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A "rolling average" multiple adaptive planning method to compensate for target volume changes in image-guided radiotherapy of prostate cancer.

Publication ,  Journal Article
Liu, H; Wu, Q
Published in: J Appl Clin Med Phys
January 5, 2012

For prostate cancer radiotherapy, the interfractional organ motion can have several forms: changes in position, shape, and volume. The interfractional motion can be managed through either online or offline image guidance (IG). The position changes are commonly corrected through online IG by correcting couch position at each treatment fraction, while the shape and volume changes, or target deformation, can be compensated by margins in offline adaptive planning. In this study, we proposed and evaluated a rolling-average (RA) adaptive replanning method to account for the target volume variations. A total of 448 repeated helical computed tomography (HCT) scans from 28 patients were included in the study. Both low-risk patients (LRP, CTV = prostate) and intermediate-risk patients (IRP, CTV = prostate + seminal vesicles) were simulated. The benefit of RA strategy was evaluated geometrically and compared with the standard online IG-only method and a single replanning adaptive hybrid strategy. A new geometric index, cumulative index of target volume (CITV), was used for the evaluation. Two extreme scenarios of target volume changes, Type Ascending and Descending, were simulated by sorting the CTV volumes of actual patient data in order to have a better evaluation of the methods. Modest target volume variations were observed in our patient group. The prostate volume change was -0.14 ± 0.11 cc/day (or -0.30% ± 0.26% per day). It is found that RA is superior to the online IG and hybrid techniques. However, the magnitude of improvement depends on how significantly and rapidly the target volume changes. On the issue of planning complexity, the hybrid is more complex than online IG only, requiring one offline replanning, and RA is significantly more complex, with multiple replanning. In clinical implementation of RA, the effectiveness and efficiency should be balanced. The effectiveness is dependent on the patient population. For low-risk patients, RA is beneficial if there is significant time trend in target volume during the treatment course of radiotherapy. The optimal number of fractions necessary for the internal target volume (ITV) construction is 2 for LRP and 3 for IRP for RA strategy.

Duke Scholars

Published In

J Appl Clin Med Phys

DOI

EISSN

1526-9914

Publication Date

January 5, 2012

Volume

13

Issue

1

Start / End Page

3697

Location

United States

Related Subject Headings

  • Radiotherapy, Image-Guided
  • Radiotherapy Planning, Computer-Assisted
  • Radiotherapy Dosage
  • Radiometry
  • Radiography
  • Prostatic Neoplasms
  • Nuclear Medicine & Medical Imaging
  • Motion
  • Male
  • Humans
 

Citation

APA
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ICMJE
MLA
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Liu, H., & Wu, Q. (2012). A "rolling average" multiple adaptive planning method to compensate for target volume changes in image-guided radiotherapy of prostate cancer. J Appl Clin Med Phys, 13(1), 3697. https://doi.org/10.1120/jacmp.v13i1.3697
Liu, Han, and Qiuwen Wu. “A "rolling average" multiple adaptive planning method to compensate for target volume changes in image-guided radiotherapy of prostate cancer.J Appl Clin Med Phys 13, no. 1 (January 5, 2012): 3697. https://doi.org/10.1120/jacmp.v13i1.3697.
Liu, Han, and Qiuwen Wu. “A "rolling average" multiple adaptive planning method to compensate for target volume changes in image-guided radiotherapy of prostate cancer.J Appl Clin Med Phys, vol. 13, no. 1, Jan. 2012, p. 3697. Pubmed, doi:10.1120/jacmp.v13i1.3697.

Published In

J Appl Clin Med Phys

DOI

EISSN

1526-9914

Publication Date

January 5, 2012

Volume

13

Issue

1

Start / End Page

3697

Location

United States

Related Subject Headings

  • Radiotherapy, Image-Guided
  • Radiotherapy Planning, Computer-Assisted
  • Radiotherapy Dosage
  • Radiometry
  • Radiography
  • Prostatic Neoplasms
  • Nuclear Medicine & Medical Imaging
  • Motion
  • Male
  • Humans