Altered helical axis patterns of the lumbar spine indicate increased instability with disc degeneration
Introduction
Low back pain is one of the most prevalent health complaints in the US, with an estimated 70–85% of the population developing back pain at some point in their life, creating a significant financial burden (Andersson, 1999). Although many causes of low back pain are poorly defined and indistinct, intervertebral disc (IVD) degeneration remains the primary cause for such symptoms. Throughout the degenerative process the proteoglycans in the nucleus pulposus are cleaved, resulting in decreased water content, hydrostatic pressure, and disc height (Urban and Roberts, 2003). These changes in the biochemical composition diminish the mechanical competency of the disc, thus altering the interaction between the nucleus and annulus during loading (Adams et al., 1996). The discs׳ inability to maintain structure and function may cause spinal instability leading to discogenic pain, nerve root pinching, or cord occlusion (Adams, 2004). The traditional definition of clinical spinal instability, as defined by Panjabi, is “the loss of normal pattern of spinal motion” (Panjabi, 2003).
Routine clinical exams for back pain include a functional exam, assessing the patient׳s spine motion and the presentation of pain, as well as diagnostic imaging of the intervertebral disc. Degeneration is traditionally evaluated using conventional T2 weighted sagittal magnetic resonance imaging (MRI) using a qualitative grading system assessing hydration levels and disc height, such the technique described by Pfirrmann et al. (2001). It has been shown that these categorical grading systems are not sensitive enough to detect early signs of degeneration, likely due to their subjectivity, and rarely provide clinically useful insights (Arana et al., 2010, Raininko et al., 1995). Therefore, emerging quantitative MRI techniques have recently been published, which avoid the pitfalls associated with qualitative measures by probing the biochemical content and structural integrity of the tissue (Ellingson et al., 2013a, Johannessen et al., 2006, Lotz et al., 2012, Mwale et al., 2008). These techniques may have a profound impact on the treatment of disc degeneration, especially with their ability to detect and quantify the subtle changes occurring at the early stages in the degeneration process.
It is of equal importance to understand the effects of diminished disc health on the functional mechanics and stability of the lumbar spine. In fact, this topic has been the focus of several studies including in vivo, in vitro, and in silico experiments (Ellingson et al., 2013a, Mimura et al., 1994, Natarajan et al., 2006, Passias et al., 2011). The conventional Kirkaldy–Willis model of spinal stability throughout degeneration describes a progressive increase in range of motion (RoM), until re-stabilization and a drop in RoM (Kirkaldy-Willis and Farfan, 1982). However, there still remains a lack of congruence in published literature, especially in the RoM exhibited. There is conflicting evidence supporting RoM either increases or decreases with worsening degeneration (Ellingson et al., 2013a, Fujiwara et al., 2000, Kettler et al., 2011, Tanaka et al., 2001). These contradicting results suggest RoM is not an adequate measure of spinal health due to its lack of sensitivity. The ratio of neutral zone to range of motion (NZR), a measure of joint instability or laxity, holds greater consensus in the literature. The NZR has been shown to increase with worsening degeneration (Ellingson et al., 2013a, Mimura et al., 1994, Panjabi, 1992, Zhao et al., 2005). RoM and NZR are scalar metrics that define kinematic endpoints, however the spine can move in infinite pathways of motion to reach those endpoints, and therefore are not sufficient in describing the quality of spinal motion. Also, NZR is a kinetic measure, which is unable to be measured in vivo. The center of rotation (COR) offers a more in-depth description of spinal motion (Gertzbein et al., 1985, Pearcy and Bogduk, 1988). The increased migration of the COR has been shown to be a biomarker in moderately degenerative discs and Spondylolisthesis, but even this metric simplifies the complex coupled motion of the spine into only two-dimensions (Schneider et al., 2005, Seligman et al., 1984). However, this analysis strategy is not adequate for complex motions in three-dimensions. Extending the COR to show the three-dimensional axis of rotation, rather than just a pivot point, can be obtained by computing the instantaneous helical axis (IHA). An IHA analysis approach provides rich temporal three-dimensional data describing the pathway of motion, which is easily visualized. IHA patterns have been used as a metric of stability in other joints and been employed to qualitatively describe the kinematics of the spine and the efficacy of implant devices (Duck et al., 2003, Grip and Häger, 2013, Kettler et al., 2004, Schmidt et al., 2008). The quantification of spinal instability or the off of the spine׳s ability to maintain its patterns of displacement under physiologic loads, is of high clinical importance, and previous analysis strategies have fallen short. It is paramount, therefore, to understand normal spinal motion to assess dysfunction in those motion patterns.
The aim of this study was to investigate the potential for IHA patterns to be used as a biomarker for spinal health and stability. It is hypothesized that the IHA vectors will display greater off-axis, or out-of-plane, rotation and a larger variability in their orientation with in worsening degeneration. It is also hypothesized that the center of rotation will exhibit greater migration and a larger variability in the migration with worsening degeneration.
Section snippets
Methods
Eighteen fresh-frozen osteoligamentous lumbar spines (L3–S1) were acquired from the University of Minnesota Bequest Program (age: 53.2±15.5 years; range: 21–71 years). Specimens were first examined using magnetic resonance imaging protocols to evaluate intervertebral disc health, and then biomechanically exercised in flexion, extension, and lateral bending in a pure moment fashion. A correlational study design was used to examine the relationship between instantaneous helical axis patterns of
Results
The orientation and location of the helical axes were computed for flexion, extension, and lateral bending for the L4–L5 spinal segment (18 functional spinal units) to understand the pathway of motion, and how it is affected by the quality of the intervertebral disc. Specimens of all degeneration levels exhibited overall similar motion patterns for flexion/extension and lateral bending, shown in a representative healthy specimen (Fig. 4).
Fig. 5 depicts representative IHA vector sets from a
Discussion
The functional mechanics of the lumbar spine, such as ROM, stiffness, NZR, are altered by disc health (Ellingson et al., 2013a, Fujiwara et al., 2000, Kettler et al., 2011, Mimura et al., 1994, Panjabi, 1992, Tanaka et al., 2001, Zhao et al., 2005). However, there have been discrepancies in the literature about the changes that occur. Additionally, these two-dimensional scalar measures simplify spinal motion. In an effort to understand the pathway of motion, and how it׳s affected by the quality
Conflict of interest statement
The authors have no conflict of interest to report.
Supplemental material
Supplemental animations are available depicting representative lateral bending helical axis profiles for both healthy and degenerative specimens.
Acknowledgments
Funding was provided through NIH/NIAMS Grants T32 AR050938 and T32 AR056950. The authors would also like to thank Daniel F. Keefe, Ph.D. and the members of the Interactive Visualization Lab for aid with the supplemental videos.
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2018, Journal of BiomechanicsCitation Excerpt :Indeed, representing lumbar joints as rotational joints with a fixed COR is almost universally applied (Daggfeldt and Thorstensson, 2003; De Zee et al., 2007; Delp et al., 2007; Senteler et al., 2016; Zhu et al., 2013) and is one of the basic design aspects featured in modern prosthetic disc replacements (Dreischarf et al., 2015). Recent improvements in dynamic imaging techniques (Ahmadi et al., 2009; Aiyangar et al., 2014; Anderst et al., 2008; Wu et al., 2014), and the ability to compute instantaneous axes of rotation for smaller rotational step sizes (Aiyangar et al., 2017; Baillargeon and Anderst, 2013; Ellingson and Nuckley, 2015), however, has rekindled interest in utilizing instantaneous COR patterns for identifying pathologies such as lumbar instability (Ahmadi et al., 2009) and degenerative spondylolisthesis (Ellingson and Nuckley, 2015). At the same time, Zander and co-workers demonstrated the inaccuracy of the accepted “average” COR in locating the point where muscle activity and joint reaction forces are minimized for a static upright pose, using the center of reaction concept (Zander et al., 2016).
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2017, Journal of BiomechanicsCitation Excerpt :The current study employed the helical axis technique. While some studies reported ICRs moving along the direction of angular motion (Ahmadi et al., 2009; Ellingson and Nuckley, 2015; Ogston et al., 1986; Schmidt et al., 2008b), others have reported ICRs moving opposite to the rotational direction (Abouhossein et al., 2013); still others have reported a looped pattern: an initial path along the direction of motion followed by a change in direction to return close to the initial location (Gertzbein et al., 1984; Ogston et al., 1986). With some exceptions, such as at the beginning of motion, the current study found ICRs broadly migrated from anterior to posterior location with progression of the extension task along with the direction of rotation: trend analysis showed significant negative slopes (p<0.05 for slope<0) for AP ICR translation in all cases.
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2016, Journal of BiomechanicsCitation Excerpt :Efforts have been undertaken to improve understanding of how the helical axis can be implemented in spinal kinematics (Crawford, 2006). However, the helical axes and CORs are typically only qualitatively reported, using 2D images of their migration on the motion segment (Ellingson and Nuckley, 2015; Kettler et al., 2004; Wachowski et al., 2010). A potential improvement to further describe changes in spine motion would be to quantify the scatter in the axes generated from a motion sequence.
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Investigation performed at the University of Minnesota, Minneapolis, Minnesota.