Quantitative analysis of the patellofemoral motion pattern using semi-automatic processing of 4D CT data
2016 (English)In: International Journal of Computer Assisted Radiology and Surgery, ISSN 1861-6410, E-ISSN 1861-6429, Vol. 11, no 9, 1731-1741 p.Article in journal (Refereed) Published
To present a semi-automatic method with minimal user interaction for quantitative analysis of the patellofemoral motion pattern. 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. 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 for the angle between femur and tibia, 1.5 mm for the patellar displacement, and 4.0-5.0 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 15-20 for three patients but with less evident differences for two of the patients. 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.
Place, publisher, year, edition, pages
SPRINGER HEIDELBERG , 2016. Vol. 11, no 9, 1731-1741 p.
Computed tomography; 4D; Patella luxation; Quantitative; Motion pattern
Medical Image Processing
IdentifiersURN: urn:nbn:se:liu:diva-132069DOI: 10.1007/s11548-016-1357-8ISI: 000383323800015PubMedID: 26932337OAI: oai:DiVA.org:liu-132069DiVA: diva2:1038434
18th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)