IHERO 2007UseCase Online Image Review: Difference between revisions

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==1. Proposed Workitem: Treatment Delivery Device Data Integration ==
==1. Proposed Workitem: Treatment Delivery Device Data Integration ==


* Proposal Editor: Mika Miettinen, mika.miettinen@varian.com, +1 650 799 7665
*Proposal Editor: Zheng Chang, zheng.chang@duke.edu, +1 919-681-2608; Bridget Koontz, bridget.koontz@duke.edu, +1 919-668-5213
* Editor: Sidrah Abdul/Rishabh Kapoor on behalf of Mika Miettinen
*Editor: Zheng Chang, Bridget Koontz, Firas Mourtada
* Date:   N/A (Wiki keeps history)
*Date: N/A (Wiki keeps history)  
* Version: N/A (Wiki keeps history)
*Version: N/A (Wiki keeps history)  
* Domain: ''Radiation Oncology''
*Domain: Radiation Oncology  
[[Category:RO]]
[[Category:RO]]


==2. The Problem==
==2. The Problem==
Radiotherapy process includes typically several data transfers that involve treatment planning, treatment management system / information system (a.k.a R&V system) and treatment delivery device. It is critical that the data is transferred and interpreted consistently, coherently and safely between all systems that are involved in the radiotherapy process.
Accurate target localization is an important issue to ensure delivering radiation precisely to the tumor while sparing adjacent healthy tissue.  Success of treatment greatly relies on timely therapy delivery (1), reliable and accurate positioning (2), and understanding of dose consequences of positioning differences (3), for both SBRT and standard fractionation therapy. On-line review has been a promising solution to these clinical needs; however, lack of integration of dosimetric information between treatment planning system (TPS) and on-line review Treatment Management System (TMS) may potentially hinder the reliability and efficiency of the patient treatment: The lack of dosimetric data integration causes potential dosimetric discrepancies from prescription putting patient safety at risk. Modern technologies must provide technical solutions to ensure the precise delivery of the radiation doses to patients as planned in TPS and updated cumulative dosimetry so that judgment about set-up approval can be made with cumulative dosimetry in mind.
 
Built into this use case is the need for on-line approval feature, so that physicians approval in the TMS is communicated to offline review as well. Finally, it would require that kv images taken after CBCT approval are converted into a “reference kv” that is used for future set-up online matching.
<br>
Recently a proposal was submitted to include Flattening Filter Free technique into the “Advanced RT Object” Integration profile, so that this new beam modality can be consistently implemented by the vendors to ensure safe treatment delivery. This is just one example of the need to create an integration profile that ensures the integration of the treatment delivery device to the treatment management system and treatment planning system. Currently there are no official, standard
interface requirements to ensure the interoperability of the treatment delivery device and treatment management system, and to make sure that the data is transferred and interpreted correctly between the systems.


==3. Key Use Case==
==3. Key Use Case==


Success scenario:
Scenario #1:  
# Treatment plan is created by treatment planning system
1. A treatment plan has been created in TPS, approved by the physician in TPS, and downloaded to TMS.
# Treatment plan is exported to Treatment Management System following the “Advanced RT Object” Integration Profile
2. Onset of Simulation and/or Treatment, TMS sends relevant treatment data to record and verification (R&V) and on-line review systems.
# Treatment Management System imports the treatment plan following the “Advanced Object” Integration Profile
3. The patient is initially positioned based on skin/mask markers, and is scanned with 3D imaging (ie CBCT, CT-on-rails, etc). 
# Patient is scheduled for treatment
4. Patient imaging on-line match was based on the estimation of the maximum dose to critical organs such as spinal cord, while keeping PTV with acceptable dose coverage.
# Treatment Delivery Device requests the worklist (e.g. patient schedule) from Treatment Management System following the “Treatment Delivery Workflow” Integration Profile.
5. A pair of planar kV images is acquired after on-line approve and couch shift and is saved as reference kV images, comparable to DRRs.
# Treatment Management System provides the worklist following the “Treatment Delivery Workflow” Integration Profile.
Scenario #2:
# Treatment Delivery System requests the treatment plan data from Treatment Management System/Archive following the extended “Advanced RT Object” Integration Profile.
1. A treatment plan has been created in TPS, approved by the physician in TPS, and downloaded to TMS.
# Treatment is performed.
2. Onset of Simulation and/or Treatment, TMS sends relevant treatment data to record and verification (R&V) and on-line review systems.  
# Treatment Delivery Device exports the treatment records to Treatment Management System/Archive following the “Treatment Delivery Workflow” Integration Profile.
3. The patient is initially positioned based on skin/mask markers, and is scanned with 3D imaging (ie CBCT, CT-on-rails, etc)
<br>
4. 3D imaging shows various discrepancies from the treatment plan (organ-at-risks or/and PTV has considerably been deformed, certain patient rotations such as pitch and roll can not corrected due to hardware limitation )
Unsuccessful scenario example:
5. The physician makes positioning shift based on tumor and critical organ dose that would be delivered by current plan and approves treatment online.
* Treatment Management system exports a treatment plan with flattening filter modality, but Treatment Delivery device interprets the data erroneously as standard beam modality. (See also Flattening Filter Free Mode – Integration Profile Proposal)
6. A pair of planar kV images is acquired after on-line approve and couch shift and is saved as reference kV images, comparable to DRRs.  
 
Scenario #3:
<br>
1. A treatment plan has been created in TPS, approved by the physician in TPS, and downloaded to TMS.  
Without standardization efforts, the potential error sources in data transfer between
2. Onset of Simulation and/or Treatment, TMS sends relevant treatment data to record and verification (R&V) and on-line review systems.  
Treatment Management System and Treatment Delivery Device are numerous.
3. The patient is initially positioned based on skin/mask markers, and is scanned with 3D imaging (ie CBCT, CT-on-rails, etc).  
 
4. 3D imaging shows various discrepancies from the treatment plan: the patient shape has greatly changed due to weight loss, soft-tissue deformation or other factors.
5. The physician could not trust dose distribution projected from planning CT or the volumetric in-room imaging.  
6. Could possibly resolved by real-time dose calculation or future adaptive radiotherapy
Samples of the interconnectivity needed for this use case:  
1. TMS download dosimetric data to on-line review system for on-line review
2. The on-line review system projects dose distribution from planning CT to the volumetric in-room imaging
3. The on-line review system updates dose distribution in real-time during imaging match
4. The on-line review system allows “on-line approve” feature after the optimal and acceptable on-line match is obtained
5. The on-line review system allows a pair of planar kV reference images acquired and saved for future treatments
This is just an example use case, and the workflow of on-line review can be modified based on the practice of individual institute.  


==4. Standards & Systems==
==4. Standards & Systems==


DICOM RT  
DICOM RT standard should be considered to include dosimetric data and reference kV images in implementation of the Use case. One of the main objectives is to transfer dosimetric data to aid on-line review and as such to enhance clinical practice.


==5. Discussion==
==5. Discussion==
 
We anticipate that the online dose review would overlay the isodose from the plan onto the online 3D imaging.  Curently, to do this we download CBCT into TPS, which cannot be done in realtime because of the length of time it takes to do so.  Overlay of the plan will only be effective for areas where inhomogeneity is thought to bring minimal dose changes, and when patient has not undergone significant weight loss or soft-tissue deformation.  Hence Scenario #3 would not be able to accurately portray a dose given.
''<Include additional discussion or consider a few details which might be useful for the detailed proposal>''
Organ deformation will be critical to full implementation which would allow DVH data to be reviewed at the TMS online station.  We’d also like to see cumulative DVHs using organ deformation.
:''<Why IHE would be a good venue to solve the problem and what you think IHE should do to solve it.>''
:''<What might the IHE technical approach be? Existing Actors? New Transactions? Additional Profiles?>''
:''<What are some of the risks or open issues to be addressed?>''

Revision as of 11:59, 15 July 2011

1. Proposed Workitem: Treatment Delivery Device Data Integration

  • Proposal Editor: Zheng Chang, zheng.chang@duke.edu, +1 919-681-2608; Bridget Koontz, bridget.koontz@duke.edu, +1 919-668-5213
  • Editor: Zheng Chang, Bridget Koontz, Firas Mourtada
  • Date: N/A (Wiki keeps history)
  • Version: N/A (Wiki keeps history)
  • Domain: Radiation Oncology

2. The Problem

Accurate target localization is an important issue to ensure delivering radiation precisely to the tumor while sparing adjacent healthy tissue. Success of treatment greatly relies on timely therapy delivery (1), reliable and accurate positioning (2), and understanding of dose consequences of positioning differences (3), for both SBRT and standard fractionation therapy. On-line review has been a promising solution to these clinical needs; however, lack of integration of dosimetric information between treatment planning system (TPS) and on-line review Treatment Management System (TMS) may potentially hinder the reliability and efficiency of the patient treatment: The lack of dosimetric data integration causes potential dosimetric discrepancies from prescription putting patient safety at risk. Modern technologies must provide technical solutions to ensure the precise delivery of the radiation doses to patients as planned in TPS and updated cumulative dosimetry so that judgment about set-up approval can be made with cumulative dosimetry in mind. Built into this use case is the need for on-line approval feature, so that physicians approval in the TMS is communicated to offline review as well. Finally, it would require that kv images taken after CBCT approval are converted into a “reference kv” that is used for future set-up online matching.

3. Key Use Case

Scenario #1: 1. A treatment plan has been created in TPS, approved by the physician in TPS, and downloaded to TMS. 2. Onset of Simulation and/or Treatment, TMS sends relevant treatment data to record and verification (R&V) and on-line review systems. 3. The patient is initially positioned based on skin/mask markers, and is scanned with 3D imaging (ie CBCT, CT-on-rails, etc). 4. Patient imaging on-line match was based on the estimation of the maximum dose to critical organs such as spinal cord, while keeping PTV with acceptable dose coverage. 5. A pair of planar kV images is acquired after on-line approve and couch shift and is saved as reference kV images, comparable to DRRs. Scenario #2: 1. A treatment plan has been created in TPS, approved by the physician in TPS, and downloaded to TMS. 2. Onset of Simulation and/or Treatment, TMS sends relevant treatment data to record and verification (R&V) and on-line review systems. 3. The patient is initially positioned based on skin/mask markers, and is scanned with 3D imaging (ie CBCT, CT-on-rails, etc). 4. 3D imaging shows various discrepancies from the treatment plan (organ-at-risks or/and PTV has considerably been deformed, certain patient rotations such as pitch and roll can not corrected due to hardware limitation ) 5. The physician makes positioning shift based on tumor and critical organ dose that would be delivered by current plan and approves treatment online. 6. A pair of planar kV images is acquired after on-line approve and couch shift and is saved as reference kV images, comparable to DRRs. Scenario #3: 1. A treatment plan has been created in TPS, approved by the physician in TPS, and downloaded to TMS. 2. Onset of Simulation and/or Treatment, TMS sends relevant treatment data to record and verification (R&V) and on-line review systems. 3. The patient is initially positioned based on skin/mask markers, and is scanned with 3D imaging (ie CBCT, CT-on-rails, etc). 4. 3D imaging shows various discrepancies from the treatment plan: the patient shape has greatly changed due to weight loss, soft-tissue deformation or other factors. 5. The physician could not trust dose distribution projected from planning CT or the volumetric in-room imaging. 6. Could possibly resolved by real-time dose calculation or future adaptive radiotherapy Samples of the interconnectivity needed for this use case: 1. TMS download dosimetric data to on-line review system for on-line review 2. The on-line review system projects dose distribution from planning CT to the volumetric in-room imaging 3. The on-line review system updates dose distribution in real-time during imaging match 4. The on-line review system allows “on-line approve” feature after the optimal and acceptable on-line match is obtained 5. The on-line review system allows a pair of planar kV reference images acquired and saved for future treatments This is just an example use case, and the workflow of on-line review can be modified based on the practice of individual institute.

4. Standards & Systems

DICOM RT standard should be considered to include dosimetric data and reference kV images in implementation of the Use case. One of the main objectives is to transfer dosimetric data to aid on-line review and as such to enhance clinical practice.

5. Discussion

We anticipate that the online dose review would overlay the isodose from the plan onto the online 3D imaging. Curently, to do this we download CBCT into TPS, which cannot be done in realtime because of the length of time it takes to do so. Overlay of the plan will only be effective for areas where inhomogeneity is thought to bring minimal dose changes, and when patient has not undergone significant weight loss or soft-tissue deformation. Hence Scenario #3 would not be able to accurately portray a dose given. Organ deformation will be critical to full implementation which would allow DVH data to be reviewed at the TMS online station. We’d also like to see cumulative DVHs using organ deformation.