Daniel Forsberg1,2, Maria Lindblom3, Petter Quick4, Håkan Gauffin5. 1. Sectra AB, Linköping, Sweden. daniel.forsberg@sectra.com. 2. Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden. daniel.forsberg@sectra.com. 3. Department of Radiology, Linköping University Hospital, Linköping, Sweden. 4. Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden. 5. Orthopaedic Department, Linköping University, Linköping, Sweden.
Abstract
PURPOSE: To present a semi-automatic method with minimal user interaction for quantitative analysis of the patellofemoral motion pattern. METHODS: 4D CT data capturing the patellofemoral motion pattern of a continuous flexion and extension were collected for five patients prone to patellar luxation both pre- and post-surgically. For the proposed method, an observer would place landmarks in a single 3D volume, which then are automatically propagated to the other volumes in a time sequence. From the landmarks in each volume, the measures patellar displacement, patellar tilt and angle between femur and tibia were computed. RESULTS: Evaluation of the observer variability showed the proposed semi-automatic method to be favorable over a fully manual counterpart, with an observer variability of approximately 1.5[Formula: see text] for the angle between femur and tibia, 1.5 mm for the patellar displacement, and 4.0[Formula: see text]-5.0[Formula: see text] for the patellar tilt. The proposed method showed that surgery reduced the patellar displacement and tilt at maximum extension with approximately 10-15 mm and 15[Formula: see text]-20[Formula: see text] for three patients but with less evident differences for two of the patients. CONCLUSIONS: A semi-automatic method suitable for quantification of the patellofemoral motion pattern as captured by 4D CT data has been presented. Its observer variability is on par with that of other methods but with the distinct advantage to support continuous motions during the image acquisition.
PURPOSE: To present a semi-automatic method with minimal user interaction for quantitative analysis of the patellofemoral motion pattern. METHODS: 4D CT data capturing the patellofemoral motion pattern of a continuous flexion and extension were collected for five patients prone to patellar luxation both pre- and post-surgically. For the proposed method, an observer would place landmarks in a single 3D volume, which then are automatically propagated to the other volumes in a time sequence. From the landmarks in each volume, the measures patellar displacement, patellar tilt and angle between femur and tibia were computed. RESULTS: Evaluation of the observer variability showed the proposed semi-automatic method to be favorable over a fully manual counterpart, with an observer variability of approximately 1.5[Formula: see text] for the angle between femur and tibia, 1.5 mm for the patellar displacement, and 4.0[Formula: see text]-5.0[Formula: see text] for the patellar tilt. The proposed method showed that surgery reduced the patellar displacement and tilt at maximum extension with approximately 10-15 mm and 15[Formula: see text]-20[Formula: see text] for three patients but with less evident differences for two of the patients. CONCLUSIONS: A semi-automatic method suitable for quantification of the patellofemoral motion pattern as captured by 4D CT data has been presented. Its observer variability is on par with that of other methods but with the distinct advantage to support continuous motions during the image acquisition.
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