PURPOSE: To design a time-efficient patient-friendly clinical diffusion tensor MRI protocol and postprocessing tool to study the complex muscle architecture of the human forearm. MATERIALS AND METHODS: The 15-minute examination was done using a 3 T system and consisted of: T(1) -weighted imaging, dual echo gradient echo imaging, single-shot spin-echo echo-planar imaging (EPI) diffusion tensor MRI. Postprocessing comprised of signal-to-noise improvement by a Rician noise suppression algorithm, image registration to correct for motion and eddy currents, and correction of susceptibility-induced deformations using magnetic field inhomogeneity maps. Per muscle one to five regions of interest were used for fiber tractography seeding. To validate our approach, the reconstructions of individual muscles from the in vivo scans were compared to photographs of those dissected from a human cadaver forearm. RESULTS: Postprocessing proved essential to allow muscle segmentation based on combined T(1) -weighted and diffusion tensor data. The protocol can be applied more generally to study human muscle architecture in other parts of the body. CONCLUSION: The proposed protocol was able to visualize the muscle architecture of the human forearm in great detail and showed excellent agreement with the dissected cadaver muscles.
PURPOSE: To design a time-efficient patient-friendly clinical diffusion tensor MRI protocol and postprocessing tool to study the complex muscle architecture of the human forearm. MATERIALS AND METHODS: The 15-minute examination was done using a 3 T system and consisted of: T(1) -weighted imaging, dual echo gradient echo imaging, single-shot spin-echo echo-planar imaging (EPI) diffusion tensor MRI. Postprocessing comprised of signal-to-noise improvement by a Rician noise suppression algorithm, image registration to correct for motion and eddy currents, and correction of susceptibility-induced deformations using magnetic field inhomogeneity maps. Per muscle one to five regions of interest were used for fiber tractography seeding. To validate our approach, the reconstructions of individual muscles from the in vivo scans were compared to photographs of those dissected from a human cadaver forearm. RESULTS: Postprocessing proved essential to allow muscle segmentation based on combined T(1) -weighted and diffusion tensor data. The protocol can be applied more generally to study human muscle architecture in other parts of the body. CONCLUSION: The proposed protocol was able to visualize the muscle architecture of the human forearm in great detail and showed excellent agreement with the dissected cadaver muscles.
Authors: R Rehmann; L Schlaffke; M Froeling; R A Kley; E Kühnle; M De Marées; J Forsting; M Rohm; M Tegenthoff; T Schmidt-Wilcke; M Vorgerd Journal: Eur Radiol Date: 2018-12-17 Impact factor: 5.315
Authors: Pierre G Carlier; Benjamin Marty; Olivier Scheidegger; Paulo Loureiro de Sousa; Pierre-Yves Baudin; Eduard Snezhko; Dmitry Vlodavets Journal: J Neuromuscul Dis Date: 2016-03-03
Authors: Bruce M Damon; Martijn Froeling; Amanda K W Buck; Jos Oudeman; Zhaohua Ding; Aart J Nederveen; Emily C Bush; Gustav J Strijkers Journal: NMR Biomed Date: 2016-06-03 Impact factor: 4.044
Authors: M T Hooijmans; B M Damon; M Froeling; M J Versluis; J Burakiewicz; J J G M Verschuuren; E H Niks; A G Webb; H E Kan Journal: NMR Biomed Date: 2015-10-09 Impact factor: 4.044