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.

DCE-MRI model selection for investigating disruption of microvascular function in livers with metastatic disease.

PURPOSE: To evaluate the Akaike information criterion (AIC) model selection technique as a method for detecting differences in microvascular characteristics between tumorous and non-tumor liver tissue. MATERIALS AND METHODS: The AIC was applied to six patient datasets with liver metastases to determine, on a per voxel basis, which of two physiologically plausible candidate models gave a more appropriate description of the data. The dual-input single-compartment Materne model, extended to incorporate a novel portal input function estimation method, was chosen to represent liver tissue and the single-input dual-compartment extended Kety model was used for tumor. RESULTS: Median AIC probabilities when comparing tumor versus liver and tumor versus tumor-margins were significantly different (P ≤ 0.01) in five of the six patient datasets. Comparisons between tumor margins and liver regions were significantly different in four datasets. Median AIC probabilities selected for the extended Kety model in all tumor regions, with the Materne model being progressively more probable through tumor margins into liver. CONCLUSION: We present a viable method for assessing the spatially varying microvascular characteristics of tumor-bearing livers, with possible applications in lesion detection, assessment of tumor invasion, and measurement of drug efficacy.

Quantifying spatial heterogeneity in dynamic contrast-enhanced MRI parameter maps.

Dynamic contrast-enhanced MRI is becoming a standard tool for imaging-based trials of anti-vascular/angiogenic agents in cancer. So far, however, biomarkers derived from DCE-MRI parameter maps have largely neglected the fact that the maps have spatial structure and instead focussed on distributional summary statistics. Such statistics-e.g., biomarkers based on median values-neglect the spatial arrangement of parameters, which may carry important diagnostic and prognostic information. This article describes two types of heterogeneity biomarker that are sensitive to both parameter values and their spatial arrangement. Methods based on Rényi fractal dimensions and geometrical properties are developed, both of which attempt to describe the complexity of DCE-MRI parameter maps. Experiments using simulated data show that the proposed biomarkers are sensitive to changes that distribution-based summary statistics cannot detect and demonstrate that heterogeneity biomarkers could be applied in the drug trial setting. An experiment using 23 DCE-MRI parameter maps of gliomas-a class of tumour that is graded on the basis of heterogeneity-shows that the proposed heterogeneity biomarkers are able to differentiate between low- and high-grade tumours.

Comparison of normal tissue R1 and R*2 modulation by oxygen and carbogen.

Magnetic resonance imaging has shown promise for evaluating tissue oxygenation. In this study differences in the tissue longitudinal relaxation rate (R(1)) and effective transverse relaxation rate (R(*)(2)), induced by inhalation of pure oxygen and carbogen, were evaluated in 10 healthy subjects. Significant reductions in R(1) were demonstrated following both oxygen and carbogen inhalation in the spleen (both P < 0.001), liver (P = 0.002 air vs. oxygen; P = 0.001 air vs. carbogen), skeletal muscle (both P < 0.001), and renal cortex (P = 0.005 air vs. oxygen; P = 0.008 air vs. carbogen). No significant change in R(*)(2) occurred following pure oxygen in any organ. However, a significant increase in R(*)(2) was observed in the spleen (P < 0.001), liver (P = 0.001), skeletal muscle (P = 0.026), and renal cortex (P = 0.001) following carbogen inhalation, an opposite effect to that observed in many studies of tumor pathophysiology. Changes in R(1) and R(*)(2) were independent of the gas administration order in the spleen and skeletal muscle. These findings suggest that the R(1) and R(*)(2) responses to hyperoxic gases are independent biomarkers of oxygen physiology.

Tumour enhancing fraction (EnF) in glioma: relationship to tumour grade.

The aim of this research was to determine whether the proportion of a tumour that enhances (enhancing fraction, EnF) and changes in EnF with enhancement threshold differ between low and high grade glioma. Forty-four patients (45 gliomas comprising 16 grade II, 5 grade III and 24 grade IV) were studied. Imaging included pre- and post-contrast-enhanced T(1)-weighted sequences and T(1)-weighted DCE-MRI. Thresholded enhancement maps were generated for each tumour by using a range of values of the initial area under the contrast concentration curve (IAUC). A plot of EnF versus threshold value was generated. We examined the relationship between tumour grade and enhancement metrics including: EnF (threshold IAUC > 0 mMol s), EnF (threshold IAUC > 2.5 mMol s), initial slope of the EnF/threshold curve (partial differentialEnF), IAUC, and two previously described signal-intensity-based metrics. EnF, defined as the proportion of tumour showing any enhancement (threshold IAUC > 0 mMol s), showed no difference between low and high grade glioma. All other measures demonstrated significant differences between grade II and IV, and low (grade II) and high grade (grades III/ IV) gliomas (p < 0.01). Two measures, partial differentialEnF and Pronin's measure of enhancement, showed differences between grade III and IV (p < 0.05). No measure separated grade II from III. Metrics which describe the enhancing fraction and its variation with enhancement threshold partial differentialEnF show considerably different behaviour in low and high grade tumours. These observations suggest that these metrics may provide important biological information concerning tumour biology and therapeutic responses and encourage further research to characterise and validate these novel biomarkers.

Comparison of the performance of tracer kinetic model-driven registration for dynamic contrast enhanced MRI using different models of contrast enhancement.

RATIONALE AND OBJECTIVES: The quantitative analysis of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) data is subject to model fitting errors caused by motion during the time-series data acquisition. However, the time-varying features that occur as a result of contrast enhancement can confound motion correction techniques based on conventional registration similarity measures. We have therefore developed a heuristic, locally controlled tracer kinetic model-driven registration procedure, in which the model accounts for contrast enhancement, and applied it to the registration of abdominal DCE-MRI data at high temporal resolution. MATERIALS AND METHODS: Using severely motion-corrupted data sets that had been excluded from analysis in a clinical trial of an antiangiogenic agent, we compared the results obtained when using different models to drive the tracer kinetic model-driven registration with those obtained when using a conventional registration against the time series mean image volume. RESULTS: Using tracer kinetic model-driven registration, it was possible to improve model fitting by reducing the sum of squared errors but the improvement was only realized when using a model that adequately described the features of the time series data. The registration against the time series mean significantly distorted the time series data, as did tracer kinetic model-driven registration using a simpler model of contrast enhancement. CONCLUSION: When an appropriate model is used, tracer kinetic model-driven registration influences motion-corrupted model fit parameter estimates and provides significant improvements in localization in three-dimensional parameter maps. This has positive implications for the use of quantitative DCE-MRI for example in clinical trials of antiangiogenic or antivascular agents.

Feasibility assessment of using oxygen-enhanced magnetic resonance imaging for evaluating the effect of pharmacological treatment in COPD.

OBJECTIVES: Oxygen-enhanced MRI (OE-MRI) biomarkers have potential value in assessment of COPD, but need further evaluation before treatment-induced changes can be interpreted. The objective was to evaluate how OE-MRI parameters of regional ventilation and oxygen uptake respond to standard pharmacological interventions in COPD, and how the response compares to that of gold standard pulmonary function tests. MATERIALS AND METHODS: COPD patients (n=40), mean FEV1 58% predicted normal, received single-dose inhaled formoterol 9µg, or placebo, followed by 8 weeks treatment bid with a combination of budesonide and formoterol Turbuhaler(®) 320/9µg or formoterol Turbuhaler(®). OE-MRI biomarkers were obtained, as well as X-ray computed tomography (CT) biomarkers and pulmonary function tests, in a two-center study. An ANCOVA statistical model was used to assess effect size of intervention measurable in OE-MRI parameters of lung function. RESULTS: OE-MRI data were successfully acquired at both study sites. 8-week treatment with budesonide/formoterol significantly decreased lung wash-out time by 31% (p<0.01), decreased the change in lung oxygen level upon breathing pure oxygen by 13% (p<0.05) and increased oxygen extraction from the lung by 58% (p<0.01). Single-dose formoterol increased both lung wash-out time (+47%, p<0.05) and lung oxygenation time (+47%, p<0.05). FEV1 was improved by single-dose formoterol (+12%, p<0.001) and 8 weeks of budesonide/formoterol (+ 18%, p<0.001), consistent with published studies. CONCLUSIONS: In COPD, OE-MRI parameters showed response to both single-dose bronchodilatory effects of a ß2-agonist, formoterol, and 8-week treatment with an inhaled corticosteroid, budesonide, and the measurements are feasible in a small-scale multi-center trial setting.

Preliminary study of oxygen-enhanced longitudinal relaxation in MRI: a potential novel biomarker of oxygenation changes in solid tumors.

PURPOSE: There is considerable interest in developing non-invasive methods of mapping tumor hypoxia. Changes in tissue oxygen concentration produce proportional changes in the magnetic resonance imaging (MRI) longitudinal relaxation rate (R(1)). This technique has been used previously to evaluate oxygen delivery to healthy tissues and is distinct from blood oxygenation level-dependent (BOLD) imaging. Here we report application of this method to detect alteration in tumor oxygenation status. METHODS AND MATERIALS: Ten patients with advanced cancer of the abdomen and pelvis underwent serial measurement of tumor R(1) while breathing medical air (21% oxygen) followed by 100% oxygen (oxygen-enhanced MRI). Gadolinium-based dynamic contrast-enhanced MRI was then performed to compare the spatial distribution of perfusion with that of oxygen-induced DeltaR(1). RESULTS: DeltaR(1) showed significant increases of 0.021 to 0.058 s(-1) in eight patients with either locally recurrent tumor from cervical and hepatocellular carcinomas or metastases from ovarian and colorectal carcinomas. In general, there was congruency between perfusion and oxygen concentration. However, regional mismatch was observed in some tumor cores. Here, moderate gadolinium uptake (consistent with moderate perfusion) was associated with low area under the DeltaR(1) curve (consistent with minimal increase in oxygen concentration). CONCLUSIONS: These results provide evidence that oxygen-enhanced longitudinal relaxation can monitor changes in tumor oxygen concentration. The technique shows promise in identifying hypoxic regions within tumors and may enable spatial mapping of change in tumor oxygen concentration.

Quantifying antivascular effects of monoclonal antibodies to vascular endothelial growth factor: insights from imaging.

PURPOSE: Little is known concerning the onset, duration, and magnitude of direct therapeutic effects of anti-vascular endothelial growth factor (VEGF) therapies. Such knowledge would help guide the rational development of targeted therapeutics from bench to bedside and optimize use of imaging technologies that quantify tumor function in early-phase clinical trials. EXPERIMENTAL DESIGN: Preclinical studies were done using ex vivo microcomputed tomography and in vivo ultrasound imaging to characterize tumor vasculature in a human HM-7 colorectal xenograft model treated with the anti-VEGF antibody G6-31. Clinical evaluation was by quantitative magnetic resonance imaging in 10 patients with metastatic colorectal cancer treated with bevacizumab. RESULTS: Microcomputed tomography experiments showed reduction in perfused vessels within 24 to 48 h of G6-31 drug administration (P

Tracer kinetic model-driven registration for dynamic contrast-enhanced MRI time-series data.

Dynamic contrast-enhanced MRI (DCE-MRI) time series data are subject to unavoidable physiological motion during acquisition (e.g., due to breathing) and this motion causes significant errors when fitting tracer kinetic models to the data, particularly with voxel-by-voxel fitting approaches. Motion correction is problematic, as contrast enhancement introduces new features into postcontrast images and conventional registration similarity measures cannot fully account for the increased image information content. A methodology is presented for tracer kinetic model-driven registration that addresses these problems by explicitly including a model of contrast enhancement in the registration process. The iterative registration procedure is focused on a tumor volume of interest (VOI), employing a three-dimensional (3D) translational transformation that follows only tumor motion. The implementation accurately removes motion corruption in a DCE-MRI software phantom and it is able to reduce model fitting errors and improve localization in 3D parameter maps in patient data sets that were selected for significant motion problems. Sufficient improvement was observed in the modeling results to salvage clinical trial DCE-MRI data sets that would otherwise have to be rejected due to motion corruption.