Dataset Information

A Metal-Free Method for Producing MRI Contrast at Amyloid-?.

ABSTRACT: Alzheimer's disease (AD) is characterized by depositions of the amyloid-? (A?) peptide in the brain. The disease process develops over decades, with substantial neurological loss occurring before a clinical diagnosis of dementia can be rendered. It is therefore imperative to develop methods that permit early detection and monitoring of disease progression. In addition, the multifactorial pathogenesis of AD has identified several potential avenues for AD intervention. Thus, evaluation of therapeutic candidates over lengthy trial periods also demands a practical, noninvasive method for measuring A? in the brain. Magnetic resonance imaging (MRI) is the obvious choice for such measurements, but contrast enhancement for A? has only been achieved using Gd(III)-based agents. There is great interest in gadolinium-free methods to image the brain. In this study, we provide the first demonstration that a nitroxide-based small-molecule produces MRI contrast in brain specimens with elevated levels of A?. The molecule is comprised of a fluorene (a molecule with high affinity for A?) and a nitroxide spin label (a paramagnetic MRI contrast species). Labeling of brain specimens with the spin-labeled fluorene produces negative contrast in samples from AD model mice whereas no negative contrast is seen in specimens harvested from wild-type mice. Injection of spin-labeled fluorene into live mice resulted in good brain penetration, with the compound able to generate contrast 24-h post injection. These results provide a proof of concept method that can be used for early, noninvasive, gadolinium-free detection of amyloid plaques by MRI.

SUBMITTER: Hilt S

PROVIDER: S-EPMC5718836 | biostudies-other | 2017

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

A Metal-Free Method for Producing MRI Contrast at Amyloid-β.

Hilt Silvia S Tang Tang T Walton Jeffrey H JH Budamagunta Madhu M Maezawa Izumi I Kálai Tamás T Hideg Kálmán K Singh Vikrant V Wulff Heike H Gong Qizhi Q Jin Lee-Way LW Louie Angelique A Voss John C JC

Journal of Alzheimer's disease : JAD 20170101 4

Alzheimer's disease (AD) is characterized by depositions of the amyloid-β (Aβ) peptide in the brain. The disease process develops over decades, with substantial neurological loss occurring before a clinical diagnosis of dementia can be rendered. It is therefore imperative to develop methods that permit early detection and monitoring of disease progression. In addition, the multifactorial pathogenesis of AD has identified several potential avenues for AD intervention. Thus, evaluation of therapeu ...[more]

PMID: 27911291

Similar Datasets

Project description:Simultaneously being a nonradiative and noninvasive technique makes magnetic resonance imaging (MRI) one of the highly required imaging approaches for the early diagnosis and follow-up of tumors, specifically for brain cancer. Paramagnetic gadolinium (Gd)-based contrast agents (CAs) are the most widely used ones in brain MRI acquisitions with special interest when assessing blood-brain barrier (BBB) integrity, a characteristic of high-grade tumors. However, alternatives to Gd-based contrast agents (CAs) are highly required to overcome their established toxicity. Organic radicals anchored on a dendrimer macromolecule surface (radical dendrimers) are promising alternatives since they also exhibit paramagnetic properties and can act as T1 CAs like Gd-based CAs while being organic species (mitigating concerns about toxic metal accumulation). Here, we studied the third generation of a water-soluble family of poly(phosphorhydrazone) radical dendrimers, with 48 PROXYL radical units anchored on their branches, exploring their potential of ex vivo and in vivo contrast enhancement in brain tumors (in particular, of immunocompetent, orthotopic GL261 murine glioblastoma (GB)). Remarkably, this radical species provides suitable contrast enhancement on murine GL261 GB tumors, which was comparable to that of commercial Gd-based CAs (at standard dose 0.1 mmol/kg), even at its 4 times lower administered dose (0.025 mmol/kg). Importantly, no signs of toxicity were detected in vivo. In addition, it showed a selective accumulation in brain tumor tissues, exhibiting longer retention within the tumor, which allows performing imaging acquisition over longer time frames (≥2.5 h) as opposed to Gd chelates. Finally, we observed high stability of the radicals in biological media, on the order of hours instead of minutes, characteristic of the isolated radicals. All of these features allow us to suggest that the G3-Tyr-PROXYL-ONa radical dendrimer could be a viable alternative to metal-based MRI contrast agents, particularly on MRI analysis of GB, representing, to the best of our knowledge, the first case of organic radical species used for this purpose and one of the very few examples of these types of radical species working as MRI CAs in vivo.

Project description:ObjectivesCurrently, administering contrast agents is necessary for accurately visualizing and quantifying presence, location, and extent of myocardial infarction (MI) with cardiac magnetic resonance (CMR). In this study, our objective is to investigate and analyze pre- and post-contrast CMR images with the goal of predicting post-contrast information using pre-contrast information only. We propose methods and identify challenges.MethodsThe study population consists of 272 retrospectively selected CMR studies with diagnoses of MI (n = 108) and healthy controls (n = 164). We describe a pipeline for pre-processing this dataset for analysis. After data feature engineering, 722 cine short-axis (SAX) images and segmentation mask pairs were used for experimentation. This constitutes 506, 108, and 108 pairs for the training, validation, and testing sets, respectively. We use deep learning (DL) segmentation (UNet) and classification (ResNet50) models to discover the extent and location of the scar and classify between the ischemic cases and healthy cases (i.e., cases with no regional myocardial scar) from the pre-contrast cine SAX image frames, respectively. We then capture complex data patterns that represent subtle signal and functional changes in the cine SAX images due to MI using optical flow, rate of change of myocardial area, and radiomics data. We apply this dataset to explore two supervised learning methods, namely, the support vector machines (SVM) and the decision tree (DT) methods, to develop predictive models for classifying pre-contrast cine SAX images as being a case of MI or healthy.ResultsOverall, for the UNet segmentation model, the performance based on the mean Dice score for the test set (n = 108) is 0.75 (±0.20) for the endocardium, 0.51 (±0.21) for the epicardium and 0.20 (±0.17) for the scar. For the classification task, the accuracy, F1 and precision scores of 0.68, 0.69, and 0.64, respectively, were achieved with the SVM model, and of 0.62, 0.63, and 0.72, respectively, with the DT model.ConclusionWe have presented some promising approaches involving DL, SVM, and DT methods in an attempt to accurately predict contrast information from non-contrast images. While our initial results are modest for this challenging task, this area of research still poses several open problems.

Dataset Information

A Metal-Free Method for Producing MRI Contrast at Amyloid-?.

Publications

A Metal-Free Method for Producing MRI Contrast at Amyloid-β.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets