OBJECTIVE: This study aimed to refine a magnetic resonance imaging (MRI)-ultrasound registration (ie, alignment) technique to make noninvasive, nonionizing, 3-dimensional measurement of the lumbar segmental motion in vivo.
METHODS: Five healthy participants participated in this validation study. We scanned the lumbar region of each participant 5 times using an ultrasound probe while he or she kept a prone lying posture on a plinth. Participant-specific models of L1-L5 were constructed from magnetic resonance (MR) images and aligned with the 3-dimensional ultrasound dataset of each scan using 4 variants of MRI-ultrasound registration approach (simplified intensity-based registration  with and  without including the transverse processes and their surrounding soft tissues [denoted as TP complex]; and hierarchical intensity-based registration  with and  without including the TP complex). The robustness and precision of these registration approaches were compared.
RESULTS: Although all registration approaches converged to a similar solution, excluding the TP complex improved the percentage of successful registration from 92% to 100%. There was no significant difference in the precision among the 4 MRI-ultrasound registration variants. For the simplified intensity-based registration without including the TP complex, average precision at each degree of freedom was 1.33° (flexion-extension), 2.48° (lateral bending), 1.32° (axial rotation), 2.15 mm (left/right), 1.08 mm (anterior-posterior), and 1.16 (superior-inferior), respectively.
CONCLUSION: Given that using simplified intensity-based MRI-ultrasound registration can substantially streamline the registration process and excluding the TP complex would improve the robustness of the registration, we conclude that this combination is the method of choice for in vivo human applications.
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Author keywords: Ultrasonography, Magnetic Resonance Imaging, Lumbar Vertebrae
Author affiliations: TKK, RLC: Foot Levelers Biomechanics Research Laboratory, New York Chiropractic College, Seneca, Falls, NY. WEK: Department of Imaging Sciences, University of Rochester, University of Rochester Center for Advanced Brain Imaging & Neurophysiology, Rochester, NY