To assess the impact of MLC tracking on target coverage and organ-at-risk (OAR) dose, the expected deviation between the planned and delivered dose must be quantified. Several methods have been proposed to compute the delivered dose based on offline dose reconstruction. [15][16][17][18] Recently, we have presented an online dose reconstruction solution for assessment of prostate SBRT, 19 which calculates and accumulates dose in real-time based on dose-influence data, while accounting for the machine/target motion interplay. Dose-influence **data** describe the influence of the fluence distribution on the patient dose. To make this approach applicable to dose calculation, the fluence distribution is subdivided into small rectangular segments, called bixels. Online dose reconstruction provides real-time quality assurance during treatment and provides the means to directly validate the performance of MLC tracking. Moreover, it is a prerequisite for replanning scenarios in which the treatment plan is changed on the fly during delivery. For example, drift motion might result in a gradually changing trade-off between target coverage and OAR dose which can be compensated for during delivery by replanning between beams.