An adaptive approach to metal artifact reduction in helical computed tomography for radiation therapy treatment planning: experimental and clinical studies.
OBJECTIVE
In this article, an approach to metal artifact reduction is proposed that is practical for clinical use in radiation therapy. It is based on a new interpolation scheme of the projections associated with metal implants in helical computed tomography (CT) scanners.


METHODS
A three-step approach was developed consisting of an automatic algorithm for metal implant detection, a correction algorithm for helical projections, and a new, efficient algorithm for projection interpolation. The modified raw projection data are transferred back to the CT scanner device where CT slices are regenerated using the built-in reconstruction operator. The algorithm was tested on a CT calibration phantom in which the density of inserted objects are known and on clinical prostate cases with two hip prostheses. The results are evaluated using the CT number and shape of the objects.


RESULTS
The validations on a CT calibration phantom with various inserts of known densities show that the algorithm improved the overall image quality by restoring the shape and the representative CT number of the objects in the image. For the clinical hip replacement cases, a large fraction of the bladder, rectum, and prostate that were not visible on the original CT slices were recovered using the algorithm. Precise contouring of the target volume was thus feasible. Without this enhancement, physicians would have drawn bigger margins to be sure to include the target and, at the same time, could have prescribed a lower dose to keep the same level of normal tissue toxicity.


CONCLUSIONS
In both phantom experiment and patient studies, the algorithm resulted in significant artifact reduction with increases in the reliability of planning procedure for the case of metallic hip prostheses. This algorithm is now clinically used as a preprocessing before treatment planning for metal artifact reduction.
Yazdi
Mehran
M
Département de radio-oncologie and Centre de Recherche en Cancérologie de l'Université Laval, Hôtel-Dieu de Québec, Centre Hospitalier Universitaire de Québec, 11 Côte du Palais, Québec City G1R 2J6, Québec, Canada.
Yazdia
Mehran
M
Gingras
Luc
L
Beaulieu
Luc
L
D000465:Algorithms; D016477:Artifacts; D006622:Hip Prosthesis; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D008297:Male; D008670:Metals; D019047:Phantoms, Imaging; D011471:Prostatic Neoplasms / Q000000981:diagnostic imaging; D019736:Prostheses and Implants; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D036542:Tomography, Spiral Computed / Q000379:methods*; D014057:Tomography, X-Ray Computed / Q000379:methods*
D008670:Metals