Radiotherapy Workflow Automation
Radiotherapy Workflow Automation - Related Videos
09:23
Integrating Automated Simulation Workflows with 3D Visualization for Virtual Experiments in the Metaverse
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2026
A generalized, FAIR-compliant method is presented for domain-expert researchers seeking to integrate simulation and data-processing tools into automated workflows for 3D virtual experiments. A neutronics example demonstrates setting up a local Galaxy instance, wrapping OpenMC and file-conversion tools, launching workflows from Omniverse, and visualizing the converted 3D outputs.
11:38
Voluntary Breath-hold Technique for Reducing Heart Dose in Left Breast Radiotherapy
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Cited by 49 •
2014
The current priority in breast cancer radiotherapy is to reduce cardiac doses without compromising target tissue coverage. The voluntary breath-hold technique described here is a simple, inexpensive solution to this problem and capable of being instituted widely without the need for specialized equipment.
08:25
Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System
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Cited by 60 •
2018
Radiation therapy is a highly complex cancer treatment that requires multiple specialists to create a treatment plan and provide quality assurance (QA) prior to delivery to a patient. This protocol describes the use of a fully automated system, the Radiation Planning Assistant (RPA), to create high-quality radiation treatment plans.
11:24
Stem Cell Transplantation Strategies for the Restoration of Cognitive Dysfunction Caused by Cranial Radiotherapy
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Cited by 10 •
2011
Brain tumor patients routinely undergo cranial radiotherapy, and while beneficial, this treatment often results in debilitating cognitive dysfunction. This serious unresolved problem has at present, no clinical recourse, and has driven our efforts to devise stem cell based therapies for the recovery of radiation-induced cognitive decrements.
08:02
Combination Radiotherapy in an Orthotopic Mouse Brain Tumor Model
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Cited by 9 •
2012
The purpose of this article is to describe the use of an orthotopic glioblastoma model for chemoradiation studies. This article will go though cell processing, implanting, and radiotherapy of the mouse using an intracranial model.
FAQs
Its central mechanism is controlled movement of clinical information between connected systems. Data from imaging can pass into treatment planning and oncology information workflows, while predefined rules determine when tasks become ready or require review. Automated checks then look for missing or inconsistent information before the workflow advances, reducing dependence on manual handoffs.
Predefined protocols provide a common sequence for recurring clinical tasks, while task triggers connect one completed step to the next required action. This structure can help coordinate scheduling, contouring, plan review, quality assurance, and documentation without requiring staff to manage every transition manually. The result is a more consistent workflow in which omissions or conflicting information can be identified earlier.
Each system contributes a different part of the treatment pathway, so automation depends on reliable exchange among imaging, treatment-planning, oncology information, and linear-accelerator systems. If information is missing or inconsistent, automated checks can identify the problem during the workflow. This makes data coordination a safety and workflow concern, not merely an administrative one.
Updated patient anatomy can serve as a trigger for faster plan adjustments during a treatment course. In an automated workflow, that trigger links changing anatomical information to the need for plan review and possible modification, rather than treating each session as unrelated to prior information. This makes automation especially relevant when anatomy changes over time.
Automation is particularly relevant to scheduling, contouring and plan review, quality assurance, and treatment documentation. These tasks span coordination, clinical review, verification, and record keeping, so applying standardized rules can reduce variation in how work moves between teams. The stated benefits include greater workflow consistency, improved safety, and increased clinical capacity.
Useful outcomes include fewer manual handoffs, earlier identification of missing or inconsistent information, more consistent task execution, and improved capacity. In medicine, these outcomes matter because radiotherapy passes through several coordinated stages, from imaging and planning to verification, delivery, and follow-up. Reviewing them helps determine whether automation is improving safety and continuity across the clinical workflow.