David P Gierga1, Julie C Turcotte2, Long W Tong2, Yen-Lin E Chen3, Thomas F DeLaney3. 1. Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts. Electronic address: dgierga@partners.org. 2. Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts. 3. Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts.
Abstract
PURPOSE: Proper positioning of patients with extremity sarcoma tumors can be challenging. A surface imaging technique was utilized to quantify the setup uncertainties for sarcoma patients and to assess whether surface imaging could improve the accuracy of patient positioning. METHODS AND MATERIALS: Pretreatment and posttreatment 3-dimensional (3D) surface images were obtained for 16 patients and 236 treatments. Offline surface registration was performed to quantify interfraction and intrafraction setup errors, and the required planning target volume (PTV) margins were calculated. Setup differences were also assessed using root mean square (RMS) error analysis. RESULTS: For intrafraction variation, the mean 3D vector shift was 2.1 mm, and the systematic and random errors were 1.3 mm or less. When using a reference surface from the first fraction, the mean interfraction setup variation (3D vector shift) was 7.6 mm. Systematic and random errors were 3-4 mm in each direction. When using a computed tomographic based reference surface, the mean 3D vector shift was 9.5 mm. Systematic and random errors ranged from 3.1 to 7.9 mm. The required PTV margins were 1.0 cm, 1.2 cm, and 1.3 cm in the anterior-posterior, superior-inferior, and lateral directions, respectively. The mean (standard deviation) RMS errors for the uncorrected position were 4.7 mm (1.9 mm) and were reduced to 2.2 mm (0.8 mm) and 1.7 mm (0.8 mm), for 4 degree of freedom (DOF) and 6 DOF surface alignment, respectively. CONCLUSIONS: Intrafraction motion is small. Interfraction motion can exceed typical PTV margins and daily imaging should be utilized to reduce setup variations. Surface imaging may reduce setup errors and is a feasible technique for daily image guidance.
PURPOSE: Proper positioning of patients with extremity sarcoma tumors can be challenging. A surface imaging technique was utilized to quantify the setup uncertainties for sarcomapatients and to assess whether surface imaging could improve the accuracy of patient positioning. METHODS AND MATERIALS: Pretreatment and posttreatment 3-dimensional (3D) surface images were obtained for 16 patients and 236 treatments. Offline surface registration was performed to quantify interfraction and intrafraction setup errors, and the required planning target volume (PTV) margins were calculated. Setup differences were also assessed using root mean square (RMS) error analysis. RESULTS: For intrafraction variation, the mean 3D vector shift was 2.1 mm, and the systematic and random errors were 1.3 mm or less. When using a reference surface from the first fraction, the mean interfraction setup variation (3D vector shift) was 7.6 mm. Systematic and random errors were 3-4 mm in each direction. When using a computed tomographic based reference surface, the mean 3D vector shift was 9.5 mm. Systematic and random errors ranged from 3.1 to 7.9 mm. The required PTV margins were 1.0 cm, 1.2 cm, and 1.3 cm in the anterior-posterior, superior-inferior, and lateral directions, respectively. The mean (standard deviation) RMS errors for the uncorrected position were 4.7 mm (1.9 mm) and were reduced to 2.2 mm (0.8 mm) and 1.7 mm (0.8 mm), for 4 degree of freedom (DOF) and 6 DOF surface alignment, respectively. CONCLUSIONS: Intrafraction motion is small. Interfraction motion can exceed typical PTV margins and daily imaging should be utilized to reduce setup variations. Surface imaging may reduce setup errors and is a feasible technique for daily image guidance.
Authors: Hania A Al-Hallaq; Laura Cerviño; Alonso N Gutierrez; Amanda Havnen-Smith; Susan A Higgins; Malin Kügele; Laura Padilla; Todd Pawlicki; Nicholas Remmes; Koren Smith; Xiaoli Tang; Wolfgang A Tomé Journal: Med Phys Date: 2022-03-15 Impact factor: 4.506
Authors: Hui Zhao; Adam Paxton; Vikren Sarkar; Ryan G Price; Jessica Huang; Fan-Chi Frances Su; Xing Li; Prema Rassiah; Martin Szegedi; Bill Salter Journal: Cureus Date: 2022-08-31