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Tumor location cannot predict the mobility of lung tumors: a 3D analysis of data generated from multiple CT scans
John R van Sörnsen de Koste1, Frank J Lagerwaard, Margriet R J Nijssen-Visser
1Department of Radiation Oncology Erasmus Medical Center, Rotterdam, The Netherlands.
Purpose:
There is limited information available on the three-dimensional (3D) motion of lung tumors. Data derived from multiple planning computed tomographic (CT) scans were used to characterize the 3D movement of small peripheral lung tumors.
Methods And Materials:
A total of 29 data sets from patients with Stage I non-small-cell lung cancer (NSCLC), each of which consisted of three "rapid" and three "slow" planning CT scans, were analyzed. All six scans were coregistered, and contoured gross tumor volumes (GTVs) were expanded by 5 mm to derive clinical target volumes (CTVs). Two-dimensional and 3D displacement vectors of the individual CTVs, relative to an "optimal" CTV derived from all six scans, were generated. Tumor mobility was correlated with location. Three-dimensional margins, which had to be added to individual CTVs to ensure coverage of "optimal" CTVs, were determined.
Results:
No significant correlation was observed between the anatomic location of tumors and the extent of mobility in the x, y, and z axes. However, supradiaphragmatic lesions exhibited more mobility, particularly in the craniocaudal direction. The addition of a 3D margin of 5 mm to a single slow CTV ensured full coverage of the "optimal CTV".
Conclusions:
Lung tumors demonstrate significant mobility in all directions, and this did not closely correlate with anatomic location. Individualized assessment of tumor mobility remains necessary, and is possible when the CTV derived from a single slow scan is used for radiotherapy planning.