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Clinical validation of a 4D-CT based method for lung ventilation measurement in phantoms and patients
- Source :
- Nyeng, T B, Kallehauge, J F, Høyer, M, Petersen, J B B, Poulsen, P R & Muren, L P 2011, ' Clinical validation of a 4D-CT based method for lung ventilation measurement in phantoms and patients ', Acta Oncologica, vol. 50, no. 6, pp. 897-907 . https://doi.org/10.3109/0284186X.2011.577096
- Publication Year :
- 2011
- Publisher :
- Informa UK Limited, 2011.
-
Abstract
- Lung cancer patients referred to radiotherapy (RT) often present with regional lung function deficits, and it is therefore of interest to image their lung function prior to treatment. In this study a method was developed that uses a deformable image registration (DIR) between the peak-inhale and peak-exhale phases of a thoracic four-dimensional computed tomography (4D-CT) scan to extract ventilation information. The method calculates the displacement vector fields (DVFs) resulting from the DIR using the Jacobian map approach in order to extract information regarding regional lung volume change.The DVFs resulting from DIRs were analysed to compute the Jacobian determinant of vectors in the field, thus obtaining a map of the vector gradients of the entire registered CT image, i.e. voxel-wise local volume change. Geometric and quantitative validation was achieved using images of both phantoms and patients. In the phantom studies, translations and deformations of known size and direction were introduced to validate both the DIR algorithm and the method as a whole. Furthermore, five patients underwent 4D-CT for planning of stereotactic body RT (SBRT). The patients were immobilised in a stereotactic body frame (SBF) and for each patient, two thoracic 4D-CT scans were acquired, one scan with respiration restricted by an abdominal compression plate and the other under free breathing.In the phantom studies deformation errors were found to be of the order of the expected precision of 3 mm, corresponding to the image slice distance, in lateral and vertical directions. For the longitudinal direction a more pronounced discrepancy was observed, with the algorithm predicting displacement lengths of less than half of the physically introduced deformation. Qualitatively the method performed as expected. In the patient study an inverse consistency test showed deviations of up to 5.8 mm, i.e. almost twice the image slice separation. Jacobian maps of the patient images indicated well-ventilated areas as anatomically expected.The established method provides a means of using a (commercially available) DIR algorithm to obtain a quantitative measure of local lung volume change. With further phantom and patient validation studies, quantitative maps of specific ventilation should be possible to produce and use in a clinical setting.
- Subjects :
- medicine.medical_specialty
Lung Neoplasms
Image registration
Computed tomography
Volume change
Radiosurgery
symbols.namesake
Carcinoma, Non-Small-Cell Lung
medicine
Humans
Radiology, Nuclear Medicine and imaging
Four-Dimensional Computed Tomography
Radionuclide Imaging
Lung cancer
Lung ventilation
Lung function
medicine.diagnostic_test
Phantoms, Imaging
business.industry
Respiration
Hematology
General Medicine
Prognosis
medicine.disease
Surgery
Oncology
Jacobian matrix and determinant
symbols
Radiographic Image Interpretation, Computer-Assisted
Radiotherapy, Intensity-Modulated
Pulmonary Ventilation
Tomography, X-Ray Computed
Nuclear medicine
business
Phantom studies
Algorithms
Subjects
Details
- ISSN :
- 1651226X and 0284186X
- Volume :
- 50
- Database :
- OpenAIRE
- Journal :
- Acta Oncologica
- Accession number :
- edsair.doi.dedup.....478932b580b7865ee89c97a565ecf381