IHERO 2007UseCase Online Image Review

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1. Proposed Workitem: On-Line Image Review

  • 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.