypoxia in the laboratory and the clinic.

Hypoxia was identified as a microenvironmental component of solid tumours over 60 years ago and was immediately recognised as a potential barrier to therapy through the reliance of radiotherapy on oxygen to elicit maximal cytotoxicity. Over the last two decades both clinical and experimental studies have markedly enhanced our understanding of how hypoxia influences cellular behaviour and therapy response. Furthermore, they have confirmed early assumptions that low oxygenation status in tumours is an exploitable target in cancer therapy. Generally such approaches will be more beneficial to patients with hypoxic tumours, necessitating the use of biomarkers that reflect oxygenation status. Tissue biomarkers have shown utility in many studies. Further significant advances have been made in the non-invasive measurement of tumour hypoxia with positron emission tomography, magnetic resonance imaging and other imaging modalities. Here, we describe the complexities of defining and measuring tumour hypoxia and highlight the therapeutic approaches to combat it.

Dynamic contrast-enhanced imaging techniques: CT and MRI.

Over the last few decades there has been considerable research into quantifying the cerebral microvasculature with imaging, for use in studies of the human brain and various pathologies including cerebral tumours. This review highlights key issues in dynamic contrast-enhanced CT, dynamic contrast-enhanced MRI and arterial spin labelling, the various applications of which are considered elsewhere in this special issue of the British Journal of Radiology.

Imaging biomarkers of angiogenesis and the microvascular environment in cerebral tumours.

Conventional contrast-enhanced CT and MRI are now in routine clinical use for the diagnosis, treatment and monitoring of diseases in the brain. The presence of contrast enhancement is a proxy for the pathological changes that occur in the normally highly regulated brain vasculature and blood-brain barrier. With recognition of the limitations of these techniques, and a greater appreciation for the nuanced mechanisms of microvascular change in a variety of pathological processes, novel techniques are under investigation for their utility in further interrogating the microvasculature of the brain. This is particularly important in tumours, where the reliance on angiogenesis (new vessel formation) is crucial for tumour growth, and the resulting microvascular configuration and derangement has profound implications for diagnosis, treatment and monitoring. In addition, novel therapeutic approaches that seek to directly modify the microvasculature require more sensitive and specific biological markers of baseline tumour behaviour and response. The currently used imaging biomarkers of angiogenesis and brain tumour microvascular environment are reviewed.

A two-part phase II study of cediranib in patients with advanced solid tumours: the effect of food on single-dose pharmacokinetics and an evaluation of safety, efficacy and imaging pharmacodynamics.

BACKGROUND: Cediranib (RECENTIN™) is an oral, highly potent VEGF inhibitor. This study evaluated the effect of food on the pharmacokinetics of cediranib and compared the administration of continual cediranib via two dosing strategies using this as a platform to investigate pharmacodynamic imaging biomarkers. METHODS: Sixty patients were randomised to receive two single doses of cediranib in either fed/fasted or fasted/fed state (Part A). In continual dosage phase (Part B), patients were randomised to a fixed-dose or dose-escalation arm. Exploratory pharmacodynamic assessments were performed using DCE-MRI and CT enhancing fraction (EnF). RESULTS: In part A, plasma AUC and C (max) of cediranib were lower in the presence of food by a mean of 24 and 33%, respectively (94% CI: AUC, 12-34% and C (max), 20-43%), indicating food reduces cediranib plasma exposure. In part B, cediranib 30 mg/day appeared to be the most sustainable for chronic dosing. Continuous cediranib therapy was associated with sustained antivascular effects up to 16 weeks, with significant reductions in DCE-MRI parameters and CT EnF. CONCLUSIONS: It is recommended that cediranib be administered at least 1 h before or 2 h after food. Evidence of antitumour activity was observed, with significant sustained effects upon imaging vascular parameters.

Cross-visit tumor sub-segmentation and registration with outlier rejection for dynamic contrast-enhanced MRI time series data.

Clinical trials of anti-angiogenic and vascular-disrupting agents often use biomarkers derived from DCE-MRI, typically reporting whole-tumor summary statistics and so overlooking spatial parameter variations caused by tissue heterogeneity. We present a data-driven segmentation method comprising tracer-kinetic model-driven registration for motion correction, conversion from MR signal intensity to contrast agent concentration for cross-visit normalization, iterative principal components analysis for imputation of missing data and dimensionality reduction, and statistical outlier detection using the minimum covariance determinant to obtain a robust Mahalanobis distance. After applying these techniques we cluster in the principal components space using k-means. We present results from a clinical trial of a VEGF inhibitor, using time-series data selected because of problems due to motion and outlier time series. We obtained spatially-contiguous clusters that map to regions with distinct microvascular characteristics. This methodology has the potential to uncover localized effects in trials using DCE-MRI-based biomarkers.

Enhancing fraction in glioma and its relationship to the tumoral vascular microenvironment: A dynamic contrast-enhanced MR imaging study.

BACKGROUND AND PURPOSE: EnF is a newly described measure of proportional tumor enhancement derived from DCE-MR imaging. The aim of this study was to assess the relationship between EnF and the more established DCE-MR imaging parameters: K(trans), v(e), and v(p). MATERIALS AND METHODS: Forty-two patients with 43 gliomas (16 grade II, 3 grade III, and 24 grade IV) were studied. Imaging included pre- and postcontrast T1-weighted sequences through the lesion and T1-weighted DCE-MR imaging. Parametric maps of EnF, K(trans), v(e), and v(p) were generated. Voxels were classified as enhancing if the IAUC was positive (EnF(IAUC)(60>0)). A threshold of IAUC > 2.5 mmol.s was used to generate EnF(IAUC)(60>2.5). Both measures of EnF were compared with the DCE-MR imaging parameters (K(trans), v(e), and v(p)). RESULTS: In grade II gliomas, EnF(IAUC60>0) and EnF(IAUC60>2.5) correlated with v(p) (R(2) = 0.6245, P < .0005; and R(2) = 0.4727, P = .003) but not with K(trans) or v(e). In grade IV tumors, both EnF(IAUC60>0) and EnF(IAUC60>2.5) correlated with K(trans) (R(2) = 0.3501, P = .001; and R(2) = 0.4699, P < .0005) and v(p) (R(2) = 0.1564, P = .01; and R(2) = 0.2429, P = .007), but not with v(e). Multiple regression analysis showed K(trans) as the only independent correlate of both EnF(IAUC60>0) and EnF(IAUC60>2.5) for grade IV tumors. CONCLUSIONS: This study suggests that in grade II tumors, EnF reflects v(p) and varies due to changes in vascular density. In grade IV gliomas, EnF is affected by K(trans) with secondary associated changes in v(p).

DCE-MRI biomarkers in the clinical evaluation of antiangiogenic and vascular disrupting agents.

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is now frequently used in early clinical trial assessment of antiangiogenic and vascular disrupting compounds. Evidence of drug efficacy and dose-dependent response has been demonstrated with some angiogenesis inhibitors. This review highlights the critical issues that influence T(1)-weighted DCE-MRI data acquisition and analysis, identifies important areas for future development and reviews the clinical trial findings to date.

Quantifying heterogeneity in dynamic contrast-enhanced MRI parameter maps.

Simple summary statistics of Dynamic Contrast-Enhanced MRI (DCE-MRI) parameter maps (e.g. the median) neglect the spatial arrangement of parameters, which appears to carry important diagnostic and prognostic information. This paper describes novel statistics that are sensitive to both parameter values and their spatial arrangement. Binary objects are created from 3-D DCE-MRI parameter maps by "extruding" each voxel into a fourth dimension; the extrusion distance is proportional to the voxel's value. The following statistics are then computed on these 4-D binary objects: surface area, volume, surface area to volume ratio, and box counting (fractal) dimension. An experiment using 4 low and 5 high grade gliomas showed significant differences between the two grades for box counting dimension computed for extruded v(e) maps, surface area of extruded K(trans) and v(e) maps and the volume of extruded v(e) maps (all p < 0.05). An experiment using 18 liver metastases imaged before and after treatment with a vascular endothelial growth factor (VEGF) inhibitor showed significant differences for surface area to volume ratio computed for extruded K(trans) and v(e) maps (p = 0.0013 and p = 0.045 respectively).