Philips unveils new MR, CT tools for radiation treatment planning

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At ASTRO (Annual American Society of Therapeutic Radiology and Oncology) this week in Philadelphia, Royal Philips strengthened its line-up of oncology systems with the announced availability of its Tumor LOC (tumor localization) application on the workstation, and unveiled Panorama 1.0T R/T, a high-field, open MR simulator.

Tumor LOC previously only has been available to departments that have the Philips Brilliance CT Big Bore, but Philips is making the software (version 3.5) available for purchase on the Extended Brilliance Workspace (EBW). The company expects that this will be beneficial for Brilliance Big Bore customers with large respiratory correlated workloads. Thus, the 4D tools found on the console now will be available on the workspace to help with a department’s efficiency. 

Tumor LOC includes features for viewing respiratory correlated CT datasets and analyzing motion of target and surrounding anatomy. Combined with remote reconstruction and pulmonary viewer, the EBW can become a 4D oncology workstation, Philips said.
Philips also highlighted the Panorama 1.0T with R/T option for radiation oncology that has received FDA clearance. The R/T option includes an external laser positioning system, an oncology tabletop with indexing, geometric distortion correction software and specialized imaging protocols. The open gantry of Panorama 1.0T allows for patient scanning in treatment position with immobilization devices or supine inclined for breast imaging. Precise patient alignment is achieved with a flat and rigid oncology table top modeled after the LINAC table and a set of MR-compatible immobilization devices.

Philips also highlighted its relatively new Model Based Segmentation (MBS) software to aid workflow for image-guided radiation therapy (IGRT). MBS is an upgrade on the company’s Pinnacle3 Radiation Therapy Planning system and can reduce the time it takes to contour tumors and anatomical structures and includes an anatomical library of 3D patient organ structure models. Users can drag and drop the models onto patient image data and the software automatically adapts to each patient’s anatomy. The library of anatomical models grows as new patient data are added, providing a unique ability to build a library based on regional demographic or clinical practice specialties, Philips said.