Cone-beam CT-based delineation of stereotactic lung targets: the influence of image modality and target size on...

It is generally agreed that the safe implementation of stereotactic body radiotherapy requires image guidance. The aim of this work was to assess interobserver variability in the delineation of lung lesions on cone-beam CT (CBCT) images compared with CT-based contouring for adaptive stereotactic body radiotherapy. The influence of target size was also evaluated.

Eight radiation oncologists delineated gross tumor volumes in 12 patient cases (non-small cell lung cancer I-II or solitary metastasis) on planning CTs and on CBCTs. Cases were divided into two groups with tumor diameters of less than (Group A) or more than 2 cm (Group B). Comparison of mean volumes delineated by all observers and range and coefficient of variation were reported for each case and image modality. Interobserver variability was assessed by means of standard error of measurement, conformity index (CI), and its generalized observer-independent approach. The variance between single observers on CT and CBCT images was measured via interobserver reliability coefficient.

Interobserver variability on CT images was 17% with 0.79 reliability, compared with 21% variability on CBCT and 0.76 reliability. On both image modalities, values of the intraobserver reliability coefficient (0.99 for CT and 0.97 for CBCT) indicated high reproducibility of results. In general, lower interobserver agreement was observed for small lesions (CI(genA) = 0.62 ± 0.06 vs. CI(genB) = 0.70 ± 0.03, p < 0.05). The analysis of single patient cases revealed that presence of spicules, diffuse infiltrations, proximity of the tumors to the vessels and thoracic wall, and respiration motion artifacts presented the main sources of the variability.

Interobserver variability for Stage I-II non-small cell lung cancer and lung metastasis was slightly higher on CBCT compared with CT. Absence of significant differences in interobserver variability suggests that CBCT imaging provides an effective tool for tumor localization, and image data could be also used for target volume delineation purposes.