Improved MRI scans could aid in development of arthritis treatments

An algorithm that analyses MRI images and automatically detects small changes in knee joints over time could be used in the development of new treatments for arthritis.

 A team of engineers, radiologists and physicians, led by the University of Cambridge, developed the algorithm, which builds a three-dimensional model of an individual's knee joint in order to map where arthritis is affecting the knee. It then automatically creates 'change maps' which not only tell researchers whether there have been significant changes during the study but allow them to locate exactly where these are.

There are few effective treatments for arthritis, and the technique could be a considerable boost to efforts to develop and monitor new therapies for the condition. The results are reported in the Journal of Magnetic Resonance Imaging. 

Osteoarthritis is the most common form of arthritis in the UK. It develops when the articular cartilage that coats the ends of bones and allows them to glide smoothly over each other at joints, is worn down, resulting in painful, immobile joints. Currently there is no recognised cure and the only definitive treatment is surgery for artificial joint replacement.

Osteoarthritis is normally identified on an X-ray by a narrowing of the space between the bones of the joint due to a loss of cartilage. However, X-rays do not have enough sensitivity to detect subtle changes in the joint over time.

 "We don't have a good way of detecting these tiny changes in the joint over time in order to see if treatments are having any effect," said Dr James MacKay from Cambridge's Department of Radiology, and the study's lead author. "In addition, if we're able to detect the early signs of cartilage breakdown in joints, it will help us understand the disease better, which could lead to new treatments for this painful condition."

The current study builds on earlier work from the same team, who developed an algorithm to monitor subtle changes in arthritic joints in CT scans. Now, they are using similar techniques for MRI, which provides more complete information about the composition of tissue - not just information about the thickness of cartilage or bone. 

MRI is already widely used to diagnose joint problems, including 

arthritis, but manually labelling each image is time-consuming, 

and may be less accurate than automated or semi-automated 

techniques when detecting small changes over a period of months 

or years.

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Method to detect pulmonary fibrosis discovered

As the researchers have discovered how the lung disease idiopathic pulmonary fibrosis (IPF) progresses, they will now be able to provide a method to discover new treatment targets for the disease.

In the study, researchers examined differentially affected regions in the lungs obtained from individuals with IPF and found that what looks like normal lung is already undergoing changes in specific genes.

They then tracked how these genes continue to change, increasing or decreasing, as the disease progresses.

A unique feature of the paper, said the researcher, is that it provides the first computational model of disease progression in the IPF lung and is accompanied by an interactive website exploring this model.

The researcher believes that widespread access to the data will accelerate research into new therapies in IPF.

Although the researcher noted that scientists at Yale and elsewhere have made "substantial scientific progress" on IPF in recent years, there are few treatment options.

IPF is a chronic disease in which the lungs become increasingly scarred and unable to function; it affects some 200,000 people in the U.S., with about 30,000 new cases each year.

Fifty per cent of patients with IPF will die in three to five years following diagnosis, and the cause of IPF is unknown.

The two FDA-approved drugs to treat IPF slow the progress of the disease, but do not reverse it.

"The drugs may not be pleasant, but they work," said the researcher, adding that, most importantly, "There's hope on the horizon."

Drug trials for IPF are ongoing, and this latest research, he said, should provide opportunities for researchers to identify new potential drug targets.

"My group has felt for years that to develop interventions for IPF that are more effective, we need to understand how the disease progresses in the human lung," the researcher said.

Animal models for IPF work to show how pulmonary fibrosis impacts the lungs, but not what regulates changes at the genetic level to drive IPF progression in humans.

The investigators used a unique system that allowed them to quantify the amount of fibrosis in differentially affected regions in the lung and then to measure the expression of all the genes in the human genome in exactly the same region by RNA sequencing.

They also measured micro-RNAs, small non-coding RNAs known to regulate the expression of genes.

They applied advanced systems biology methods to identify tracks of gene expression associated with the progression of IPF in the lung and the molecules that regulate them.

Using this approach, they made three key findings. First, they discovered that what looked like normal tissue in the diseased lung was in fact abnormal.

Second, they identified gene expression changes that were specific to tissue associated with early, progressive and end-stage fibrosis. Third, they identified distinct molecular regulators for each of these stages.

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