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Promising New Imaging Technology Precisely Tracks Lung Tumor Motion

Date:
October 5, 2004
Source:
University Of Pittsburgh Medical Center
Summary:
A new imaging technology may more precisely track tumor movement for patients under treatment for lung cancer than conventional 3D imaging. Results presented indicate that the new technology, 4D CT, or four-dimensional computed tomography, may allow radiation oncologists to determine and predict tumor movement based on the tumor's location in near real time.

ATLANTA, Oct. 4 – According to a study presented today by a University of Pittsburgh researcher at the 46th Annual Meeting of the American Society for Therapeutic Radiology and Oncology (ASTRO) in Atlanta, a new imaging technology may more precisely track tumor movement for patients under treatment for lung cancer than conventional 3D imaging. Results presented indicate that the new technology, 4D CT, or four-dimensional computed tomography, may allow radiation oncologists to determine and predict tumor movement based on the tumor's location in near real time.

"One of the major challenges in treating lung tumors with radiation is precisely targeting a moving tumor while simultaneously decreasing the amount of healthy tissue that may be exposed," said Dwight Heron, M.D., assistant professor of radiation oncology, University of Pittsburgh School of Medicine and vice chairman of radiation oncology, University of Pittsburgh Medical Center (UPMC) and study co-author. "Lung tumors are akin to moving targets. As a patient inhales and exhales, the tumor moves, making it challenging to target the tumor and to avoid exposure of radiation to the area that surrounds the tumor. By being able to predict tumor movement based on its location and attachment to the lung, we have the ability to more precisely target tumors with radiation therapy."

In the study, lung tumor motion was measured in 12 patients based on multiple images provided by 4D CT. Images were then sorted according to the phase of the respiratory cycle in which the image was acquired. Findings indicated that tumor motion correlated significantly with the position of the tumor on the lungs – tumors that moved more than 5 mm were located in the lower lobes of the lungs and those that moved the most were attached to the posterior, or back, of the lungs. Findings also indicated that tumors that were extensively attached to the chest wall or major airway moved the least.

"This technology is promising because it may improve our ability to develop more precise treatment plans for the delivery of radiation therapy to lung cancer patients and ensure the tumor receives the full amount of the treatment dose possible," said Dr. Heron. The technology was developed by GE Medical Systems.

"The better we understand lung tumor motion, the better radiation oncologists can plan radiotherapy treatments and track changes in lung tumors that might affect the efficacy of the treatment," said Edward Brandner, Ph.D., medical physicist at UPMC and co-author of the study.

The study's co-authors included Edward Brandner, Ph.D.; Andrew Wu, Ph.D.; Hungcheng Chen, M.S.; and Steven Burton, M.D., department of radiation oncology at the University of Pittsburgh; and Shalom Kalnicki, M.D., now of the department of radiation oncology, Montefiore Medical Center, New York.


Story Source:

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


Cite This Page:

University Of Pittsburgh Medical Center. "Promising New Imaging Technology Precisely Tracks Lung Tumor Motion." ScienceDaily. ScienceDaily, 5 October 2004. <www.sciencedaily.com/releases/2004/10/041005074303.htm>.
University Of Pittsburgh Medical Center. (2004, October 5). Promising New Imaging Technology Precisely Tracks Lung Tumor Motion. ScienceDaily. Retrieved April 19, 2014 from www.sciencedaily.com/releases/2004/10/041005074303.htm
University Of Pittsburgh Medical Center. "Promising New Imaging Technology Precisely Tracks Lung Tumor Motion." ScienceDaily. www.sciencedaily.com/releases/2004/10/041005074303.htm (accessed April 19, 2014).

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