Tag Archives: Army Research Office

New iron oxide nanoparticle as an MRI (magnetic resonance imaging) contrast agent

This high-resolution transmission electron micrograph of particles made by the research team shows the particles’ highly uniform size and shape. These are iron oxide particles just 3 nanometers across, coated with a zwitterion layer. Their small size means they can easily be cleared through the kidneys after injection. Courtesy of the researchers

A Feb. 14, 2017 news item on ScienceDaily announces a new MRI (magnetic resonance imaging) contrast agent,

A new, specially coated iron oxide nanoparticle developed by a team at MIT [Massachusetts Institute of Technology] and elsewhere could provide an alternative to conventional gadolinium-based contrast agents used for magnetic resonance imaging (MRI) procedures. In rare cases, the currently used gadolinium agents have been found to produce adverse effects in patients with impaired kidney function.

A Feb. 14, 2017 MIT news release (also on EurekAlert), which originated the news item, provides more technical detail,


The advent of MRI technology, which is used to observe details of specific organs or blood vessels, has been an enormous boon to medical diagnostics over the last few decades. About a third of the 60 million MRI procedures done annually worldwide use contrast-enhancing agents, mostly containing the element gadolinium. While these contrast agents have mostly proven safe over many years of use, some rare but significant side effects have shown up in a very small subset of patients. There may soon be a safer substitute thanks to this new research.

In place of gadolinium-based contrast agents, the researchers have found that they can produce similar MRI contrast with tiny nanoparticles of iron oxide that have been treated with a zwitterion coating. (Zwitterions are molecules that have areas of both positive and negative electrical charges, which cancel out to make them neutral overall.) The findings are being published this week in the Proceedings of the National Academy of Sciences, in a paper by Moungi Bawendi, the Lester Wolfe Professor of Chemistry at MIT; He Wei, an MIT postdoc; Oliver Bruns, an MIT research scientist; Michael Kaul at the University Medical Center Hamburg-Eppendorf in Germany; and 15 others.

Contrast agents, injected into the patient during an MRI procedure and designed to be quickly cleared from the body by the kidneys afterwards, are needed to make fine details of organ structures, blood vessels, and other specific tissues clearly visible in the images. Some agents produce dark areas in the resulting image, while others produce light areas. The primary agents for producing light areas contain gadolinium.

Iron oxide particles have been largely used as negative (dark) contrast agents, but radiologists vastly prefer positive (light) contrast agents such as gadolinium-based agents, as negative contrast can sometimes be difficult to distinguish from certain imaging artifacts and internal bleeding. But while the gadolinium-based agents have become the standard, evidence shows that in some very rare cases they can lead to an untreatable condition called nephrogenic systemic fibrosis, which can be fatal. In addition, evidence now shows that the gadolinium can build up in the brain, and although no effects of this buildup have yet been demonstrated, the FDA is investigating it for potential harm.

“Over the last decade, more and more side effects have come to light” from the gadolinium agents, Bruns says, so that led the research team to search for alternatives. “None of these issues exist for iron oxide,” at least none that have yet been detected, he says.

The key new finding by this team was to combine two existing techniques: making very tiny particles of iron oxide, and attaching certain molecules (called surface ligands) to the outsides of these particles to optimize their characteristics. The iron oxide inorganic core is small enough to produce a pronounced positive contrast in MRI, and the zwitterionic surface ligand, which was recently developed by Wei and coworkers in the Bawendi research group, makes the iron oxide particles water-soluble, compact, and biocompatible.

The combination of a very tiny iron oxide core and an ultrathin ligand shell leads to a total hydrodynamic diameter of 4.7 nanometers, below the 5.5-nanometer renal clearance threshold. This means that the coated iron oxide should quickly clear through the kidneys and not accumulate. This renal clearance property is an important feature where the particles perform comparably to gadolinium-based contrast agents.

Now that initial tests have demonstrated the particles’ effectiveness as contrast agents, Wei and Bruns say the next step will be to do further toxicology testing to show the particles’ safety, and to continue to improve the characteristics of the material. “It’s not perfect. We have more work to do,” Bruns says. But because iron oxide has been used for so long and in so many ways, even as an iron supplement, any negative effects could likely be treated by well-established protocols, the researchers say. If all goes well, the team is considering setting up a startup company to bring the material to production.

For some patients who are currently excluded from getting MRIs because of potential side effects of gadolinium, the new agents “could allow those patients to be eligible again” for the procedure, Bruns says. And, if it does turn out that the accumulation of gadolinium in the brain has negative effects, an overall phase-out of gadolinium for such uses could be needed. “If that turned out to be the case, this could potentially be a complete replacement,” he says.

Ralph Weissleder, a physician at Massachusetts General Hospital who was not involved in this work, says, “The work is of high interest, given the limitations of gadolinium-based contrast agents, which typically have short vascular half-lives and may be contraindicated in renally compromised patients.”

The research team included researchers in MIT’s chemistry, biological engineering, nuclear science and engineering, brain and cognitive sciences, and materials science and engineering departments and its program in Health Sciences and Technology; and at the University Medical Center Hamburg-Eppendorf; Brown University; and the Massachusetts General Hospital. It was supported by the MIT-Harvard NIH Center for Cancer Nanotechnology, the Army Research Office through MIT’s Institute for Soldier Nanotechnologies, the NIH-funded Laser Biomedical Research Center, the MIT Deshpande Center, and the European Union Seventh Framework Program.

Here’s a link to and a citation for the paper,

Exceedingly small iron oxide nanoparticles as positive MRI contrast agents by He Wei, Oliver T. Bruns, Michael G. Kaul, Eric C. Hansen, Mariya Barch, Agata Wiśniowsk, Ou Chen, Yue Chen, Nan Li, Satoshi Okada, Jose M. Cordero, Markus Heine, Christian T. Farrar, Daniel M. Montana, Gerhard Adam, Harald Ittrich, Alan Jasanoff, Peter Nielsen, and Moungi G. Bawendi. PNAS February 13, 2017 doi: 10.1073/pnas.1620145114 Published online before print February 13, 2017

This paper is behind a paywall.

Robo Brain; a new robot learning project

Having covered the RoboEarth project (a European Union funded ‘internet for robots’ first mentioned here in a Feb. 14, 2011 posting [scroll down about 1/4 of the way] and again in a March 12 2013 posting about the project’s cloud engine, Rapyuta and. most recently in a Jan. 14, 2014 posting), an Aug. 25, 2014 Cornell University news release by Bill Steele (also on EurekAlert with some editorial changes) about the US Robo Brain project immediately caught my attention,

Robo Brain – a large-scale computational system that learns from publicly available Internet resources – is currently downloading and processing about 1 billion images, 120,000 YouTube videos, and 100 million how-to documents and appliance manuals. The information is being translated and stored in a robot-friendly format that robots will be able to draw on when they need it.

The news release spells out why and how researchers have created Robo Brain,

To serve as helpers in our homes, offices and factories, robots will need to understand how the world works and how the humans around them behave. Robotics researchers have been teaching them these things one at a time: How to find your keys, pour a drink, put away dishes, and when not to interrupt two people having a conversation.

This will all come in one package with Robo Brain, a giant repository of knowledge collected from the Internet and stored in a robot-friendly format that robots will be able to draw on when they need it. [emphasis mine]

“Our laptops and cell phones have access to all the information we want. If a robot encounters a situation it hasn’t seen before it can query Robo Brain in the cloud,” explained Ashutosh Saxena, assistant professor of computer science.

Saxena and colleagues at Cornell, Stanford and Brown universities and the University of California, Berkeley, started in July to download about one billion images, 120,000 YouTube videos and 100 million how-to documents and appliance manuals, along with all the training they have already given the various robots in their own laboratories. Robo Brain will process images to pick out the objects in them, and by connecting images and video with text, it will learn to recognize objects and how they are used, along with human language and behavior.

Saxena described the project at the 2014 Robotics: Science and Systems Conference, July 12-16 [2014] in Berkeley.

If a robot sees a coffee mug, it can learn from Robo Brain not only that it’s a coffee mug, but also that liquids can be poured into or out of it, that it can be grasped by the handle, and that it must be carried upright when it is full, as opposed to when it is being carried from the dishwasher to the cupboard.

The system employs what computer scientists call “structured deep learning,” where information is stored in many levels of abstraction. An easy chair is a member of the class of chairs, and going up another level, chairs are furniture. Sitting is something you can do on a chair, but a human can also sit on a stool, a bench or the lawn.

A robot’s computer brain stores what it has learned in a form mathematicians call a Markov model, which can be represented graphically as a set of points connected by lines (formally called nodes and edges). The nodes could represent objects, actions or parts of an image, and each one is assigned a probability – how much you can vary it and still be correct. In searching for knowledge, a robot’s brain makes its own chain and looks for one in the knowledge base that matches within those probability limits.

“The Robo Brain will look like a gigantic, branching graph with abilities for multidimensional queries,” said Aditya Jami, a visiting researcher at Cornell who designed the large-scale database for the brain. It might look something like a chart of relationships between Facebook friends but more on the scale of the Milky Way.

Like a human learner, Robo Brain will have teachers, thanks to crowdsourcing. The Robo Brain website will display things the brain has learned, and visitors will be able to make additions and corrections.

The “robot-friendly format” for information in the European project (RoboEarth) meant machine language but if I understand what’s written in the news release correctly, this project incorporates a mix of machine language and natural (human) language.

This is one of the times the funding sources (US National Science Foundation, two of the armed forces, businesses and a couple of not-for-profit agencies) seem particularly interesting (from the news release),

The project is supported by the National Science Foundation, the Office of Naval Research, the Army Research Office, Google, Microsoft, Qualcomm, the Alfred P. Sloan Foundation and the National Robotics Initiative, whose goal is to advance robotics to help make the United States more competitive in the world economy.

For the curious, here’s a link to the Robo Brain and RoboEarth websites.