A research, couch-mounted, VisionRT (VRT) system was used to acquire optical surface data (15 Hz, ROI = 15 × 20 cm2 ) from the thoraco-abdominal surface of a consented lung SBRT patient, concurrently with their standard-of-care 4DCT. 
VisionRT
We develop and validate a motion model that uses real-time surface photogrammetry acquired concurrently with four-dimensional computed tomography (4DCT) to estimate respiration-induced changes within the entire irradiated volume, over arbitrarily many respiratory cycles.


 A research, couch-mounted, VisionRT (VRT) system was used to acquire optical surface data (15 Hz, ROI = 15 × 20 cm2 ) from the thoraco-abdominal surface of a consented lung SBRT patient, concurrently with their standard-of-care 4DCT.  The end-exhalation phase from the 4DCT was regarded as reference and for each remaining phase, deformation vector fields (DVFs) with respect to the reference phase were computed.  For five of the six fluoroscopic acquisition sessions, the model out-performed 4DCT in predicting contour Dice coefficient with respect to fluoroscopy-derived contours.  Similarly, the model exhibited a marked improvement over 4DCT for patch positions on the diaphragm.  Model patch position errors varied from 5 to -15 mm while 4DCT errors ranged between 5 and -22.4 mm.  For one fluoroscopic acquisition, a marked change in the a priori internal-external correlation resulted in model errors comparable to those of 4DCT.


 These early results indicate that the proposed approach can result in a marked improvement over 4DCT. 
4DCT