Automatic Delineation of On-Line Head-And-Neck Computed Tomography Images: Toward On-Line Adaptive Radiotherapy

Introduction: The registration accuracy of megavoltage computed tomography images is limited by low image contrast when compared to that of kilovoltage computed tomography images. Such issues may degrade the deformable image registration accuracy. This study evaluates the deformable image registration from kilovoltage to megavoltage images when using different deformation methods and assessing nasopharyngeal carcinoma patient images. Methods: The kilovoltage and the megavoltage images from the first day and the 20th fractions of the treatment day of 12 patients with nasopharyngeal carcinoma were used to evaluate the deformable image registration application. The deformable image registration image procedures were classified into 3 groups, including kilovoltage to kilovoltage, megavoltage to megavoltage, and kilovoltage to megavoltage. Three deformable image registration methods were employed using the deformable image registration and adaptive radiotherapy software. The validation was compared by volume-based, intensity-based, and deformation field analyses. Results: The use of different deformation methods greatly affected the deformable image registration accuracy from kilovoltage to megavoltage. The asymmetric transformation with the demon method was significantly better than other methods and illustrated satisfactory value for adaptive applications. The deformable image registration accuracy from kilovoltage to megavoltage showed no significant difference from the kilovoltage to kilovoltage images when using the appropriate method of registration. Conclusions: The choice of deformation method should be considered when applying the deformable image registration from kilovoltage to megavoltage images. The deformable image registration accuracy from kilovoltage to megavoltage revealed a good agreement in terms of intensity-based, volume-based, and deformation field analyses and showed clinically useful methods for nasopharyngeal carcinoma adaptive radiotherapy in tomotherapy applications.

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Metal Artifact Reduction in Cone-Beam Computed Tomography for Head and Neck Radiotherapy

Technology in Cancer Research & Treatment ◽

10.1177/1533034615618319 ◽

2016 ◽

Vol 15 (6) ◽

pp. NP88-NP94 ◽

Cited By ~ 3

Author(s):

Mark Korpics ◽

Paul Johnson ◽

Rakesh Patel ◽

Murat Surucu ◽

Mehee Choi ◽

...

Keyword(s):

Computed Tomography ◽

Head And Neck ◽

Cone Beam Computed Tomography ◽

Regions Of Interest ◽

Cone Beam ◽

Artifact Reduction ◽

Metal Artifacts ◽

Dental Fillings ◽

Computed Tomography Images ◽

Streak Artifacts

Purpose: To evaluate a method for reducing metal artifacts, arising from dental fillings, on cone-beam computed tomography images. Materials and Methods: A projection interpolation algorithm is applied to cone-beam computed tomography images containing metal artifacts from dental fillings. This technique involves identifying metal regions in individual cone-beam computed tomography projections and interpolating the surrounding values to remove the metal from the projection data. Axial cone-beam computed tomography images are then reconstructed, resulting in a reduction in the streak artifacts produced by the metal. Both phantom and patient imaging data are used to evaluate this technique. Results: The interpolation substitution technique successfully reduced metal artifacts in all cases. Corrected images had fewer or no streak artifacts compared to their noncorrected counterparts. Quantitatively, regions of interest containing the artifacts showed reduced variance in the corrected images versus the uncorrected images. Average pixel values in regions of interest around the metal object were also closer in value to nonmetal regions after artifact reduction. Artifact correction tended to perform better on patient images with less complex metal objects versus those with multiple large dental fillings. Conclusion: The interpolation substitution is potentially an efficient and effective technique for reducing metal artifacts caused by dental fillings on cone-beam computed tomography image. This technique may be effective in reducing such artifacts in patients with head and neck cancer receiving daily image-guided radiotherapy.

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