In recent history, Artificial Intelligence (AI) has been employed throughout many industries. Many dosimetrists are concerned that they may be replaced by this technology. In our field, we possess something that artificial intelligence does not yet have the capability of doing. Thinking! Actual intelligence applies to the understanding of what will happen and how to manipulate the treatment planning system to achieve high-quality plans while still considering the patient as a unique individual. This requires an intimate understanding of the physical treatment unit, beam profiles, field geometry, and tools within the TPS that can be used that may not be common knowledge. Any planning system can produce clinically acceptable plans with automation, but it is the knowledge and skill of the planner that will produce high-quality plans that AI will be challenged to achieve. The tips and tricks that we hold up our sleeves should be shared. The ones I have found beneficial will be discussed.

Tips and tricks that can be utilized to increase plan quality and efficiency. These can be applied to 3D, VMAT, SRS/SBRT techniques. 

Learner Outcomes:

1. Discuss the physical limitations of the treatment unit and apply them to their planning process
2. Apply specific field geometry techniques to maximize plan quality
3. Locate and utilize tools that may not be common knowledge

CE credit = 1.0

Thomas Costantino, MS, CMD, RT(T), Manager, Dosimetry

This presentation will provide a detailed overview of a Medical Dosimetrist’s role in MR-guided adaptive SABR patient pathway. Medical Dosimetrists are intricately involved from the patient’s simulation to the real time plan adaption process, in addition to the usual contouring and dosimetry duties. 

For complex cases, a Medical Dosimetrist is required to provide detailed simulation instructions to Radiation Therapists, and these include tumor(s) location coordinates; scan length requirements; setup requests; whether breath-hold is required, tracking instructions and gating parameters; as well as an assessment whether a single or multiple iso centers are required. This requires a completion of an Adaptive Handover Form (AHF) and a simulation session using radiology images saved in MIM Software. For highly complex cases a Medical Dosimetrist must be present during simulation.  

Contouring on MR images is slightly different compared to CT images due to difference in contrast. There is currently no MIM auto-contouring workflow for Thoracic and Abdominal MR images. Therefore, there is more extensive manual contouring required. In post-surgical cases (e.g. post Whipple’s cases) contouring can be very complex, detailed knowledge of anatomy and image fusion is essential. 

A Medical Dosimetrist is expected to create a clinically acceptable, robust, and adaptable plan. This involves a creation of rules/formulae for a quick and accurate creation of target margins and optimization structures; anticipate anatomical changes on plan adaption and set up plan objectives accordingly. Provide detailed plan adaption instructions on the AHF and these include, contouring instructions, and optimization instructions.      Real Time Plan Adaption includes teamwork; attention to detail; efficiency; analytical and critical/clinical thinking skills are a must for a Medical Dosimetrist to safely execute on the day re-optimizations; quality assurance task

Learner Outcomes:

1.    Outline the daily responsibilities of a Medical Dosimetrist in Adaptive SABR patient pathway
2.    Provide examples of the differences between MR guided adaptive role and conventional planning Medical Dosimetrist role
3.    Summarize the roles of a Medical Dosimetrist in Adaptive RT

CE Credit = 1.0

Ebison Chinherende, CMD, Specialist Senior Medical Dosimetrist - MR Planning

In this session, expect to gain key insights specifically tailored to enhance the standards of lung SBRT treatment planning. Develop a comprehensive understanding of the advantages and limitations of two approaches for determining safe beam geometries. Explore the effects of coplanar and noncoplanar beam geometries on critical metrics such as CI, R50, and other points on the dose gradient. Additionally, utilize a simplified VMAT optimization method, exploring the nuanced influence of optimization settings on plan quality. 

Learner Outcomes:

1. List example of the pros and cons of two methods for determining safe beam geometries
2. Outline the effects of coplanar and noncoplanar beam geometries on the CI, R50, and other points on the dose gradient
3. Describe a simple VMAT optimization technique and how the optimization settings affect plan quality

CE credits – 1.0

Kirk Luca, MS, CMD, Medical Dosimetrist

Adaptive radiation therapy is a topic on the rise, but not everyone has the staffing to do true adaptive treatments or is able to afford a new specialized machine.  With this in mind, designing a prospective treatment plan that involves having multiple PTV sizes to cover the varying possible target sizes and variations.  This allows for quicker evaluation of how to treat the patient's daily anatomy variation, and reduces time requirements on staff.

Learner Outcomes:
1. Decide how to construct a prospective adaptive treatment plan
2. Explain how to proceed with treating patients with this technique
3. Discuss the importance of being able to template the planning process for efficient planning

CE Credit = 0.5

Jeremy Donaghue, MS, DABR, Medical Physicist

Do you ever wonder what it’s like to work in proton dosimetry, but not sure what it’s like to create robust plans and work on adaptive treatments? This talk is for you! Proton therapy does offer precise treatment which is helpful for a certain cohort of patients. Due to the high accuracy of the beam, adaptive treatment plans may need to be created to ensure the proton therapy is delivered properly to the patient. There will be a discussion on what factors can impact the proton beam. In addition, what types of patients may require additional CT scans throughout treatment and why. How can the dosimetrist work to mitigate adaptive treatment up front in the original treatment plan? Finally, the talk will walk through the entire process from adaptive CT scan to finalizing the adaptive proton therapy treatment plan.

Learner Outcomes:

1. List the factors that can impact the proton therapy treatment beam. 
2. Explore the types of patients who may be more likely to need adaptive treatment plans.
3. Discuss the adaptive proton treatment planning workflow

CE credit = 1.0

Linnae Campbell, MSHA, MS, CMD RT(R)(T), Certified Medical Dosimetrist

The stereotactic technique has quickly become a standard of care for many cancer centers; however, it is not unusual to find this commonly utilized treatment modality difficult to authorize even when dosing and fractionation expectations have been met.  This session will focus on additional published clinical coverage criteria required to be met in order to receive authorization or reimbursement.  Being knowledgeable of these criteria and confirming the information is documented prior to authorization may lessen delays in treatment and additional time and effort by you and your peers.  Tips and tricks for quality documentation to support these criteria will be discussed, as well as appropriate coding and documentation for courses when the published stereotactic criteria are not met.      

Learner Outcomes:

1. Recognize the key dose and fractionation criteria required for the SRS and SBRT techniques
2. Discuss the clinical coverage criteria published for the stereotactic techniques per treatment area or diagnosis
3. Identify best practice options for documentation of the clinical coverage criteria

CE credit = 1.0

Tamara Syverson, BSRT(T), CHONC, Executive Director, Oncology Client Services

The online adaptive radiotherapy (oART) technique described in this study is technically feasible with a C-arm linac. To our knowledge, this is the first clinical experience with oART for prostate cancer including full replanning and delivered with a C-arm linac without artificial intelligence capability. Mobius3D can be effectively be used for independent pre-treatment verifications of online adaptive prostate SBRT plans. All online adaptive plans analyzed in this study passed the pre-treatment patient specific QA (PSQA) procedure when a specific DLGc value was used. The whole treatment planning and pre-treatment PSQA are performed in our department only by skilled dosimetrists. 

Learner Outcomes:

1. Discuss the feasibility of performing online adaptive SBRT for prostate cancer with a standard linac
2. Explain why Mobius3D is a key tool for pre-treatment verification of the generated adapted plan
3. Outline the improved results are obtained with a sDLGc
4. Justify that a trained dosimetrist can lead the online adaptive workflow

CE Credit = 0.5

Coral Laosa Bello, Radiation Therapist/Dosimetrist

A complete PSQA has been described for HA SRS plans. According to our experience, a dosimetrist can lead the PSQA task using Monte Carlo software that permit saving time and linac resources. The case study will describe the use of High dosimetric accuracy of the HyperArc-based SRS technique.

Learner Outcome:

1. Describe the use  of high dosimetric accuracy of the HyperArc-based SRS technique
2. Explain how Monte Carlo-based pre-treatment verification can be used as a feasible and accuracy method to perform PSQA of HypeArc plans

CE Credit = 0.5

Coral Laosa Bello, Radiation Therapist/Dosimetrist

There is a long-standing idea that QA plan analysis failure can be directly correlated to the modulation of the plan itself. But often, this is communicated to the planner by a physicist with little more than anecdotal evidence to support the claim. Planners are frequently put in a position where they are asked to replan cases due to QA failures without direct guidance as to how to change the plan and what an acceptable amount of modulation will be needed to create a passable QA plan. Our hope was to investigate the correlation between modulation (as defined by MU/dose for a given field) and the QA pass rate using 2%2mm and 3%3mm gamma criteria. 

Also, because modulation is often thought to be related to delivery efficiency, the estimated delivery time for each beam, as stated in the optimization console in the planning system, was also compared to the actual delivery time. This was done in the hopes that cases where beam-on time mattered most (breath-hold, patients under sedation, etc.) could be prospectively analyzed, and assuming a low correlation of pass rate to modulation, the lowest possible beam-on-time could be prioritized, with less regard to possible QA failures. 

Learner Outcomes

1. identify which planning parameters and metrics influence the QA pass rate
2. correlate estimated with actual delivery time
3. Explain the relative importance of Plan Modulation on patient experience

CE credit = 1.0

Matthew Goss, DABR, Senior Medical Physicist

Danielle Waters, CMD, RT(T), Dosimetrist

Ryan Turner, MS, Medical Physics Resident

A review of a novel software by TheraPanacea that uses AI and Deep Learning algorithms to help make the offline adaptive planning decision-making process more efficient, streamlined, and standardized. Bringing cutting-edge technology to all radiation oncology patients, not just for ones being treated on online adaptive specialty machines.

Learner Outcomes:
1. Outline the offline adaptive decision-making process
2. Discuss how AI and Deep Learning algorithms are involved in the offline adaptive process
3. Review the use of enhanced CBCTs and synthetic CT generation in offline adaptive processes

CE credit = 0.5

Stephanie Torres, CMD, Technical Sales Specialist