Initial Experience with Correlation Object-Based DRR Targeting Using Stereoscopic X-Ray Imaging in Lung SBRT.

BACKGROUND/

OBJECTIVES

Despite significant advances in imaging technology, real-time intra-fraction monitoring of moving targets remains a challenge in markerless radiotherapy. This retrospective study investigates the use of ExacTrac Dynamic by Brainlab as an intra-fraction monitoring tool for stereotactic body radiotherapy (SBRT) in both early-stage NSCLC and oligometastatic disease.

METHODS

A total of 63 X-ray pairs from 21 patients were analyzed to evaluate tumor visualization with and without a surrogate approach. Statistical analysis was conducted to determine whether failures could be attributed to tumor size or localization using the Mann-Whitney U-test and Fisher's exact test. The accuracy of the X-ray/digitally reconstructed radiograph (DRR) surrogate-based fusion was assessed by calculating and comparing the corresponding 3D vectors according to the linear mixed effects model, with a random slope effect for size of surrogate and a random intercept per patient.

RESULTS

Surrogates enhanced tumor visualization on X-ray/DRR fusions from 14.3% to 75.5%. Tumor size and lung affected (left or right) did not predict visualization success. Tumor location, however, tended to influence visibility, with lesions in the upper lobes being more readily visualized (88%) than those in the lower lobes (48.1%), although no statistical significance was reported (p > 0.05). Regarding geometric accuracy, 76% of the analyzed data points deviated less than 5 mm in the 3D vector measurements, the mean values were around 4 mm (±3 mm), and the medians were within 3 mm across all conditions. No statistically significant differences (p > 0.05) were found based on the surrogate size or the triggering time of the X-ray during the breathing cycle.

CONCLUSIONS

Surrogate-based DRRs, referred to as Correlation Objects, demonstrate consistent geometric accuracy across multiple surrogate sizes and X-ray acquisitions, supporting the clinical translation of markerless lung targeting workflows for lung SBRT.