Rat model of metastatic breast cancer monitored by MRI at 3 tesla and bioluminescence imaging with histological correlation

<p>Abstract</p> <p>Background</p> <p>Establishing a large rodent model of brain metastasis that can be monitored using clinically relevant magnetic resonance imaging (MRI) techniques is challenging. Non-invasive imaging of brain metastasis in mice usually requires high field strength MR units and long imaging acquisition times. Using the brain seeking MDA-MB-231BR transfected with luciferase gene, a metastatic breast cancer brain tumor model was investigated in the nude rat. Serial MRI and bioluminescence imaging (BLI) was performed and findings were correlated with histology. Results demonstrated the utility of multimodality imaging in identifying unexpected sights of metastasis and monitoring the progression of disease in the nude rat.</p> <p>Methods</p> <p>Brain seeking breast cancer cells MDA-MB-231BR transfected with firefly luciferase (231BRL) were labeled with ferumoxides-protamine sulfate (FEPro) and 1-3 × 10⁶cells were intracardiac (IC) injected. MRI and BLI were performed up to 4 weeks to monitor the early breast cancer cell infiltration into the brain and formation of metastases. Rats were euthanized at different time points and the imaging findings were correlated with histological analysis to validate the presence of metastases in tissues.</p> <p>Results</p> <p>Early metastasis of the FEPro labeled 231BRL were demonstrated onT2*-weighted MRI and BLI within 1 week post IC injection of cells. Micro-metastatic tumors were detected in the brain on T2-weighted MRI as early as 2 weeks post-injection in greater than 85% of rats. Unexpected skeletal metastases from the 231BRL cells were demonstrated and validated by multimodal imaging. Brain metastases were clearly visible on T2 weighted MRI by 3-4 weeks post infusion of 231BRL cells, however BLI did not demonstrate photon flux activity originating from the brain in all animals due to scattering of the photons from tumors.</p> <p>Conclusion</p> <p>A model of metastatic breast cancer in the nude rat was successfully developed and evaluated using multimodal imaging including MRI and BLI providing the ability to study the temporal and spatial distribution of metastases in the brain and skeleton.</p

In Vivo, Multimodal Imaging of B Cell Distribution and Response to Antibody Immunotherapy in Mice

BACKGROUND: B cell depletion immunotherapy has been successfully employed to treat non-Hodgkin's lymphoma. In recent years, increasing attention has been directed towards also using B-cell depletion therapy as a treatment option in autoimmune disorders. However, it appears that the further development of these approaches will depend on a methodology to determine the relation of B-cell depletion to clinical response and how individual patients should be dosed. Thus far, patients have generally been followed by quantification of peripheral blood B cells, but it is not apparent that this measurement accurately reflects systemic B cell dynamics. METHODOLOGY/PRINCIPAL FINDINGS: Cellular imaging of the targeted population in vivo may provide significant insight towards effective therapy and a greater understanding of underlying disease mechanics. Superparamagnetic iron oxide (SPIO) nanoparticles in concert with near infrared (NIR) fluorescent dyes were used to label and track primary C57BL/6 B cells. Following antibody mediated B cell depletion (anti-CD79), NIR-only labeled cells were expeditiously cleared from the circulation and spleen. Interestingly, B cells labeled with both SPIO and NIR were not depleted in the spleen. CONCLUSIONS/SIGNIFICANCE: Whole body fluorescent tracking of B cells enabled noninvasive, longitudinal imaging of both the distribution and subsequent depletion of B lymphocytes in the spleen. Quantification of depletion revealed a greater than 40% decrease in splenic fluorescent signal-to-background ratio in antibody treated versus control mice. These data suggest that in vivo imaging can be used to follow B cell dynamics, but that the labeling method will need to be carefully chosen. SPIO labeling for tracking purposes, generally thought to be benign, appears to interfere with B cell functions and requires further examination

Longitudinal Tracking of Human Fetal Cells Labeled with Super Paramagnetic Iron Oxide Nanoparticles in the Brain of Mice with Motor Neuron Disease

Stem Cell (SC) therapy is one of the most promising approaches for the treatment of Amyotrophic Lateral Sclerosis (ALS). Here we employed Super Paramagnetic Iron Oxide nanoparticles (SPIOn) and Hoechst 33258 to track human Amniotic Fluid Cells (hAFCs) after transplantation in the lateral ventricles of wobbler (a murine model of ALS) and healthy mice. By in vitro, in vivo and ex vivo approaches we found that: 1) the main physical parameters of SPIOn were maintained over time; 2) hAFCs efficiently internalized SPIOn into the cytoplasm while Hoechst 33258 labeled nuclei; 3) SPIOn internalization did not alter survival, cell cycle, proliferation, metabolism and phenotype of hAFCs; 4) after transplantation hAFCs rapidly spread to the whole ventricular system, but did not migrate into the brain parenchyma; 5) hAFCs survived for a long time in the ventricles of both wobbler and healthy mice; 6) the transplantation of double-labeled hAFCs did not influence mice survival

Developing the Questionnaire

AbstractThis chapter outlines the essential topics for developing and testing a questionnaire for a discrete choice experiment survey. It addresses issues such as the description of the environmental good, pretesting of the survey, incentive compatibility, consequentiality or mitigation of hypothetical bias. For the latter, cheap talk scripts, opt-out reminders or an oath script are discussed. Moreover, the use of instructional choice sets, the identification of protest responses and strategic bidders are considered. Finally, issues related to the payment vehicle and the cost vector design are the subject of this section

The influence of noise on BOLD-mediated vessel size imaging analysis methods

Vessel size imaging (VSI) is a magnetic resonance imaging (MRI) technique that aims to provide quantitative measurements of tissue microvasculature. An emerging variation of this technique uses the blood oxygenation level-dependent (BOLD) effect as the source of the imaging contrast. Gas challenges have the advantage over contrast injection techniques in that they are noninvasive and easily repeatable because of the fast washout of the contrast. However, initial results from BOLD-VSI studies are somewhat contradictory, with substantially different estimates of the mean vessel radius. Owing to BOLD-VSI being an emerging technique, there is not yet a standard processing methodology, and different techniques have been used to calculate the mean vessel radius and reject uncertain estimates. In addition, the acquisition methodology and signal modeling vary from group to group. Owing to these differences, it is difficult to determine the source of this variation. Here we use computer modeling to assess the impact of noise on the accuracy and precision of different BOLD-VSI calculations. Our results show both potential overestimates and underestimates of the mean vessel radius, which is confirmed with a validation study at 3T. © 2013 ISCBFM

The influence of noise on BOLD-mediated vessel size imaging analysis methods.

Vessel size imaging (VSI) is a magnetic resonance imaging (MRI) technique that aims to provide quantitative measurements of tissue microvasculature. An emerging variation of this technique uses the blood oxygenation level-dependent (BOLD) effect as the source of the imaging contrast. Gas challenges have the advantage over contrast injection techniques in that they are noninvasive and easily repeatable because of the fast washout of the contrast. However, initial results from BOLD-VSI studies are somewhat contradictory, with substantially different estimates of the mean vessel radius. Owing to BOLD-VSI being an emerging technique, there is not yet a standard processing methodology, and different techniques have been used to calculate the mean vessel radius and reject uncertain estimates. In addition, the acquisition methodology and signal modeling vary from group to group. Owing to these differences, it is difficult to determine the source of this variation. Here we use computer modeling to assess the impact of noise on the accuracy and precision of different BOLD-VSI calculations. Our results show both potential overestimates and underestimates of the mean vessel radius, which is confirmed with a validation study at 3T

Quantitative fMRI using hyperoxia calibration: reproducibility during a cognitive Stroop task.

Arterial spin labelling allows simultaneous measurement of both the blood-oxygenation-level-dependent (BOLD) and the cerebral blood flow (CBF) response to changes in neural activity. The addition of a hypercapnia or hyperoxia calibration allows additional quantification of changes in the cerebral metabolic rate of oxygen (CMRO(2)). In this study we test the reproducibility of measurements derived using the hyperoxia approach, during a cognitive Stroop task. A QUIPSSII sequence is used at 3 T to collect simultaneous CBF and BOLD signal during two 3 min periods of hyperoxia and an 8 min Stroop task. Hyperoxia was administered via an open system and end-tidal values were sampled via a nasal cannula; average end-tidal values of 60% were reached. This procedure is repeated to allow the reproducibility of the estimated parameters to be tested. The use of a cognitive Stroop task allows testing of the measurements in frontal and parietal regions as well as sensorimotor areas in which previous studies have been focussed. We find reduced reproducibility of the calculated parameters compared to the hypercapnia approach, thought to be attributable to lower absolute BOLD and CBF responses. In particular we do not find 'n' to have improved reproducibility compared to other parameters, as has been found in previous work using the hypercapnia approach. Across all brain areas we report a value of DeltaCMRO(2) of 12% and neurovascular coupling constant n of 2.5. Interestingly we find n to be higher in parietal and frontal areas in comparison to the primary motor cortex