Advances in Transfemoral Amputee Rehabilitation: Early Experience with Targeted Muscle Reinnervation
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- Souza, J.M., Fey, N.P., Cheesborough, J.E. et al. Curr Surg Rep (2014) 2: 51. doi:10.1007/s40137-014-0051-4
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While myoelectric prosthetic devices have been used for decades in the upper extremities, only recently have motorized knee and ankle components proven durable and effective enough for use in the lower extremity amputee. The control schemes developed to capitalize on these prosthetic advances must take into account the biomechanical differences between upper and lower extremity function. Already a valuable adjunct for the myoelectric control of upper extremity prostheses, targeted muscle reinnervation in the transfemoral amputee offers the potential to further enhance lower extremity prosthesis control and may simultaneously address post-amputation neuroma pain. Current strategies for lower extremity prosthesis control are discussed, along with a review of the transfemoral TMR technique and early clinical experience.
KeywordsTargeted muscle reinnervation Transfemoral amputee rehabilitation Transfemoral Lower extremity prosthesis control Myoelectric device Pattern recognition Neuroma
There are ~1.7 million people in the United States living with limb loss. This correlates to roughly 1 in 200 Americans, with the number of amputees in the United States projected to double by 2050 [1, 2]. According to the World Health Organization, chronic disease accounts for 65 % of all amputations in the United States, while trauma and cancer cause the remainder . Between 2001 and 2010, the US military interventions in Iraq and Afghanistan produced 1,222 major limb amputations . While the relative number of amputations due to these conflicts is small, the dramatic nature of these high-level, multiple limb combat injuries has brought amputee care to the forefront of the American consciousness. The increased public awareness of the challenges faced by amputees has been matched by a renewed scientific interest in a field of surgery that is as old as war itself.
Targeted muscle reinnervation (TMR) is one of the notable recent advances in amputee care. A true multidisciplinary endeavor, TMR combines peripheral nerve surgery with electromyography-based prosthetic control algorithms and advanced prosthetics to provide intuitive and coordinated control of multi-jointed prosthetic devices. Developed for use in the upper extremity amputee, TMR reroutes the distally transected brachial nerves and coapts them to small recipient nerves innervating residual limb muscles that have been left otherwise nonfunctional due to the amputation. Once reinnervated by the donor nerves, the muscles act as biologic amplifiers, creating an electromyographic (EMG) representation of the lost limb that can be captured by surface electrodes and used for prosthesis control [5, 6, 7]. The retained neural information provides a rich source of data, which when combined with pattern recognition algorithms, has been demonstrated to provide functional benefits during reaching or grasping tasks [8, 9, 10]. Beyond its role in improving prosthetic function, animal studies and retrospective clinical series suggest that TMR may also be effective as a strategy to treat post-amputation neuroma pain [11, 12, 13, 14••]. First performed in 2002 as an experimental procedure for a patient with bilateral shoulder disarticulations, TMR has now become an established part of upper extremity amputee care .
Lower extremity amputations are not only more common, but are often more proximal than those that occur in the upper extremity [2, 16]. However, the infrequent use of lower extremity myoelectric devices precluded early adaptation of the TMR technique for use in the lower extremity. Continued advances in motorized knees and ankles now justify more thorough evaluation of the possible benefits of TMR for the lower extremity amputee. Analogous to the concept behind TMR in the upper extremity, the goal of the transfemoral TMR procedure is to use nerve transfers between distally transected nerves and functionally redundant muscles in the residual limb to increase the number of independently innervated muscles from which to harvest EMG data. Early experience with this technique is promising.
Lower Extremity Prosthesis Control: Previous Limitations
Using conventional prostheses and rehabilitative care practices, individuals with lower extremity amputations commonly develop asymmetrical gait characteristics [17, 18] that increase the metabolic energy costs of transport . These abnormal gait patterns are frequently associated with chronic leg and back pain, and increased incidences of degenerative joint disorders such as osteoarthritis are well-documented [20, 21, 22, 23, 24]. These behaviors are typically more severe and more prevalent as the level of leg amputation increases [19, 20]. This trend is to be expected, as higher levels of amputation result in greater functional loss, thus placing increased demand on the prosthetic replacement. Therefore, improved prostheses design and control methods are of particular value to the transfemoral amputee.
Nearly all commercially available prosthetic knees and ankles are mechanically passive (e.g., spring-like) devices, which do not actively deliver power about their joints. In fact, as opposed to delivering increased energy, passive devices dissipate energy from step to step. This is particularly problematic during the demanding tasks of daily living, such as ambulating up stairs or an incline, or rising from a seated position. This constraint also limits some low-demand activities, such as repositioning the prosthesis during non-weight-bearing tasks. Simple tasks like dressing or transitioning into or out of a vehicle can be difficult and require compensatory movements of the sound limbs. The development of mechanically active (i.e., powered) knee or ankle prostheses offer the ability to deliver net positive energy for user assistance during these ambulatory and non-ambulatory tasks of daily living [25, 26, 27, 28, 29, 30, 31, 32]. However, the current control systems for these devices are lacking, particularly in transfemoral prostheses. Most devices are not intuitive, often requiring button presses or a compensatory movement to trigger a change in a device’s mode of operation.
Incorporating the use of neural information into the control of powered knee and ankle prostheses allows user intent to be paired with function. Specifically, neural information can enable direct control of non-weight-bearing (i.e., non-ambulatory) movements. In addition, it can provide more seamless (without stopping), automatic (without manual adjustments), and natural (without compensation) transitions between modes of ambulation. As demonstrated in upper extremity amputees, TMR provides a means by which to deliver neural information for the control of joints distal to the level of amputation [6, 7, 33].
Lower Extremity Prosthesis Control: TMR and Other Recent Advances
The characteristics of measured EMG signals vary with specific tasks. For example, during sustained contractions like those used during grasping, the EMG signals are typically stationary (i.e., not time varying) until the onset of muscle fatigue. Techniques for upper-limb prostheses control and exploit these signal characteristics [33, 34, 35, 36]. Similar EMG characteristics can be observed in sustained contractions of lower-limb muscles during non-weight-bearing tasks. Thus, it would follow that the pattern recognition approaches used to govern non-weight-bearing tasks of lower-limb amputees should be very similar to those used to control upper-limb functions. These approaches have been applied to transfemoral prostheses control, and high classification accuracies have been shown in offline analyses, particularly for seated knee flexion and extension movements [37, 38]. In addition, advanced filtering methods and other pattern recognition algorithms that record from smaller sets of muscle sites have shown promise when used for knee control in offline analyses or in virtual environments [39, 40].
In contrast to the EMG patterns exhibited during non-weight-bearing functions, lower limb EMG recordings during overground ambulation show greater variability in time (i.e., are non-stationary) and are cyclic in nature. These differences necessitate alternative pattern recognition-based approaches for lower limb prosthesis control. Alternative algorithms have been developed to select EMG data from discrete portions of the gait cycle to predict various modes of ambulation (e.g., level ground walking, stair ascent/descent, and ramp ascent/descent) . These approaches merge EMG data with data from mechanical sensors (e.g., acceleration, load, or position data) within the prostheses to anticipate transitions between various ambulation modes. This fusion of signal modalities (EMG and mechanical) has shown better performance than using mechanical sensor data alone .
A more advanced approach to lower extremity prosthesis control incorporates time-history information (how EMG and mechanical signals vary in time) collected over the course of the gait cycle to allow ambulation mode switching decisions to occur at specific gait cycle events (i.e., either at toe-off or heel-strike). This control scheme has been tested on multiple transfemoral amputees without TMR. These studies found that combining time-history information with a fusion of mechanical and EMG data offers the lowest error rate when predicting ambulation mode [45, 46]. This advanced pattern recognition approach was evaluated across various ambulation modes in the same knee-disarticulation-level TMR patient previously mentioned. While the error rate for ambulation mode prediction was low using mechanical data and EMG data captured exclusively from natively innervated muscles (2.2 %), this error rate was even lower (1.8 %) when EMG data from the reinnervated muscles were added [43••].
The additional neural information provided by TMR may provide additional benefits. For example, the supplemental lower leg information provided by TMR may allow for improvement of the device’s within-mode performance during ambulation, thus providing a greater degree of user-adaptability. Recent research has used EMG from the residual limb gastrocnemius muscle of transtibial amputees to modify the plantar-flexion mechanics of a powered ankle prosthesis during the terminal stance phase of walking . There is potential that transfemoral amputees with TMR could provide similarly beneficial control information to modify the late stance performance of a prosthetic knee and/or ankle in an analogous manner. This would be impossible in transfemoral amputees without TMR.
TMR as a Strategy for Post-Amputation Neuroma Treatment
Despite being developed primarily for prosthesis function, TMR has been demonstrated to have a beneficial effect on residual limb neuroma pain. This finding is particularly encouraging in light of the fact that at least 25 % of all major limb amputees, and upwards of 71 % of those with traumatic amputations, will develop chronic localized pain due to symptomatic end neuromas [48, 49, 50, 51]. These painful neuromas often limit prosthesis use, thus further reducing the functional capacity of the amputee.
Early clinical observations of improved residual limb pain following TMR were confirmed by a retrospective review of 28 consecutive upper extremity TMR cases performed at our institution, in conjunction with the San Antonio Military Medical Center. Despite the fact that 58 % of patients presented with symptomatic residual limb neuromas, 93 % experienced complete resolution of neuroma pain and 100 % were successfully fit with a prosthesis [14••]. A separate review of 31 TMR cases performed at the University of Washington’s Harborview Medical Center found the technique to be similarly effective for the management of residual neuroma pain [14••].
In addition to these clinical reviews, a novel rabbit neuroma model demonstrated significant improvement in fascicle number and size following neuroma excision and subsequent TMR . Similarly, a rat hind-limb model showed improved nerve histology after TMR was performed with both mixed and pure sensory nerves. Most notably, TMR significantly decreased histologic evidence of neuroma formation when compared to burying of the nerve ends into natively innervated muscles—a technique many consider to be the gold standard treatment for end neuromas [14••]. These preclinical findings are consistent with a clinical report showing nerve repair to be superior to neuroma excision and muscle/bone implantation for the treatment of symptomatic neuromas in the intact upper extremity . By providing both a distal target and a vascularized scaffold upon which to guide sprouting nerve axons, TMR offers the potential to restore continuity to the peripheral nervous system despite amputation of the native distal nerve segments. Motivated by these retrospective outcomes and supportive preclinical findings, seven cases of lower extremity TMR have been performed at our institution for the primary purpose of improving persistent post-amputation neuroma pain. Standardized patient-reported pain outcomes were collected prior to these procedures. However, while our early experience has been uniformly positive, the duration of follow-up is still too short to allow for meaningful interpretation of the pain outcomes data. Beyond this small subset of patients, a large multi-institutional randomized clinical trial of TMR versus standard neuroma excision and muscle implantation is now underway.
Current Surgical Technique
The evolution in motorized knee and ankle components of lower extremity prostheses has introduced a need for more advanced approaches to prosthesis control. Some of the myoelectric control schemes useful in the upper extremity can be applied to the lower extremity, but must be merged with mechanical and timing-based control methods if seamless and natural ambulation is to be achieved. TMR in the transfemoral amputee offers the potential to further enhance prosthesis control by providing an EMG representation of the amputated lower leg muscles within the residual limb. While the early results are promising, critical assessment of outcomes will be needed in order to obtain a deeper understanding of the true benefits offered by this technique.