raystation – automation is the future of planning 2016... · current planning process • uses...
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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