A technique for reducing patient setup uncertainties by aligning and verifying daily positioning of a moving tumor using implanted fiducials.
This study aimed to validate and implement a methodology in which fiducials implanted in the periphery of lung tumors can be used to reduce uncertainties in tumor location. Alignment software that matches marker positions on two-dimensional (2D) kilovoltage portal images to positions on three-dimensional (3D) computed tomography data sets was validated using static and moving phantoms. This software also was used to reduce uncertainties in tumor location in a patient with fiducials implanted in the periphery of a lung tumor. Alignment of fiducial locations in orthogonal projection images with corresponding fiducial locations in 3D data sets can position both static and moving phantoms with an accuracy of 1 mm. In a patient, alignment based on fiducial locations reduced systematic errors in the left-right direction by 3 mm and random errors by 2 mm, and random errors in the superior-inferior direction by 3 mm as measured by anterior-posterior cine images. Software that matches fiducial markers on 2D and 3D images is effective for aligning both static and moving fiducials before treatment and can be implemented to reduce patient setup uncertainties.
Nelson
Christopher
C
Departments of Radiation Physics, The University of Texas M.D. Anderson Cancer Center, Houston, Texas, U.S.A.
Balter
Peter
P
Departments of Radiation Physics, The University of Texas M.D. Anderson Cancer Center, Houston, Texas, U.S.A.
Morice
Rodolfo C
RC
Pulmonary Medicine, The University of Texas M.D. Anderson Cancer Center, Houston, Texas, U.S.A.
Choi
Bum
B
Departments of Radiation Physics, The University of Texas M.D. Anderson Cancer Center, Houston, Texas, U.S.A.
Kudchadker
Rajat J
RJ
Departments of Radiation Physics, The University of Texas M.D. Anderson Cancer Center, Houston, Texas, U.S.A.
Bucci
Kara
K
Radiation Oncology, The University of Texas M.D. Anderson Cancer Center, Houston, Texas, U.S.A.
Chang
Joe Y
JY
Radiation Oncology, The University of Texas M.D. Anderson Cancer Center, Houston, Texas, U.S.A.
Dong
Lei
L
Departments of Radiation Physics, The University of Texas M.D. Anderson Cancer Center, Houston, Texas, U.S.A.
Tucker
Susan
S
Bioinformatics and Computational Biology, The University of Texas M.D. Anderson Cancer Center, Houston, Texas, U.S.A.
Vedam
Sastry
S
Departments of Radiation Physics, The University of Texas M.D. Anderson Cancer Center, Houston, Texas, U.S.A.
Briere
Tina
T
Departments of Radiation Physics, The University of Texas M.D. Anderson Cancer Center, Houston, Texas, U.S.A.
Starkschall
George
G
Departments of Radiation Physics, The University of Texas M.D. Anderson Cancer Center, Houston, Texas, U.S.A.
D000369:Aged, 80 and over; D000465:Algorithms; D003198:Computer Simulation; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008175:Lung Neoplasms / Q000175:diagnosis* / Q000473:pathology*; D008297:Male; D008495:Medical Oncology / Q000379:methods; D019047:Phantoms, Imaging; D011856:Radiographic Image Enhancement / Q000379:methods; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012984:Software; D013997:Time Factors; D014057:Tomography, X-Ray Computed / Q000379:methods*