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Comprehensive assessment of walking function after human spinal cord injury
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Lea Awai1, Armin Curt Spinal Cord Injury Center, Balgrist University Hospital, Z€ urich, Switzerland 1 Corresponding author: Tel.:+41-44-386-37-34; Fax: +41-44-386-37-31, e-mail address: [email protected]
Abstract Regaining any locomotor function after spinal cord injury is not only of immediate importance for affected patients but also for clinical research as it allows to investigate mechanisms underlying motor impairment and locomotor recovery. Clinical scores inform on functional outcomes that are clinically meaningful to value effects of therapy while they all lack the ability to explain underlying mechanisms of recovery. For this purpose, more elaborate recordings of walking kinematics combined with assessments of spinal cord conductivity and muscle activation patterns are required. A comprehensive assessment framework comprising of multiple complementary modalities is necessary. This will not only allow for capturing even subtle changes induced by interventions that are likely missed by standard clinical outcome measures. It will be fundamental to attribute observed changes to naturally occurring spontaneous recovery in contrast to specific changes induced by novel therapeutic interventions beyond the improvements achieved by conventional therapy.
Keywords spinal cord injury, motor, walking, function, recovery, outcome measures, human
1 INTRODUCTION In incomplete spinal cord injury (iSCI), walking is characterized by manifold complex alterations like a slower than normal speed (Awai and Curt, 2014; Pepin et al., 2003), limited hip and knee flexion during swing (Perry and Burnfield, 2010), insufficient hip extension during stance, and excessive plantar flexion during swing (van der Salm et al., 2005). These observed impairments of joint and limb movements could be based on different underlying mechanisms such as limitations in hip flexion during swing phase that were attributed to muscle weakness, while the reduced knee flexion during swing was related to aberrant coactivation of antagonistic extensor Progress in Brain Research, Volume 218, ISSN 0079-6123, http://dx.doi.org/10.1016/bs.pbr.2014.12.004 © 2015 Elsevier B.V. All rights reserved.
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CHAPTER 1 Walking after SCI
Linear measures
muscles (Ditunno and Scivoletto, 2009). Thus, a multimodal and comprehensive approach to study normal and altered gait and its recovery is required for elucidating underlying mechanisms of gait control. The majority of clinical studies that monitor recovery processes or training effects during different interventions after spinal cord injury (SCI) chose measures of walking performance (i.e., walking speed/distance) and functional independence (e.g., type of required assistive device, performance during activities of daily living) to reflect motor function (Fig. 1). However, “motor function” and “walking function” are ill-defined terms as they rather nonspecifically refer to different aspects of gait (i.e., speed and time-distance parameters, type of walking assistance), while such
• Mobility • Type of assistive device
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FIGURE 1 Measures of time and distance objectively assess the walking capacity or performance of a person and represent continuous data. They are often used to monitor recovery of walking function during rehabilitation or interventions. Clinical scores (e.g., walking index for spinal cord injury (WISCI), spinal cord independence measure (SCIM)) assess the mobility of a person (i.e., what type of assistive device does a person rely on, how well can a person perform activities of daily living) and were often developed for a specific type of subjects (i.e., spinal cord injured patients, stroke patients). They are ordinal values assessed at discrete time points. Gait quality is commonly assessed via subjective observation by trained persons in a descriptive manner. The quality may then be scored and represented by an ordinal value.
2 Clinical assessments of recovery
outcomes may not be well compared across studies and remain nonconclusive at explaining mechanisms of recovery. Even the examination of highly selected measures (e.g., changes in single joint angles), although presenting very concise information, is likely limited at elucidating underlying complex interactions. In order to acquire more comprehensive evaluations to address questions of physiological gait control as well as observed alterations and recovery profiles in iSCI, combined multimodal assessments are required. Especially in high risk and potentially highreturn clinical trials (phase I/II studies), investigators should consider any possible efforts to search for complementary information (including surrogate markers) beyond standard clinical outcome measures. These readouts may reveal more detailed insights into different mechanisms of action that eventually may be important to identify effects evoked by specific interventions (i.e., obvious as well as clinically masked changes).
2 CLINICAL ASSESSMENTS OF RECOVERY 2.1 NEUROLOGICAL ASSESSMENTS The completeness of lesion (i.e., the preservation of sensory function below the level of lesion) is crucial for the clinical description and prediction of ambulatory outcome (Maynard et al., 1979; Waters et al., 1994). Patients who are ASIA A early after injury have little chance of regaining functional ambulation, while ASIA B patients may reach a functional level (Crozier et al., 1992; Maynard et al., 1979; Waters et al., 1994). However, it is commonly accepted that the ASIA classification is too crude to reveal functional changes (i.e., improved walking ability) that may occur within one ASIA grade (i.e., ASIA D patients may increase walking speed and muscle strength without a conversion in ASIA grade). For a general evaluation of motor function, the assessment of ASIA motor scores as well as the spinal cord independence measure III (SCIM III) was strongly recommended (Labruyere et al., 2010). Even though the lower extremity motor scores (LEMS) are assessed in a lying position while the respective muscles are activated in a nontask specific manner (i.e., not during locomotion), LEMS were shown to be a good predictor for ambulatory outcome after rehabilitation (van Middendorp et al., 2011; Zorner et al., 2010). Furthermore, the LEMS of both legs were found to correlate best with walking speed, distance, and ambulatory capacity in chronic iSCI subjects compared to unilateral LEMS of the individual lower limb muscles (Kim et al., 2004). Thus, muscle strength seems to be an important determinant for walking performance (speed and distance) but may not have an influence on movement quality. It was shown that iSCI patients have preserved movement accuracy in the lower limbs despite diminished muscle strength, which distinguished them from stroke patients. The latter showed both diminished muscle strength in the affected leg as well as bilaterally impaired movement accuracy (van Hedel et al., 2010), suggesting that movement accuracy may not be corrupted by muscle weakness in iSCI.
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2.2 FUNCTIONAL ASSESSMENTS The SCIM was developed as a scale to score disability in patients with SCI (Catz et al., 1997). In acute patients, the SCIM III was evaluated to have the most appropriate performance with respect to specific psychometric properties (i.e., reliability, validity, reproducibility, responsiveness) when compared to other measures such as Functional Independence Measure, Walking Index for Spinal Cord Injury (WISCI), Modified Barthel Index, Timed Up & Go, 6-minute walk test (6MinWT), or 10-meter walk test (10MWT) (Furlan et al., 2011). Compared to measures of walking capacity (i.e., speed, WISCI), the SCIM also assesses improvements in ASIA A and B patients who are wheelchair bound (van Hedel and Dietz, 2009). Depending on the aim of a study, the appropriate outcome measures should be chosen. If walking function and its recovery are to be investigated and the question of whether or not patients improve locomotor function and by what means they might improve their walking capacity, the SCIM score might not be a sensitive tool while it does inform on to what extent a patient can perform activities of daily living independent of aids or support from third parties. Recovery of walking function is routinely assessed by functional outcome measures such as the widely used 10MWT and 6MinWT (Alcobendas-Maestro et al., 2012; Buehner et al., 2012; Hayes et al., 2014; Jayaraman et al., 2013; Kim et al., 2004; Kumru et al., 2013; Petersen et al., 2012a; van Hedel et al., 2006), where walking speed and distance (endurance) are evaluated (Fig. 1). Walking capacity (speed and distance) are important prerequisites for successful community ambulation (Lapointe et al., 2001). Despite improvements in walking speed during rehabilitation, iSCI patients typically show a reduced velocity compared to a healthy control cohort, especially when asked to walk at their maximally possible walking speed (Awai and Curt, 2014; Lapointe et al., 2001; Pepin et al., 2003; van Hedel et al., 2007). Several studies discussed the question as to whether the 10MWT and 6MinWT actually bear complementary information (Forrest et al., 2014; van Hedel et al., 2007). van Hedel et al. (2007) found a certain redundancy in walking speed assessed by these two measures when performed at a comfortable walking speed, while the results at maximal speed revealed additional information. However, these studies did not aim at answering the question of why patients may or may not walk faster or longer distances. Limitations in walking speed, particularly pronounced at maximal speed, may indicate a limited access to supraspinal drive (Bachmann et al., 2013) while endurance might be corrupted as a consequence of the increased energy expenditure found in iSCI patients (Lapointe et al., 2001; Waters and Lunsford, 1985). Different training approaches that all include some sort of walking (e.g., on a treadmill, overground, robot-assisted, body-weight supported, FES-supported) all found improvements in walking function as assessed by walking speed, distance, or WISCI II (Alexeeva et al., 2011; Dobkin et al., 2006; Field-Fote, 2001; FieldFote and Roach, 2011; Harkema et al., 2012; Postans et al., 2004; Thomas and Gorassini, 2005; Wirz et al., 2005). However, many of the studies that compared
3 Clinical neurophysiology
several training methods with respect to overground walking outcome did not find any differences between training approaches. This may either imply that a specific training method may not be superior to another or that the outcome measures are not sensitive to capture differences.
3 CLINICAL NEUROPHYSIOLOGY Due to the lack of more direct methods to investigate neural pathways underlying certain behaviors (i.e., implantable electrodes, fiber tracking, optogenetics, genetically modified animals), alternative assessments need to be employed in humans. Noninvasive or minimally invasive electrophysiological recordings can elucidate the integrity and connectivity of central and peripheral sensory and motor pathways in SCI patients either during a resting state (i.e., while subjects are lying; Chabot et al., 1985; Curt and Dietz, 1996, 1997; Curt et al., 1998; Kirshblum et al., 2001; Kovindha and Mahachai, 1992) or during activities such as locomotion (Barthelemy et al., 2010; Capaday et al., 1999; Dietz et al., 1998, 2002, 2009; Fung and Barbeau, 1994; Harkema et al., 1997; Schubert et al., 1997).
3.1 SPINAL CORD INTEGRITY Interestingly, SCI patients may improve their ambulatory capacity in the absence of concomitant improvements of corticospinal conduction velocity assessed via the latencies of motor- and somatosensory-evoked potentials (MEPs and SSEPs) (Curt et al., 2008). At the same time, the amplitudes of the evoked potentials are paralleled by improved walking function (Curt and Dietz, 1997; Curt et al., 1998; Petersen et al., 2012a; Spiess et al., 2008), suggesting that remyelination of injured axons or conduction velocity may not be the driving forces for functional recovery, but rather an improved synchronization of action potentials or adaptations at the neuromuscular site.
3.2 SPINAL NEURAL CIRCUITS Alterations of spinal reflexes have been shown to reveal changes in spinal neuronal (dys-)function and are related to walking ability in SCI patients (Dietz et al., 2009; Hubli et al., 2011, 2012). Concomitant with an improved locomotor function, spinal reflex responses shifted from exhibiting a predominant late component to a predominant early component, suggesting that neural pathways mediating nonnoxious spinal reflexes are also involved during locomotion (Hubli et al., 2012). A similar phenomenon was reported by another group (Thompson and Wolpaw, 2014; Thompson et al., 2013) via modulation of reflex circuits induced by operant conditioning. They showed that iSCI subjects could improve their walking ability after 30 sessions of voluntary soleus H-reflex downconditioning, supporting the idea of common pathways for rather simple reflex responses and more complex motor behaviors.
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Even in complete human SCI, muscle activity could be elicited during stepping movements and increased during training when appropriate afferent input was provided (Dietz et al., 1994, 2002; Harkema et al., 1997). Yet, to date, no independent, weight-bearing walking has been achieved after human complete SCI albeit intensive and long-lasting training. In a distinct set of patients, limited voluntary lower limb control and manually assisted locomotion could be elicited during epidural spinal cord stimulation in motor complete spinal cord injured patients following intensive training (Angeli et al., 2014; Harkema et al., 2011). These findings suggest that current clinical tests for the identification of completeness of injury are not sufficient to detect a small number of spared fibers. Also, the results of this group substantiated the general assumption that human subjects, to a larger extent than animals, require input from supraspinal centers in order to walk. How strongly humans rely on brain input and to what extent locomotor activity is controlled on a rather autonomous spinal level remains to be elucidated. Certain phases of the gait cycle (i.e., initial swing phase) and specific muscle groups (i.e., distal leg muscles) obviously receive input via the corticospinal tract (CST), as revealed by TMS studies (Calancie et al., 1999; Schubert et al., 1997). Coherence analysis of two EMG signals within the same or synergistic muscles reveals the amount of common synaptic drive to motor output and the coherence frequency within a specific range (i.e., 8–20 Hz) possibly indicates supraspinal origin of walking (Halliday et al., 2003; Hansen et al., 2005; Petersen et al., 2012b).
4 GAIT ANALYSIS With the aim of disentangling the mechanisms underlying motor recovery and locomotor control of normal and pathological gait, the assessment of walking speed and distance is insufficient. Furthermore, additional measures are of need to reveal factors contributing to recovery of walking and gait control. In addition to gait-cycle parameters (e.g., stance/swing phase, single/double limb support, step length, cadence), kinematic data objectively reveal information on the quality of walking. The gait of SCI patients is particularly characterized by muscle weakness on the one hand and an elevated muscle tone on the other hand. These conditions lead to limited knee mobility expressed by a reduced knee excursion and knee angular velocity as reported by Krawetz and Nance (1996), while greater knee flexion during swing and increased total hip excursion were reported by Pepin et al. (2003). Additionally, iSCI walking is typically characterized by an excessive ankle plantar flexion (foot drop) during the swing phase, which was considered to be an expression of diminished CST drive (Barthelemy et al., 2010, 2013). Only few studies investigated features of gait quality such as the interplay of lower limb joint angles (hip–knee cyclograms) revealing information on intersegmental coordination (Field-Fote and Tepavac, 2002; Nooijen et al., 2009; Pepin et al., 2003). This lower limb coordination is believed to offer insights into control mechanisms underlying locomotor behavior that are not revealed by gait-cycle parameters or measures of speed and
5 Neural control of walking
distance. These latter measures were even shown to be well modulated in iSCI patients (Pepin et al., 2003, unpublished data from our own studies) in contrast to the intralimb coordination that cannot be properly modulated according to speed (Fig. 2) and even deviates further from healthy control subjects when increasing speed from slow to preferred (Awai and Curt, 2014; Pepin et al., 2003, unpublished data from our own studies). The deficient intralimb coordination was suggested to be a contributing factor to the limited walking speed typically found in iSCI patients and upon visual evaluation was stated to be unique for each patient (Pepin et al., 2003). Nevertheless, specific characteristics of the cyclogram shared by several patients could be identified and this measure was used to classify four groups of impairment (Awai and Curt, 2014). A meaningful patient stratification is required for tailored rehabilitation programs as well as a homogenization of intervention groups for a more precise investigation of treatment effects. Interestingly, even though the cyclogram configuration was not immediately responsive to an increase in speed, the cyclogram shape reflected the preferred walking speed of the patients and could be quantified by calculating the shape difference to a normal cyclogram (Awai and Curt, 2014). Although the shape of the cyclogram did not normalize with increasing walking speed, patients could actually increase the cycle-to-cycle consistency (i.e., angular component of coefficient of correspondence). These distinct findings may allude to the possible existence of a discretely organized control of specific gait features that may be more or less affected by a SCI and reflect various recovery processes that are differently amenable to therapeutic interventions.
5 NEURAL CONTROL OF WALKING A reduction of walking speed is commonly observed in patients with a neurological disorder but is an unspecific indicator of the underlying cause. A patient with a lower limb bone fracture may also walk slower even in the absence of neural deficits. However, distinct recovery profiles and the way specific parameters are modulated with respect to increasing speed may be more informative with respect to underlying mechanisms of motor control. Given the complexity of bipedal locomotor control, it is necessary to take into account numerous measures of different modalities that explain specific characteristics of human gait and the underlying physiology (Fig. 3). The incapacity of clinically complete SCI patients to spontaneously walk and the studies that have shown that only a very limited locomotor pattern may be elicited in the absence of supraspinal input (Dietz et al., 1994; Harkema et al., 1997) suggest that compared to animals (Barbeau and Rossignol, 1987; De Leon et al., 1998) humans depend more strongly on supraspinal input (Barthelemy et al., 2011; Thomas and Gorassini, 2005) but have spinal neural centers capable of spontaneously producing rhythmic output (Calancie et al., 1994). The absence of recovering MEP latencies in the first year after injury suggests that regeneration of disrupted fibers or remyelination of injured axons are not the cause for functional improvements observed in SCI patients (Curt et al., 1998, 2008). It is therefore most probable
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CHAPTER 1 Walking after SCI
Control subjects Slow
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FIGURE 2 Intralimb coordination may be represented by so-called hip–knee cyclograms and evaluates multisegmental lower limb coordination and therefore reveals information on motor control. The cyclogram configuration may be rather heterogeneous at a slow speed (0.5 km/h), while it normalizes to a very uniform shape at preferred walking speed in healthy control subjects. In contrast, iSCI patients are unable to normalize their pattern when walking at their respective preferred walking speed demonstrating their limited capacity to modulate complex lower limb movements.
5 Neural control of walking
Neural control Cortex Brain stem Spinal cord Motoneurons Muscle properties
Walking capacity Speed (10MWT) Distance (6MinWT) Type of assistive device
Gait quality Joint angles Range of motion (ROM) Angular velocity Limb coordination Movement reliability
Mechanisms of neural control of walking Mechanisms of (motor) recovery
Neuromuscular innervation Spinal cord integrity Motor-evoked potentials (MEPs) Somatosensory-evoked potentials (SSEPs) Nerve conduction studies (NCS) Spinal neural circuits Spinal reflexes H-reflex Electromyogram (EMG)
Gait-cycle parameters Step length Cadence Stance/swing phase Single/double limb support
FIGURE 3 In order to gain insight into mechanisms of neural control of walking and underlying processes of motor recovery, it is important to integrate complementary information considering different aspects of motor function. Measures assessing the anatomical and physiological integrity of specific pathways as well as parameters quantifying performance and gait quality are required for a comprehensive understanding of complex mutual interactions underlying specific phenotypes.
that SCI patients regain locomotor capacity via detour connections or adaptations that take place below the level of injury and therefore the control of walking might shift significantly. Concomitant with improvements in functional measures patients usually show increased MEP amplitudes and motor scores, which is most probably not attributable to regenerative processes within the lesion site (Curt et al., 2008). Moreover, most walking parameters increase during recovery while the gait quality seems to remain largely pathological (Awai L., Curt A., unpublished data) suggesting that compensatory mechanisms may not drive the recovery of complex movements as reflected by the intralimb coordination, which may depend predominantly on intact supraspinal input, making intralimb coordination a valuable measure for recovery beyond spontaneous/conventionally induced improvements. A clear segregation of motor control into spinal and supraspinal is probably neither doable nor correct. It is most likely that locomotion depends on the intricate temporal and spatial coordination of both feedforward and feedback control
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mechanisms performed at multiple levels of the neuraxis. Yet, knowledge about the anatomical structures underlying specific phenotypes of motor behavior is of need if outcome measures are to be correctly interpreted.
6 CONCLUSION A comprehensive assessment framework reveals different aspects of locomotion (Fig. 3). Clinical/functional measures inform on the performance of a patient during specific tasks (i.e., activities of daily living), while measures of speed and distance may decide on whether or not regained function enables a patient to achieve community ambulation. Electrophysiological procedures assess neural and/or muscular signal propagation, which may be differentiated into central and peripheral conduction. Spinal reflexes were shown to reflect spinal cord excitability and may be used as a simplified marker for locomotor function. These reflexes can be altered by and reveal the plasticity of neural circuits. Kinematic outcome measures representing complex coordinative movements and their responsiveness to speed modulation reveal the integration of a multitude of signals involved in locomotion. Measures of intralimb coordination may be used to stratify patients with respect to their gait impairment enhancing targeted patient interventions and reduction of outcome variability. Only an elaborate assessment battery including complementary measures provides sufficient information for a profound understanding of an existing disorder. To tackle the amount and diversity of data, a multivariate approach (e.g., principal components analysis) may be the method of choice.
ACKNOWLEDGMENTS This study was partly funded by the European Commission’s Seventh Framework Program (CP-IP 258654, NEUWalk) and the Clinical Research Priority Program CRPP Neurorehab UZH.
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Hayes, H.B., Jayaraman, A., Herrmann, M., Mitchell, G.S., Rymer, W.Z., Trumbower, R.D., 2014. Daily intermittent hypoxia enhances walking after chronic spinal cord injury: a randomized trial. Neurology 82, 104–113. Hubli, M., Bolliger, M., Dietz, V., 2011. Neuronal dysfunction in chronic spinal cord injury. Spinal Cord 49, 582–587. Hubli, M., Dietz, V., Bolliger, M., 2012. Spinal reflex activity: a marker for neuronal functionality after spinal cord injury. Neurorehabil. Neural Repair 26, 188–196. Jayaraman, A., Thompson, C.K., Rymer, W.Z., Hornby, T.G., 2013. Short-term maximalintensity resistance training increases volitional function and strength in chronic incomplete spinal cord injury: a pilot study. J. Neurol. Phys. Ther. 37, 112–117. Kim, C.M., Eng, J.J., Whittaker, M.W., 2004. Level walking and ambulatory capacity in persons with incomplete spinal cord injury: relationship with muscle strength. Spinal Cord 42, 156–162. Kirshblum, S., Lim, S., Garstang, S., Millis, S., 2001. Electrodiagnostic changes of the lower limbs in subjects with chronic complete cervical spinal cord injury. Arch. Phys. Med. Rehabil. 82, 604–607. Kovindha, A., Mahachai, R., 1992. Short-latency somatosensory evoked potentials (SSEPs) of the tibial nerves in spinal cord injuries. Paraplegia 30, 502–506. Krawetz, P., Nance, P., 1996. Gait analysis of spinal cord injured subjects: effects of injury level and spasticity. Arch. Phys. Med. Rehabil. 77, 635–638. Kumru, H., Benito, J., Murillo, N., Valls-Sole, J., Valles, M., Lopez-Blazquez, R., Costa, U., Tormos, J.M., Pascual-Leone, A., Vidal, J., 2013. Effects of high-frequency repetitive transcranial magnetic stimulation on motor and gait improvement in incomplete spinal cord injury patients. Neurorehabil. Neural Repair 27, 421–429. Labruyere, R., Agarwala, A., Curt, A., 2010. Rehabilitation in spine and spinal cord trauma. Spine 35, S259–S262. Lapointe, R., Lajoie, Y., Serresse, O., Barbeau, H., 2001. Functional community ambulation requirements in incomplete spinal cord injured subjects. Spinal Cord 39, 327–335. Maynard, F.M., Reynolds, G.G., Fountain, S., Wilmot, C., Hamilton, R., 1979. Neurological prognosis after traumatic quadriplegia. Three-year experience of California Regional Spinal Cord Injury Care System. J. Neurosurg. 50, 611–616. Nooijen, C.F., Ter Hoeve, N., Field-Fote, E.C., 2009. Gait quality is improved by locomotor training in individuals with SCI regardless of training approach. J. Neuroeng. Rehabil. 6, 36. Pepin, A., Norman, K.E., Barbeau, H., 2003. Treadmill walking in incomplete spinal-cordinjured subjects: 1. Adaptation to changes in speed. Spinal Cord 41, 257–270. Perry, J., Burnfield, J., 2010. Gait Analysis: Normal and Pathological Function, second ed. Slack Inc., Thorofare, NJ. Petersen, J.A., Spiess, M., Curt, A., Dietz, V., Schubert, M., 2012a. Spinal cord injury: one-year evolution of motor-evoked potentials and recovery of leg motor function in 255 patients. Neurorehabil. Neural Repair 26, 939–948. Petersen, T.H., Willerslev-Olsen, M., Conway, B.A., Nielsen, J.B., 2012b. The motor cortex drives the muscles during walking in human subjects. J. Physiol. 590, 2443–2452. Postans, N.J., Hasler, J.P., Granat, M.H., Maxwell, D.J., 2004. Functional electric stimulation to augment partial weight-bearing supported treadmill training for patients with acute incomplete spinal cord injury: a pilot study. Arch. Phys. Med. Rehabil. 85, 604–610. Schubert, M., Curt, A., Jensen, L., Dietz, V., 1997. Corticospinal input in human gait: modulation of magnetically evoked motor responses. Exp. Brain Res. 115, 234–246.
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Spiess, M., Schubert, M., Kliesch, U., Halder, P., 2008. Evolution of tibial SSEP after traumatic spinal cord injury: baseline for clinical trials. Clin. Neurophysiol. 119, 1051–1061. Thomas, S.L., Gorassini, M.A., 2005. Increases in corticospinal tract function by treadmill training after incomplete spinal cord injury. J. Neurophysiol. 94, 2844–2855. Thompson, A.K., Wolpaw, J.R., 2014. Restoring walking after spinal cord injury: operant conditioning of spinal reflexes can help. The Neuroscientist (Epub ahead of print). http://dx.doi.org/10.1177/1073858414527541. Thompson, A.K., Pomerantz, F.R., Wolpaw, J.R., 2013. Operant conditioning of a spinal reflex can improve locomotion after spinal cord injury in humans. J. Neurosci. 33, 2365–2375. Van Der Salm, A., Nene, A.V., Maxwell, D.J., Veltink, P.H., Hermens, H.J., Mj, I.J., 2005. Gait impairments in a group of patients with incomplete spinal cord injury and their relevance regarding therapeutic approaches using functional electrical stimulation. Artif. Organs 29, 8–14. Van Hedel, H.J., Dietz, V., 2009. Walking during daily life can be validly and responsively assessed in subjects with a spinal cord injury. Neurorehabil. Neural Repair 23, 117–124. Van Hedel, H.J., Wirz, M., Curt, A., 2006. Improving walking assessment in subjects with an incomplete spinal cord injury: responsiveness. Spinal Cord 44, 352–356. Van Hedel, H.J., Dietz, V., Curt, A., 2007. Assessment of walking speed and distance in subjects with an incomplete spinal cord injury. Neurorehabil. Neural Repair 21, 295–301. Van Hedel, H.J., Wirth, B., Curt, A., 2010. Ankle motor skill is intact in spinal cord injury, unlike stroke: implications for rehabilitation. Neurology 74, 1271–1278. Van Middendorp, J.J., Hosman, A.J., Donders, A.R., Pouw, M.H., Ditunno Jr., J.F., Curt, A., Geurts, A.C., Van De Meent, H., 2011. A clinical prediction rule for ambulation outcomes after traumatic spinal cord injury: a longitudinal cohort study. Lancet 377, 1004–1010. Waters, R.L., Lunsford, B.R., 1985. Energy cost of paraplegic locomotion. J. Bone Joint Surg. 67, 1245–1250. Waters, R.L., Adkins, R., Yakura, J., Vigil, D., 1994. Prediction of ambulatory performance based on motor scores derived from standards of the American Spinal Injury Association. Arch. Phys. Med. Rehabil. 75, 756–760. Wirz, M., Zemon, D.H., Rupp, R., Scheel, A., Colombo, G., Dietz, V., Hornby, T.G., 2005. Effectiveness of automated locomotor training in patients with chronic incomplete spinal cord injury: a multicenter trial. Arch. Phys. Med. Rehabil. 86, 672–680. Zorner, B., Blanckenhorn, W.U., Dietz, V., Curt, A., 2010. Clinical algorithm for improved prediction of ambulation and patient stratification after incomplete spinal cord injury. J. Neurotrauma 27, 241–252.
Comprehensive assessment of walking function after human spinal cord injury
1
Lea Awai1, Armin Curt Spinal Cord Injury Center, Balgrist University Hospital, Z€ urich, Switzerland 1 Corresponding author: Tel.:+41-44-386-37-34; Fax: +41-44-386-37-31, e-mail address: [email protected]
Abstract Regaining any locomotor function after spinal cord injury is not only of immediate importance for affected patients but also for clinical research as it allows to investigate mechanisms underlying motor impairment and locomotor recovery. Clinical scores inform on functional outcomes that are clinically meaningful to value effects of therapy while they all lack the ability to explain underlying mechanisms of recovery. For this purpose, more elaborate recordings of walking kinematics combined with assessments of spinal cord conductivity and muscle activation patterns are required. A comprehensive assessment framework comprising of multiple complementary modalities is necessary. This will not only allow for capturing even subtle changes induced by interventions that are likely missed by standard clinical outcome measures. It will be fundamental to attribute observed changes to naturally occurring spontaneous recovery in contrast to specific changes induced by novel therapeutic interventions beyond the improvements achieved by conventional therapy.
Keywords spinal cord injury, motor, walking, function, recovery, outcome measures, human
1 INTRODUCTION In incomplete spinal cord injury (iSCI), walking is characterized by manifold complex alterations like a slower than normal speed (Awai and Curt, 2014; Pepin et al., 2003), limited hip and knee flexion during swing (Perry and Burnfield, 2010), insufficient hip extension during stance, and excessive plantar flexion during swing (van der Salm et al., 2005). These observed impairments of joint and limb movements could be based on different underlying mechanisms such as limitations in hip flexion during swing phase that were attributed to muscle weakness, while the reduced knee flexion during swing was related to aberrant coactivation of antagonistic extensor Progress in Brain Research, Volume 218, ISSN 0079-6123, http://dx.doi.org/10.1016/bs.pbr.2014.12.004 © 2015 Elsevier B.V. All rights reserved.
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CHAPTER 1 Walking after SCI
Linear measures
muscles (Ditunno and Scivoletto, 2009). Thus, a multimodal and comprehensive approach to study normal and altered gait and its recovery is required for elucidating underlying mechanisms of gait control. The majority of clinical studies that monitor recovery processes or training effects during different interventions after spinal cord injury (SCI) chose measures of walking performance (i.e., walking speed/distance) and functional independence (e.g., type of required assistive device, performance during activities of daily living) to reflect motor function (Fig. 1). However, “motor function” and “walking function” are ill-defined terms as they rather nonspecifically refer to different aspects of gait (i.e., speed and time-distance parameters, type of walking assistance), while such
• Mobility • Type of assistive device
Subjective gait quality
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FIGURE 1 Measures of time and distance objectively assess the walking capacity or performance of a person and represent continuous data. They are often used to monitor recovery of walking function during rehabilitation or interventions. Clinical scores (e.g., walking index for spinal cord injury (WISCI), spinal cord independence measure (SCIM)) assess the mobility of a person (i.e., what type of assistive device does a person rely on, how well can a person perform activities of daily living) and were often developed for a specific type of subjects (i.e., spinal cord injured patients, stroke patients). They are ordinal values assessed at discrete time points. Gait quality is commonly assessed via subjective observation by trained persons in a descriptive manner. The quality may then be scored and represented by an ordinal value.
2 Clinical assessments of recovery
outcomes may not be well compared across studies and remain nonconclusive at explaining mechanisms of recovery. Even the examination of highly selected measures (e.g., changes in single joint angles), although presenting very concise information, is likely limited at elucidating underlying complex interactions. In order to acquire more comprehensive evaluations to address questions of physiological gait control as well as observed alterations and recovery profiles in iSCI, combined multimodal assessments are required. Especially in high risk and potentially highreturn clinical trials (phase I/II studies), investigators should consider any possible efforts to search for complementary information (including surrogate markers) beyond standard clinical outcome measures. These readouts may reveal more detailed insights into different mechanisms of action that eventually may be important to identify effects evoked by specific interventions (i.e., obvious as well as clinically masked changes).
2 CLINICAL ASSESSMENTS OF RECOVERY 2.1 NEUROLOGICAL ASSESSMENTS The completeness of lesion (i.e., the preservation of sensory function below the level of lesion) is crucial for the clinical description and prediction of ambulatory outcome (Maynard et al., 1979; Waters et al., 1994). Patients who are ASIA A early after injury have little chance of regaining functional ambulation, while ASIA B patients may reach a functional level (Crozier et al., 1992; Maynard et al., 1979; Waters et al., 1994). However, it is commonly accepted that the ASIA classification is too crude to reveal functional changes (i.e., improved walking ability) that may occur within one ASIA grade (i.e., ASIA D patients may increase walking speed and muscle strength without a conversion in ASIA grade). For a general evaluation of motor function, the assessment of ASIA motor scores as well as the spinal cord independence measure III (SCIM III) was strongly recommended (Labruyere et al., 2010). Even though the lower extremity motor scores (LEMS) are assessed in a lying position while the respective muscles are activated in a nontask specific manner (i.e., not during locomotion), LEMS were shown to be a good predictor for ambulatory outcome after rehabilitation (van Middendorp et al., 2011; Zorner et al., 2010). Furthermore, the LEMS of both legs were found to correlate best with walking speed, distance, and ambulatory capacity in chronic iSCI subjects compared to unilateral LEMS of the individual lower limb muscles (Kim et al., 2004). Thus, muscle strength seems to be an important determinant for walking performance (speed and distance) but may not have an influence on movement quality. It was shown that iSCI patients have preserved movement accuracy in the lower limbs despite diminished muscle strength, which distinguished them from stroke patients. The latter showed both diminished muscle strength in the affected leg as well as bilaterally impaired movement accuracy (van Hedel et al., 2010), suggesting that movement accuracy may not be corrupted by muscle weakness in iSCI.
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2.2 FUNCTIONAL ASSESSMENTS The SCIM was developed as a scale to score disability in patients with SCI (Catz et al., 1997). In acute patients, the SCIM III was evaluated to have the most appropriate performance with respect to specific psychometric properties (i.e., reliability, validity, reproducibility, responsiveness) when compared to other measures such as Functional Independence Measure, Walking Index for Spinal Cord Injury (WISCI), Modified Barthel Index, Timed Up & Go, 6-minute walk test (6MinWT), or 10-meter walk test (10MWT) (Furlan et al., 2011). Compared to measures of walking capacity (i.e., speed, WISCI), the SCIM also assesses improvements in ASIA A and B patients who are wheelchair bound (van Hedel and Dietz, 2009). Depending on the aim of a study, the appropriate outcome measures should be chosen. If walking function and its recovery are to be investigated and the question of whether or not patients improve locomotor function and by what means they might improve their walking capacity, the SCIM score might not be a sensitive tool while it does inform on to what extent a patient can perform activities of daily living independent of aids or support from third parties. Recovery of walking function is routinely assessed by functional outcome measures such as the widely used 10MWT and 6MinWT (Alcobendas-Maestro et al., 2012; Buehner et al., 2012; Hayes et al., 2014; Jayaraman et al., 2013; Kim et al., 2004; Kumru et al., 2013; Petersen et al., 2012a; van Hedel et al., 2006), where walking speed and distance (endurance) are evaluated (Fig. 1). Walking capacity (speed and distance) are important prerequisites for successful community ambulation (Lapointe et al., 2001). Despite improvements in walking speed during rehabilitation, iSCI patients typically show a reduced velocity compared to a healthy control cohort, especially when asked to walk at their maximally possible walking speed (Awai and Curt, 2014; Lapointe et al., 2001; Pepin et al., 2003; van Hedel et al., 2007). Several studies discussed the question as to whether the 10MWT and 6MinWT actually bear complementary information (Forrest et al., 2014; van Hedel et al., 2007). van Hedel et al. (2007) found a certain redundancy in walking speed assessed by these two measures when performed at a comfortable walking speed, while the results at maximal speed revealed additional information. However, these studies did not aim at answering the question of why patients may or may not walk faster or longer distances. Limitations in walking speed, particularly pronounced at maximal speed, may indicate a limited access to supraspinal drive (Bachmann et al., 2013) while endurance might be corrupted as a consequence of the increased energy expenditure found in iSCI patients (Lapointe et al., 2001; Waters and Lunsford, 1985). Different training approaches that all include some sort of walking (e.g., on a treadmill, overground, robot-assisted, body-weight supported, FES-supported) all found improvements in walking function as assessed by walking speed, distance, or WISCI II (Alexeeva et al., 2011; Dobkin et al., 2006; Field-Fote, 2001; FieldFote and Roach, 2011; Harkema et al., 2012; Postans et al., 2004; Thomas and Gorassini, 2005; Wirz et al., 2005). However, many of the studies that compared
3 Clinical neurophysiology
several training methods with respect to overground walking outcome did not find any differences between training approaches. This may either imply that a specific training method may not be superior to another or that the outcome measures are not sensitive to capture differences.
3 CLINICAL NEUROPHYSIOLOGY Due to the lack of more direct methods to investigate neural pathways underlying certain behaviors (i.e., implantable electrodes, fiber tracking, optogenetics, genetically modified animals), alternative assessments need to be employed in humans. Noninvasive or minimally invasive electrophysiological recordings can elucidate the integrity and connectivity of central and peripheral sensory and motor pathways in SCI patients either during a resting state (i.e., while subjects are lying; Chabot et al., 1985; Curt and Dietz, 1996, 1997; Curt et al., 1998; Kirshblum et al., 2001; Kovindha and Mahachai, 1992) or during activities such as locomotion (Barthelemy et al., 2010; Capaday et al., 1999; Dietz et al., 1998, 2002, 2009; Fung and Barbeau, 1994; Harkema et al., 1997; Schubert et al., 1997).
3.1 SPINAL CORD INTEGRITY Interestingly, SCI patients may improve their ambulatory capacity in the absence of concomitant improvements of corticospinal conduction velocity assessed via the latencies of motor- and somatosensory-evoked potentials (MEPs and SSEPs) (Curt et al., 2008). At the same time, the amplitudes of the evoked potentials are paralleled by improved walking function (Curt and Dietz, 1997; Curt et al., 1998; Petersen et al., 2012a; Spiess et al., 2008), suggesting that remyelination of injured axons or conduction velocity may not be the driving forces for functional recovery, but rather an improved synchronization of action potentials or adaptations at the neuromuscular site.
3.2 SPINAL NEURAL CIRCUITS Alterations of spinal reflexes have been shown to reveal changes in spinal neuronal (dys-)function and are related to walking ability in SCI patients (Dietz et al., 2009; Hubli et al., 2011, 2012). Concomitant with an improved locomotor function, spinal reflex responses shifted from exhibiting a predominant late component to a predominant early component, suggesting that neural pathways mediating nonnoxious spinal reflexes are also involved during locomotion (Hubli et al., 2012). A similar phenomenon was reported by another group (Thompson and Wolpaw, 2014; Thompson et al., 2013) via modulation of reflex circuits induced by operant conditioning. They showed that iSCI subjects could improve their walking ability after 30 sessions of voluntary soleus H-reflex downconditioning, supporting the idea of common pathways for rather simple reflex responses and more complex motor behaviors.
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Even in complete human SCI, muscle activity could be elicited during stepping movements and increased during training when appropriate afferent input was provided (Dietz et al., 1994, 2002; Harkema et al., 1997). Yet, to date, no independent, weight-bearing walking has been achieved after human complete SCI albeit intensive and long-lasting training. In a distinct set of patients, limited voluntary lower limb control and manually assisted locomotion could be elicited during epidural spinal cord stimulation in motor complete spinal cord injured patients following intensive training (Angeli et al., 2014; Harkema et al., 2011). These findings suggest that current clinical tests for the identification of completeness of injury are not sufficient to detect a small number of spared fibers. Also, the results of this group substantiated the general assumption that human subjects, to a larger extent than animals, require input from supraspinal centers in order to walk. How strongly humans rely on brain input and to what extent locomotor activity is controlled on a rather autonomous spinal level remains to be elucidated. Certain phases of the gait cycle (i.e., initial swing phase) and specific muscle groups (i.e., distal leg muscles) obviously receive input via the corticospinal tract (CST), as revealed by TMS studies (Calancie et al., 1999; Schubert et al., 1997). Coherence analysis of two EMG signals within the same or synergistic muscles reveals the amount of common synaptic drive to motor output and the coherence frequency within a specific range (i.e., 8–20 Hz) possibly indicates supraspinal origin of walking (Halliday et al., 2003; Hansen et al., 2005; Petersen et al., 2012b).
4 GAIT ANALYSIS With the aim of disentangling the mechanisms underlying motor recovery and locomotor control of normal and pathological gait, the assessment of walking speed and distance is insufficient. Furthermore, additional measures are of need to reveal factors contributing to recovery of walking and gait control. In addition to gait-cycle parameters (e.g., stance/swing phase, single/double limb support, step length, cadence), kinematic data objectively reveal information on the quality of walking. The gait of SCI patients is particularly characterized by muscle weakness on the one hand and an elevated muscle tone on the other hand. These conditions lead to limited knee mobility expressed by a reduced knee excursion and knee angular velocity as reported by Krawetz and Nance (1996), while greater knee flexion during swing and increased total hip excursion were reported by Pepin et al. (2003). Additionally, iSCI walking is typically characterized by an excessive ankle plantar flexion (foot drop) during the swing phase, which was considered to be an expression of diminished CST drive (Barthelemy et al., 2010, 2013). Only few studies investigated features of gait quality such as the interplay of lower limb joint angles (hip–knee cyclograms) revealing information on intersegmental coordination (Field-Fote and Tepavac, 2002; Nooijen et al., 2009; Pepin et al., 2003). This lower limb coordination is believed to offer insights into control mechanisms underlying locomotor behavior that are not revealed by gait-cycle parameters or measures of speed and
5 Neural control of walking
distance. These latter measures were even shown to be well modulated in iSCI patients (Pepin et al., 2003, unpublished data from our own studies) in contrast to the intralimb coordination that cannot be properly modulated according to speed (Fig. 2) and even deviates further from healthy control subjects when increasing speed from slow to preferred (Awai and Curt, 2014; Pepin et al., 2003, unpublished data from our own studies). The deficient intralimb coordination was suggested to be a contributing factor to the limited walking speed typically found in iSCI patients and upon visual evaluation was stated to be unique for each patient (Pepin et al., 2003). Nevertheless, specific characteristics of the cyclogram shared by several patients could be identified and this measure was used to classify four groups of impairment (Awai and Curt, 2014). A meaningful patient stratification is required for tailored rehabilitation programs as well as a homogenization of intervention groups for a more precise investigation of treatment effects. Interestingly, even though the cyclogram configuration was not immediately responsive to an increase in speed, the cyclogram shape reflected the preferred walking speed of the patients and could be quantified by calculating the shape difference to a normal cyclogram (Awai and Curt, 2014). Although the shape of the cyclogram did not normalize with increasing walking speed, patients could actually increase the cycle-to-cycle consistency (i.e., angular component of coefficient of correspondence). These distinct findings may allude to the possible existence of a discretely organized control of specific gait features that may be more or less affected by a SCI and reflect various recovery processes that are differently amenable to therapeutic interventions.
5 NEURAL CONTROL OF WALKING A reduction of walking speed is commonly observed in patients with a neurological disorder but is an unspecific indicator of the underlying cause. A patient with a lower limb bone fracture may also walk slower even in the absence of neural deficits. However, distinct recovery profiles and the way specific parameters are modulated with respect to increasing speed may be more informative with respect to underlying mechanisms of motor control. Given the complexity of bipedal locomotor control, it is necessary to take into account numerous measures of different modalities that explain specific characteristics of human gait and the underlying physiology (Fig. 3). The incapacity of clinically complete SCI patients to spontaneously walk and the studies that have shown that only a very limited locomotor pattern may be elicited in the absence of supraspinal input (Dietz et al., 1994; Harkema et al., 1997) suggest that compared to animals (Barbeau and Rossignol, 1987; De Leon et al., 1998) humans depend more strongly on supraspinal input (Barthelemy et al., 2011; Thomas and Gorassini, 2005) but have spinal neural centers capable of spontaneously producing rhythmic output (Calancie et al., 1994). The absence of recovering MEP latencies in the first year after injury suggests that regeneration of disrupted fibers or remyelination of injured axons are not the cause for functional improvements observed in SCI patients (Curt et al., 1998, 2008). It is therefore most probable
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Control subjects Slow
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FIGURE 2 Intralimb coordination may be represented by so-called hip–knee cyclograms and evaluates multisegmental lower limb coordination and therefore reveals information on motor control. The cyclogram configuration may be rather heterogeneous at a slow speed (0.5 km/h), while it normalizes to a very uniform shape at preferred walking speed in healthy control subjects. In contrast, iSCI patients are unable to normalize their pattern when walking at their respective preferred walking speed demonstrating their limited capacity to modulate complex lower limb movements.
5 Neural control of walking
Neural control Cortex Brain stem Spinal cord Motoneurons Muscle properties
Walking capacity Speed (10MWT) Distance (6MinWT) Type of assistive device
Gait quality Joint angles Range of motion (ROM) Angular velocity Limb coordination Movement reliability
Mechanisms of neural control of walking Mechanisms of (motor) recovery
Neuromuscular innervation Spinal cord integrity Motor-evoked potentials (MEPs) Somatosensory-evoked potentials (SSEPs) Nerve conduction studies (NCS) Spinal neural circuits Spinal reflexes H-reflex Electromyogram (EMG)
Gait-cycle parameters Step length Cadence Stance/swing phase Single/double limb support
FIGURE 3 In order to gain insight into mechanisms of neural control of walking and underlying processes of motor recovery, it is important to integrate complementary information considering different aspects of motor function. Measures assessing the anatomical and physiological integrity of specific pathways as well as parameters quantifying performance and gait quality are required for a comprehensive understanding of complex mutual interactions underlying specific phenotypes.
that SCI patients regain locomotor capacity via detour connections or adaptations that take place below the level of injury and therefore the control of walking might shift significantly. Concomitant with improvements in functional measures patients usually show increased MEP amplitudes and motor scores, which is most probably not attributable to regenerative processes within the lesion site (Curt et al., 2008). Moreover, most walking parameters increase during recovery while the gait quality seems to remain largely pathological (Awai L., Curt A., unpublished data) suggesting that compensatory mechanisms may not drive the recovery of complex movements as reflected by the intralimb coordination, which may depend predominantly on intact supraspinal input, making intralimb coordination a valuable measure for recovery beyond spontaneous/conventionally induced improvements. A clear segregation of motor control into spinal and supraspinal is probably neither doable nor correct. It is most likely that locomotion depends on the intricate temporal and spatial coordination of both feedforward and feedback control
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mechanisms performed at multiple levels of the neuraxis. Yet, knowledge about the anatomical structures underlying specific phenotypes of motor behavior is of need if outcome measures are to be correctly interpreted.
6 CONCLUSION A comprehensive assessment framework reveals different aspects of locomotion (Fig. 3). Clinical/functional measures inform on the performance of a patient during specific tasks (i.e., activities of daily living), while measures of speed and distance may decide on whether or not regained function enables a patient to achieve community ambulation. Electrophysiological procedures assess neural and/or muscular signal propagation, which may be differentiated into central and peripheral conduction. Spinal reflexes were shown to reflect spinal cord excitability and may be used as a simplified marker for locomotor function. These reflexes can be altered by and reveal the plasticity of neural circuits. Kinematic outcome measures representing complex coordinative movements and their responsiveness to speed modulation reveal the integration of a multitude of signals involved in locomotion. Measures of intralimb coordination may be used to stratify patients with respect to their gait impairment enhancing targeted patient interventions and reduction of outcome variability. Only an elaborate assessment battery including complementary measures provides sufficient information for a profound understanding of an existing disorder. To tackle the amount and diversity of data, a multivariate approach (e.g., principal components analysis) may be the method of choice.
ACKNOWLEDGMENTS This study was partly funded by the European Commission’s Seventh Framework Program (CP-IP 258654, NEUWalk) and the Clinical Research Priority Program CRPP Neurorehab UZH.
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