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Purposes: to implement and compare four newly developed image‐guided radiotherapy systems (Varian's Cone‐Beam CT, BrainLAB ExacTrac, Restitu Ultrasound (U/S)‐Sim and Guide, and in‐house stereovision) in one department. Methods and Materials: The cone‐beam CT (CBCT) and the ultrasound (US) systems provide volumetric images of the target at daily setup. The ExacTrac system acquires the biplanar radiographs at patient setup. Both the US and ExacTrac systems are integrated with infrared‐tracking systems for patient‐couch positioning. The in‐house stereovision system captures 3D surface images of the patient at the instants of daily patient setup and during individual beam irradiation. All of four IGRT systems have used treatment planning volumetric imaging information for target position verification and adjustment. Electronic portal images are routinely used for patient position verification. External markers and possible internal markers such as seeds or small cysts or calcifications can be localized and used for additional verification. Results: Emerging data from several institutional IRB‐approved clinical trials demonstrate that the target reposition error and dose delivery uncertainties can be significantly reduced by using such image‐guided systems, each of which may be most useful in specific clinical situations. Conclusions: Our customized stereovision system, which, like US, involves no radiation exposure, is extremely efficient (<2 minutes) and accurate (<2 millimeters) for superficial sites, such as breast cancer. The ExacTrac system appears ideal for lesions associated with bony structures, such as spine and skull. The US and CBCT may be most useful for deformable internal structures, such as prostate cancer. Special methods for dealing with imaging artifacts, such as ring patterns in CBCT, shadow casts and multiple reflections in stereovision and US, and patient motion in ExacTrac and stereovision will be presented.

Purpose: To investigate an efficient method for assessing the impact of target deviations detected by daily image‐guidance on planning volumes. We hypothesize that, using this method, on‐line daily correction may not be warranted. Method and Materials: Geometrical surface models of the CTV and PTV were generated from the respective planning volumes via a surface reconstruction algorithm. Given a set of target deviations, represented by 6‐degree positioning shifts (translation, pitch, roll, yaw) from IGRT systems (e.g. Varian's OBI/CBCT), collision detection was performed to find geometric distance between CTV and PTV surface models when the shifts are applied to the CTV. Since the method is based on shifts, which do not incorporate intra‐fraction motion, a criterion was defined such that on‐line shifts are not applied if the CTV and PTV surfaces are greater than a distance defined by a population‐based margin for intra‐fraction motion. Results: A software module was developed to: import IMRT plans, generate surface models, communicate with the IGRT system, and calculate CTV/PTV spatial geometric distances. Surface model generation is performed off‐line. Collision detection between CTV and PTV surface models from daily shifts is done on‐line within minutes on a desktop PC. In the examples shown, “collisions” are defined by minimum distances of 3 mm in any direction (intrafraction motion margin) between the CTV and PTV. If a collision is detected, an on‐line shift is applied; otherwise the treatment proceeds as planned. Conclusions: The proposed method represents a quick and quantitative way to manage target deviations determined during image‐guidance, without the need to apply on‐line corrections. The approach is not limited to target analysis, but may also include normal tissues, such as the bladder and rectum. Adaptive and on‐line treatment planning studies are under way to determine the validity of the hypothesis, and to improve the collision detection criteria.

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