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Atlas-based semiautomatic target volume definition (CTV) for head-and-neck tumors
Gerd Strassmann1, Soulimane Abdellaoui, Detlef Richter
1Department of Radiotherapy and Radiation Oncology, University of Marburg, Marburg, Germany. gstrassmann@t-online.de
Purpose:
To develop a new semiautomatic method to improve target delineation in head-and-neck cancer.
Methods And Materials:
We implemented an atlas-based software program using fourteen anatomic landmarks as well as the most superior and inferior computerd tomography slices for automatic target delineation, using an advanced laryngeal carcinoma as an example. Registration was made by an affine transformation. Evaluation was performed with manually drawn contours for comparison. Three physicians sampled and further applied a target volume atlas to ten other computer tomography data sets. In addition, a rapid three-dimensional (3D) correction program was developed.
Results:
The mean time to the first semiautomatic target delineation proposal was 2.7 minutes. Manual contouring required 20.2 minutes per target, whereas semiautomatic target volume definition with the rapid 3D correction was completed in only 9.7 minutes. The net calculation time for image registration of the target volume atlas was negligible (approximately 0.6 seconds). Our method depicted a sufficient adaptation of the target volume atlas on the new data sets, with a mean similarity index of 77.2%. The similarity index increased up to 85% after 3D correction performed by the physicians.
Conclusions:
We have developed a new, feasible method for semiautomatic contouring that saves a significant amount (51.8%) of target delineation time for head-and-neck cancer patients. This approach uses a target volume atlas and a landmark model. The software was evaluated by means of laryngeal cancer but has important implications for various tumor types whereby target volumes remain constant in form and do not move with respiration.
Insights
A new semiautomatic method significantly reduces head-and-neck cancer target delineation time by 51.8%. This atlas-based approach improves efficiency for radiation therapy planning.
Area of Science:
- Medical Imaging
- Radiation Oncology
- Computational Anatomy
Background:
- Accurate target delineation is crucial for effective radiation therapy in head-and-neck cancer.
- Manual contouring is time-consuming and subject to inter-observer variability.
- Existing automated methods may lack precision for complex anatomical regions.
Purpose of the Study:
- To develop and evaluate a novel semiautomatic method for improving target volume delineation in head-and-neck cancer.
- To reduce the time required for manual contouring in radiation therapy planning.
- To assess the accuracy and efficiency of an atlas-based software with 3D correction.
Main Methods:
- Implementation of an atlas-based software utilizing fourteen anatomic landmarks and CT slices for automatic delineation.
- Application of affine transformation for image registration.
- Evaluation through manual contour comparison and physician-led 3D correction on ten datasets.
Main Results:
- Semiautomatic delineation achieved in a mean of 2.7 minutes, significantly faster than manual contouring (20.2 minutes).
- Semiautomatic definition with rapid 3D correction took 9.7 minutes, a 51.8% time saving.
- Mean similarity index of 77.2% for atlas adaptation, increasing to 85% after physician correction.
Conclusions:
- A feasible semiautomatic contouring method using a target volume atlas and landmark model significantly reduces delineation time for head-and-neck cancer.
- The developed software offers substantial time savings and maintains sufficient accuracy.
- This method has broad applicability for tumors with stable target volumes, irrespective of respiration.
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