Ross Little

The effect of blood inflow and B1-field inhomogeneity on measurement of the arterial input function in axial 3D spoiled gradient echo dynamic contrast-enhanced MRI

A major potential confound in axial 3D dynamic contrast‐enhanced magnetic resonance imaging studies is the blood inflow effect; therefore, the choice of slice location for arterial input function measurement within the imaging volume must be considered carefully. The objective of this study was to use computer simulations, flow phantom, and in vivo studies to describe and understand the effect of blood inflow on the measurement of the arterial input function. All experiments were done at 1.5 T using a typical 3D dynamic contrast‐enhanced magnetic resonance imaging sequence, and arterial input functions were extracted for each slice in the imaging volume. We simulated a set of arterial input functions based on the same imaging parameters and accounted for blood inflow and radiofrequency field inhomogeneities. Measured arterial input functions along the vessel length from both in vivo and the flow phantom agreed with simulated arterial input functions and show large overestimations in the arterial input function in the first 30 mm of the vessel, whereas arterial input functions measured more centrally achieve accurate contrast agent concentrations. Use of inflow‐affected arterial input functions in tracer kinetic modeling shows potential errors of up to 80% in tissue microvascular parameters. These errors emphasize the importance of careful placement of the arterial input function definition location to avoid the effects of blood inflow. Magn Reson Med, 2010.

Mutual information as a measure of image quality for 3D dynamic lung imaging with EIT

We report on a pilot study of dynamic lung electrical impedance tomography (EIT) at the University of Manchester. Low-noise EIT data at 100 frames per second were obtained from healthy male subjects during controlled breathing, followed by magnetic resonance imaging (MRI) subsequently used for spatial validation of the EIT reconstruction. The torso surface in the MR image and electrode positions obtained using MRI fiducial markers informed the construction of a 3D finite element model extruded along the caudal-distal axis of the subject. Small changes in the boundary that occur during respiration were accounted for by incorporating the sensitivity with respect to boundary shape into a robust temporal difference reconstruction algorithm. EIT and MRI images were co-registered using the open source medical imaging software, 3D Slicer. A quantitative comparison of quality of different EIT reconstructions was achieved through calculation of the mutual information with a lung-segmented MR image. EIT reconstructions using a linear shape correction algorithm reduced boundary image artefacts, yielding better contrast of the lungs, and had 10% greater mutual information compared with a standard linear EIT reconstruction.

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.

Mapping Hypoxia in Renal Carcinoma with Oxygen-enhanced MRI: Comparison with Intrinsic Susceptibility MRI and Pathology

Purpose To cross-validate T1-weighted oxygen-enhanced (OE) MRI measurements of tumor hypoxia with intrinsic susceptibility MRI measurements and to demonstrate the feasibility of translation of the technique for patients. Materials and Methods Preclinical studies in nine 786–0-R renal cell carcinoma (RCC) xenografts and prospective clinical studies in eight patients with RCC were performed. Longitudinal relaxation rate changes (∆R1) after 100% oxygen inhalation were quantified, reflecting the paramagnetic effect on tissue protons because of the presence of molecular oxygen. Native transverse relaxation rate (R2*) and oxygen-induced R2* change (∆R2*) were measured, reflecting presence of deoxygenated hemoglobin molecules. Median and voxel-wise values of ∆R1 were compared with values of R2* and ∆R2*. Tumor regions with dynamic contrast agent–enhanced MRI perfusion, refractory to signal change at OE MRI (referred to as perfused Oxy-R), were distinguished from perfused oxygen-enhancing (perfused Oxy-E) and nonperfused regions. R2* and ∆R2* values in each tumor subregion were compared by using one-way analysis of variance. Results Tumor-wise and voxel-wise ∆R1 and ∆R2* comparisons did not show correlative relationships. In xenografts, parcellation analysis revealed that perfused Oxy-R regions had faster native R2* (102.4 sec–1 vs 81.7 sec–1) and greater negative ∆R2* (−22.9 sec–1 vs −5.4 sec–1), compared with perfused Oxy-E and nonperfused subregions (all P < .001), respectively. Similar findings were present in human tumors (P < .001). Further, perfused Oxy-R helped identify tumor hypoxia, measured at pathologic analysis, in both xenografts (P = .002) and human tumors (P = .003). Conclusion Intrinsic susceptibility biomarkers provide cross validation of the OE MRI biomarker perfused Oxy-R. Consistent relationship to pathologic analyses was found in xenografts and human tumors, demonstrating biomarker translation. Published under a CC BY 4.0 license. Online supplemental material is available for this article.

Data-driven mapping of hypoxia-related tumor heterogeneity using DCE-MRI and OE-MRI

Previous work has shown that combining dynamic contrast‐enhanced (DCE)‐MRI and oxygen‐enhanced (OE)‐MRI binary enhancement maps can identify tumor hypoxia. The current work proposes a novel, data‐driven method for mapping tissue oxygenation and perfusion heterogeneity, based on clustering DCE/OE‐MRI data.

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.

Inter-tumor validation, through advanced MRI and circulating biomarkers, of plasma Tie2 as the vascular response biomarker for bevacizumab.

11521Background: VEGF inhibitor (VEGFi) use is compromised by lack of predictive/ response biomarkers. Previously, we identified plasma Tie2 (pTie2) as a vascular response biomarker (VRB) for bevacizumab (bev) in ovarian cancer (OC). Here, we applied dynamic contrast-enhanced MRI (DCE-MRI) and circulating biomarkers in colorectal cancer (CRC), to validate pTie2 as the first tumor VRB. Methods: Seventy patients were recruited, with untreated, mCRC and ≥1 lesion of 3-10cm diameter for DCE-MRI. Patients received bev 10mg/kg for 2 weeks to elicit a biomarker response and then FOLFOX6/bev until progressive disease (PD) Thirteen circulating and 6 imaging biomarkers were measured before and during treatment and at PD. Unsupervised correlation analysis identified bev-induced biomarker correlations. Biomarkers were evaluated by clustered parameter-time course studies to determine their epithelial or vascular origin. Clinical significance was determined by relating the biomarker data to tumor 3D volumetric change a...