Finding Lost Bone Mass

New diagnostic techniques are making osteoporosis detection and diagnostic more accurate then ever. That’s good news for the 44 million people age 50 and over who are losing bone mass or density. Public health experts say osteoporosis affect 55 percent of Americans over 50.

Osteoporosis, or thinning bones, is generally a disease of aging, though certain medications can cause or accelerate bone loss at any age. Bone mass can start to decline as early as age 35, though it generally takes a while for the depletion to be significant enough, and fast enough, to constitute osteoporosis. Women, particularly thin white or Asian women, are especially prone to the condition, as are people with a family history of it. Smoking, drinking alcohol, and not getting enough calcium can all contribute.

Another thing that can contribute is breast cancer. Breast cancer and osteoporosis are both particularly common in post-menopausal women, since cancer risk goes up with age and bone loss is exacerbated by a drop in estrogen. In addition, however, breast cancer treatments can diminish bone tissue. Some cancer treatments involve deliberately reducing estrogen levels, temporarily or permanently; either way, it can lower bone density. Chemotherapy also affects bone mass. People being treated for breast cancer should be sure they’re getting enough vitamin D.

Bone loss often has no visible symptoms; it can go undetected for years until you experience a fracture. Stress fractures may occur simply as a result of everyday activities such as walking. A fall isn’t ordinarily enough to result in broken bones, but people with osteoporosis who fall often experience hip fractures.

Current tests for osteoporosis are imprecise, inferential, and subjective. Built around x-ray examination by doctors and technicians, they are prone to both false positives and false negatives; coming after a fracture has already happened, they are of limited usefulness at best for prevention of harm.

Now a new computer-based technique solves this problem. Using complex image recognition and reconstruction processes, it removes a great deal of the human element from diagnosis. This system is also sensitive to fine changes a human might miss, meaning it can detect signs of bone loss at a particularly early stage, allowing the patient to start treatment sooner rather than later. In testing, with patients whose osteoporosis was known, the algorithm had an error rate of under two percent.

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