dc.contributor.author | Menten, MJ | |
dc.contributor.author | Fast, MF | |
dc.contributor.author | Nill, S | |
dc.contributor.author | Oelfke, U | |
dc.date.accessioned | 2017-10-25T11:01:53Z | |
dc.date.issued | 2015-12-01 | |
dc.identifier.citation | Medical physics, 2015, 42 (12), pp. 6987 - 6998 | |
dc.identifier.issn | 0094-2405 | |
dc.identifier.uri | https://repository.icr.ac.uk/handle/internal/876 | |
dc.identifier.eissn | 2473-4209 | |
dc.identifier.doi | 10.1118/1.4935431 | |
dc.description.abstract | PURPOSE: Real-time, markerless localization of lung tumors with kV imaging is often inhibited by ribs obscuring the tumor and poor soft-tissue contrast. This study investigates the use of dual-energy imaging, which can generate radiographs with reduced bone visibility, to enhance automated lung tumor tracking for real-time adaptive radiotherapy. METHODS: kV images of an anthropomorphic breathing chest phantom were experimentally acquired and radiographs of actual lung cancer patients were Monte-Carlo-simulated at three imaging settings: low-energy (70 kVp, 1.5 mAs), high-energy (140 kVp, 2.5 mAs, 1 mm additional tin filtration), and clinical (120 kVp, 0.25 mAs). Regular dual-energy images were calculated by weighted logarithmic subtraction of high- and low-energy images and filter-free dual-energy images were generated from clinical and low-energy radiographs. The weighting factor to calculate the dual-energy images was determined by means of a novel objective score. The usefulness of dual-energy imaging for real-time tracking with an automated template matching algorithm was investigated. RESULTS: Regular dual-energy imaging was able to increase tracking accuracy in left-right images of the anthropomorphic phantom as well as in 7 out of 24 investigated patient cases. Tracking accuracy remained comparable in three cases and decreased in five cases. Filter-free dual-energy imaging was only able to increase accuracy in 2 out of 24 cases. In four cases no change in accuracy was observed and tracking accuracy worsened in nine cases. In 9 out of 24 cases, it was not possible to define a tracking template due to poor soft-tissue contrast regardless of input images. The mean localization errors using clinical, regular dual-energy, and filter-free dual-energy radiographs were 3.85, 3.32, and 5.24 mm, respectively. Tracking success was dependent on tumor position, tumor size, imaging beam angle, and patient size. CONCLUSIONS: This study has highlighted the influence of patient anatomy on the success rate of real-time markerless tumor tracking using dual-energy imaging. Additionally, the importance of the spectral separation of the imaging beams used to generate the dual-energy images has been shown. | |
dc.format | Print | |
dc.format.extent | 6987 - 6998 | |
dc.language | eng | |
dc.language.iso | eng | |
dc.publisher | WILEY | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0 | |
dc.subject | Bone and Bones | |
dc.subject | Lung | |
dc.subject | Humans | |
dc.subject | Lung Neoplasms | |
dc.subject | Tomography, X-Ray Computed | |
dc.subject | Radiotherapy | |
dc.subject | Monte Carlo Method | |
dc.subject | Respiration | |
dc.subject | X-Rays | |
dc.subject | Models, Biological | |
dc.subject | Computer Simulation | |
dc.subject | Pattern Recognition, Automated | |
dc.title | Using dual-energy x-ray imaging to enhance automated lung tumor tracking during real-time adaptive radiotherapy. | |
dc.type | Journal Article | |
rioxxterms.versionofrecord | 10.1118/1.4935431 | |
rioxxterms.licenseref.uri | https://creativecommons.org/licenses/by/4.0 | |
rioxxterms.licenseref.startdate | 2015-12 | |
rioxxterms.type | Journal Article/Review | |
dc.relation.isPartOf | Medical physics | |
pubs.issue | 12 | |
pubs.notes | Not known | |
pubs.organisational-group | /ICR | |
pubs.organisational-group | /ICR/Primary Group | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging/Radiotherapy Physics Modelling | |
pubs.organisational-group | /ICR | |
pubs.organisational-group | /ICR/Primary Group | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging/Radiotherapy Physics Modelling | |
pubs.publication-status | Published | |
pubs.volume | 42 | |
pubs.embargo.terms | Not known | |
icr.researchteam | Radiotherapy Physics Modelling | |
dc.contributor.icrauthor | Menten, Martin | |
dc.contributor.icrauthor | Nill, Simeon | |