SU-E-J-138: Fast 2-D Fiducial Marker Detection on Sequential MV Projections in Arc Therapy.

PURPOSE

To automatically detect intrafraction motion during arc radiotherapy for prostate cancer patients by tracking fiducial markers in two-dimensional MV images acquired using the treatment beam, in order to adjust radiation dose accordingly.

METHODS

Four fiducial gold markers are implanted in a patient's prostate. Patients are irradiated using a Varian Linac 2100 C/D with RapidArc upgrade (Varian Medical Systems, Palo Alto, CA). MV images (1024 × 768 pixels, 0.392 × 0.392 mm pixel size) acquired during a 360 degree gantry rotation at a one second interval (5 degrees) are preprocessed by subtracting a smoothed version of the image to retain only high image frequencies. Edge detection is then applied, followed by a one pixel wide dilation and erosion to transform the edges into contiguous regions. Next, our method searches the centers of visible markers (i.e. not covered by the MLC), constrained by marker estimates from the planning CT. This is done by finding all contiguous regions and maximizing a marker-region distance criterion for every visible marker. A two-dimensional estimate correction over consecutive projections is also implemented to improve marker estimates during gantry rotation.

RESULTS

We applied our method on four treatment fractions of the same patient. As such, a total of 191 projections with manually indicated marker ends as ground truth were used as validation. Markers were indicated twice on all images, to include observer errors. Results show a mean detection error of less than 0.5 mm in the projection image (standard deviation 0.6 mm), with an execution time of less than one second per image in matlab. Undetected markers and false positives mostly occurred at moving leaf boundaries, where marker visibility was determined by the observer.

CONCLUSIONS

Preliminary findings demonstrate that this method can be used to detect intrafraction motion during arc radiotherapy by only using projected MV images. Research sponsored by Varian Medical Systems, Palo Alto, CA.