Geometric uncertainty of 2D projection imaging in monitoring 3D tumor motion.
The purpose of this study was to investigate the accuracy of two-dimensional (2D) projection imaging methods in three-dimensional (3D) tumor motion monitoring. Many commercial linear accelerator types have projection imaging capabilities, and tumor motion monitoring is useful for motion inclusive, respiratory gated or tumor tracking strategies. Since 2D projection imaging is limited in its ability to resolve the motion along the imaging beam axis, there is unresolved motion when monitoring 3D tumor motion. From the 3D tumor motion data of 160 treatment fractions for 46 thoracic and abdominal cancer patients, the unresolved motion due to the geometric limitation of 2D projection imaging was calculated as displacement in the imaging beam axis for different beam angles and time intervals. The geometric uncertainty to monitor 3D motion caused by the unresolved motion of 2D imaging was quantified using the root-mean-square (rms) metric. Geometric uncertainty showed interfractional and intrafractional variation. Patient-to-patient variation was much more significant than variation for different time intervals. For the patient cohort studied, as the time intervals increase, the rms, minimum and maximum values of the rms uncertainty show decreasing tendencies for the lung patients but increasing for the liver and retroperitoneal patients, which could be attributed to patient relaxation. Geometric uncertainty was smaller for coplanar treatments than non-coplanar treatments, as superior-inferior (SI) tumor motion, the predominant motion from patient respiration, could be always resolved for coplanar treatments. Overall rms of the rms uncertainty was 0.13 cm for all treatment fractions and 0.18 cm for the treatment fractions whose average breathing peak-trough ranges were more than 0.5 cm. The geometric uncertainty for 2D imaging varies depending on the tumor site, tumor motion range, time interval and beam angle as well as between patients, between fractions and within a fraction.
Suh
Yelin
Y
Department of Radiation Oncology, Virginia Commonwealth University, Richmond, VA, and Department of Radiation Medicine, Georgetown University Hospital, Washington, DC, USA.
Dieterich
Sonja
S
Keall
Paul J
PJ
D006801:Humans; D021621:Imaging, Three-Dimensional; D008113:Liver Neoplasms / Q000000981:diagnostic imaging*; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D009068:Movement / Q000502:physiology*; D011857:Radiographic Image Interpretation, Computer-Assisted; D012119:Respiration; D012186:Retroperitoneal Neoplasms / Q000000981:diagnostic imaging*