Abstract

BackgroundTo 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.MethodsWe 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.ResultsThe 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.ConclusionIGTVMIP and IGTV2Phases underestimate IGTVs. IGTVMIP-Modified is recommended to improve IGTV delineation in lung cancer.

Highlights

  • 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

  • In order to make the determination of the internal target volume (ITV) more efficient, we have proposed the concept of the internal gross tumor volume (IGTV), which explicitly accounts for internal variations in tumor position, size, and shape but can be derived directly from imaging studies [2]

  • A paired sample t-test revealed that the IGTVMIP and IGTV2Phases differed significantly from the IGTVAllPhases(p < 0.001), while the IGTVMIP-Modified did not differ significantly from the reference IGTV (p = 0.08)

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Summary

Introduction

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. Lung cancer remains the leading cause of cancer-related mortality. Conventional photon radiotherapy for lung cancer is associated with about 50% local tumor control [1]. Missing the target as a result of tumor motion has been considered one of the main reasons for local failure [2]. Researchers have reported that ~40% of lung tumors move > 5 mm and that 10–12% move > 1 cm [3,4]. Several strategies have recently been developed to address the issue of tumor motion and improve local control [2].

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