SP-0004 IMAGE-GUIDED ADAPTIVE RADIOTHERAPY (IGART): STATE OF THE ART

Abstract

Image-guided adaptive radiation therapy (IGART) uses patient-specific dynamic and/or temporal information for treatment planning and potential plan modification during the treatment course. The overarching goal of IGART is to employ routine imaging techniques to provide feedback information that is then used to re-optimize the treatment plan. With the advent of high quality on-board imaging modalities including kilovoltage (kV) cone beam computed tomography (CBCT) and megavoltage-CBCT (MV-CBCT), a natural progression has been made toward using these datasets for IGART. Having this volumetric data provides feedback on location, shape, and displacement of both target and nearby organs at risk, thereby providing an opportunity for online positional correction and adaptive planning. This session provides an overview of the state of the art for IGART, highlights different adaptive planning strategies, and describes both the opportunities and challenges of implementing an IGART program in a clinical setting. In the simplest sense, many clinics are currently implementing IGART in the context of online repositioning (i.e. instituting couch repositioning after daily images are rigidly registered to the reference images (digitally reconstructed radiographs or the treatment planning CT)). While rigid registration is efficient, it does not reflect voxel-tovoxel anatomy mapping, and can be problematic in instances of target/OAR deformation or anatomy changes. A more complex IGART approach can include an offline replanning strategy that involves reoptimization of the plan based on multiple imaging fractions as the feedback loop to derive modified margins, or applies dose accumulation by employing deformable image registration (DIR). A major limitation preventing widespread clinical acceptance of IGART is a lack of robust, real-time DIR algorithms and dose reconstruction methods that can be readily integrated into routine clinical workflow. Furthermore, DIR quality can be difficult to assess, and accurate dose accumulation requires high quality displacement vector fields (DVFs) generated via DIR. Online real-time IGART plan adaptation, involving full treatment plan re-optimization using the patient’s pre-treatment images, would be ideal. Plan reoptimization can account for inter-fraction changes such as systematic organ displacement, which may not be possible with couch repositioning alone. Historically, online plan adaptation was difficult to achieve in near real-time, with the patient immobilized on the treatment table. However, improvements in computing technology such as the use of graphics processing units (GPUs) are making this a more viable option. The IGART process is further complicated by both physiological and anatomical changes that can arise from tumor regression, inflammation, and normal tissue response. Furthermore, current online imaging techniques may not fully demonstrate the residual microscopic extent of disease, and caution must be exercised for plan adaptation. Having response or metabolic activity assessment, through a PET-CT or other functional imaging, during the treatment course may help with more meaningful treatment plan adaptation. This session will address specific challenges and practical solutions in the application of IGART to treatment sites, including prostate and lung cancers, based on our institutional experience in tandem with the published literature. Consideration is also given to emerging topics in IGART such as the incorporation of biological feedback. Finally, some next steps are outlined to simplify adaptive planning strategies so that they may be better streamlined into clinical practice.