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Dentists Could Detect Osteoporosis, Automatically

Date:
January 5, 2007
Source:
University of Manchester
Summary:
Researchers in the School of Dentistry at the University of Manchester have created a unique way of identifying osteoporosis sufferers from ordinary dental x-rays.

Researchers in the School of Dentistry at The University of Manchester have created a unique way of identifying osteoporosis sufferers from ordinary dental x-rays.

Professor Keith Horner and Dr Hugh Devlin co-ordinated a three year, EU-funded collaboration with the Universities of Athens, Leuven, Amsterdam and Malmo, to develop the largely automated approach to detecting the disease. Their findings are published online by the Elsevier journal Bone.

Osteoporosis affects almost 15% of Western women in their fifties, 22% in their sixties and 38.5% in their seventies. As many as 70% of women over 80 are at risk*, and the condition carries a high risk of bone fractures - over a third of adult women falling victim at least once in their lifetime.

Despite these figures and pressure from the EU to improve the identification of people at risk, wide-scale screening for the disease is not currently viable - largely due to the cost and scarcity of specialist equipment and staff.

The team has therefore developed a revolutionary, software-based approach to detecting osteoporosis during routine dental x-rays, by automatically measuring the thickness of part of the patient's lower jaw.

X-rays are used widely in the NHS to examine wisdom teeth, gum disease and during general check-ups, and their use is on the rise. In 2005 almost 6000 were taken on female patients aged 65 or over in a single month, and the number taken has increased by 181% since 1981**.

To harness these high usage-rates, the team has drawn on 'active shape modeling' technology developed by the University's Division of Imaging Sciences to automatically detect jaw cortex widths of less than 3mm - a key indicator of osteoporosis - during the x-ray process, and alert the dentist.

Professor Horner explained: "At the start of our study we tested 652 women for osteoporosis using the current 'gold standard', and highly expensive, DXA test. This identified 140 sufferers.

"Our automated X-ray test immediately flagged-up over half of these. The patients concerned may not otherwise have been tested for osteoporosis, and in a real-life situation would immediately be referred for conclusive DXA testing.

"This cheap, simple and largely-automated approach could be carried out by every dentist taking routine x-rays, yet the success rate is as good as having a specialist consultant on hand."

Dr Devlin continued: "As well as being virtually no extra work for the dentist, the diagnosis does not depend on patients being aware that they are at risk of the disease. Just by introducing a simple tool and getting healthcare professionals working together, around two in five sufferers undertaking routine dental x-rays could be identified.

"We're extremely encouraged by our findings, and keen to see the approach adopted within the NHS. The next stage will be for an x-ray equipment company to integrate the software with its products, and once it's available to dentists we'd hope that entire primary care trusts might opt in.

"The test might even encourage older women to visit the dentist more regularly!"


Story Source:

The above story is based on materials provided by University of Manchester. Note: Materials may be edited for content and length.


Cite This Page:

University of Manchester. "Dentists Could Detect Osteoporosis, Automatically." ScienceDaily. ScienceDaily, 5 January 2007. <www.sciencedaily.com/releases/2007/01/070103110605.htm>.
University of Manchester. (2007, January 5). Dentists Could Detect Osteoporosis, Automatically. ScienceDaily. Retrieved September 15, 2014 from www.sciencedaily.com/releases/2007/01/070103110605.htm
University of Manchester. "Dentists Could Detect Osteoporosis, Automatically." ScienceDaily. www.sciencedaily.com/releases/2007/01/070103110605.htm (accessed September 15, 2014).

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