RayStation – Automation is the Future of Planning

Carmen Sawyers, MS, DABR Ackerman Cancer Center

Overview • Why Automation?

o RayStation Automation Tools • A Different Approach

o RayStation Advanced Automation Tools • Pros/Cons • Future of Planning

Ackerman Cancer Center • Private practice in Jacksonville & Amelia Island • 3 Elekta Linacs • 1 Mevion Proton Unit (vault 2 in progress) • 100 patients/day between 2 sites • 3D-CRT, IMRT, VMAT, Protons • 5 Physicists, 5 Dosimetrists • RayStation user since 2013; Clinical since Feb 2014

Why Automation? • Goal is to create quality plans to meet clinical

objectives • Efficient Process

o Automate standard procedures • Clinic time constraints

o Spend valuable time on complex cases o Evaluate different treatment techniques

• Help department workflow

RayStation Tools • Automation of Standard Procedures

o Automate specific portions of the planning process • Tools are generally “problem solvers”

o Templates o Protocols o Scripting o 3D Optimization o Automatic Breast Planning

Templates • Physical work can be

automated and simplified as much as possible o ROI Naming and Colors o Beam Arrangements o Isodose Lines o Optimization Objectives o Clinical Goals, RTOG

Protocols

Protocols • Templates grouped

together for standardized planning o Create ROI o Load beam list o Load IMRT objectives o Load clinical goals o Run optimization o Compute final dose

• One, Two, Three mouse clicks to achieve a plan

Scripting

• Provides automation, connectivity, and flexibility beyond the standard user interface

• IronPython programming language o Create data files o Start processes o Execute optimization,

deformable registration o Communicate with other

programs and computers

3D Optimization • Direct optimization of 3D-CRT treatment parameters

o Leaf positions, Beam weights, Wedge angles o Collimator angle, Gantry angle, Couch angle

Automated Breast Planning • Created by Princess

Margaret Hospital o Study shows added efficiency,

standardization, and quality to current planning process

• Uses markers place during CT (sup, inf, med, lat)

• 3 button clicks to automatically: o Locate markers o Create target and OAR o Set beam angles (gantry and

collimator) o Optimize and create

segments

T.G. Purdie et al., “Automated Planning of Tangential Breast Intensity-Modulated Radiotherapy Using Heuristic Optimization”, Int.J. Radiation Oncology Biol.Phys.Vol. 81, No.2, pp. 575-583, 2011

A Different Approach • Future is knowledge-based planning

o Use previous experience to drive the solution • Plan optimization driven by big data

o Multi-variate problem with complex, 3D Pareto fronts • Pareto fronts/surface

o A plane in space where the perfect combination of objectives sit

• Computer Speed o Need advanced hardware, algorithms, and techniques

• Future of adaptive therapy o Need quick automatic assessment and replanning

Raystation Advanced Tools • Beginning of true computer driven solutions

o Fallback Planning o Multi-Criteria Optimization (MCO) o Reduce Organ at Risk (OAR) o Plan Explorer

FallBack Planning • Create contingency plans for

other machines and modalities • Uses a Dose Mimicking

algorithm to replicate DVHs • Example: VMAT IMRT and 3DCRT

• Reduce planning time, stress on staff, and avoid treatment interruption for patients

• Alternate uses o Determine what modality is best

(IMRT vs Proton) o Proof for insurance companies

• Import any dose and mimic it o other TPS, TOMO, Cyberknife,

proton

MCO – Pareto Optimization • Pareto fronts: find the

plans that satisfy all the objectives and work within this space o Navigate this solution

space o Moving sliders o Lock ROI, narrow the

“solution space” o Guided by clinical

goals • Real time effect on

the plan

Reduce OAR • One click post processing

tool • Improve OARs without

negatively impacting PTV • Assessment tool – see if

better plan is possible • Run it, if you don’t like it,

click UNDO • Key piece to what

computers need to do to ensure the best possible plan

Plan Explorer • Automated generation of a large

number of treatment plans for defined clinical goals and combinations of treatment techniques and machines

• Capability to filter and browse among plan candidates to find the most desired one

• Generate plans for different machines: VMAT, 7-field IMRT, 9-field IMRT, and filter by beam delivery time or clinical goals met

• Explore more a solution space to ensure highest quality plan

• Maximize the use of current delivery machines

Concerns • Use of automation is an up front time investment

o Work to setup templates, protocols, learning how to use MCO/optimization “tricks”

• Determine how to use protocols/which cases • Cooperation and organization • Cost of licenses (Automated Breast Planning, MCO,

FallBack, VMAT, Proton, Plan Explorer) o Why purchase these auto-planning license when I have

qualified CMDs on staff?

Does Speed Affect Quality? • Automated tools affect the

planner’s speed • Study to show that given a

high performing system, a dosimetrist will produce a higher quality plan compared to one equipped with a slow system

• Study shows direct relationship between speed and plan quality

• Dosimetrists planning on the faster computer had significant increase in fulfilment of clinical goals

Future of Planning • Computers will get better at finding solutions to

multi-variate problems • Dosimetrists will be needed to drive computer

solutions and for clinical plan evaluation and decisions

• More patients needing adaptive therapy will increase workload o Day to day dose tracking o Implementing multiple changes over the course of

treatment • Automation will help bring efficiency to these

processes and higher quality care to the clinic

Future of RaySearch • RaySearch Goal: higher quality plans for ALL

patients, ALL disease sites, ALL oncology centers • The future workflow (next 2-7 years) will see

computer created plans for 50-75% of patients • Automated dosimetric and physical assessment

during treatment will become the norm • Automation will also include clinic specific

operational efficiency • Next steps include patient specific solutions based

on genomics and big data • Need for powerful OIS, RayCare, to handle data

Thank you • Special thanks to

o Dayna Bodensteiner, Director of Product Management, RaySearch Americas

o Freddie Cardel, Director of Customer Support, RaySearch Americas

o Marc Mlyn, President and CEO, RaySearch Americas