Flash CT Reduces Radiation Dose by Up to 90%

November 19, 2009

With its two rotating x-ray tubes, the Flash CT's enhanced speed and power allows children and overweight adults to be screened more effectively.

NYU Langone Medical Center is the first hospital in the Northeast to offer one of the world’s fastest and most radiation dose efficient computed tomography (CT) scanner. The Siemens SOMATOM Definition Flash can image ten times as fast as other clinical units, with an up to 90% dose reduction in radiation compared to conventional imaging. The scanner’s dual source technology allows NYU Langone Medical Center to provide new levels of patient care, especially for trauma, pediatric, cancer and cardiac patients.

“The new CT scanner allows us to produce high quality diagnostic images in the least amount of time and with the least amount of radiation,” said Michael Recht, MD, the Louis Marx Professor of Radiology and chair of the Department of Radiology at NYU Langone Medical Center.

With its two rotating x-ray tubes, the Flash CT’s enhanced speed and power allows children and overweight adults to be screened more effectively. Flash CT also turns off the radiation when it comes close to sensitive tissue areas of the body such as the thyroid gland or breasts, or lens of the eye. It also eliminates the need for a baseline scan prior to iodine injection, so the patient does not have to be scanned twice. Because of its speed, patients do not need to hold their breath, lay completely still during an exam or take a beta blocker to slow the speed of the heart to get clear images. Pediatric patients benefit because they don’t have to be sedated during the procedure.

“The Dual Energy technology of the new Flash CT provides higher contrast between normal and abnormal tissues making it easier to see abnormalities while reducing radiation” said Alec. J. Megibow, MD, MPH, FACR, professor of radiology at NYU Langone Medical Center. “Because we can now analyze findings by chemical composition, we predict that the unique information from this scanner may also better able predict which patients will have the best response to a proposed treatment regimen.”

Source: New York University Langone Medical Center