Computed tomography (CT) has become increasingly important in radiotherapy planning: CT add-ons have been introduced for therapy simulators, and specialized CT scanners have been developed as stand-alone therapy planning systems. However, because of therapy simulator limitations, CT add-ons have poor throughput and thus cannot create sufficient image slices for adequate therapy planning. CT-based simulators have better throughput, but the CT data they produce does not have accurate enough positional information, since they do not duplicate the physical environment of therapy machines. We plan to improve throughput of CT add-on equipment by using volume CT imaging. Current CT add-ons use line sensor cameras or linear detector arrays in front of the simulator's image intensifier. These detectors are used because the image intensifier camera lacks the dynamic range necessary for scanning large fields of view (such as the size of the human body). We propose to use a dual camera and optics scheme that will solve the dynamic range problem and allow volume reconstruction to be performed on large data sets. If successful, this technique will increase throughput by 300% using research already proven at BIR, and further improvements are foreseen which will be started in Phase I and continued in Phase II.
A product that solves the imaging problems associated with CT add-ons will have large market potential with the hundreds of hospitals that use x-ray therapy simulators. Evidence of the market potential can be seen in the fact that current CT add-ons, offering comparatively poor performance, are now being purchased.
