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New Technology Enhances Lung Cancer Detection

Date:
December 4, 2003
Source:
University Hospitals Of Cleveland
Summary:
Lung cancer is rarely diagnosed in its early stages, but new digital technology available at University Hospitals of Cleveland (UHC) is significantly enhancing a physician's ability to diagnose this deadly disease when it is most treatable.
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CLEVELAND -- Lung cancer is rarely diagnosed in its early stages, but new digital technology available at University Hospitals of Cleveland (UHC) is significantly enhancing a physician's ability to diagnose this deadly disease when it is most treatable. Essentially, the new technology adds a pair of "digital eyes" with an extensive database that automatically highlights suspicious lung tissue, alerting the radiologist and improving sensitivity by more than 20 percent.

The Department of Radiology at UHC is the first in the world to use GE's RapidScreen Digital, a new digital computer-aided detection (CAD) device for x-ray detection of lung cancer. UHC is the clinical test site for the innovative technology, and applies it to the 160,000 chest X-rays performed each year. At the heart of RapidScreen Digital is a sophisticated post-processing algorithm that analyzes the digital x-ray data and draws circles around suspicious regions of interest. The new CAD system, also used for mammography at UHC, focuses the attention of radiologists on these potential abnormalities.

"As a tertiary care center, we see a lot of complex cases," says Dr. Robert Gilkeson, assistant professor of radiology and director of cardiothoracic imaging at UHC and Case Western Reserve University School of Medicine. "RapidScreen allows us to make significant improvements in detecting lung cancer. UHC has a very large cancer patient population with a significant amount of chest disease. This technology will be very helpful in evaluating those patients."

Dr. Gilkeson and his team are using the new CAD system in conjunction with another advancement in digital X-ray technology called "dual energy subtraction." The radiologist can literally erase bones from the image to study the soft tissue normally hidden by the ribs and sternum. According to a thoracic imaging study published in Radiology in January (Volume 226, Number 1), more than 90% of lung cancers that are missed today lie behind bone structures. With the "subtraction" of bone from the image, the detection of these hidden cancers is obviously easier.

"Dual energy subtraction makes a significant difference in the evaluation and diagnosis of 15 to 20% of our cases," says Dr. Gilkeson. "It is particularly valuable in distinguishing benign from malignant nodules, in addition to improving our analysis of other lung diseases such as asbestos plural disease."

Lung cancer is the number one cancer killer in the United States and worldwide. Studies have shown that early detection is critical to successful treatment. According to the American Cancer Society, the overall five-year survival rate is less than 15 percent.

However when lung cancer is found in the early stages, the five-year survival rate increases to more than 50 percent. Currently, only 15 percent of lung cancer is detected in the early, most treatable stages.

Dr. Gilkeson will be presenting on these promising new technologies in the detection of lung cancer at the upcoming Radiological Society of North America (RSNA) conference in Chicago from November 30 to December 5, 2003.


Story Source:

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


Cite This Page:

University Hospitals Of Cleveland. "New Technology Enhances Lung Cancer Detection." ScienceDaily. ScienceDaily, 4 December 2003. <www.sciencedaily.com/releases/2003/12/031204074705.htm>.
University Hospitals Of Cleveland. (2003, December 4). New Technology Enhances Lung Cancer Detection. ScienceDaily. Retrieved May 22, 2015 from www.sciencedaily.com/releases/2003/12/031204074705.htm
University Hospitals Of Cleveland. "New Technology Enhances Lung Cancer Detection." ScienceDaily. www.sciencedaily.com/releases/2003/12/031204074705.htm (accessed May 22, 2015).

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