Retrograde Wallerian degeneration of cranial corticospinal tracts in cervical spinal cord injury patients using diffusion tensor imaging

2008 ◽  
Vol 86 (10) ◽  
pp. 2271-2280 ◽  
Author(s):  
Saurabh Guleria ◽  
Rakesh K. Gupta ◽  
Sona Saksena ◽  
Anil Chandra ◽  
R.N. Srivastava ◽  
...  
Keyword(s):  
Spinal Cord ◽  
Spinal Cord Injury ◽  
Diffusion Tensor Imaging ◽  
Wallerian Degeneration ◽  
Diffusion Tensor ◽  
Cervical Spinal Cord ◽  
Cervical Spinal Cord Injury ◽  
Corticospinal Tracts ◽  
Cord Injury

scholarly journals Diagnostic accuracy of diffusion tensor imaging for pediatric cervical spinal cord injury

Spinal Cord ◽  
2013 ◽  
Vol 51 (7) ◽  
pp. 532-537 ◽  
Author(s):  
M J Mulcahey ◽  
A F Samdani ◽  
J P Gaughan ◽  
N Barakat ◽  
S Faro ◽  
...  
Keyword(s):  
Spinal Cord ◽  
Spinal Cord Injury ◽  
Diffusion Tensor Imaging ◽  
Diagnostic Accuracy ◽  
Diffusion Tensor ◽  
Cervical Spinal Cord ◽  
Cervical Spinal Cord Injury ◽  
Cord Injury

Cervical spinal cord injury assessment based on diffusion tensor imaging

2016 ◽  
Vol 16 (4) ◽  
pp. S87
Author(s):  
Marcin Czyz ◽  
Pawel Szewczyk ◽  
Wai Yoon ◽  
Włodzimierz Jarmundowicz ◽  
Bronek M. Boszczyk
Keyword(s):  
Spinal Cord ◽  
Spinal Cord Injury ◽  
Diffusion Tensor Imaging ◽  
Diffusion Tensor ◽  
Cervical Spinal Cord ◽  
Cervical Spinal Cord Injury ◽  
Cord Injury ◽  
Injury Assessment

scholarly journals Segmented quantitative diffusion tensor imaging evaluation of acute traumatic cervical spinal cord injury

2020 ◽  
pp. 20201000
Author(s):  
Mahmud Mossa-Basha ◽  
Daniel J Peterson ◽  
Daniel S Hippe ◽  
Justin E Vranic ◽  
Christoph Hofstetter ◽  
...  
Keyword(s):  
Spinal Cord ◽  
Spinal Cord Injury ◽  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Diffusion Tensor ◽  
Cervical Spinal Cord ◽  
Cervical Spinal Cord Injury ◽  
Cord Injury ◽  
Motor Tracts ◽  
Normal Controls

Objectives: To evaluate segmented diffusion tensor imaging (DTI) white matter tract fractional anisotropy (FA) and mean diffusivity (MD) values in acute cervical spinal cord injury (CSCI). Methods: 15 patients with acute CSCI and 12 control subjects were prospectively recruited and underwent axial DTI as part of the spine trauma MRI. Datasets were put through a semi-automated probabilistic segmentation algorithm that analyzed white matter, motor and sensory tracts. FA and MD values were calculated for white matter, sensory (spinal lemniscal) and motor tracts (ventral/lateral corticospinal) at the level of clinical injury, levels remote from injury and in normal controls. Results: There were significant differences in FA between the level of injury and controls for total white matter (0.65 ± .09 vs 0.68 ± .07; p = .044), motor tracts (0.64 ± .07 vs 0.7 ± .09; p = .006), and combined motor/sensory tracts (0.63 ± .09 vs 0.69 ± .08; p = .022). In addition, there were significant FA differences between the level of injury and one level caudal to the injury for combined motor tracts (0.64 ± .07 vs 0.69 ± .05; p = .002) and combined motor/sensory tracts (0.63 ± .09 vs 0.7 ± .07; p = .011). There were no significant differences for MD between the level of injury and one level caudal to the injury or normal controls. Conclusion: Abnormalities in DTI metrics of DTI-segmented white matter tracts were detected at the neurological level of injury relative to normal controls and levels remote from the injury site, confirming its value in CSCI assessment. Advances in knowledge: Segmented DTI analysis can help identify microstructural spinal cord abnormalities in the setting of traumatic cervical spinal cord injury.

Application of Diffusion Tensor Imaging in Forecasting Neurological Injury and Recovery after Human Cervical Spinal Cord Injury

2019 ◽  
Vol 36 (21) ◽  
pp. 3051-3061 ◽  
Author(s):  
Michael M. Poplawski ◽  
Mahdi Alizadeh ◽  
Christina V. Oleson ◽  
Joshua Fisher ◽  
Ralph J. Marino ◽  
...  
Keyword(s):  
Spinal Cord ◽  
Spinal Cord Injury ◽  
Diffusion Tensor Imaging ◽  
Diffusion Tensor ◽  
Cervical Spinal Cord ◽  
Cervical Spinal Cord Injury ◽  
Neurological Injury ◽  
Cord Injury

scholarly journals Reduced FOV diffusion tensor MR imaging and fiber tractography of pediatric cervical spinal cord injury

Spinal Cord ◽  
2016 ◽  
Vol 55 (3) ◽  
pp. 314-320 ◽  
Author(s):  
M Alizadeh ◽  
A Intintolo ◽  
D M Middleton ◽  
C J Conklin ◽  
S H Faro ◽  
...  
Keyword(s):  
Spinal Cord ◽  
Spinal Cord Injury ◽  
Mr Imaging ◽  
Diffusion Tensor ◽  
Cervical Spinal Cord ◽  
Cervical Spinal Cord Injury ◽  
Fiber Tractography ◽  
Cord Injury ◽  
Diffusion Tensor Mr Imaging

scholarly journals An Inertial Measurement Unit-Based Wireless System for Shoulder Motion Assessment in Patients with Cervical Spinal Cord Injury: A Validation Pilot Study in a Clinical Setting

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1057
Author(s):  
Riccardo Bravi ◽  
Stefano Caputo ◽  
Sara Jayousi ◽  
Alessio Martinelli ◽  
Lorenzo Biotti ◽  
...  
Keyword(s):  
Spinal Cord ◽  
Spinal Cord Injury ◽  
Clinical Setting ◽  
Cervical Spinal Cord ◽  
Wearable Sensors ◽  
Cervical Spinal Cord Injury ◽  
Measurement Unit ◽  
Innovative Technology ◽  
Inertial Measurement ◽  
Cord Injury

Residual motion of upper limbs in individuals who experienced cervical spinal cord injury (CSCI) is vital to achieve functional independence. Several interventions were developed to restore shoulder range of motion (ROM) in CSCI patients. However, shoulder ROM assessment in clinical practice is commonly limited to use of a simple goniometer. Conventional goniometric measurements are operator-dependent and require significant time and effort. Therefore, innovative technology for supporting medical personnel in objectively and reliably measuring the efficacy of treatments for shoulder ROM in CSCI patients would be extremely desirable. This study evaluated the validity of a customized wireless wearable sensors (Inertial Measurement Units—IMUs) system for shoulder ROM assessment in CSCI patients in clinical setting. Eight CSCI patients and eight healthy controls performed four shoulder movements (forward flexion, abduction, and internal and external rotation) with dominant arm. Every movement was evaluated with a goniometer by different testers and with the IMU system at the same time. Validity was evaluated by comparing IMUs and goniometer measurements using Intraclass Correlation Coefficient (ICC) and Limits of Agreement (LOA). inter-tester reliability of IMUs and goniometer measurements was also investigated. Preliminary results provide essential information on the accuracy of the proposed wireless wearable sensors system in acquiring objective measurements of the shoulder movements in CSCI patients.

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