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Uncertainties in lung motion prediction relying on external surrogate: a 4DCT study in regular vs. irregular breathers
- Source :
- Technology in cancer researchtreatment. 9(3)
- Publication Year :
- 2010
-
Abstract
- This paper examines the uncertainty in estimating lung motion from external surrogates for lung cancer patients with regular and irregular breathing. 4DCT data sets were analyzed using a template matching algorithm to track the spatial movement of vessel bifurcations in 12 patients. The detected internal movement of features in 3D was retrospectively synchronized with the RPM surrogate signal, and the correlation index R2 and the prediction error were computed. Patients were classified into two groups depending on the presence or not of irregularities in their breathing pattern. Peak-to-peak values of feature motion in the SI direction ranged from 0.8 mm (upper lung) to 25.3 mm (lower lung). Some patients exhibited large motion also in the latero-lateral (10.6 mm) and anterior-posterior (12.2 mm) directions. The median ± quartile of R2 in SI direction was 0.89 ± 0.09. Prediction error values were up to 4.2 mm (95th percentile) with a maximum value of 4.9 mm. Statistical differences between regular and irregular breathers were found for R2, while prediction error depended only on the range of motion. This study is relevant for image guided radiotherapy methods that rely on external surrogates to monitor motion.
- Subjects :
- Cancer Research
Percentile
Lung
Lung Neoplasms
Breather
Template matching
Mean squared prediction error
Movement
Respiration
Uncertainty
medicine.anatomical_structure
Oncology
Quartile
Feature (computer vision)
medicine
Humans
Radiographic Image Interpretation, Computer-Assisted
Four-Dimensional Computed Tomography
Range of motion
Algorithms
Biomedical engineering
Mathematics
Subjects
Details
- ISSN :
- 15330338
- Volume :
- 9
- Issue :
- 3
- Database :
- OpenAIRE
- Journal :
- Technology in cancer researchtreatment
- Accession number :
- edsair.doi.dedup.....462030bc3aba8656742ef9e8c035e2a2