[home] [Personal Program] [Help]

---

Session: Poster session II
Session starts: Thursday 24 January, 16:00

---

Pieter Oomen (Maastricht University Medical Center +)
Kenneth Meijer (Maastricht University Medical Center + )
Paul Willems (Maastricht University Medical Center + )
Maarten Drost (Maastricht University Medical Center + )

Abstract:
Introduction Muscle architecture is a main determinant of muscle function. Architecture of a muscle can be described as the arrangement of muscle fibers within a muscle relative to the axis of force generation [1]. In addition, pennation angle, physiological cross sectional area (PCSA) and tension per unit of PCSA can determine muscle force. Previous literature only provides these muscle parameters post-mortem [2, 3]. Recent advances in imaging techniques gave the opportunity to study these parameters in-vivo [4]. Diffusion Tensor Imaging (DTI) is a promising non-invasive method to determine muscle fiber trajectories in-vivo. In this study we will focus on PCSA only. Therefore, the purpose of this study is to calculate PCSA of the m. rectus femoris from DT images. Method In this study one healthy adult male (age: 24 years, weight: 80kg, height: 1.89m) participated. A Philips 3.0 Tesla scanner was used to obtain T1 and DT images. The upper leg was measured within 3 stacks with a 20 mm overlap. The following imaging parameters were used: FOV 400 mm × 400 mm; Voxel size T1: 0.83 mm × 0.83 mm × 4 mm; Voxel size DTI: 3.1 mm × 3.1 mm × 4 mm. Segmentation of both right and left m. rectus femoris (RF) volumes were done using Research Volumetool v1.3.0 [5]. Intra-rater reproducibility was assessed by segmenting left and right RF twice. RF volumes were imported in vISTe [6], and fiber trajectories were tracked within the muscle volume. Trajectories were imported in a custom developed program in Matlab and finally PCSA was calculated. Results & Discussion The volumes of the RF (right: 339 ml; left: 346 ml) were found to have excellent ICC: 0.997. Importing these volumes in the DTItool gave promising results in visualising fiber trajectories of the muscle. A PCSA of 27.5 cm2 for the right RF and 26.2 cm2 for the left RF were calculated from the custom build Matlab program. However, validation is required to demonstrate the reliability of this computational approach of calculating PCSA. Relative to fixed cadaveric measurements from literature these volumes and PCSAs are much larger (volume: 54.5 ml - 104.7 ml and PCSA 8.9 cm2 - 15.2 cm2) [2, 3]. This discrepancy is most likely due to a different target population in the cadaveric studies. The mean age in these studies was 83 years which could induce atrophy of the muscles; the mean height was 1.68m which can result in considerably smaller muscles than our test subject. However, a cadaver study by Klein Horstman et al [7] found RF PCSA of 28.9 cm2 (volume 225.5ml) within a 105 kg male specimen. Conclusion DTI is a relative new technique to measure skeletal muscle architecture in-vivo [4]. This study showed possibilities in calculating PCSA of the RF from DT images. More research is needed to validate these outcomes and the application in other skeletal muscles. References 1. Lieber, R.L., Skeletal muscle structure, function, and plasticity : the physiological basis of rehabilitation. 3rd ed. 2010, Philadelphia, Pa., [etc.]: Wolters Kluwer/Lippincott Williams & Wilkins. VIII, 304, [8] p. pl. 2. Ward, S.R., et al., Are current measurements of lower extremity muscle architecture accurate? Clin Orthop Relat Res, 2009. 467(4): p. 1074-82. 3. Wickiewicz, T.L., et al., Muscle architecture of the human lower limb. Clin Orthop Relat Res, 1983(179): p. 275-83. 4. Galban, C.J., et al., Diffusive sensitivity to muscle architecture: a magnetic resonance diffusion tensor imaging study of the human calf. Miyatani, M., 2004. 93(3): p. 253-62. 5. Bol, G.H., et al., Simultaneous multi-modality ROI delineation in clinical practice. Ravichandiran, K., 2009. 96(2): p. 133-40. 6. Department of Biomedical Engineering. vIST/e. 2012; Available from: http://bmia.bmt.tue.nl/software/VISTE/. 7. Klein Horsman, M.D., et al., Morphological muscle and joint parameters for musculoskeletal modelling of the lower extremity. Clin Biomech (Bristol, Avon), 2008. 22(2): p. 239-47.