Literature DB >> 28244504

Ambulatory function in motor incomplete spinal cord injury: a magnetic resonance imaging study of spinal cord edema and lower extremity muscle morphometry.

A C Smith1,2, K A Weber3, T B Parrish4, T G Hornby5, V M Tysseling2, J G McPherson6, M Wasielewski2, J M Elliott2.   

Abstract

STUDY
DESIGN: This research utilized a cross-sectional design.
OBJECTIVES: Spinal cord edema length has been measured with T2-weighted sagittal MRI to predict motor recovery following spinal cord injury. The purpose of our study was to establish the correlational value of axial spinal cord edema using T2-weighted MRI. We hypothesized a direct relationship between the size of damage on axial MRI and walking ability, motor function and distal muscle changes seen in motor incomplete spinal cord injury (iSCI).
SETTING: University-based laboratory in Chicago, IL, USA.
METHODS: Fourteen participants with iSCI took part in the study. Spinal cord axial damage ratios were assessed using axial T2-weighted MRI. Walking ability was investigated using the 6-min walk test and daily stride counts. Maximum plantarflexion torque was quantified using isometric dynomometry. Muscle fat infiltration (MFI) and relative muscle cross-sectional area (rmCSA) were quantified using fat/water separation magnetic resonance imaging.
RESULTS: Damage ratios were negatively correlated with distance walked in 6 min, average daily strides and maximum plantarflexion torque, and a negative linear trend was found between damage ratios and lower leg rmCSA. While damage ratios were not significantly correlated with MFI, we found significantly higher MFI in the wheelchair user participant group compared to community walkers.
CONCLUSIONS: Damage ratios may be useful in prognosis of motor recovery in spinal cord injury. The results warrant a large multi-site research study to investigate the value of high-resolution axial T2-weighted imaging to predict walking recovery following motor incomplete spinal cord injury.

Entities:  

Mesh:

Year:  2017        PMID: 28244504      PMCID: PMC5501756          DOI: 10.1038/sc.2017.18

Source DB:  PubMed          Journal:  Spinal Cord        ISSN: 1362-4393            Impact factor:   2.772


Introduction

Annually, an estimated 250,000 to 500,000 individuals suffer a spinal cord injury (SCI) worldwide.[1] Incomplete spinal cord injury refers to a type of SCI where partial sensory and/or motor function is, to some degree, preserved below the level of the injury.[2] Generally, patients with motor incomplete spinal cord injury (iSCI) are expected to recover at least some walking ability[3] but not without deficits in generating maximal volitional torque.[4] The size and volitional activation of the lower extremity musculature is likely to factor[4,5] in maximizing ambulatory recovery, which remains a top priority in rehabilitative programs.[6] An expected adaptation of motor incomplete spinal cord injury is change in muscle structure distal to the level of injury[7,8] (e.g. decreased muscle cross-sectional area (atrophy), and muscle fat infiltration (MFI)).[9-11] While atrophy and MFI of lower extremity musculature can be quantified using magnetic resonance imaging (MRI),[5,12] their directional relationship to the damaged area of the cervical cord and ambulatory status are largely unknown. Predicting neurologic functional recovery in cervical spinal cord injury with postoperative MRI has been widely utilized.[13-22] A number of studies have demonstrated that edema without hemorrhage in the cervical cord suggests a more favorable functional outcome with iSCI.[14,17,23] Further work has measured and related the length of edema to motor abilities and prognosis.[13-15,24,25] However, due to insufficient T2 contrast in the damaged cord, questions remain regarding the prognostic value of such an approach.[26] With technological advancements in today’s and tomorrow’s MRI sequences, the quantification of spinal cord edema and its predictive relationship to muscle health and motor function (e.g. walking ability,[27] decreased lower extremity maximum torque output,[4] decreased muscle cross-sectional area (atrophy) distal to the injury site,[12] and muscle fat infiltration[9-11]) may be realized. The purpose of this cross-sectional study was to use high resolution axial T2-weighted MRI to quantify spinal cord edema in participants with iSCI, and to relate this metric of cord damage to walking ability (6-minute walk test and daily stride count), lower extremity torque production, lower extremity muscle CSA, and MFI. We hypothesized that spinal cord edema would be negatively correlated with walking ability, torque production, and muscle CSA, but positively correlated with the lower extremity MFI. For a secondary analysis, we hypothesized wheelchair ambulators to have higher MFI and lower muscle CSA compared to those not requiring a wheelchair.

Methods

Participant characteristics

Participants were recruited from the Rehabilitation Institute of Chicago’s Spinal Cord Injury database, in accordance with Northwestern University IRB #STU00087983 and the Declaration of Helsinki. Fourteen individuals with chronic cervical iSCI participated (1 female and 13 males, average age = 43 ± 12 years old). Four individuals with iSCI were classified using the American Spinal Cord Injury Association Impairment Scale (AIS) as AIS C C5–8 level, 2 participants were classified as AIS D C1–4 level, and 8 participants were classified as AIS D C5–8 level. Seven participants used walking as their primary mode of community ambulation, while seven used wheelchairs for community ambulation. See Table 1 for details on the participant characteristics, including time since injury.
Table 1

Participant Characteristics

Participant #GenderAge (years)Height (cm)Weight (kg)BMI (units)Time since Injury (years)Mechanism of InjuryLevel of InjuryASIA Impairment ScalePrimary Ambulation
iSCI1M5318582.123.96MVCC5CWheelchair
iSCI2M5717879.425.18Cycling InjuryC3DWalk with AD
iSCI3F5215783.933.80.5MVCC6DWalk with AD
iSCI4M3117872.623.04Diving InjuryC5DWalk with AD
iSCI5M2818895.327.03Diving InjuryC5DWalk
iSCI6M5016883.929.92Fall from HeightC6DWalk
iSCI7M30193115.731.04Diving InjuryC6CWheelchair
iSCI8M2719186.223.74Skiing InjuryC5CWheelchair
iSCI9M3217381.727.45MVCC7DWalk
iSCI10M4517559.019.24ATV InjuryC3DWalk with AD
iSCI11M3618573.521.42Motorcycle InjuryC6CWheelchair
iSCI12M5017872.623.05Fall from HeightC4DWheelchair
iSCI13M64175108.935.54FallC5DWheelchair
iSCI14M5217570.322.931Diving injuryC5DWheelchair

BMI = Body Mass Index, MVC = Motor Vehicle Collision, AD = Assistive Device, ATV = All Terrain Vehicle

We certify that all applicable institutional and governmental regulations concerning the ethical use of human volunteers were followed during the course of this research.

Magnetic resonance imaging

Spinal Cord imaging

T2 weighted imaging of the cervical spinal cord was performed using a 3.0 Tesla Prisma magnetic resonance (MR) scanner equipped with a 64-channel head/neck coil (Siemens, Erlangen, Germany). A high-resolution T2-weighted structural image of the cervical spine and spinal cord damage site was acquired using a 2D turbo spin echo sequence, and 16 slices were oriented to be perpendicular to the spinal cord edema (FOV = 260 mm square field of view, TR = 2380 ms, TE = 102 ms, flip angle = 120°, number of averages = 3, bandwidth = 651 Hz/Px, phase encoding direct: right to left, resolution = 0.5 × 0.5 × 2.0 mm3, acquisition matrix = 512 × 282). The acquisition time was 6:30 minutes. Spinal cord MRI data were analyzed offline using OsiriX image processing software (Pixmeo, Geneva, Switzerland). The OsiriX interpolation function was used for clearer visualization of edema. For each participant, using the slice where the spinal cord edema of maximum area was measured, the cross-sectional area of edema was obtained, and a damage ratio was calculated as maximum spinal cord edema CSA divided by the CSA of the surrounding spinal cord. A value of zero suggests no edema, where a value of one equates to the edema covering the full region of the spinal cord (Figure 1).
Figure 1

Axial T2-weighted images of spinal cord edema in each participant with iSCI, with corresponding damage ratios listed. Damage ratios were calculated as edema area divided by the surrounding spinal cord area.

6-Minute Walk Test

Each participant completed an over ground 6-minute walk test, where the total distance walked within a 6-minute time frame was measured.[28] Participants were instructed to walk at their normal, self-selected pace, and were allowed to use assistive devices and braces as necessary. The 6-minute walk test has been shown to be reliable and valid in iSCI.[28,29]

Daily Stepping

Each participant wore an ankle step monitor with an accelerometer for a 2-week window, in order to quantify average daily strides.[30] Participants were instructed to wear the step monitor at all times except when bathing/showering. Previous literature verified that a ≥ 3-day window of acquiring step data is sufficient for a reliable estimate of stepping activity.[31]

Walking Index for Spinal Cord Injury

A licensed physical therapist rated each participant on a locomotor scale, the Walking Index for Spinal Cord Injury II. This scale ranks the ability of the participant to walk 10 meters, and has been demonstrated to have excellent inter-rater reliability and to be a valid tool in SCI.[32]

Isometric Plantarflexion Torque

For isometric ankle plantarflexion torque measurement, participants were secured in a seated position with both ankles at neutral, knees flexed at 20°, and hips flexed to 75°. Maximum volitional torque (MVT) was established following 3 maximal isometric contractions of the plantarflexors, each contraction held 3–4 seconds duration in an isokinetic dynamometer, with each leg tested separately (Biodex Rehabilitation System v3, Shirley NY USA). Verbal encouragement to facilitate maximum torque production was provided.[33] Torque traces were monitored during each trial on a biofeedback screen.

Muscle Fat Infiltration and Lower Extremity Muscle CSA

For both the leg muscle cross-sectional area and muscle fat infiltration quantification, a chemical shift based, 3D dual-echo gradient, Dixon method fat-water separation MRI technique was performed on all participants.[34,35] The 2-point Dixon examination included the major muscle groups of the lower leg: gastrocnemius, soleus, tibialis anterior, and peroneous longus. The specific Dixon MRI parameters for the lower extremities included: TR = 6.59 ms, TE1 = 2.45 ms TE2 = 3.675 ms, flip angle = 12 degrees, bandwidth 1 = 510 bandwidth 2 = 660 Hz/Px and an imaging matrix of 448 × 266. A read field of view of 320 – 340 mm was used on the lower extremity muscles using a 16-channel body array surface coil, and 60 slices per slab with a slice thickness of 5 mm and a slice oversampling of 6.7% were acquired. The acquisition time was 4:12 minutes with a rectangular view of 60%, 4 averages and an in-plane resolution of 0.5 mm. Localizer scans were used to obtain the fat/water data in the axial plane perpendicular to the tibia. Analysis of the lower extremity MRI data was performed using customized imaging analysis scripts created in MatLab (Version 2014b, MathWorks, Natick, MA). One experienced researcher manually defined each region of interest (ROI) in the four leg muscle groups by contouring each muscle within its fascial borders with the co-registered fat- and water-saturated sequences. The MFI percentage is a value of fat signal intensity to fat-plus-water signal intensity, and these MFI percentages were created using the equation: Sixty slices were obtained through the leg, and averages were taken over 10 consecutive slices throughout the muscle bulk of each of the four lower extremity muscles to form individual MFI percentages.[35] Each outline of the 4 individual lower extremity muscles yielded a CSA value. Average individual muscle CSA values were taken across 10 consecutive slices of muscle bulk, total CSA values were taken as a sum of all 4 muscles, and the relative muscle CSA (rmCSA) was calculated by removing the fat infiltration[36], using the equation: rmCSA = CSA * (1 – MFI).

Statistical Analysis

All statistical analyses of the data were performed using IBM SPSS (Version 21, Armonk, NY, USA). All data were tested for normality using Kolmogorov-Smirnov (KS) statistical analyses. Intra-class correlation coefficients (ICC 2,1) were used to test the inter- and intra-rater reliability of the spinal cord damage ratio measure. Rater one took measurements two months apart for intra-rater testing, and rater two took a separate measure of damage ratios to establish inter-rater reliability. Pearson correlations were employed to examine linear relationships between spinal cord damage ratios and distance walked in 6 minutes, average daily strides, plantarflexion torque production, relative muscle CSA, and MFI. A 2-way ANOVA was utilized to test for significant MFI differences between wheelchair user and community walker participant groups, as well as between the four muscle groups, with Bonferroni post-hoc correction. An independent samples t-test was used to test for a significant difference in total lower leg rmCSA between the wheelchair user and community walker participant groups. P values of < 0.05 were considered significant.

Results

All of the data met assumptions of normality using KS statistical analyses. Individual data are presented in Tables 2 and 3.
Table 2

Individual Participant Data – Damage Ratios, Walking, and Plantarflexion Torque

Participant #Primary AmbulationDamage Ratio6MW Distance (m)Average Daily StridesRight Plantarflexion MVT (Nm)Left PlantarflexionMVT (Nm)
iSCI1Wheelchair0.296424730.0345.52
iSCI2Walk with AD0.20187203664.4582.93
iSCI3Walk with AD0.39147116693.0086.00
iSCI4Walk with AD0.35134155729.5644.35
iSCI5Walk0.32409148372.98149.05
iSCI6Walk0.104122786133.29104.91
iSCI7Wheelchair0.474937212.6952.80
iSCI8Wheelchair0.573033029.7312.66
iSCI9Walk0.17431307761.2683.56
iSCI10Walk with AD0.49165110855.4668.29
iSCI11Wheelchair0.399874536.1380.84
iSCI12Wheelchair0.3224487995.6192.40
iSCI13Wheelchair0.43166168157.8549.25
iSCI14Wheelchair0.34241203547.5937.70

6MW = 6 Minute Walk Test, MVT = Maximum Voluntary Torque

Table 3

Individual Participant Data – Leg Muscle Measures

Participant #Primary AmbulationWeaker Leg MFI Average %Stronger Leg MFI Average %Weaker Leg rmCSA (mm2)Stronger Leg rmCSA (mm2)Weaker Plantarflexor rmCSA (mm2)Stronger Plantarflexor rmCSA (mm2)
iSCI1Wheelchair15.7720.493419.243316.512427.902374.22
iSCI2Walk with AD10.5510.185474.115645.743777.804530.76
iSCI3Walk with AD16.4018.593638.033479.532796.452646.78
iSCI4Walk with AD14.7613.503416.863740.002135.722631.87
iSCI5Walk18.1711.494199.985798.232766.604377.08
iSCI6Walk17.1215.774967.275167.293638.703856.84
iSCI7Wheelchair14.8514.564547.625437.893488.804328.72
iSCI8Wheelchair15.5915.173493.283595.582298.982480.93
iSCI9Walk8.277.384312.884260.173127.483136.14
iSCI10Walk with AD9.4414.664095.982848.333035.902217.98
iSCI11Wheelchair15.0515.683015.632858.922244.922099.31
iSCI12Wheelchair19.5721.474860.934437.773673.203266.37
iSCI13Wheelchair41.2326.983751.463837.912740.812443.50
iSCI14Wheelchair20.0819.094037.513725.693077.572692.69

6MW = 6 Minute Walk Test, MFI = Muscle Fat Infiltration, rmCSA = relative muscle cross-sectional area

Spinal Cord Imaging

The damage ratio measurement showed high inter-rater (ICC 2,1 = 0.82) and high intra-rater reliability (ICC 2,1 = 0.92). Damage ratios were negatively correlated with distance walked in 6 minutes (R = −0.72, P < 0.01, see Figure 2a), average daily strides (R = −0.74, P < 0.01, see Figure 2b), and isometric plantarflexion MVT (R = −0.61, P = 0.02, see Figure 2c). Damage ratios were also negatively correlated with the Walking Index for Spinal Cord Injury II scores (Spearman’s rho = −0.70, P < 0.01). A non-significant negative linear trend was found between damage ratios and lower leg rmCSA (R = −0.50, P = 0.06). Damage ratios were not significantly correlated with MFI (R = 0.30, P = 0.31).
Figure 2

Damage ratios versus meters walked in 6 minutes (2A), average daily strides (2B), and isometric plantarflexion maximum voluntary torque (2C). Significant negative linear correlations were found (R = −0.72, P < 0.01; R= −0.74, P < 0.01; R = −0.61, P = 0.02; respectively). Wheelchair user participants are identified as circular data points, while community ambulator participants are identified as triangular data points.

Isometric plantarflexion MVT was significantly positively correlated with plantarflexor rmCSA (R = 0.53, P < 0.01). This relationship held when the weaker sided MVT was correlated with the weaker plantarflexor rmCSA (R = 0.55, P = 0.04) and when the stronger sided MVT was correlated with the stronger sided plantarflexor rmCSA (R = 0.54, P = 0.04). The wheelchair user participant group had significantly elevated lower extremity MFI compared to the community walker group (F = 17.62, df = 1, P < 0.01, mean difference = 6.38, see Figure 3c). The peroneous longus had higher MFI compared to the tibialis anterior (F = 3.91, df = 3, mean difference = 6.93, P = 0.01), otherwise there were no significant differences between the other muscle groups. There were no significant interaction effects. There were no significant differences in leg rmCSA between groups (mean difference = 958 mm2, P = 0.28).
Figure 3

Cross-sectional fat-saturated images of the leg muscles in a representative wheelchair user participant (3A) and a representative community walker participant (3B). Outlines delineate major leg muscle groups (blue: gastrocnemius, red: soleus, yellow: tibialis anterior, green: peroneus longus). (3C) A significant difference in MFI was found between groups (P < 0.01). Error bars denote standard error of mean.

Discussion

This study demonstrated a negative correlation between damaged cord ratios and both walking ability and plantarflexion torque output in participants with iSCI. These findings suggest that axial spinal cord damage ratios on high resolution T2-weighted MRI may be useful in predicting recovery of walking ability early after spinal cord injury. However, important questions must be addressed. How soon following injury can the extent of the spinal cord edema be used in such a predictive model? Evidence from canine and murine weight-drop contusion models of SCI found a 2-week time point for the initial formation of a fluid-filled cavity and a 4-week time point for completed edema formation.[37] Human work into SCI found that spinal cord edema was visualized using sagittal T2-weighted MRI within approximately 3–4 days post injury.[17] Previous literature evinced the length of the spinal cord edema on T2-weighted MRI was related to neurological status tested using ASIA and Frankel classifications.[13,38,39] One study showed that edema length was negatively linearly correlated with the Functional Independence Measure (FIM) locomotor score (R = −0.22) and with the FIM motor scale (R = −0.36) upon discharge.[24] Using advanced but available spinal cord fiber tractography (FT), a positive correlation was reported between FT parameters and upper extremity motor scores post SCI (Spearman’s rho range = 0.648 – 0.794).[40] For a secondary analysis of our data, focusing on our clinical measures, we found that damage ratios were significantly negatively correlated with FIM locomotor scores (Spearman’s rho = −0.62, P = 0.02), ASIA lower extremity motor scores (Spearman’s rho = −0.72, P < 0.01), and the Walking Index for Spinal Cord Injury II (Spearman’s rho = −0.70, P < 0.01). See Table 4 for individual clinical measures.
Table 4

Individual Participant Data – FIM Locomotor, ASIA LEMS, and WISCI II Scores

Participant #Primary AmbulationDamage RatioFIM Locomotor(out of 7)WISCI II(out of 20)ASIA LEMS Left (out of 25)ASIA LEMS Right (out of 25)
iSCI1Wheelchair0.295131514
iSCI2Walk with AD0.206162419
iSCI3Walk with AD0.396151923
iSCI4Walk with AD0.356192414
iSCI5Walk0.327202520
iSCI6Walk0.107202325
iSCI7Wheelchair0.4726198
iSCI8Wheelchair0.5716810
iSCI9Walk0.177202522
iSCI10Walk with AD0.496161614
iSCI11Wheelchair0.39692310
iSCI12Wheelchair0.326192315
iSCI13Wheelchair0.436131922
iSCI14Wheelchair0.346151724

FIM = Functional Independence Measure, WISCI = Walking Index for Spinal Cord Injury, ASIA LEMS = American Spinal Cord Injury Association Lower Extremity Motor Scores

Additionally, we observed a negative linear trend between damage ratios and leg rmCSA, and found that rmCSA was significantly correlated with ability to generate plantarflexion torque. These findings are in accordance with previous research reporting decreased lower extremity CSA[5] and decreased torque production in iSCI.[4] One surprising finding was that damage ratios were not significantly correlated with lower extremity MFI. Though denervation is one established cause of increased MFI,[41-43] other factors such as physical in-activity,[44] altered metabolic function,[45] and overall weight gain[46] certainly play a role. One theory is that while the spinal cord injury may dictate overall motor function, the amount of muscle fat infiltration may be more related to the post-injury physical activity levels on a patient-by-patient basis. Indeed, when our participants were sub-grouped into wheelchair users versus community walkers, a significant lower extremity MFI difference was found. This finding is in-line with previous research where patients with iSCI had significantly higher lower extremity MFI than able-bodied matched controls.[10]

Future Direction

Using qualitative MRI parameters (i.e. presence/absence of edema) along with clinical metrics, researchers used a multiple regression model to create a clinical prediction rule for determining long-term functional outcome following spinal cord injury,[19] reporting an R2 value of 0.52. We believe that our quantitative damage ratio metric may be valuable for a clinical prediction rule of future walking ability. Damage ratios alone yielded an R2 value of 0.52 when correlating with distance walked in 6 minutes. After selecting the 3 most robust variables from our data set, we created a multiple regression equation using damage ratios, ASIA lower extremity motor scores (LEMS), and average plantarflexion MVT to predict average daily strides. With an R2 of 0.77, this type of multiple regression analysis using quantitative MRI parameters may be useful for predicting walking ability following spinal cord injury. While we acknowledge that these data were measured in the chronic state, we believe these strong relationships warrant longitudinal investigation.

Limitations

An inherent limitation of this cross-sectional study remains our inability to provide a cause-and-effect relationship between the amount of spinal cord damage and ambulatory ability. However, once the optimal time-course for axial T2 imaging of spinal cord edema is established, the prognostic value of the cord edema ratio measure towards predicting ambulatory recovery should be further explored.

Conclusion

In this study, we demonstrated that measurement of spinal cord edema using high-resolution axial T2-weighted imaging is possible and that damage ratios were negatively correlated with ambulatory status as well as plantarflexion torque generation in 14 participants with iSCI. The 7 community walkers had significantly lower MFI in their lower extremities compared to the 7 using a wheelchair. A large multi-site investigation is warranted to examine the value of high-resolution axial T2-weighted imaging to predict walking recovery following motor incomplete spinal cord injury.
  45 in total

1.  Influence of complete spinal cord injury on skeletal muscle cross-sectional area within the first 6 months of injury.

Authors:  M J Castro; D F Apple; E A Hillegass; G A Dudley
Journal:  Eur J Appl Physiol Occup Physiol       Date:  1999-09

2.  Potential associations between chronic whiplash and incomplete spinal cord injury.

Authors:  Andrew C Smith; Todd B Parrish; Mark A Hoggarth; Jacob G McPherson; Vicki M Tysseling; Marie Wasielewski; Hyosub E Kim; T George Hornby; James M Elliott
Journal:  Spinal Cord Ser Cases       Date:  2015-10-08

3.  Walking index for spinal cord injury (WISCI): an international multicenter validity and reliability study.

Authors:  J F Ditunno; P L Ditunno; V Graziani; G Scivoletto; M Bernardi; V Castellano; M Marchetti; H Barbeau; H L Frankel; J M D'Andrea Greve; H Y Ko; R Marshall; P Nance
Journal:  Spinal Cord       Date:  2000-04       Impact factor: 2.772

4.  Evaluation of Traumatic Spine by Magnetic Resonance Imaging and Correlation with Neurological Recovery.

Authors:  Sarita Magu; Deepak Singh; Rohtas Kanwar Yadav; Manju Bala
Journal:  Asian Spine J       Date:  2015-09-22

5.  A clinical prediction model for long-term functional outcome after traumatic spinal cord injury based on acute clinical and imaging factors.

Authors:  Jefferson R Wilson; Robert G Grossman; Ralph F Frankowski; Alexander Kiss; Aileen M Davis; Abhaya V Kulkarni; James S Harrop; Bizhan Aarabi; Alexander Vaccaro; Charles H Tator; Marcel Dvorak; Christopher I Shaffrey; Susan Harkema; James D Guest; Michael G Fehlings
Journal:  J Neurotrauma       Date:  2012-07-31       Impact factor: 5.269

Review 6.  Translating state-of-the-art spinal cord MRI techniques to clinical use: A systematic review of clinical studies utilizing DTI, MT, MWF, MRS, and fMRI.

Authors:  Allan R Martin; Izabela Aleksanderek; Julien Cohen-Adad; Zenovia Tarmohamed; Lindsay Tetreault; Nathaniel Smith; David W Cadotte; Adrian Crawley; Howard Ginsberg; David J Mikulis; Michael G Fehlings
Journal:  Neuroimage Clin       Date:  2015-12-04       Impact factor: 4.881

7.  Rapid atrophy of the lumbar multifidus follows experimental disc or nerve root injury.

Authors:  Paul Hodges; Allison Kaigle Holm; Tommy Hansson; Sten Holm
Journal:  Spine (Phila Pa 1976)       Date:  2006-12-01       Impact factor: 3.468

Review 8.  Spinal and supraspinal factors in human muscle fatigue.

Authors:  S C Gandevia
Journal:  Physiol Rev       Date:  2001-10       Impact factor: 37.312

9.  Diffusion tensor imaging and fiber tractography of patients with cervical spinal cord injury.

Authors:  Yongmin Chang; Tae-Du Jung; Dong Soo Yoo; Jung Keun Hyun
Journal:  J Neurotrauma       Date:  2010-11       Impact factor: 5.269

10.  Independent spinal cord atrophy measures correlate to motor and sensory deficits in individuals with spinal cord injury.

Authors:  H Lundell; D Barthelemy; A Skimminge; T B Dyrby; F Biering-Sørensen; J B Nielsen
Journal:  Spinal Cord       Date:  2010-08-10       Impact factor: 2.772

View more
  9 in total

1.  The Relationship Between Volitional Activation and Muscle Properties in Incomplete Spinal Cord Injury.

Authors:  Kristen L Jakubowski; Andrew C Smith; James M Elliott; Sabrina S M Lee
Journal:  Top Spinal Cord Inj Rehabil       Date:  2017-09-27

2.  Midsagittal tissue bridges are associated with walking ability in incomplete spinal cord injury: A magnetic resonance imaging case series.

Authors:  Denise R O'Dell; Kenneth A Weber; Jeffrey C Berliner; James M Elliott; Jordan R Connor; David P Cummins; Katherine A Heller; Joshua S Hubert; Megan J Kates; Katarina R Mendoza; Andrew C Smith
Journal:  J Spinal Cord Med       Date:  2018-10-22       Impact factor: 1.985

3.  Lateral Corticospinal Tract Damage Correlates With Motor Output in Incomplete Spinal Cord Injury.

Authors:  Andrew C Smith; Kenneth A Weber; Denise R O'Dell; Todd B Parrish; Marie Wasielewski; James M Elliott
Journal:  Arch Phys Med Rehabil       Date:  2017-10-26       Impact factor: 3.966

4.  Short- and long-term reproducibility of diffusion-weighted magnetic resonance imaging of lower extremity musculature in asymptomatic individuals and a comparison to individuals with spinal cord injury.

Authors:  Jacob G McPherson; Andrew C Smith; Daniel A Duben; Katie L McMahon; Marie Wasielewski; Todd B Parrish; James M Elliott
Journal:  BMC Musculoskelet Disord       Date:  2018-12-06       Impact factor: 2.362

5.  Deep Learning Convolutional Neural Networks for the Automatic Quantification of Muscle Fat Infiltration Following Whiplash Injury.

Authors:  Kenneth A Weber; Andrew C Smith; Marie Wasielewski; Kamran Eghtesad; Pranav A Upadhyayula; Max Wintermark; Trevor J Hastie; Todd B Parrish; Sean Mackey; James M Elliott
Journal:  Sci Rep       Date:  2019-05-28       Impact factor: 4.379

6.  Establishing the inter-rater reliability of spinal cord damage manual measurement using magnetic resonance imaging.

Authors:  David P Cummins; Jordan R Connor; Katherine A Heller; Joshua S Hubert; Megan J Kates; Katarina R Wisniewski; Jeffrey C Berliner; Denise R O'Dell; James M Elliott; Kenneth A Weber; Andrew C Smith
Journal:  Spinal Cord Ser Cases       Date:  2019-02-18

7.  The relation between local and distal muscle fat infiltration in chronic whiplash using magnetic resonance imaging.

Authors:  Anette Karlsson; Anneli Peolsson; James Elliott; Thobias Romu; Helena Ljunggren; Magnus Borga; Olof Dahlqvist Leinhard
Journal:  PLoS One       Date:  2019-12-05       Impact factor: 3.240

8.  Lateral Corticospinal Tract and Dorsal Column Damage: Predictive Relationships With Motor and Sensory Scores at Discharge From Acute Rehabilitation After Spinal Cord Injury.

Authors:  Andrew C Smith; Denise R O'Dell; Stephanie R Albin; Jeffrey C Berliner; David Dungan; Eli Robinson; James M Elliott; Julio Carballido-Gamio; Jennifer Stevens-Lapsley; Kenneth A Weber
Journal:  Arch Phys Med Rehabil       Date:  2021-08-08       Impact factor: 3.966

9.  Spinal Cord Imaging Markers and Recovery of Volitional Leg Movement With Spinal Cord Epidural Stimulation in Individuals With Clinically Motor Complete Spinal Cord Injury.

Authors:  Enrico Rejc; Andrew C Smith; Kenneth A Weber; Beatrice Ugiliweneza; Robert J Bert; Mohammadjavad Negahdar; Maxwell Boakye; Susan J Harkema; Claudia A Angeli
Journal:  Front Syst Neurosci       Date:  2020-10-21
  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.