TRAINING COURSES

Objectives
The physics course is aimed at medical physicists and should give an understanding of the photon and electron beam models, and how the different parameters affect the models. Other objectives are learning how to make QA-plans and how to use the Beam 3D Modeling-module and commission CT-machines.

Prerequisites
Knowledge in medical radiotherapy physics.

Contents

• Machine characterization, how and what to measure before the modeling process to have a good set of data.
• Dose calculation for photons and electrons. For photons: fluence generation, density and material handling, collapsed cone photon dose engine. For electrons: the phase space generation and the Monte Carlo based VMC++ electron engine.
• Photon model parameters: Photon energy spectrum, contamination electrons energy spectrum, off-axis softening and beam profile corrections, primary and flattening filter sources, output factor corrections, MLC and Jaw position and transmission, wedges and auto modeling tools.
• Electron model parameters: Electron energy spectrum, contamination photon energy spectrum, source phase space.
• CT-commissioning: Material handling in RayStation, creation of CT to mass density table.
• QA: Using the Beam 3D Modeling tools. Generate, approving and using phantoms for QA preparation. Creating and exporting patient QA plans in RayStation.

RaySearch has applied to CAMPEP for 25 MPCECs.

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Prerequisites:

Medical physicists and dosimetrists with a working knowledge of proton therapy concepts, including range uncertainty, RBE considerations, and basic proton terminology (Bragg peak, robustness).

Course Overview:

• Patient data management: CT to density tables, DICOM import and export, patient backup and restore, handling of fraction image data.
• Patient modeling: Standard options like manual contouring, deep learning segmentation and structure templates, ROI algebra and contouring on registered image sets, as well as more advanced options for contouring such as the use of deformable registrations and Simulate organ motion in patient modeling. 

This course is focused on practical application of proton therapy planning within the RayStation platform.

• Creating and evaluating PBS treatment plans
• Use of range shifters, Beam computation settings, and apertures/compensators in RayStation 
• Overview of LET-based evaluation tools
• Robust optimization and scenario evaluation workflows
• Dose engine selection and usage (Pencil Beam vs Monte Carlo) 
• Clinical case-based walkthroughs for common indications

requisites:

Medical physicists and dosimetrists with a working knowledge of proton therapy concepts, including range uncertainty, RBE considerations, and basic proton terminology (Bragg peak, robustness).

Course Overview:

• Patient data management: CT to density tables, DICOM import and export, patient backup and restore, handling of fraction image data.
• Patient modeling: Standard options like manual contouring, deep learning segmentation and structure templates, ROI algebra and contouring on registered image sets, as well as more advanced options for contouring such as the use of deformable registrations and Simulate organ motion in patient modeling. 

This course is focused on practical application of proton therapy planning within the RayStation platform.

·       Creating and evaluating PBS treatment plans

·       Use of range shifters, Beam computation settings, and apertures/compensators in RayStation 

·       Overview of LET-based evaluation tools

·       Robust optimization and scenario evaluation workflows

·       Dose engine selection and usage (Pencil Beam vs Monte Carlo) 

·       Clinical case-based walkthroughs for common indications

Objectives
The scripting course goes through the basics of Python scripting but focuses on its application in RayStation. Students will learn how scripting can be used for applications in patient modeling, planning and optimization, or for automating of entire workflows in everyday practice as well as for use in research and data mining.

Prerequisites
Basic knowledge in Python scripting or programming.

Contents
Basics of Pythons scripting and application of scripting in RayStation, with use of a lot of hands-on exercises and examples from today’s clinical practice. Topics such as automatic planning, data export to excel and creation of a GUI will all be covered. Students are encouraged to bring their own scripting ideas. 

Objectives
The Introduction to RayStation Planning course is aimed at new RayStation users. It covers almost all functionality and is intended to give new users a comprehensive introduction to RayStation. At the end of the training the participants will be able to use RayStation clinically. There is an emphasis on practical exercises to give users hands-on experience.

Prerequisites
Medical dosimetrists and physicists familiar with treatment planning

Contents

• Patient data management: CT to density tables, DICOM import and export, patient backup and restore, handling of fraction image data
• Patient modeling: Standard options like manual contouring, Model Based Segmentation, Atlas Based segmentation, Deep Learning Segmentation, ROI algebra and contouring on registered image sets, as well as more advanced options for contouring such as the use of deformable registrations for patient modeling.
• Planning and optimization: Basic planning for 3D-CRT, IMRT and VMAT techniques, and electron planning. Standard IMRT optimization, Multi-Criteria Optimization and Plan Protocols are covered. Upon request if time allows: Fallback Planning and Automated Breast Planning.
• Adaptive planning: Theory and practice in deformable registrations and its use for dose deformation, dose tracking and adaptive planning process.

Objectives

The DrugLog Academy is aimed at pharmacists and nurses that conduct medicine compounding procedures at the clinics. At the end of this training, the participants will be able to: 

• Understand the principles of spectrometry and applications in drug verification 

• Able to navigate and use the online dashboard 

• Able to use DrugLog device methodologically 

• Able to create new catalogs, change catalog statuses, check measurements 

• Able to record measurements for new drug calibration 

• Understand linear regression analysis and systematic deviation correction 

• Able to analyze curves and solve basic issues 

Prerequisites
Basic knowledge of the principles of medicine compounding procedure.

Contents

This training course is delivered with a mixture of demos, real cases, and theoretical learning. 

• Principle of spectrometry and applications in drug verification 

• Using the online dashboard 

• How to take good samples 

• How to set a good baseline 

• Proper cuvette handling 

• Calibration methods and theories 

• Curve analysis and interpretation 

Part 1: PYTHON – 4.0 Hours
 Introduction [0.5 hour]
 The Python Language [2.5 hour]
 Python Introduction
 Basics
 Built-ins
 Python Functions
 Python Strings
 Operators
 Methods
 Slices
 Format
 Python Lists
 Methods
 Slices
 List Comprehensions
 Python Sorting
 Sort vs. Sorted
 Key
 Lambda Functions
 Python Functions – Cont.
 Pass by Reference
 Return
 Arguments
 Unpacking
 Variable Scope
 Lab [1.0 hour]
Part 2: PYTHON – CONT. – 3.0 Hours
 The Python Language – Cont. [2.0 hour]
 Python Dictionaries
 Methods
 Access
 Python Tuples
 Python Files
 Modes
 Methods

RayStation Scripting Training Class
Page 2 of 3
December 2022
 Python Exceptions
 Exception Types
 Try – Except
 Raise
 Python Modules
 Import vs. From
 __name__
 Lab [1.0 hour]
Part 3: Scripting in RayStation – 4.5 Hours
 Introduction to Scripting in RayStation [1.5 hours]
 RayStation Scripting Interface
 The Interactive Console
 Patient State Tree
 Machine State Tree
 State Trees – General Concepts
 Offline Documentation
 Recording
 Units (Coordinate System)
 Suggested Work Method
 Python Basics – Review
 Scope, Index, and Comments
 Classes
 General Tools
 Operators
 Loops
 List Comprehensions
 If Statement
 While Loop
 For Loop
 Expando Objects
 Try – Except
 Automated Planning & Batch Planning [3.0 hours]
 Creating a Plan
 Create a Plan
 Create a BeamSet
 Create a Dose Grid
 Adding Beams
 Adding Optimization Functions

RayStation Scripting Training Class
Page 3 of 3
December 2022
 Optimization Settings
 Importing Patients
 UI Scripting/Yield
Part 4: Data Mining – 2.0 Hours
 Data Mining [2.0 hours]
 Introduction
 Initializing a Script for Excel
 Initialize the Script
 Create an Excel File
 Create a List of Lists (Table)
 Create the Header
 Extracting Dose Statistics from RayStation
 Connect to RayStation
 Add Data to the Worksheet
 Tips
 Selecting Patients
Part 5: Creating A User Interface – 2.0 Hours
 Creating a User Interface [2.0 hours]
 Introduction
 Initializing the GUI
 Visual Studios
 Create the Project
 The Workspace
 Text Labels
 Text Boxes and Buttons
 Text Boxes
 Buttons
 Events
 Check Boxes
 Events
 Combo Boxes

Objectives
The advanced RayStation planning course gives the already experienced user a deeper knowledge on the topics of IMRT/VMAT plan optimization, deformable image registrations and dose tracking.

Prerequisites
Medical dosimetrists and physicists with basic experience from treatment planning in RayStation.

Contents

• Day 1 and 2: planning (IMRT and VMAT), optimization (conventional and Multi-Criteria Optimization) on advanced cases.
• Day 3 and 4: Morfeus and Anaconda deformable registration covering a variety of different anatomical sites, as well as dose tracking and treatment adaptation is further elaborated in this advanced planning course. The use of scripting in the adaptive workflow will also be covered.

With a combination of more challenging use cases, plan comparisons and discussions along with opportunities to network with the functionality developers at RaySearch Laboratories, the user is trained to an advanced level.

The course begins Tuesday morning and will finish at lunch on Friday.

Objectives
The Introduction to RayStation Planning course is aimed at new RayStation users. It covers almost all functionality and is intended to give new users a comprehensive introduction to RayStation. At the end of the training the participants will be able to use RayStation clinically. There is an emphasis on practical exercises to give users hands-on experience.

Prerequisites
Medical dosimetrists and physicists familiar with treatment planning

Contents

• Patient data management: CT to density tables, DICOM import and export, patient backup and restore, handling of fraction image data
• Patient modeling: Standard options like manual contouring, Model Based Segmentation, Atlas Based segmentation, Deep Learning Segmentation, ROI algebra and contouring on registered image sets, as well as more advanced options for contouring such as the use of deformable registrations for patient modeling.
• Planning and optimization: Basic planning for 3D-CRT, IMRT and VMAT techniques, and electron planning. Standard IMRT optimization, Multi-Criteria Optimization and Plan Protocols are covered. Upon request if time allows: Fallback Planning and Automated Breast Planning.
• Adaptive planning: Theory and practice in deformable registrations and its use for dose deformation, dose tracking and adaptive planning process.

Prerequisites:

Medical physicists and dosimetrists with a working knowledge of proton therapy concepts, including range uncertainty, RBE considerations, and basic proton terminology (Bragg peak, robustness).

Course Overview:

• Patient data management: CT to density tables, DICOM import and export, patient backup and restore, handling of fraction image data.
• Patient modeling: Standard options like manual contouring, deep learning segmentation and structure templates, ROI algebra and contouring on registered image sets, as well as more advanced options for contouring such as the use of deformable registrations and Simulate organ motion in patient modeling. 

This course is focused on practical application of proton therapy planning within the RayStation platform.

• Creating and evaluating PBS treatment plans
• Use of range shifters, Beam computation settings, and apertures/compensators in RayStation 
• Overview of LET-based evaluation tools
• Robust optimization and scenario evaluation workflows
• Dose engine selection and usage (Pencil Beam vs Monte Carlo) 
• Clinical case-based walkthroughs for common indications

Objectives
The Introduction to RayStation Planning course is aimed at new RayStation users. It covers almost all functionality and is intended to give new users a comprehensive introduction to RayStation. At the end of the training the participants will be able to use RayStation clinically. There is an emphasis on practical exercises to give users hands-on experience.

Prerequisites
Medical dosimetrists and physicists familiar with treatment planning

Contents

• Patient data management: CT to density tables, DICOM import and export, patient backup and restore, handling of fraction image data
• Patient modeling: Standard options like manual contouring, Model Based Segmentation, Atlas Based segmentation, Deep Learning Segmentation, ROI algebra and contouring on registered image sets, as well as more advanced options for contouring such as the use of deformable registrations for patient modeling.
• Planning and optimization: Basic planning for 3D-CRT, IMRT and VMAT techniques, and electron planning. Standard IMRT optimization, Multi-Criteria Optimization and Plan Protocols are covered. Upon request if time allows: Fallback Planning and Automated Breast Planning.
• Adaptive planning: Theory and practice in deformable registrations and its use for dose deformation, dose tracking and adaptive planning process.

Objectives
The advanced RayStation planning course gives the already experienced user a deeper knowledge on the topics of IMRT/VMAT plan optimization, deformable image registrations and dose tracking.

Prerequisites
Medical dosimetrists and physicists with basic experience from treatment planning in RayStation.

Contents

• Day 1 and 2: planning (IMRT and VMAT), optimization (conventional and Multi-Criteria Optimization) on advanced cases.
• Day 3 and 4: Morfeus and Anaconda deformable registration covering a variety of different anatomical sites, as well as dose tracking and treatment adaptation is further elaborated in this advanced planning course. The use of scripting in the adaptive workflow will also be covered.

With a combination of more challenging use cases, plan comparisons and discussions along with opportunities to network with the functionality developers at RaySearch Laboratories, the user is trained to an advanced level.

The course begins Tuesday morning and will finish at lunch on Friday.

Objectives
The RayStation IT Administration course is aimed at personnel that will handle IT support and administration of the RayStation installation at the clinic.

Prerequisites
Basic knowledge of IT terms like Microsoft Active Directory, Citrix XenApp, VMware Horizon, Microsoft Windows, Microsoft SQL Server and network architecture.

Contents

The training course is delivered with a mixture of hands-on labs and theoretical learning

• RayStation – Understanding the application architecture and its components
• Microsoft SQL Server – Configuration for RayStation and Microsoft best practices. Setting up maintenance jobs and handling backups. Also you will learn how to do performance testing with SQLIO.
• LM-X Licensing Server - Understanding and troubleshooting.
• DICOM Connectivity – Understanding and troubleshooting.
• System Environment Guidelines – Exploring the hardware demands for RayStation and the different deployment scenarios.
• Citrix XenApp - Basic administration and troubleshooting

Objectives
The physics course is aimed at medical physicists and should give an understanding of the photon and electron beam models, and how the different parameters affect the models. Other objectives are learning how to make QA-plans and how to use the Beam 3D Modeling-module and commission CT-machines.

Prerequisites
Knowledge in medical radiotherapy physics.

Contents

• Machine characterization, how and what to measure before the modeling process to have a good set of data.
• Dose calculation for photons and electrons. For photons: fluence generation, density and material handling, collapsed cone photon dose engine. For electrons: the phase space generation and the Monte Carlo based VMC++ electron engine.
• Photon model parameters: Photon energy spectrum, contamination electrons energy spectrum, off-axis softening and beam profile corrections, primary and flattening filter sources, output factor corrections, MLC and Jaw position and transmission, wedges and auto modeling tools.
• Electron model parameters: Electron energy spectrum, contamination photon energy spectrum, source phase space.
• CT-commissioning: Material handling in RayStation, creation of CT to mass density table.
• QA: Using the Beam 3D Modeling tools. Generate, approving and using phantoms for QA preparation. Creating and exporting patient QA plans in RayStation.

RaySearch has applied to CAMPEP for 25 MPCECs.

Part 1: PYTHON – 4.0 Hours
 Introduction [0.5 hour]
 The Python Language [2.5 hour]
 Python Introduction
 Basics
 Built-ins
 Python Functions
 Python Strings
 Operators
 Methods
 Slices
 Format
 Python Lists
 Methods
 Slices
 List Comprehensions
 Python Sorting
 Sort vs. Sorted
 Key
 Lambda Functions
 Python Functions – Cont.
 Pass by Reference
 Return
 Arguments
 Unpacking
 Variable Scope
 Lab [1.0 hour]
Part 2: PYTHON – CONT. – 3.0 Hours
 The Python Language – Cont. [2.0 hour]
 Python Dictionaries
 Methods
 Access
 Python Tuples
 Python Files
 Modes
 Methods

RayStation Scripting Training Class
Page 2 of 3
December 2022
 Python Exceptions
 Exception Types
 Try – Except
 Raise
 Python Modules
 Import vs. From
 __name__
 Lab [1.0 hour]
Part 3: Scripting in RayStation – 4.5 Hours
 Introduction to Scripting in RayStation [1.5 hours]
 RayStation Scripting Interface
 The Interactive Console
 Patient State Tree
 Machine State Tree
 State Trees – General Concepts
 Offline Documentation
 Recording
 Units (Coordinate System)
 Suggested Work Method
 Python Basics – Review
 Scope, Index, and Comments
 Classes
 General Tools
 Operators
 Loops
 List Comprehensions
 If Statement
 While Loop
 For Loop
 Expando Objects
 Try – Except
 Automated Planning & Batch Planning [3.0 hours]
 Creating a Plan
 Create a Plan
 Create a BeamSet
 Create a Dose Grid
 Adding Beams
 Adding Optimization Functions

RayStation Scripting Training Class
Page 3 of 3
December 2022
 Optimization Settings
 Importing Patients
 UI Scripting/Yield
Part 4: Data Mining – 2.0 Hours
 Data Mining [2.0 hours]
 Introduction
 Initializing a Script for Excel
 Initialize the Script
 Create an Excel File
 Create a List of Lists (Table)
 Create the Header
 Extracting Dose Statistics from RayStation
 Connect to RayStation
 Add Data to the Worksheet
 Tips
 Selecting Patients
Part 5: Creating A User Interface – 2.0 Hours
 Creating a User Interface [2.0 hours]
 Introduction
 Initializing the GUI
 Visual Studios
 Create the Project
 The Workspace
 Text Labels
 Text Boxes and Buttons
 Text Boxes
 Buttons
 Events
 Check Boxes
 Events
 Combo Boxes

Objectives
The physics course is aimed at medical physicists and should give an understanding of the photon and electron beam models, and how the different parameters affect the models. Other objectives are learning how to make QA-plans and how to use the Beam 3D Modeling-module and commission CT-machines.

Prerequisites
Knowledge in medical radiotherapy physics.

Contents

Photon physics (2 days, start 09:00 Tuesday, end 17:00 Wednesday):

• Machine characterization, how and what to measure before the modeling process to have a good set of data.
• Dose calculation: fluence generation, density and material handling, Collapsed Cone and Monte Carlo dose engine. 
• Photon model parameters: Photon energy spectrum, contamination electrons energy spectrum, off-axis softening and beam profile corrections, primary and flattening filter sources, output factor corrections, MLC and Jaw position and transmission, wedges and auto modeling tools.
• CT-commissioning: Material handling in RayStation, creation of CT to mass density table.
• QA: Using the Beam 3D Modeling tools. Generate, approving and using phantoms for QA preparation. Creating and exporting patient QA plans in RayStation.

Electron physics (1 day, start 9:00 Thursday, end 17:00 Thursday):

• • Dose calculation: phase space generation and the electron Monte Carlo dose engine.
  • Electron model parameters: Electron energy spectrum, contamination photon energy spectrum, source phase space.

Objectives
The scripting course goes through the basics of Python scripting but focuses on its application in RayStation. Students will learn how scripting can be used for applications in patient modeling, planning and optimization, or for automating of entire workflows in everyday practice as well as for use in research and data mining.

Prerequisites
Basic knowledge in Python scripting or programming.

Contents
Basics of Pythons scripting and application of scripting in RayStation, with use of a lot of hands-on exercises and examples from today’s clinical practice. Topics such as automatic planning, data export to excel and creation of a GUI will all be covered. Students are encouraged to bring their own scripting ideas. 

Objectives
The RayStation IT Administration course is aimed at personnel that will handle IT support and administration of the RayStation installation at the clinic.

Prerequisites
Basic knowledge of IT terms like Microsoft Active Directory, Remote Desktop, Microsoft Windows, Microsoft SQL Server and network architecture.

Contents

The training course is delivered with a mixture of hands-on labs and theoretical learning

• RayStation – Understanding the application architecture and its components
• Microsoft SQL Server – Configuration for RayStation and Microsoft best practices. Setting up maintenance jobs and handling backups. 
• LM-X Licensing Server - Understanding and troubleshooting.
• DICOM Connectivity – Understanding and troubleshooting.
• System Environment Guidelines – Exploring the hardware demands for RayStation and the different deployment scenarios.
• RayStorage and RayStation Patient Data Management.

Objectives
The Introduction to RayStation Planning course is aimed at new RayStation users. It covers almost all functionality and is intended to give new users a comprehensive introduction to RayStation. At the end of the training the participants will be able to use RayStation clinically. There is an emphasis on practical exercises to give users hands-on experience.

Prerequisites
Medical dosimetrists and physicists familiar with treatment planning

Contents

• Patient data management: CT to density tables, DICOM import and export, patient backup and restore, handling of fraction image data
• Patient modeling: Standard options like manual contouring, Model Based Segmentation, Atlas Based segmentation, Deep Learning Segmentation, ROI algebra and contouring on registered image sets, as well as more advanced options for contouring such as the use of deformable registrations for patient modeling.
• Planning and optimization: Basic planning for 3D-CRT, IMRT and VMAT techniques, and electron planning. Standard IMRT optimization, Multi-Criteria Optimization and Plan Protocols are covered. Upon request if time allows: Fallback Planning and Automated Breast Planning.
• Adaptive planning: Theory and practice in deformable registrations and its use for dose deformation, dose tracking and adaptive planning process.

Objectives
The Introduction to RayStation Planning course is aimed at new RayStation users. It covers almost all functionality and is intended to give new users a comprehensive introduction to RayStation. At the end of the training the participants will be able to use RayStation clinically. There is an emphasis on practical exercises to give users hands-on experience.

Prerequisites
Medical dosimetrists and physicists familiar with treatment planning

Contents

• Patient data management: CT to density tables, DICOM import and export, patient backup and restore, handling of fraction image data
• Patient modeling: Standard options like manual contouring, Model Based Segmentation, Atlas Based segmentation, Deep Learning Segmentation, ROI algebra and contouring on registered image sets, as well as more advanced options for contouring such as the use of deformable registrations for patient modeling.
• Planning and optimization: Basic planning for 3D-CRT, IMRT and VMAT techniques, and electron planning. Standard IMRT optimization, Multi-Criteria Optimization and Plan Protocols are covered. Upon request if time allows: Fallback Planning and Automated Breast Planning.
• Adaptive planning: Theory and practice in deformable registrations and its use for dose deformation, dose tracking and adaptive planning process.

Objectives

The Introduction to RayStation Proton planning course is intended to give new users a comprehensive introduction to RayStation. There is an emphasis on practical exercises to give users hands-on experience.

The objective of the proton physics training is to obtain a detailed understanding of physical principles and algorithms implemented in RayStation – from CT image data to scoring of dose in the patient.

Prerequisites

Medical dosimetrists and physicists familiar with proton treatment planning.     

Contents

Proton planning (3 days, start 13:00 Monday, end 12:00 Thursday):

• Patient data management: CT to density tables, DICOM import and export, patient backup and restore, handling of fraction image data
• Patient modeling: Standard options like manual contouring, Model Based Segmentation, atlas based segmentation, deep learning segmentation and ROI algebra. Rigid image registrations and introduction to deformable image registrations.
• Planning and optimization: PBS planning (in depth on objective functions, spot selection techniques etc), PBS with block apertures, robust optimization (patient setup-, range- and 4D-robustness), introduction to Multi Criteria Optimization, introduction to proton arc planning and LET optimization, use of different dose engines (approximate pencil beam, pencil beam and monte carlo). Case examples based on interest, may include cranio spinal, head and neck, pelvic, lung etc.
• Plan evaluation: Dose computations on additional datasets, deforming dose to new datasets, perturbed dose calculations.
• Adaptive planning:  introduction to dose tracking and adaptive replanning
• Upon request: passive techniques and fallback planning

Optional day at the end, Proton physics (1 day, start 13:00 Thursday, end 12:00 Friday):

• Proton dose calculation: CT to stopping power conversion, Pencil-Beam dose engine, Monte Carlo dose engine. Dose engine limitations, comparisons and validation.
• Proton beam commissioning: Beam data requirements, file format and beam modeling
• RayPhysics for proton PBS: Import of measured pristine Bragg peaks, spot profiles and absolute dosimetry data. Beam model generated from measured data by auto modeling. Beam model parameters displayed in the GUI. Computation of pristine Bragg peaks, spot profiles and absolute dosimetry data using Monte Carlo and/or Pencil Beam dose engine. Export of measured and computed pristine Bragg peaks and spot profiles. Beam modelling check list and commissioning of PBS machines.

Objectives
The advanced RayStation planning course gives the already experienced user a deeper knowledge on the topics of IMRT/VMAT plan optimization, deformable image registrations and dose tracking.

Prerequisites
Medical dosimetrists and physicists with basic experience from treatment planning in RayStation.

Contents

• Day 1 and 2: planning (IMRT and VMAT), optimization (conventional and Multi-Criteria Optimization) on advanced cases.
• Day 3 and 4: Morfeus and Anaconda deformable registration covering a variety of different anatomical sites, as well as dose tracking and treatment adaptation is further elaborated in this advanced planning course. The use of scripting in the adaptive workflow will also be covered.

With a combination of more challenging use cases, plan comparisons and discussions along with opportunities to network with the functionality developers at RaySearch Laboratories, the user is trained to an advanced level.

The course begins Tuesday morning and will finish at lunch on Friday.

Objectives
The RayStation IT Administration course is aimed at personnel that will handle IT support and administration of the RayStation installation at the clinic.

Prerequisites
Basic knowledge of IT terms like Microsoft Active Directory, Citrix XenApp, VMware Horizon, Microsoft Windows, Microsoft SQL Server and network architecture.

Contents

The training course is delivered with a mixture of hands-on labs and theoretical learning

• RayStation – Understanding the application architecture and its components
• Microsoft SQL Server – Configuration for RayStation and Microsoft best practices. Setting up maintenance jobs and handling backups. Also you will learn how to do performance testing with SQLIO.
• LM-X Licensing Server - Understanding and troubleshooting.
• DICOM Connectivity – Understanding and troubleshooting.
• System Environment Guidelines – Exploring the hardware demands for RayStation and the different deployment scenarios.
• Citrix XenApp - Basic administration and troubleshooting

Prerequisites:

Medical physicists and dosimetrists with a working knowledge of proton therapy concepts, including range uncertainty, RBE considerations, and basic proton terminology (Bragg peak, robustness).

Course Overview:

• Patient data management: CT to density tables, DICOM import and export, patient backup and restore, handling of fraction image data.
• Patient modeling: Standard options like manual contouring, deep learning segmentation and structure templates, ROI algebra and contouring on registered image sets, as well as more advanced options for contouring such as the use of deformable registrations and Simulate organ motion in patient modeling. 

This course is focused on practical application of proton therapy planning within the RayStation platform.

• Creating and evaluating PBS treatment plans
• Use of range shifters, Beam computation settings, and apertures/compensators in RayStation 
• Overview of LET-based evaluation tools
• Robust optimization and scenario evaluation workflows
• Dose engine selection and usage (Pencil Beam vs Monte Carlo) 
• Clinical case-based walkthroughs for common indications

Part 1: PYTHON – 4.0 Hours
 Introduction [0.5 hour]
 The Python Language [2.5 hour]
 Python Introduction
 Basics
 Built-ins
 Python Functions
 Python Strings
 Operators
 Methods
 Slices
 Format
 Python Lists
 Methods
 Slices
 List Comprehensions
 Python Sorting
 Sort vs. Sorted
 Key
 Lambda Functions
 Python Functions – Cont.
 Pass by Reference
 Return
 Arguments
 Unpacking
 Variable Scope
 Lab [1.0 hour]
Part 2: PYTHON – CONT. – 3.0 Hours
 The Python Language – Cont. [2.0 hour]
 Python Dictionaries
 Methods
 Access
 Python Tuples
 Python Files
 Modes
 Methods

RayStation Scripting Training Class
Page 2 of 3
December 2022
 Python Exceptions
 Exception Types
 Try – Except
 Raise
 Python Modules
 Import vs. From
 __name__
 Lab [1.0 hour]
Part 3: Scripting in RayStation – 4.5 Hours
 Introduction to Scripting in RayStation [1.5 hours]
 RayStation Scripting Interface
 The Interactive Console
 Patient State Tree
 Machine State Tree
 State Trees – General Concepts
 Offline Documentation
 Recording
 Units (Coordinate System)
 Suggested Work Method
 Python Basics – Review
 Scope, Index, and Comments
 Classes
 General Tools
 Operators
 Loops
 List Comprehensions
 If Statement
 While Loop
 For Loop
 Expando Objects
 Try – Except
 Automated Planning & Batch Planning [3.0 hours]
 Creating a Plan
 Create a Plan
 Create a BeamSet
 Create a Dose Grid
 Adding Beams
 Adding Optimization Functions

RayStation Scripting Training Class
Page 3 of 3
December 2022
 Optimization Settings
 Importing Patients
 UI Scripting/Yield
Part 4: Data Mining – 2.0 Hours
 Data Mining [2.0 hours]
 Introduction
 Initializing a Script for Excel
 Initialize the Script
 Create an Excel File
 Create a List of Lists (Table)
 Create the Header
 Extracting Dose Statistics from RayStation
 Connect to RayStation
 Add Data to the Worksheet
 Tips
 Selecting Patients
Part 5: Creating A User Interface – 2.0 Hours
 Creating a User Interface [2.0 hours]
 Introduction
 Initializing the GUI
 Visual Studios
 Create the Project
 The Workspace
 Text Labels
 Text Boxes and Buttons
 Text Boxes
 Buttons
 Events
 Check Boxes
 Events
 Combo Boxes

Objectives
The Introduction to RayStation Planning course is aimed at new RayStation users. It covers almost all functionality and is intended to give new users a comprehensive introduction to RayStation. At the end of the training the participants will be able to use RayStation clinically. There is an emphasis on practical exercises to give users hands-on experience.

Prerequisites
Medical dosimetrists and physicists familiar with treatment planning

Contents

• Patient data management: CT to density tables, DICOM import and export, patient backup and restore, handling of fraction image data
• Patient modeling: Standard options like manual contouring, Model Based Segmentation, Atlas Based segmentation, Deep Learning Segmentation, ROI algebra and contouring on registered image sets, as well as more advanced options for contouring such as the use of deformable registrations for patient modeling.
• Planning and optimization: Basic planning for 3D-CRT, IMRT and VMAT techniques, and electron planning. Standard IMRT optimization, Multi-Criteria Optimization and Plan Protocols are covered. Upon request if time allows: Fallback Planning and Automated Breast Planning.
• Adaptive planning: Theory and practice in deformable registrations and its use for dose deformation, dose tracking and adaptive planning process.

Objectives
The advanced RayStation planning course gives the already experienced user a deeper knowledge on the topics of IMRT/VMAT plan optimization, deformable image registrations and dose tracking.

Prerequisites
Medical dosimetrists and physicists with basic experience from treatment planning in RayStation.

Contents

• Planning (IMRT and VMAT), optimization (conventional and Multi-Criteria Optimization) on advanced cases.
• Morfeus and Anaconda deformable registration covering a variety of different anatomical sites. Dose tracking and treatment adaptation is further elaborated.
• Overview of Machine Learning products.

With a combination of more challenging use cases, plan comparisons and discussions the user is trained to an advanced level.

The course begins afternoon of the Monday and will finish at lunch on Friday.

Objectives
The advanced RayStation planning course gives the already experienced user a deeper knowledge on the topics of IMRT/VMAT plan optimization, deformable image registrations and dose tracking.

Prerequisites
Medical dosimetrists and physicists with basic experience from treatment planning in RayStation.

Contents

• Day 1 and 2: planning (IMRT and VMAT), optimization (conventional and Multi-Criteria Optimization) on advanced cases.
• Day 3 and 4: Morfeus and Anaconda deformable registration covering a variety of different anatomical sites, as well as dose tracking and treatment adaptation is further elaborated in this advanced planning course. The use of scripting in the adaptive workflow will also be covered.

With a combination of more challenging use cases, plan comparisons and discussions along with opportunities to network with the functionality developers at RaySearch Laboratories, the user is trained to an advanced level.

The course begins Tuesday morning and will finish at lunch on Friday.

Objectives
The scripting course goes through the basics of Python scripting but focuses on its application in RayStation. Students will learn how scripting can be used for applications in patient modeling, planning and optimization, or for automating of entire workflows in everyday practice as well as for use in research and data mining.

Prerequisites
Basic knowledge in Python scripting or programming.

Contents
Basics of Pythons scripting and application of scripting in RayStation, with use of a lot of hands-on exercises and examples from today’s clinical practice. Topics such as automatic planning, data export to excel and creation of a GUI will all be covered. Students are encouraged to bring their own scripting ideas. 

Objectives

The Advanced Proton Planning course gives the already experienced user a deeper knowledge on the topics PBS plan optimization, LET optimization, deformable image registrations, dose tracking and adaptive replanning.

Prerequisites

Medical dosimetrists and physicists familiar with proton treatment planning. Having attended the Introduction to Proton Planning course or equivalent experience.   

Contents

Proton planning (3,5 days, start 13:00 Monday, end 17:00 Thursday):

• Planning and optimization: PBS planning (in depth on objective functions, spot selection techniques etc), PBS with block apertures, robust optimization (patient setup-, range- and 4D-robustness), machine learning planning overview, LET optimization, proton arc planning, use of different dose engines (approximate pencil beam, pencil beam and Monte Carlo). Case examples based on interest, may include cranio spanial, head and neck, pelvic, lung etc.
• Plan evaluation: Dose computations on additional datasets, deforming dose to new datasets, perturbed dose calculations, alternative RBE models, LET evaluation.
• Adaptive planning: Theory and practice in deformable registrations and its use for dose deformation, dose tracking and adaptive planning process.
• Radiobiology for protons
• Upon request: passive techniques, Multi Criteria Optimization.

Optional day at the end, Proton physics (1 day, start 09:00 Friday, end 17:00 Friday):

• Proton dose calculation: CT to stopping power conversion, Pencil-Beam dose engine, Monte Carlo dose engine. Dose engine limitations, comparisons and validation.
• Proton beam commissioning: Beam data requirements, file format and beam modeling
• RayPhysics for proton PBS: Import of measured pristine Bragg peaks, spot profiles and absolute dosimetry data. Beam model generated from measured data by auto modeling. Beam model parameters displayed in the GUI. Computation of pristine Bragg peaks, spot profiles and absolute dosimetry data using Monte Carlo and/or Pencil Beam dose engine. Export of measured and computed pristine Bragg peaks and spot profiles. Beam modelling check list and commissioning of PBS machines.

Objectives
The physics course is aimed at medical physicists and should give an understanding of the photon and electron beam models, and how the different parameters affect the models. Other objectives are learning how to make QA-plans and how to use the Beam 3D Modeling-module and commission CT-machines.

Prerequisites
Knowledge in medical radiotherapy physics.

Contents

• Machine characterization, how and what to measure before the modeling process to have a good set of data.
• Dose calculation for photons and electrons. For photons: fluence generation, density and material handling, collapsed cone photon dose engine. For electrons: the phase space generation and the Monte Carlo based VMC++ electron engine.
• Photon model parameters: Photon energy spectrum, contamination electrons energy spectrum, off-axis softening and beam profile corrections, primary and flattening filter sources, output factor corrections, MLC and Jaw position and transmission, wedges and auto modeling tools.
• Electron model parameters: Electron energy spectrum, contamination photon energy spectrum, source phase space.
• CT-commissioning: Material handling in RayStation, creation of CT to mass density table.
• QA: Using the Beam 3D Modeling tools. Generate, approving and using phantoms for QA preparation. Creating and exporting patient QA plans in RayStation.

RaySearch has applied to CAMPEP for 25 MPCECs.

Objectives
The Introduction to RayStation Planning course is aimed at new RayStation users. It covers almost all functionality and is intended to give new users a comprehensive introduction to RayStation. At the end of the training the participants will be able to use RayStation clinically. There is an emphasis on practical exercises to give users hands-on experience.

Prerequisites
Medical dosimetrists and physicists familiar with treatment planning

Contents

• Patient data management: CT to density tables, DICOM import and export, patient backup and restore, handling of fraction image data
• Patient modeling: Standard options like manual contouring, Model Based Segmentation, Atlas Based segmentation, Deep Learning Segmentation, ROI algebra and contouring on registered image sets, as well as more advanced options for contouring such as the use of deformable registrations for patient modeling.
• Planning and optimization: Basic planning for 3D-CRT, IMRT and VMAT techniques, and electron planning. Standard IMRT optimization, Multi-Criteria Optimization and Plan Protocols are covered. Upon request if time allows: Fallback Planning and Automated Breast Planning.
• Adaptive planning: Theory and practice in deformable registrations and its use for dose deformation, dose tracking and adaptive planning process.