Split-volume treatment planning of multiple consecutive vertebral body metastases for cyberknife image-guided robotic radiosurgery.

Cyberknife treatment planning of multiple consecutive vertebral body metastases is challenging due to large target volumes adjacent to critical normal tissues. A split-volume treatment planning technique was developed to improve the treatment plan quality of such lesions. Treatment plans were generated for 1 to 5 consecutive thoracic vertebral bodies (CVBM) prescribing a total dose of 24 Gy in 3 fractions. The planning target volume (PTV) consisted of the entire vertebral body(ies). Treatment plans were generated considering both the de novo clinical scenario (no prior radiation), imposing a dose limit of 8 Gy to 1 cc of spinal cord, and the retreatment scenario (prior radiation) with a dose limit of 3 Gy to 1 cc of spinal cord. The split-volume planning technique was compared with the standard full-volume technique only for targets ranging from 2 to 5 CVBM in length. The primary endpoint was to obtain best PTV coverage by the 24 Gy prescription isodose line. A total of 18 treatment plans were generated (10 standard and 8 split-volume). PTV coverage by the 24-Gy isodose line worsened consistently as the number of CVBM increased for both the de novo and retreatment scenario. Split-volume planning was achieved by introducing a 0.5-cm gap, splitting the standard full-volume PTV into 2 equal length PTVs. In every case, split-volume planning resulted in improved PTV coverage by the 24-Gy isodose line ranging from 4% to 12% for the de novo scenario and, 8% to 17% for the retreatment scenario. We did not observe a significant trend for increased monitor units required, or higher doses to spinal cord or esophagus, with split-volume planning. Split-volume treatment planning significantly improves Cyberknife treatment plan quality for CVBM, as compared to the standard technique. This technique may be of particular importance in clinical situations where stringent spinal cord dose limits are required.