Identifying Tissue Weakness Before Injury
This is an interesting technology demonstration that suggests an obvious pairing with regenerative treatments based on the use of stem cells or similar means to spur tissue repair. With regular scans it might be possible to preempt many instances of muscle and bone injury caused by use and stress, preventing them from ever developing by repairing tissue weak spots before they develop into injuries.
[Researchers] have developed algorithms to identify weak spots in tendons, muscles and bones prone to tearing or breaking. The technology, which needs to be refined before it is used in patients, one day may help pinpoint minor strains and tiny injuries in the body's tissues long before bigger problems occur. "Tendons are constantly stretching as muscles pull on them, and bones also bend or compress as we carry out everyday activities. Small cracks or tears can result from these loads and lead to major injuries. Understanding how these tears and cracks develop over time therefore is important for diagnosing and tracking injuries."[The researchers] developed a way to visualize and even predict spots where tissues are weakened. To accomplish this, they stretched tissues and tracked what happened as their shapes changed or became distorted. [They] combined mechanical engineering fundamentals with image-analysis techniques to create the algorithms, which were tested in different materials and in animal models. "The new algorithm allowed us to find the places where the tears were beginning to form and to track them as they extended. Older algorithms are not as good at finding and tracking localized strains as the material stretches."
In fact, one of the two new algorithms is 1,000 times more accurate than older methods at quantifying very large stretches near tiny cracks and tears, the research showed. And a second algorithm has the ability to predict where cracks and failures are likely to form. "This extra accuracy is critical for quantifying large strains. Commercial algorithms that estimate strain often are much less sensitive, and they are prone to detecting noise that can arise from the algorithm itself rather than from the material being examined. The new algorithms can distinguish the noise from true regions of large strains."