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The aim of this work is to describe the technical characteristics of anAI-powered radiotherapy workflow that enables full-process automation(All-in-One), evaluate its performance implemented for on-couch initialtreatment of rectal cancer, and provide insight into the behavior offull-workflow automation in the specialty of radiotherapy. The All-in-Oneworkflow was developed based on a CT-integrated linear accelerator. Itincorporates routine radiotherapy procedures from simulation, autosegmentation,autoplanning, image guidance, beam delivery, and in vivo quality assurance (QA)into one scheme, with critical decision points involved, while the patient ison the treatment couch during the whole process. For the enrolled ten patientswith rectal cancer, minor modifications of the autosegmented target volumeswere required, and the Dice similarity coefficient and 95% Hausdorff distancebefore and after modifications were 0.892{\pm}0.061 and 18.2{\pm}13.0 mm,respectively. The autosegmented normal tissues and automatic plans wereclinically acceptable without any modifications or reoptimization. Thepretreatment IGRT corrections were within 2 mm in all directions, and theEPID-based in vivo QA showed a {\gamma} passing rate better than 97{\%}(3{\%}/3 mm/10{\%} threshold). The duration of the whole process was23.2{\pm}3.5 minutes, depending mostly on the time required for manualmodification and plan evaluation. The All-in-One workflow enables fullautomation of the entire radiotherapy process by seamlessly integratingmultiple routine procedures. The one-stop solution shortens the time scale ittakes to ready the first treatment from days to minutes, significantlyimproving the patient experience and the efficiency of the workflow, and showspotential to facilitate the clinical application of online adaptive replanning.

First implementation of full-workflow automation in radiotherapy: the All-in-One solution on rectal cancer