[home] [Personal Program] [Help]

---

Session: Poster session I
Session starts: Thursday 24 January, 15:00

---

Pim Pellikaan (University of Twente)
Vincenzo Carbone (University of Twente)
René Fluit (University of Twente)
Marjolein van der Krogt (University of Twente)
Nico Verdonschot (University of Twente)
Bart Koopman (University of Twente)

Abstract:
Introduction: To generate subject-specific musculo-skeletal models of the lower extremity, muscle attachment sites needs to be estimated with high accuracy. Therefore, the aim of this study was to develop a morphing-based method to automatically predict the location of muscle attachment sites in the lower extremity, based on the assumption that their position is in direct relation with the geometry of the bone. Methods: Two cadaver dissections were performed to measure the contour of all muscle attachment sites on the bones of the lower extremity. CT scans of both cadavers were used to segment the bones using Mimics software (www.materialise.com). STL-files containing the geometry of the bones and the measured muscle attachment sites were morphed from one cadaver to the other and vice versa. Muscle attachment sites were divided into three types: point, line and surface area, following the Twente Lower Extremity Model (TLEM) [1]. To determine the accuracy of the morphed attachment sites, a distance error was calculated as the mean Euclidean distance between: the mean of the morphed and un-morphed points in case of attachment points, the pairs of 6 equidistance points on a third order polynomial line in case of attachment lines, the pairs of 6 equi-area points on the projected surface area in case of attachment areas. Preliminary results: The mean distance error for all attachment sites was 13.31 mm ± 8.08 mm for cadaver 1 and 12.69 mm ± 7.95 mm for cadaver 2. The smallest mean distance error was 1.33 mm for the origin area of the medial part of the Gluteus Maximus and the largest mean distance error was 43.40 mm for the origin area of the Soleus Lateralis. Discussion: The proposed method shows reasonable average error (<15mm) between measured and morphed attachment sites. Large distance errors can be partially explained by differences in shape of attachment sites between the two cadavers. In particular, differences in length along the long axis of the bone had a large influence on the calculated distance error. The potential effect of these errors on subject-specific musculo-skeletal model prediction should be quantified in the future. In conclusion, the proposed method showed promising results in estimating muscle attachment sites, and further improvements may help to reach the accuracy needed to obtain reliable subject-specific musculo-skeletal models. Significance: Automatic estimation of the location of muscle attachment sites, based on medical imaging techniques, represents an important step in order to generate reliable subject-specific musculo-skeletal models.