Background: To determine the optimal approach to delineating patient-specific internal gross target volumes (IGTV) from four-dimensional (4-D) computed tomography (CT) image data sets used in the planning of radiation treatment for lung cancers.
Methods: We analyzed 4D-CT image data sets of 27 consecutive patients with non-small-cell lung cancer (stage I: 17, stage III: 10). The IGTV, defined to be the envelope of respiratory motion of the gross tumor volume in each 4D-CT data set was delineated manually using four techniques: (1) combining the gross tumor volume (GTV) contours from ten respiratory phases (IGTVAllPhases); (2) combining the GTV contours from two extreme respiratory phases (0% and 50%) (IGTV2Phases); (3) defining the GTV contour using the maximum intensity projection (MIP) (IGTVMIP); and (4) defining the GTV contour using the MIP with modification based on visual verification of contours in individual respiratory phase (IGTVMIP-Modified). Using the IGTVAllPhases as the optimum IGTV, we compared volumes, matching indices, and extent of target missing using the IGTVs based on the other three approaches.
Results: The IGTVMIP and IGTV2Phases were significantly smaller than the IGTVAllPhases (p < 0.006 for stage I and p < 0.002 for stage III). However, the values of the IGTVMIP-Modified were close to those determined from IGTVAllPhases (p = 0.08). IGTVMIP-Modified also matched the best with IGTVAllPhases.
Conclusion: IGTVMIP and IGTV2Phases underestimate IGTVs. IGTVMIP-Modified is recommended to improve IGTV delineation in lung cancer.