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The introduction of adaptive image-guided radiotherapy (ART) has contributed to the rapid accumulation of spatiotemporal medical image data, often making it difficult to consolidate information on a single patient. For oncology patients, the lack of data integration can negatively impact on patient care. We developed a volume visualization system with augmented reality interaction to display radiotherapy plan contents including computed tomography (CT) images, dose distribution, and mesh models of radiotherapy targets. This system also provided quantitative indices about the radiotherapy dose coverage based on composite measurement of surface distance and volume difference between target volume and the volume of multiple isodose levels. The dose coverage data of a radiotherapy plan could be incorporated as feedback for deriving "accept or reject" decisions to improve the quality of radiotherapy on an individual patient basis using the surface distance comparison methods for different volumes.