Human Tumor Cell Proliferation Evaluated Using Manganese-Enhanced MRI

Tumor cell proliferation can depend on calcium entry across the cell membrane. As a first step toward the development of a non-invasive test of the extent of tumor cell proliferation in vivo, we tested the hypothesis that tumor cell uptake of a calcium surrogate, Mn(2+) [measured with manganese-enhanced MRI (MEMRI)], is linked to proliferation rate in vitro.Proliferation rates were determined in vitro in three different human tumor cell lines: C918 and OCM-1 human uveal melanomas and PC-3 prostate carcinoma. Cells growing at different average proliferation rates were exposed to 1 mM MnCl(2) for one hour and then thoroughly washed. MEMRI R(1) values (longitudinal relaxation rates), which have a positive linear relationship with Mn(2+) concentration, were then determined from cell pellets. Cell cycle distributions were determined using propidium iodide staining and flow cytometry. All three lines showed Mn(2+)-induced increases in R(1) compared to cells not exposed to Mn(2+). C918 and PC-3 cells each showed a significant, positive correlation between MEMRI R(1) values and proliferation rate (p≤0.005), while OCM-1 cells showed no significant correlation. Preliminary, general modeling of these positive relationships suggested that pellet R(1) for the PC-3 cells, but not for the C918 cells, could be adequately described by simply accounting for changes in the distribution of the cell cycle-dependent subpopulations in the pellet.These data clearly demonstrate the tumor-cell dependent nature of the relationship between proliferation and calcium influx, and underscore the usefulness of MEMRI as a non-invasive method for investigating this link. MEMRI is applicable to study tumors in vivo, and the present results raise the possibility of evaluating proliferation parameters of some tumor types in vivo using MEMRI

In Vivo Detection of Amyloid-β Deposits Using Heavy Chain Antibody Fragments in a Transgenic Mouse Model for Alzheimer's Disease

This study investigated the in vivo properties of two heavy chain antibody fragments (VHH), ni3A and pa2H, to differentially detect vascular or parenchymal amyloid-β deposits characteristic for Alzheimer's disease and cerebral amyloid angiopathy. Blood clearance and biodistribution including brain uptake were assessed by bolus injection of radiolabeled VHH in APP/PS1 mice or wildtype littermates. In addition, in vivo specificity for Aβ was examined in more detail with fluorescently labeled VHH by circumventing the blood-brain barrier via direct application or intracarotid co-injection with mannitol. All VHH showed rapid renal clearance (10–20 min). Twenty-four hours post-injection 99mTc-pa2H resulted in a small yet significant higher cerebral uptake in the APP/PS1 animals. No difference in brain uptake were observed for 99mTc-ni3A or DTPA(111In)-pa2H, which lacked additional peptide tags to investigate further clinical applicability. In vivo specificity for Aβ was confirmed for both fluorescently labeled VHH, where pa2H remained readily detectable for 24 hours or more after injection. Furthermore, both VHH showed affinity for parenchymal and vascular deposits, this in contrast to human tissue, where ni3A specifically targeted only vascular Aβ. Despite a brain uptake that is as yet too low for in vivo imaging, this study provides evidence that VHH detect Aβ deposits in vivo, with high selectivity and favorable in vivo characteristics, making them promising tools for further development as diagnostic agents for the distinctive detection of different Aβ deposits

Mouse models of neurodegenerative disease: preclinical imaging and neurovascular component.

Neurodegenerative diseases represent great challenges for basic science and clinical medicine because of their prevalence, pathologies, lack of mechanism-based treatments, and impacts on individuals. Translational research might contribute to the study of neurodegenerative diseases. The mouse has become a key model for studying disease mechanisms that might recapitulate in part some aspects of the corresponding human diseases. Neurode- generative disorders are very complicated and multifacto- rial. This has to be taken in account when testing drugs. Most of the drugs screening in mice are very di cult to be interpretated and often useless. Mouse models could be condiderated a ‘pathway models’, rather than as models for the whole complicated construct that makes a human disease. Non-invasive in vivo imaging in mice has gained increasing interest in preclinical research in the last years thanks to the availability of high-resolution single-photon emission computed tomography (SPECT), positron emission tomography (PET), high eld Magnetic resonance, Optical Imaging scanners and of highly speci c contrast agents. Behavioral test are useful tool to characterize di erent ani- mal models of neurodegenerative pathology. Furthermore, many authors have observed vascular pathological features associated to the di erent neurodegenerative disorders. Aim of this review is to focus on the di erent existing animal models of neurodegenerative disorders, describe behavioral tests and preclinical imaging techniques used for diagnose and describe the vascular pathological features associated to these diseases

Deep Learning for Low-Field to High-Field MR:Image Quality Transfer with Probabilistic Decimation Simulator

MR images scanned at low magnetic field ($<1$T) have lower resolution in the slice direction and lower contrast, due to a relatively small signal-to-noise ratio (SNR) than those from high field (typically 1.5T and 3T). We adapt the recent idea of Image Quality Transfer (IQT) to enhance very low-field structural images aiming to estimate the resolution, spatial coverage, and contrast of high-field images. Analogous to many learning-based image enhancement techniques, IQT generates training data from high-field scans alone by simulating low-field images through a pre-defined decimation model. However, the ground truth decimation model is not well-known in practice, and lack of its specification can bias the trained model, aggravating performance on the real low-field scans. In this paper we propose a probabilistic decimation simulator to improve robustness of model training. It is used to generate and augment various low-field images whose parameters are random variables and sampled from an empirical distribution related to tissue-specific SNR on a 0.36T scanner. The probabilistic decimation simulator is model-agnostic, that is, it can be used with any super-resolution networks. Furthermore we propose a variant of U-Net architecture to improve its learning performance. We show promising qualitative results from clinical low-field images confirming the strong efficacy of IQT in an important new application area: epilepsy diagnosis in sub-Saharan Africa where only low-field scanners are normally available

Mutual interferences and design principles for mechatronic devices in magnetic resonance imaging

PURPOSE: Robotic and mechatronic devices that work compatibly with magnetic resonance imaging (MRI) are applied in diagnostic MRI, image-guided surgery, neurorehabilitation and neuroscience. MRI-compatible mechatronic systems must address the challenges imposed by the scanner's electromagnetic fields. We have developed objective quantitative evaluation criteria for device characteristics needed to formulate design guidelines that ensure MRI-compatibility based on safety, device functionality and image quality. METHODS: The mutual interferences between an MRI system and mechatronic devices working in its vicinity are modeled and tested. For each interference, the involved components are listed, and a numerical measure for "MRI-compatibility" is proposed. These interferences are categorized into an MRI-compatibility matrix, with each element representing possible interactions between one part of the mechatronic system and one component of the electromagnetic fields. Based on this formulation, design principles for MRI-compatible mechatronic systems are proposed. Furthermore, test methods are developed to examine whether a mechatronic device indeed works without interferences within an MRI system. Finally, the proposed MRI-compatibility criteria and design guidelines have been applied to an actual design process that has been validated by the test procedures. RESULTS: Objective and quantitative MRI-compatibility measures for mechatronic and robotic devices have been established. Applying the proposed design principles, potential problems in safety, device functionality and image quality can be considered in the design phase to ensure that the mechatronic system will fulfill the MRI-compatibility criteria. CONCLUSION: New guidelines and test procedures for MRI instrument compatibility provide a rational basis for design and evaluation of mechatronic devices in various MRI applications. Designers can apply these criteria and use the tests, so that MRI-compatibility results can accrue to build an experiential database