Evaluation of a template-based algorithm for markerless lung tumour localization on single- and dual-energy kilovoltage images

OBJECTIVE

To evaluate a template-based matching algorithm on single-energy (SE) and dual-energy (DE) radiographs for markerless localization of lung tumours.

METHODS

A total of 74 images from 17 patients with Stages IA-IV lung cancer were considered. At the time of radiotherapy treatment, gated end-expiration SE radiographs were obtained at 60 and 120 kVp at different gantry angles (33° anterior and 41° oblique), from which soft-tissue-enhanced DE images were created. A template-based matching algorithm was used to localize individual tumours on both SE and DE radiographs. Tumour centroid co-ordinates obtained from the template-matching software on both SE and DE images were compared with co-ordinates defined by physicians.

RESULTS

The template-based matching algorithm was able to successfully localize the gross tumor volume within 5 mm on 70% (52/74) of the SE images vs 91% (66/74) of the DE images (p < 0.01). The mean vector differences between the co-ordinates of the template matched by the algorithm and the co-ordinates of the physician-defined ground truth were 3.2 ± 2.8 mm for SE images vs 2.3 ± 1.7 mm for DE images (p = 0.03).

CONCLUSION

Template-based matching on DE images was more accurate and precise than using SE images. Advances in knowledge: This represents, to the authors' knowledge, the largest study evaluating template matching on clinical SE and DE images, considering not only anterior gantry angles but also oblique angles, suggesting a novel lung tumour matching technique using DE subtraction that is reliable, accurate and precise.

Markerless motion tracking of lung tumors using dual-energy fluoroscopy

PURPOSE

To evaluate the efficacy of dual-energy (DE) vs single-energy (SE) fluoroscopic imaging of lung tumors using a markerless template-based tracking algorithm.

METHODS

Ten representative patient breathing patterns were programmed into a Quasar™ motion phantom. The phantom was modified by affixing pork ribs to the surface, and a cedar insert with a small spherical volume was used to simulate lung and tumor, respectively. Sequential 60 kVp (6 mA) and 120 kVp (1.5 mA) fluoroscopic sequences were acquired. Frame-by-frame weighted logarithmic subtraction was performed resulting in a DE fluoroscopic sequence. A template-based algorithm was then used to track tumor motion throughout the DE and SE fluoroscopy sequences. Tracking coordinates were evaluated against ground-truth tumor locations. Fluoroscopic images were also acquired for two lung cancer patients, neither of which had implanted fiducials.

RESULTS

For phantom imaging, a total of 1925 frames were analyzed. The algorithm successfully tracked the target on 99.9% (1923/1925) of DE frames vs 90.7% (1745/1925) SE images (p < 0.01). The displacement between tracking coordinates and ground truth for the phantom was 1.4 mm ± 1.1 mm for DE vs 2.0 mm ± 1.3 mm for SE (p < 0.01). Images from two patients, one with a larger tumor and one with a smaller tumor, were also analyzed. For the patient with the larger tumor, the average displacement from physician defined ground truth was 1.2 mm ± 0.6 mm for DE vs 1.4 mm ± 0.7 mm for SE (p = 0.016). For the patient that presented with a smaller tumor, the average displacement from physician defined ground truth was 2.2 mm ± 1.0 mm for DE vs 3.2 mm ± 1.4 mm for SE (p < 0.01). Importantly, for this single patient with the smaller tumor, 15.6% of the SE frames had >5 mm displacements from the ground truth vs 0% for DE fluoroscopy.

CONCLUSIONS

This work indicates the potential for markerless tumor tracking utilizing DE fluoroscopy. With DE imaging, the algorithm showed improved detectability vs SE fluoroscopy and was able to accurately track the tumor in nearly all cases.