The development of an artificial placenta – used successfully in premature lambs – could revolutionize the treatment of extreme prematurity.
Researchers at the University of Michigan are working to improve survival rates in the tiniest, most premature babies in a ground-breaking way: through an artificial placenta that mimics the womb.
The technology hasn’t reached a clinical trial, but researchers from U-M’s C.S. Mott Children’s Hospital and Extracorporeal Circulation Research Laboratory are making dramatic progress. An extracorporeal artificial placenta at the institution has kept five extremely premature lambs alive for a week. The lambs were transferred to the artificial placenta, which utilizes extracorporeal membrane oxygenation (ECMO), without ever taking their first breath.
The ultimate goal of nearly a decade of sustained work would be for an artificial placenta to help extremely premature babies with the greatest risks of disability or death continue critical organ development outside of their mother’s womb.
Despite significant advances in the treatment of prematurity, the risk of death and long-term disability remains high for extremely premature infants (born before 24 weeks). Their bodies simply are not prepared for life outside the womb.
‘One of the gravest risks for extremely premature babies is undeveloped lungs that are too fragile to handle even the gentlest ventilation techniques,’ says George Mychaliska, M.D., the principal investigator and the director of U-M’s Fetal Diagnosis and Treatment Center. ‘If a baby’s lungs are severely immature, they cannot provide the brain, heart and other organs the oxygen they need to survive.’
Mychaliska, who has been referred to as Michigan’s ‘fetus fixer’ for his renowned fetal intervention work, has been leading research to improve outcomes for premature infants.
‘We thought, Why don’t we solve the problem of prematurity by re-creating the intrauterine environment?” he says. ‘Maybe we should treat this tiny baby like a fetus. Maybe we should treat these babies as if they are still in the womb. This is a complete paradigm shift. Our research is still in a very preliminary stage, but we’ve passed a significant milestone that gives us promise of revolutionizing the treatment of prematurity.
‘Although many of our current therapies are lifesaving, they are not designed for premature babies and are often ineffective or contribute to complications,’ he adds.
The innovative artificial placenta simulates the intrauterine environment and provides gas exchange without mechanical ventilation. By recapitulating normal fetal physiology to re-create the intrauterine environment, the artificial placenta holds the promise of normal growth and development outside the womb for extremely premature infants until they are ready for postnatal life.
The success of keeping lambs alive through this technique was a crucial milestone in securing a $2.7 million ( Euro 2.4 million) R01 National Institutes of Health grant to accelerate this research.
Over the next five years, researchers expect to demonstrate that an artificial placenta can simulate the intrauterine environment and support a foetal lamb from extreme prematurity to normal newborn physiology. The next step would be to determine if the milestones would justify preliminary clinical trials in extremely premature babies.

University of Michigan http://tinyurl.com/zzhz9o3

A team of Oxford University researchers has developed a technique that could improve heart scans for patients, giving more information about the heart than traditional scans and without any injections, making them safer and faster.
The group of medical, physics and engineering researchers are based at the Oxford Centre for Clinical Magnetic Resonance Research (OCMR). They are using a property of hydrogen atoms to create a pixel-by-pixel map of the heart, called a T1-map, which allows examination of healthy and diseased heart tissue in greater detail than before.
Currently, stress scans of the heart using magnetic resonance imaging (MRI) require patients to be injected with two substances. Adenosine is a medication injected into the patient that causes effects similar to exercise during the scan. Gadolinium – a rare earth heavy metal – is injected as a contrast agent to highlight areas of the heart suffering from decreased blood flow under exercise conditions.
Patients with severe kidney failure – who are usually at higher risk for heart disease – cannot clear Gadolinium and often are unable to benefit from a full MRI scan of the heart. T1-maps can potentially solve this problem in the future.
Dr Alexander Liu, who leads the research with the guidance of his supervisors – Dr. Vanessa Ferreira, Dr. Stefan Piechnik and Professor Neubauer (the centre director), explained: We wanted to see if using T1 mapping can give clearer, more clinically-useful results compared to traditional MRI scans that require injections of contrast agents. On traditional MRI scans, doctors are judging relative shades of light and dark on a scan, and even the most experienced specialists can disagree on what the image is showing them. T1 maps provide an objective number, which can be coded in colours, and may be less subjective. Additionally, patients with severe kidney failure – who are usually at higher risk for heart disease – cannot clear Gadolinium and often are unable to benefit from a full MRI scan of the heart. T1-maps can potentially solve this problem in the future.’
In physics, T1 is the time constant that describes how quickly atoms return to normal thermodynamic state after being affected by radio waves and strong magnetic fields. Just like measuring body temperature in Celsius or Fahrenheit, the numbers themselves may not mean much, but any deviation from established normal ranges can suggest disease. In the case of T1 mapping, long T1 times indicate the presence of more water, something found in a number of heart conditions, including areas of the heart suffering from lack of blood supply due to blocked arteries. A T1-map just helps to visualize T1 values across the heart and find the precise location of the problem. It takes around three minutes to map the whole heart, and the values it measures are turned into a colour map, giving doctors an image which is potentially quicker to understand with less subjective interpretation.
Dr Stefan Piechnik developed the specific T1 mapping technique at Oxford, named ShMOLLI. He said: T1 mapping allows us to look in finer detail at the heart in a non-invasive way, which has not been possible before. We can now get results without Gadolinium, meaning we have a technique that is safer and quicker and can be used with more people. The results are also less dependent on interpreting the images – medics have something based on hard numbers.’

Oxford University http://tinyurl.com/h4ruhca

Machine learning is a type of artificial intelligence that allows computer programs to learn when exposed to new data without being programmed. Now, researchers in The Netherlands have coupled machine learning methods with a special MRI technique that measures the perfusion, or tissue absorption rate, of blood throughout the brain to detect early forms of dementia, such as mild cognitive impairment (MCI), Radiology.
‘MRI can help with the diagnosis of Alzheimer’s disease,’ said principal investigator Alle Meije Wink, Ph.D., from the VU University Medical Centre in Amsterdam. ‘However, the early diagnosis of Alzheimer’s disease is problematic.’

Scientists have long known that Alzheimer’s disease is a gradual process and that the brain undergoes functional changes before the structural changes associated with the disease show up on imaging results. Physicians have no definitive way of identifying who has early dementia or which cases of mild cognitive impairment will progress to Alzheimer’s disease.

‘With standard diagnostic MRI, we can see advanced Alzheimer’s disease, such as atrophy of the hippocampus,’ Dr. Meije Wink said. ‘But at that point, the brain tissue is gone and there’s no way to restore it. It would be helpful to detect and diagnose the disease before it’s too late.’

For the new study, the researchers applied machine learning methods to special type of MRI called arterial spin labelling (ASL) imaging. ASL MRI is used to create images called perfusion maps, which show how much blood is delivered to various regions of the brain.

The automated machine learning program is taught to recognize patterns in these maps to distinguish among patients with varying levels of cognitive impairment and predict the stage of Alzheimer’s disease in new (unseen) cases.
The study included 260 of 311 participants from the Alzheimer Center of the VU University Medical Center dementia cohort who underwent ASL MRI between October 2010 and November 2012.

The study group included 100 patients diagnosed with probable Alzheimer’s disease, 60 patients with mild cognitive impairment (MCI) and 100 patients with subjective cognitive decline (SCD), and 26 healthy controls.
SCD and MCI are considered to be early stages of the dementia process and are diagnosed based on the severity of cognitive symptoms, including memory loss and thought- and decision-making problems.

The automated system was able to distinguish effectively among participants with Alzheimer’s disease, MCI and SCD. Using classifiers based on the automated machine learning training, the researchers were then able to predict the Alzheimer’s diagnosis or progression of single patients with a high degree of accuracy, ranging from 82 percent to 90 percent.
‘ASL is a promising alternative functional biomarker for the early diagnosis of Alzheimer’s disease,’ Dr. Meije Wink said.

Radiological Society of North Americawww2.rsna.org/timssnet/media/pressreleases/14_pr_target.cfm?ID=1890

A study led by investigators from the Ragon Institute of MGH, MIT and Harvard finds evidence that antibody protection may help control infection with the bacteria that causes tuberculosis (TB). In their study the research team describes finding consistent differences in both the structure and function of antibodies targeting the TB bacteria between individuals with active TB disease and those with latent TB, which neither produces symptoms nor can be transmitted. The findings may lead to better ways of distinguishing between active and latent disease and to a more effective vaccine against a disease that kills more than 1.5 million people each year.

‘Ending tuberculosis by 2030 is one of the targets of the World Health Organization’s newly adopted Sustainable Developmental Goals,’ says Lenette Lu, MD, PhD, of the Ragon Institute and the Massachusetts General Hospital (MGH) Department of Medicine. ‘A more effective vaccine against TB could substantially contribute towards that goal, impacting the nearly one in three people worldwide who are infected and addressing the leading killer of individuals infected with HIV.’

The only currently available preventive against infection with the TB bacteria – the BCG vaccine – has been available since the 1920s; but its effectiveness against pulmonary TB, the most common form of the disease, has always been uncertain. BCG is believed to work by stimulating cellular immunity, which is carried out by specialized immune cells including T cells and the macrophages that are directly infected by TB bacteria. Previous investigations into a possible role for antibodies in the immune response to TB have had conflicting results, but the Ragon team – led by Galit Alter, PhD, of MGH Department of Medicine and Sarah Fortune, MD, of the Harvard T.H. Chan School of Public Health – used a novel approach.

In addition to binding to their target pathogens and marking them for destruction by the immune system, antibodies also directly stimulate pathogen-killing cells of the innate immune system by binding to a cell-surface protein called the Fc receptor. The Ragon team profiled TB-specific antibodies from 22 individuals with latent TB and 20 with active TB for 70 different features associated with Fc-mediated antibody function. They first identified nine characteristics that differentiated between antibodies of the two groups of participants, and further investigation identified the biomarker that best distinguished between them.

A key regulator of Fc-mediated immune function is the addition to antibodies of compounds called glycans, made up of sugar molecules; and distinct differences in glycosylation patterns were found to clearly distinguish latent TB antibodies from active TB antibodies. To confirm these results in the initial group of participants, who were from South Africa, the team conducted a similar analysis of antibodies from 20 individuals from Texas and Mexico – half with latent and half with active TB – and had the same results. Further experiments revealed that application of latent TB antibodies to TB-infected human macrophages not only increased the activation of several antimicrobial processes but also reduced the survival of the TB bacteria.

Co-lead author Amy Chung, PhD, now at the Peter Doherty Institute for Infection and Immunity in Melbourne, Australia – a joint venture between The University of Melbourne and The Royal Melbourne Hospital – explains, ‘This is a completely new area of immune research in tuberculosis, since these antibodies don’t just recognize the infection, they also recruit immune cells to target it. People with latent infection have inactive disease for a reason, and if antibodies are playing a role in controlling the infection, the mechanism they use could be harnessed for future vaccine development.’

Alter, an associate professor of Medicine at Harvard Medical School, adds, ‘The diagnostic potential of these findings should not be overlooked. The detection of Fc-related modifications of TB-specific antibodies could be easily translated into a rapid, inexpensive point-of-care diagnostic that could have enormous public health impact, particularly in those parts of the globe where TB is endemic.’

Massachusetts General Hospitalwww.massgeneral.org/about/pressrelease.aspx?id=1992

A new study from the Medical Research Council Lifecourse Epidemiology Unit, University of Southampton, shows lesions, which can best be seen on MRI scans, could help identify individuals who are more likely to suffer from more rapidly progressing osteoarthritis.
The SEKOIA study, a major international osteoarthritis disease-modifying trial, carried out MRI scanning on the knees of 176 men and women over 50 years old. They were then followed up for an average of three years with repeated knee X-rays. Individuals with abnormalities on their MRI scans at the first appointment were compared to those without to examine the effect on disease progression.
Individuals with bone marrow lesions (BMLs) on their MRI scan were found to have osteoarthritis that progressed more rapidly than those that did not. On average, the space within the joint is lost at a rate of 0.15mm per year however the Southampton study shows that, overall, individuals with BMLs had a loss rate that was 0.10mm per year faster than those without BMLs. This may lead to earlier need for joint replacement or other intervention.
BMLs show up on MRI as regions of bone beneath the cartilage with ill-defined high signal and represent areas of bone marrow edema, fibrosis, and necrosis. The Southampton researchers believe that therapies to target these abnormalities may slow the progression of this disabling joint disease, but further work is required to examine this.

University of Southampton http://tinyurl.com/zgoujax