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RT_Image: An Open-Source Tool for Investigating PET in Radiation Oncology (p. 111-122)
Positron emission tomography (PET) has emerged as a valuable imaging modality for the diagnosis and staging of cancer. However, despite evidence that PET may be useful for defining target volumes for radiation therapy, no standardized methodology for accomplishing this task exists. To facilitate the investigation of the utility of PET imaging in radiotherapy treatment planning and accelerate its integration into clinical radiation oncology, we have developed software for exploratory analysis and segmentation of functional imaging datasets.
The application, RT_Image, allows display of multiple imaging datasets and associated three-dimensional regions-of-interest (ROIs) at arbitrary view angles and fields of view. It also includes semi-automated image segmentation tools for defining metabolically active tumor volumes that may aid creation of target volumes for treatment planning. RT_Image is DICOM compliant, permitting the transfer of imaging data and DICOM-RT structure sets between the application and treatment planning software.
RT_Image has been used by radiation oncologists, nuclear medicine physicians, and radiation physicists to analyze over 200 PET datasets. Novel segmentation techniques have been implemented within this programming framework for therapy planning and for evaluation of molecular imaging-derived parameters as prognostic indicators.
RT_Image represents a freely-available software base on which further investigations of the utlity of PET and molecular imaging in radiation oncology may be built. The development of tools such as this is critical in order to realize the potential of molecular imaging-guided radiation therapy.
Keywords: Positron Emission Tomography; Radiation therapy; Image processing; and Image segmentation.
TCRT April 2007
No. 2 (p 57-150)
Featured ImageOzyigit, G., Cengiz, M, Hurmuz, P, Yazici, G, Gultekin, M, Akyol, F., Yildiz, F, Gurkaynak, M, Zorlu, F. (2013) Robotic Stereotactic Radiosurgery in Patients with Nasal Cavity and Paranasal Sinus Tumors. Technol Cancer Res Treat Ahead of Print Aug. 31 2013. http://www.tcrt.org/product-18090.html