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Comparing different image registration methods in kilovolt cone-beam computed tomography image-guided radiotherapy for liver cancer / 中华放射肿瘤学杂志
Chinese Journal of Radiation Oncology ; (6): 444-448, 2015.
Article in Chinese | WPRIM | ID: wpr-467358
ABSTRACT
Objective To study the methods of matching kilovolt CBCT image with planning CT scan. Methods A total of 121 CBCT scans were matched with planning CT scan using a manual and four automatic match methods by four observers in the offline. In the manual match, the live contour was used as a surrogate for image registration. Four automatic match methods, including routine soft?tissue match, routine bone match, automatic liver match and vertebral body match, were performed using image registration sofeware. First, the stability of the sofeware was tested. Then, the reproducibility of the same automatic match method was evaluated by comparing different observers’ match results. After the manual match by four observers, the mean of the match results was used as a standard to compare with others. The differerces was test by McNemar method. Results In the uniform match factors, automatic match result would not change. The reproducibility of routine soft?tissue and bone match are best, automatic vertebral body match is better than automatic liver match. Howerver, the automatic liver match result is the most similar to manual match, the percentages of match result have an absolute error no more than 3 mm in left?right, superior?inferior and anterior?posterior directions are 84?? 3%, 77?? 7% and 92?? 6%. Conclusions Automatic liver match can be used in image?guided radiotherapy for liver cancer, however, it should be performed by experienced oncologist and technologist together in each fraction, after that, the matching result should be adjusted carefully according to live contour.

Full text: Available Index: WPRIM (Western Pacific) Language: Chinese Journal: Chinese Journal of Radiation Oncology Year: 2015 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Language: Chinese Journal: Chinese Journal of Radiation Oncology Year: 2015 Type: Article