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.
The Radiation Planning Assistant (RPA) is a system developed for the fully automated creation of radiotherapy treatment plans, including volume-modulated arc therapy (VMAT) plans for patients with head/neck cancer and 4-field box plans for patients with cervical cancer. It is a combination of specially developed in-house software that uses an application programming interface to communicate with a commercial radiotherapy treatment planning system. It also interfaces with a commercial secondary dose verification software. The necessary inputs to the system are a Treatment Plan Order, approved by the radiation oncologist, and a simulation computed tomography (CT) image, approved by the radiographer. The RPA then generates a complete radiotherapy treatment plan. For the cervical cancer treatment plans, no additional user intervention is necessary until the plan is complete. For head/neck treatment plans, after the normal tissue and some of the target structures are automatically delineated on the CT image, the radiation oncologist must review the contours, making edits if necessary. They also delineate the gross tumor volume. The RPA then completes the treatment planning process, creating a VMAT plan. Finally, the completed plan must be reviewed by qualified clinical staff.
In radiotherapy clinics, the International Atomic Energy Agency (IAEA) recommends 1 treatment planner per 300 patients, and 1 radiation physicist per 400 patients treated annually1. In many countries, these roles (treatment planner and physicist) are combined. In other countries, the radiation therapy technologists (often called radiographers) also take on a treatment planning role. Low- and middle-income countries (LMICs) have serious deficits in radiation oncologists, medical physicists and radiation therapy technologists. By 2020, it is estimated that we will need an additional 12,000 radiation oncologists, 10,000 medical physicists, and 29,000 technologists.2. These estimates are based on data from various data sets in the public domain (e.g., IAEA), with staffing levels based on recommendations from the European Society for Radiotherapy & Oncology (ESTRO) and IAEA3. The training needs are immense. For example, for medical physicists, most guidelines recommend a 2- to 3-year internship or residency, often after completion of medical physics graduate school4,5,6. This 4-year commitment means that 40,000 man-years of training are needed just to address the global deficiency in medical physicists alone.
Automation of treatment planning could reduce some of these staffing deficiencies, particularly medical physicists and planning staff. Automated planning could reduce the time that radiation oncologists spend on treatment planning3 and certainly have important roles in drawing radiation treatment beam apertures. This work describes the operation of a fully automated treatment planning system, the Radiation Planning Assistant (RPA), developed under a project funded by the National Cancer Institute to ultimately improve access to high quality radiotherapy across the world7.
Figure 1 shows an overview of the automated treatment planning process implemented in the RPA. The treatment planning tasks are performed using either functions in the treatment planning system (see the Table of Materials for the planning system used), controlled using the application programming interface (API), or using in-house developed functions. A key component of the RPA is the independent verification of all tasks that have been automated8. This is achieved using a second, different set of algorithms/functions. The results of the primary algorithms, which are used for the treatment plan, are compared with the results of the secondary algorithm, and flagged if the difference is larger than a pre-determined criteria9. Treatment plans that pass the independent checks and further manual checks by local staff are ready to be used for the patient treatment. The output documentation of the RPA has been specifically designed to streamline the manual check process.
The workflow of the RPA system from the users' point of view is shown in Figure 2. The inputs to the system are an approved plan order and an approved CT image. The radiation oncologist creates and approves the plan order containing basic patient information and details about the expected plan (prescription, treatment type, etc.). The CT image set must also be approved (by the CT technician). This is to ensure that the plan is calculated on the correct CT image. This is important, for example, when multiple CT image sets are taken of a single patient. Once the RPA receives an approved plan order and an approved CT image set, the treatment plan is automatically generated. In some cases, such as when creating 4-field box cervical cancer treatments, the following steps are fully automated, and no additional user intervention is needed until the treatment plan is ready. In other cases, such as the creation of head/neck VMAT treatment plans, intervention is needed halfway through the automated treatment process. For head/neck plans, the radiation oncologist is required to review/edit automatically generated contours. They also need to delineate the gross tumor volume (GTV). In this situation, after receiving approved plan orders and CTs, the RPA performs some initial contouring tasks, including contouring of normal tissues and some targets. The radiation oncologist then reviews and approves the contours, and the RPA continues with the remaining treatment planning tasks. The current system has been tested with 6 MV and 18 MV X-ray beams for head/neck and cervix treatment plans, respectively, both with flattening filter. Once the treatment plan is complete, a document is created for review and approval by the appropriate clinical staff, e.g., physicists and radiation oncologists. Some of these tasks can be delegated to other staff.
Modern treatment planning systems already offer some automated planning processes. The RPA integrates these, whenever possible, offering a complete automated planning process, such that the user can generate treatment plans without the need to open a complicated treatment planning system interface. This manuscript described the protocol for the RPA, and then presents some example results for the output of the treatment planning process.
All patient data used for evaluating the RPA were used retrospectively, with approval from the University of Texas MD Anderson Institutional Review Board.
1. Monitoring Planning Progress
2. Plan Order Approval
NOTE: Plan order approval (typically by the radiation oncologist) is required before the RPA creates a treatment plan.
3. CT Image Approval
NOTE: CT approval is required before the RPA creates a treatment plan.
4. Initiate Automatic Treatment Planning
NOTE: This step is only needed if Autoplan start (in the plan order) is set to Technician.
5. Contouring Review and Approval
NOTE: For some treatments, such as head/neck VMAT, contouring review and approval is required. This is typically performed by the radiation oncologist.
6. Radiotherapy Plan Review and Approval
7. Final Plan Transfer
An example Treatment Plan Order created for a head/neck case is shown in Figure 3. Figure 4 shows the dose distribution for an automatically generated VMAT plan for a patient with a base of tongue squamous cell carcinoma7,10. A review by an attending radiation oncologist confirmed that this plan was acceptable for treatment. On average the head/neck VMAT plans take 46 minutes for a 2-arc plan, and we expect to bring this down to less than 30 minutes with a faster dose calculation algorithm and a distributed architecture for the automated contouring step.
Figure 5 shows automatically generated field apertures for a 4-field box treatment for a patient with cervical cancer. Review by an experienced radiation oncologist confirmed the clinical appropriateness of 90-96% of these fields7,11. On average, these plans took 21 minutes.
Once the treatment plan is ready, documentation is automatically created for review by radiation oncologists, technical staff, medical physicists, and radiographers. We have designed an illustrated procedure that leads the user through checks of marked isocenter and body contour identification, consistency of patient orientation/laterality/treatment site, field apertures (for a 4-field box example), and presence of image or dose calculation artifacts12. Each step of the procedure has simple instructions and library examples to which the user can refer. An example of the instructions is shown in Figure 6.
Although the need for physics and radiation oncologist review is well documented, the role of additional staff has not been evaluated. We assessed this by creating plan documents for 16 cervical cancer patients, 12 of which included intentional errors: incorrect isocenter (3 cases), incorrect body contour (3 cases), incorrect CT couch removal (1 case), incorrect field apertures (5 cases), incorrect dose calculation (1 case), and incorrect number of fields (1 case). These plans were then reviewed by 4 volunteers with minimal experience in radiotherapy and no experience in checking plans. The final version of the plan documentation required ~30 minutes of training. On average, plan checks required 8 minutes per plan. The testers were able to find all errors in the body contours, isocenter (based on fiducial markers) and dose calculation artifacts. They were not able to reliably identify small (but clinically important) errors in the field apertures. They were also not able to identify the case that had only 3 fields instead of 4 – an example of an unanticipated error that is not examined with a specific check-list item. In summary, these results indicate that initial checking of some vital features of radiotherapy plans created by automated processes may be assigned to staff with limited radiotherapy experience, allowing any need for remedial action to be identified before physician review. These staff will not, however, find all errors and additional checks by qualified staff (radiation oncologists and physicists) are still a vital part of the radiotherapy planning workflow.
Figure 1. Schematic of the automated treatment planning process. The human icons show the points in the workflow where human intervention is necessary. All other steps are automated. Each automated step in the planning process has a primary algorithm, which is used to create the actual plan, and a secondary algorithm that is used to verify the result of the primary algorithm. If any of the verification checks fail (i.e. fall outside a predetermined criteria), or if the radiation oncologist does not approve the plan, then a manual planning process becomes necessary. Additional quality procedures that are important to the treatment planning process, specifically routine checks by a qualified medical physicist, are not shown here. Please click here to view a larger version of this figure.
Figure 2. Schematic of the RPA from the users' point of view. The radiation oncologist is responsible for completing and approving the Physician's Plan Order. After taking the simulation image of the patient, this is approved by the radiographer or other appropriate staff present. The RPA then automatically starts and creates the radiotherapy treatment plan. The goal of this work is to create each radiotherapy plan, including documentation, within 30 minutes. Please click here to view a larger version of this figure.
Figure 3 An example Treatment Plan Order for a head/neck VMAT plan. The Plan Order shows the patient identifiers (name, MRN, etc.), some general information about the patient, and some treatment specific information. This includes the dose prescription, target coverage and normal tissue constraints.
Figure 4. An example automatically generated head/neck VMAT plan. The shaded regions show the Planning Target Volumes – red, blue and yellow correspond to PTV1 PTV2, and PTV3, respectively. The lines show the isodose distribution of the automatically generated plan.
Figure 5. An example of automatically generated apertures for a 4-field box cervical cancer treatment. AP, PA, left lateral and right lateral fields are shown.
Figure 6. Example of the illustrated instructions designed to aid chart review for radiotherapy plans automatically generated using the RPA. This example page is for the review of the automatically generated body contour. It includes the results of the primary algorithm, some questions for the user, and a library case for the user to review
A protocol outlining the steps in creating an automated treatment plan using the Radiation Planning Assistant (RPA) system was described. The crucial steps, from a user’s point of view, are (1) CT approval (2) Plan Order Approval (3) Contour review/editing for head/neck cases, and (4) Treatment Plan review. The order of the first two steps is interchangeable. The Radiation Planning Assistant currently automatically creates radiotherapy plans for head/neck (VMAT) and cervical cancer (4-field box), and we are currently working on plans for breast cancer treatments. The final goal is to fully automate radiotherapy treatment planning for all sites/modalities, creating a tool that generates safe and effective radiotherapy treatment plans.
The current system has several limitations. First, it cannot create treatment plans for all treatment sites and approaches, although we expect its capabilities to improve over time, we are some way away from full automation for all treatment sites. There is also a risk of over reliance by the users on automation – this is a risk that we have attempted to mitigate by including many independent verification checks (Figure 1). It was demonstrated that the use of our purpose-developed plan documentation to check treatment plans will enable some potential errors to be identified by relatively inexperienced staff, but review by the radiation oncologist, and plan checks by other qualified staff are important.
We expect to improve the RPA interfaces over time, in response to user feedback. The general workflow and tasks should, however, remain similar to those described in this document. This document should, therefore, continue to be useful. Additional documentation will also be available, describing any modifications, training for plan checks, etc.
There are existing examples of automation of specific steps of the radiotherapy treatment planning. To our knowledge this is the first system for which the entire workflow is fully automated, requiring almost no input from the user. This protocol describes, from the user’s point of view, the important steps needed to operate the Radiation Planning Assistant, and generate a radiotherapy treatment plan.
The authors have nothing to disclose.
This work was funded by the National Cancer Institute, with additional support by Varian Medical Systems and Mobius Medical Systems. Our current system uses Eclipse for treatment planning functions, and Mobius 3D for verification of dose calculation.
Eclipse | Varian Medical Systems | na | Treatment planning system |
Mobius 3D | Mobius Medical Systems | na | Dose calculation verification system |