Influence of 4D CT-based respiratory signal acquisition methods on delineation of moving tumor targets / 中国辐射卫生
Chinese Journal of Radiological Health
; (6): 35-39, 2023.
Article
in Zh
| WPRIM
| ID: wpr-965369
Responsible library:
WPRO
ABSTRACT
@#<b>Objective</b> To compare the effects of different respiratory signal acquisition methods on the delineation of moving tumor targets. <b>Methods</b> A cube phantom containing a sphere was placed on a motion platform to simulate respiratory movement by setting motion period, frequency, and direction. Respiratory signal was acquired by real-time position management (RPM) method and GE method independently. Target delineation was conducted using the maximum intensity projection (MIP) sequence. The difference between the reconstructed volume and the theoretical moving volume was compared under the two respiratory signal acquisition methods for cube and sphere targets. <b>Results</b> Under the same respiratory signal acquisition method, the same respiratory amplitude, and different respiratory frequencies, reconstructed volume changes were relatively small. For the sphere target, the deviation between the reconstructed volume and the theoretical moving volume was −1.5% to 5.7% with the RPM method and −1.3% to −13.8% with the GE method (both <i>P</i> < 0.05). For the cube target, the deviation between the reconstructed volume and the theoretical moving volume was 0.2% to 0.9% with the RPM method and −2.6% to 0.9% with the GE method, with no statistical significance. <b>Conclusion</b> For small-volume sphere targets, the target volumes obtained from MIP images by the two respiratory signal acquisition methods are both smaller than the actual moving volume. For large-volume cube targets, there is no significant difference between the reconstructed and theoretical results with any respiratory signal acquisition method. The RPM method produces smaller deviation and better image quality when reconstructing small-volume targets.
Full text:
1
Database:
WPRIM
Language:
Zh
Journal:
Chinese Journal of Radiological Health
Year:
2023
Document type:
Article