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Diagnostic and Interventional Imaging Dec 2015The flexor system of the fingers consisting of flexor tendons and finger pulleys is a key anatomic structure for the grasping function. Athletes and manual workers are... (Review)
Review
The flexor system of the fingers consisting of flexor tendons and finger pulleys is a key anatomic structure for the grasping function. Athletes and manual workers are particularly at risk for closed injuries of the flexor system: ruptured pulleys, ruptures of the flexor digitorum profundus from its distal attachment ("jersey finger"), and less frequently, ruptures of the flexor digitorum superficialis and of the lumbrical muscles. Open injuries vary more and their imaging features are more complex since tendons may be torn in several locations, the locations may be unusual, the injuries may be associated with nerve and vascular injuries, fibrosis… Sonography is the best imaging modality to associate with the clinical exam for it allows an experienced physician to make an accurate and early diagnosis, crucial to appropriate early treatment planning.
Topics: Diagnostic Imaging; Finger Injuries; Humans; Tendon Injuries
PubMed: 26564614
DOI: 10.1016/j.diii.2015.09.010 -
JAMA Network Open Nov 2022Cervical spinal cord injury (SCI) causes devastating loss of upper extremity function and independence. Nerve transfers are a promising approach to reanimate upper...
IMPORTANCE
Cervical spinal cord injury (SCI) causes devastating loss of upper extremity function and independence. Nerve transfers are a promising approach to reanimate upper limbs; however, there remains a paucity of high-quality evidence supporting a clinical benefit for patients with tetraplegia.
OBJECTIVE
To evaluate the clinical utility of nerve transfers for reanimation of upper limb function in tetraplegia.
DESIGN, SETTING, AND PARTICIPANTS
In this prospective case series, adults with cervical SCI and upper extremity paralysis whose recovery plateaued were enrolled between September 1, 2015, and January 31, 2019. Data analysis was performed from August 2021 to February 2022.
INTERVENTIONS
Nerve transfers to reanimate upper extremity motor function with target reinnervation of elbow extension and hand grasp, pinch, and/or release.
MAIN OUTCOMES AND MEASURES
The primary outcome was motor strength measured by Medical Research Council (MRC) grades 0 to 5. Secondary outcomes included Sollerman Hand Function Test (SHFT); Michigan Hand Outcome Questionnaire (MHQ); Disabilities of Arm, Shoulder, and Hand (DASH); and 36-Item Short Form Health Survey (SF-36) physical component summary (PCS) and mental component summary (MCS) scores. Outcomes were assessed up to 48 months postoperatively.
RESULTS
Twenty-two patients with tetraplegia (median age, 36 years [range, 18-76 years]; 21 male [95%]) underwent 60 nerve transfers on 35 upper limbs at a median time of 21 months (range, 6-142 months) after SCI. At final follow-up, upper limb motor strength improved significantly: median MRC grades were 3 (IQR, 2.5-4; P = .01) for triceps, with 70% of upper limbs gaining an MRC grade of 3 or higher for elbow extension; 4 (IQR, 2-4; P < .001) for finger extensors, with 79% of hands gaining an MRC grade of 3 or higher for finger extension; and 2 (IQR, 1-3; P < .001) for finger flexors, with 52% of hands gaining an MRC grade of 3 or higher for finger flexion. The secondary outcomes of SHFT, MHQ, DASH, and SF36-PCS scores improved beyond the established minimal clinically important difference. Both early (<12 months) and delayed (≥12 months) nerve transfers after SCI achieved comparable motor outcomes. Continual improvement in motor strength was observed in the finger flexors and extensors across the entire duration of follow-up.
CONCLUSIONS AND RELEVANCE
In this prospective case series, nerve transfer surgery was associated with improvement of upper limb motor strength and functional independence in patients with tetraplegia. Nerve transfer is a promising intervention feasible in both subacute and chronic SCI.
Topics: Adult; Humans; Male; Nerve Transfer; Quadriplegia; Upper Extremity; Hand; Fingers
PubMed: 36441549
DOI: 10.1001/jamanetworkopen.2022.43890 -
Experimental Brain Research May 2018We explored whether the synergic control of the hand during multi-finger force production tasks depends on the hand muscles involved. Healthy subjects performed accurate...
We explored whether the synergic control of the hand during multi-finger force production tasks depends on the hand muscles involved. Healthy subjects performed accurate force production tasks and targeted force pulses while pressing against loops positioned at the level of fingertips, middle phalanges, and proximal phalanges. This varied the involvement of the extrinsic and intrinsic finger flexors. The framework of the uncontrolled manifold (UCM) hypothesis was used to analyze the structure of inter-trial variance, motor equivalence, and anticipatory synergy adjustments prior to the force pulse in the spaces of finger forces and finger modes (hypothetical finger-specific control signals). Subjects showed larger maximal force magnitudes at the proximal site of force production. There were synergies stabilizing total force during steady-state phases across all three sites of force production; no differences were seen across the sites in indices of structure of variance, motor equivalence, or anticipatory synergy adjustments. Indices of variance, which did not affect the task (within the UCM), correlated with motor equivalent motion between the steady states prior to and after the force pulse; in contrast, variance affecting task performance did not correlate with non-motor equivalent motion. The observations are discussed within the framework of hierarchical control with referent coordinates for salient effectors at each level. The findings suggest that multi-finger synergies are defined at the level of abundant transformation between the low-dimensional hand level and higher dimensional finger level while being relatively immune to transformations between the finger level and muscle level. The results also support the scheme of control with two classes of neural variables that define referent coordinates and gains in back-coupling loops between hierarchical control levels.
Topics: Adult; Feedback, Sensory; Female; Fingers; Hand; Hand Strength; Humans; Male; Motor Skills; Movement; Muscle Contraction; Muscle, Skeletal; Psychomotor Performance
PubMed: 29532100
DOI: 10.1007/s00221-018-5231-5 -
Proceedings of the National Academy of... Mar 2022Stable precision grips using the fingertips are a cornerstone of human hand dexterity. However, our fingers become unstable sometimes and snap into a hyperextended...
Stable precision grips using the fingertips are a cornerstone of human hand dexterity. However, our fingers become unstable sometimes and snap into a hyperextended posture. This is because multilink mechanisms like our fingers can buckle under tip forces. Suppressing this instability is crucial for hand dexterity, but how the neuromuscular system does so is unknown. Here we show that people rely on the stiffness from muscle contraction for finger stability. We measured buckling time constants of 50 ms or less during maximal force application with the index finger—quicker than feedback latencies—which suggests that muscle-induced stiffness may underlie stability. However, a biomechanical model of the finger predicts that muscle-induced stiffness cannot stabilize at maximal force unless we add springs to stiffen the joints or people reduce their force to enable cocontraction. We tested this prediction in 38 volunteers. Upon adding stiffness, maximal force increased by 34 ± 3%, and muscle electromyography readings were 21 ± 3% higher for the finger flexors (mean ± SE). Muscle recordings and mathematical modeling show that adding stiffness offloads the demand for muscle cocontraction, thus freeing up muscle capacity for fingertip force. Hence, people refrain from applying truly maximal force unless an external stabilizing stiffness allows their muscles to apply higher force without losing stability. But more stiffness is not always better. Stiff fingers would affect the ability to adapt passively to complex object geometries and precisely regulate force. Thus, our results show how hand function arises from neurally tuned muscle stiffness that balances finger stability with compliance.
Topics: Biomechanical Phenomena; Electromyography; Fingers; Hand Strength; Humans; Muscle Contraction; Muscle, Skeletal; Posture
PubMed: 35294291
DOI: 10.1073/pnas.2122903119 -
BioRxiv : the Preprint Server For... Aug 2023The ability to control each finger independently is an essential component of human hand dexterity. A common observation of hand function impairment after stroke is the...
The ability to control each finger independently is an essential component of human hand dexterity. A common observation of hand function impairment after stroke is the loss of this finger individuation ability, often referred to as enslavement, i.e., the unwanted coactivation of non-intended fingers in individuated finger movements. In the previous literature, this impairment has been attributed to several factors, such as the loss of corticospinal drive, an intrusion of flexor synergy due to upregulations of the subcortical pathways, and/or biomechanical constraints. These factors may or may not be mutually exclusive and are often difficult to tease apart. It has also been suggested, based on a prevailing impression, that the intrusion of flexor synergy appears to be an exaggerated pattern of the involuntary coactivations of task-irrelevant fingers seen in a healthy hand, often referred to as a flexor bias. Most previous studies, however, were based on assessments of enslavement in a single dimension (i.e., finger flexion/extension) that coincide with the flexor bias, making it difficult to tease apart the other aforementioned factors. Here, we set out to closely examine the nature of individuated finger control and finger coactivation patterns in all dimensions. Using a novel measurement device and a 3D finger-individuation paradigm, we aim to tease apart the contributions of lower biomechanical, subcortical constraints, and top-down cortical control to these patterns in both healthy and stroke hands. For the first time, we assessed all five fingers' full capacity for individuation. Our results show that these patterns in the healthy and paretic hands present distinctly different shapes and magnitudes that are not influenced by biomechanical constraints. Those in the healthy hand presented larger angular distances that were dependent on top-down task goals, whereas those in the paretic hand presented larger Euclidean distances that arise from two dissociable factors: a loss of complexity in finger control and the dominance of an intrusion of flexor bias. These results suggest that finger individuation impairment after stroke is due to two dissociable factors: the loss of finger control complexity present in the healthy hand reflecting a top-down neural control strategy and an intrusion of flexor bias likely due to an upregulation of subcortical pathways. Our device and paradigm are demonstrated to be a promising tool to assess all aspects of the dexterous capacity of the hand.
PubMed: 37693573
DOI: 10.1101/2023.08.29.555444