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Chernysh AA, Loftus DH, Zheng B, Arditi J, Leary OP, Fridley JS. Utility of Diffusion Tensor Imaging for Prognosis and Management of Cervical Spondylotic Myelopathy: A PRISMA Review. World Neurosurg 2024; 190:88-98. [PMID: 38986943 DOI: 10.1016/j.wneu.2024.07.032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Revised: 07/02/2024] [Accepted: 07/03/2024] [Indexed: 07/12/2024]
Abstract
OBJECTIVE As advances are made in quantitative magnetic resonance imaging, specifically diffusion tensor imaging, researchers have investigated its potential to serve as a biomarker of disease or prognosticator for postoperative recovery in the management of cervical spondylotic myelopathy. Here, we narratively review the current state of the emerging literature, describing areas of consensus and disagreement. METHODS In accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses, we queried 2 large databases for original manuscripts published in English and systematically produced a narrative review of the use of diffusion tensor imaging in the management of cervical spondylotic myelopathy. RESULTS Of the 437 manuscripts initially returned in our query, 29 met the final inclusion criteria, and data were extracted regarding diffusion tensor imaging indices and their relationships with clinical outcomes following surgery. Preoperative fractional anisotropy was most commonly found to correlate closely with postsurgical clinical outcomes, though results were mixed. CONCLUSIONS Preoperative fractional anisotropy most frequently and best correlates with functional outcomes following surgery for cervical spondylotic myelopathy, according to a review of the current literature. The findings were not universal and at times contradictory, highlighting the need for high-quality future investigations to better define the utility of diffusion tensor imaging in spinal disease.
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Affiliation(s)
- Alexander A Chernysh
- Warren Alpert Medical School of Brown University, Rhode Island Hospital, Department of Neurosurgery, Providence, Rhode Island, USA.
| | - David H Loftus
- Warren Alpert Medical School of Brown University, Rhode Island Hospital, Department of Neurosurgery, Providence, Rhode Island, USA
| | - Bryan Zheng
- Warren Alpert Medical School of Brown University, Rhode Island Hospital, Department of Neurosurgery, Providence, Rhode Island, USA
| | - Jonathan Arditi
- Warren Alpert Medical School of Brown University, Rhode Island Hospital, Department of Neurosurgery, Providence, Rhode Island, USA
| | - Owen P Leary
- Warren Alpert Medical School of Brown University, Rhode Island Hospital, Department of Neurosurgery, Providence, Rhode Island, USA
| | - Jared S Fridley
- Warren Alpert Medical School of Brown University, Rhode Island Hospital, Department of Neurosurgery, Providence, Rhode Island, USA
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Scullen T, Milburn J, Aria K, Mathkour M, Tubbs RS, Kalyvas J. The use of diffusion tensor imaging in spinal pathology: a comprehensive literature review. EUROPEAN SPINE JOURNAL : OFFICIAL PUBLICATION OF THE EUROPEAN SPINE SOCIETY, THE EUROPEAN SPINAL DEFORMITY SOCIETY, AND THE EUROPEAN SECTION OF THE CERVICAL SPINE RESEARCH SOCIETY 2024:10.1007/s00586-024-08231-8. [PMID: 39014075 DOI: 10.1007/s00586-024-08231-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/14/2023] [Revised: 05/14/2023] [Accepted: 09/23/2023] [Indexed: 07/18/2024]
Abstract
STUDY DESIGN We reviewed the available literature systematically without meta-analysis following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. OBJECTIVE To evaluate contemporary literature on use of spinal diffusion tensor imaging(sDTI) in spinal pathology. BACKGROUND sDTI reveals the location and functional state of critical long tracts and is a potentially useful adjunct in disease management. METHODS Studies were included if they presented or discussed data from investigative or therapeutic procedures involving sDTI on human subjects in the setting of surgically amenable spinal pathology. Studies were excluded if they were (1) restricted to computational models investigating parameters using data not obtained clinically, (2) about cranial DTI methods, (3) about spinal pathology data not related to surgical management, (4) discussions or overviews of methods/techniques with minimal inclusion of objective experimental or clinical data. RESULTS Degenerative pathologies of interest were restricted to either cervical myelopathy (22/29,75.9%) or lumbar spondylosis 7/29,24.1%). Mass-occupying lesions included intradural pathology and discussed preoperative (7/9,77.8%) and intraoperative imaging(2/9,22.2%) as an adjunct to surgery 22.2%. Traumatic pathology focused on spinal cord injury prognosis and severity grading. CONCLUSIONS sDTI seems useful in surgical decision making and outcome measurements and in establishing clinical prognoses over a wide range of surgical pathologies. Further research is warranted with longer follow-up and larger population sizes in a prospective and controlled protocol.
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Affiliation(s)
- Tyler Scullen
- Department of Neurological Surgery, Ochsner Clinic Foundation, 1514 Jefferson Hwy, Jefferson, LA, 70112, USA.
- Department of Neurological Surgery, Tulane University School of Medicine, New Orleans, LA, 70114, USA.
| | - James Milburn
- Department of Radiology, Ochsner Clinic Foundation, Jefferson, LA, 70121, USA
| | - Kevin Aria
- Department of Neurological Surgery, Ochsner Clinic Foundation, 1514 Jefferson Hwy, Jefferson, LA, 70112, USA
- Department of Neurological Surgery, Tulane University School of Medicine, New Orleans, LA, 70114, USA
| | - Mansour Mathkour
- Department of Neurological Surgery, Ochsner Clinic Foundation, 1514 Jefferson Hwy, Jefferson, LA, 70112, USA
- Department of Neurological Surgery, Tulane University School of Medicine, New Orleans, LA, 70114, USA
| | - R Shane Tubbs
- Department of Neurological Surgery, Tulane University School of Medicine, New Orleans, LA, 70114, USA
| | - James Kalyvas
- Department of Neurological Surgery, Ochsner Clinic Foundation, 1514 Jefferson Hwy, Jefferson, LA, 70112, USA
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Mohammadi M, Roohollahi F, Mahmoudi MM, Mohammadi A, Mohamadi M, Kankam SB, Ghamari Khameneh A, Baghdasaryan D, Farahbakhsh F, Martin AR, Harrop J, Rahimi-Movaghar V. Correlation Between Pre-Operative Diffusion Tensor Imaging Indices and Post-Operative Outcome in Degenerative Cervical Myelopathy: A Systematic Review and Meta-Analysis. Global Spine J 2024; 14:1800-1817. [PMID: 38168663 PMCID: PMC11268306 DOI: 10.1177/21925682231225634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/05/2024] Open
Abstract
STUDY DESIGN Systematic review. OBJECTIVES The correlation between pre-operative diffusion tensor imaging (DTI) metrics and post-operative clinical outcomes in patients with degenerative cervical myelopathy (DCM) has been widely investigated with different studies reporting varied findings. We conducted a systematic review to determine the association between DTI metric and clinical outcomes after surgery. METHODS We identified relevant articles that investigated the relationship between pre-operative DTI indices and post-operative outcome in DCM patients by searching PubMed/MEDLINE, Web of Science, Scopus, and EMBASE from inception until October 2023. In addition, quantitative synthesis and meta-analyses were performed. RESULTS FA was significantly correlated with postoperative JOA or mJOA across all age and follow up subgroups, changes observed in JOA or mJOA from preoperative to postoperative stages (Δ JOA or Δ mJOA) in subgroups aged 65 and above and in those with a follow-up period of 6 months or more, as well as recovery rate in all studies pooled together and also in the under-65 age bracket. Additionally, a significant correlation was demonstrated between recovery rate and ADC across all age groups. No other significant correlations were discovered between DTI parameters (MD, AD, and ADC) and post-operative outcomes. CONCLUSION DTI is a quantitative noninvasive evaluation tool that correlates with severity of DCM. However, the current evidence is still elusive regarding whether DTI metric is a validated tool for predicting the degree of post-operative recovery, which could potentially be useful in patient selection for surgery.
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Affiliation(s)
| | - Faramarz Roohollahi
- Sports Medicine Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
- Yas Spine Center of Excellence, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohamad Mahdi Mahmoudi
- Department of General Surgery, Shahid Mofateh Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Aynaz Mohammadi
- School of Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Mobin Mohamadi
- School of Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Samuel Berchi Kankam
- Image guided Neurosurgery Lab, Department of Neurosurgery, Brigham and Women Hospital, Harvard Medical School, Boston, MA, USA
- Brain Trauma Lab, Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Afshar Ghamari Khameneh
- Department of Radiology, Advanced Diagnostic and Interventional Radiology (ADIR) Research Center, Imam Khomeini Hospital Complex, Tehran University of Medical Sciences, Tehran, Iran
| | | | - Farzin Farahbakhsh
- Sina Trauma and Surgery Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Allan R. Martin
- Department of Neurosurgery, University of California Davis, Davis, CA, USA
| | - James Harrop
- Department of Neurological and Orthopedic Surgery, Thomas Jefferson University, Philadelphia, PA, USA
| | - Vafa Rahimi-Movaghar
- Sina Trauma and Surgery Research Center, Tehran University of Medical Sciences, Tehran, Iran
- Brain and Spinal Cord Injury Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
- Department of Neurosurgery, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran
- Universal Scientific Education and Research Network (USERN), Tehran, Iran
- Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran
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Mohammadi M, Roohollahi F, Farahbakhsh F, Mohammadi A, Mortazavi Mamaghani E, Kankam SB, Moarrefdezfouli A, Ghamari Khameneh A, Mahmoudi MM, Baghdasaryan D, Martin AR, Harrop J, Rahimi-Movaghar V. Diffusion Tensor Imaging in Diagnosing and Evaluating Degenerative Cervical Myelopathy: A Systematic Review and Meta-Analysis. Global Spine J 2024:21925682241263792. [PMID: 38877604 PMCID: PMC11572101 DOI: 10.1177/21925682241263792] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/16/2024] Open
Abstract
STUDY DESIGN Systematic review. OBJECTIVE Degenerative cervical myelopathy (DCM) is a common spinal cord disorder necessitating surgery. We aim to explore how effectively diffusion tensor imaging (DTI) can distinguish DCM from healthy individuals and assess the relationship between DTI metrics and symptom severity. METHODS We included studies with adult DCM patients who had not undergone decompressive surgery and implemented correlation analyses between DTI parameters and severity, or compared healthy controls and DCM patients. RESULTS 57 studies were included in our meta-analysis. At the maximal compression (MC) level, fractional anisotropy (FA) exhibited lower values in DCM patients, while apparent diffusion coefficient (ADC), mean diffusivity (MD), and radial diffusivity (RD) were notably higher in the DCM group. Moreover, our investigation into the diagnostic utility of DTI parameters disclosed high sensitivity, specificity, and area under the curve values for FA (.84, .80, .83 respectively) and ADC (.74, .84, .88 respectively). Additionally, we explored the correlation between DTI parameters and myelopathy severity, revealing a significant correlation of FA (.53, 95% CI:0.40 to .65) at MC level with JOA/mJOA scores. CONCLUSION Current guidelines for DCM suggest decompressive surgery for both mild and severe cases. However, they lack clear recommendations on which mild DCM patients might benefit from conservative treatment vs immediate surgery. ADC's role here could be pivotal, potentially differentiating between healthy individuals and DCM. While it may not correlate with symptom severity, it might predict surgical outcomes, making it a valuable imaging biomarker for clearer management decisions in mild DCM.
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Affiliation(s)
| | - Faramarz Roohollahi
- Sports Medicine Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
- Yas Spine Center of Excellence, Tehran University of Medical Sciences, Tehran, Iran
| | - Farzin Farahbakhsh
- Sina Trauma and Surgery Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Aynaz Mohammadi
- School of Medicine, Iran University of Medical Sciences, Tehran, Iran
| | | | - Samuel Berchi Kankam
- Image guided Neurosurgery Lab, Department of Neurosurgery, Brigham and Women Hospital, Harvard Medical School, Boston, MA, USA
- Brain Trauma Lab, Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Azin Moarrefdezfouli
- Sina Trauma and Surgery Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Afshar Ghamari Khameneh
- Department of Radiology, Advanced Diagnostic and Interventional Radiology (ADIR) Research Center, Imam Khomeini Hospital Complex, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohamad Mahdi Mahmoudi
- Department of General Surgery, Shahid Mofateh Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | | | - Allan R. Martin
- Department of Neurosurgery, University of California Davis, Davis, CA, USA
| | - James Harrop
- Department of Neurological and Orthopedic Surgery, Thomas Jefferson University, Philadelphia, PA, USA
| | - Vafa Rahimi-Movaghar
- Sina Trauma and Surgery Research Center, Tehran University of Medical Sciences, Tehran, Iran
- Brain and Spinal Cord Injury Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
- Department of Neurosurgery, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran
- Universal Scientific Education and Research Network (USERN), Tehran, Iran
- Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran
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Talbott JF, Shah V, Ye AQ. Diffusion Imaging of the Spinal Cord: Clinical Applications. Radiol Clin North Am 2024; 62:273-285. [PMID: 38272620 DOI: 10.1016/j.rcl.2023.10.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2024]
Abstract
Spinal cord pathologic condition often presents as a neurologic emergency where timely and accurate diagnosis is critical to expedite appropriate treatment and minimize severe morbidity and even mortality. MR imaging is the gold standard imaging technique for diagnosing patients with suspected spinal cord pathologic condition. This review will focus on the basic principles of diffusion imaging and how spinal anatomy presents technical challenges to its application. Both the promises and shortcomings of spinal diffusion imaging will then be explored in the context of several clinical spinal cord pathologies for which diffusion has been evaluated.
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Affiliation(s)
- Jason F Talbott
- Department of Radiology and Biomedical Imaging, Zuckerberg San Francisco General Hospital and Trauma Center, 1001 Potrero Avenue, Room 1X57, San Francisco, CA 94110, USA; Brain and Spinal Injury Center, Zuckerberg San Francisco General Hospital.
| | - Vinil Shah
- Department of Radiology and Biomedical Imaging, Neuroradiology Division, University of California San Francisco, 505 Parnassus Avenue, #M-391, San Francisco, CA 94143, USA
| | - Allen Q Ye
- Department of Radiology and Biomedical Imaging, Zuckerberg San Francisco General Hospital and Trauma Center, 1001 Potrero Avenue, Room 1X57, San Francisco, CA 94110, USA; Department of Radiology and Biomedical Imaging, Neuroradiology Division, University of California San Francisco, 505 Parnassus Avenue, #M-391, San Francisco, CA 94143, USA
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Boerger TF, McGinn L, Bellman M, Wang MC, Schmit BD, Hyngstrom AS. People with degenerative cervical myelopathy have impaired reactive balance during walking. Gait Posture 2024; 109:303-310. [PMID: 38412683 PMCID: PMC11181995 DOI: 10.1016/j.gaitpost.2024.02.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 01/30/2024] [Accepted: 02/19/2024] [Indexed: 02/29/2024]
Abstract
BACKGROUND People with degenerative cervical myelopathy are known to have impaired standing balance and walking abilities, but less is known about balance responses during walking. RESEARCH QUESTION The aim of this project was to assess reactive balance impairments during walking in people with degenerative cervical myelopathy (PwDCM). We hypothesized that center of mass motion following perturbations would be larger in PwDCM and gluteus medius electromyographic amplitude responses would be decreased in PwDCM. METHODS Reactive balance responses were quantified during unanticipated lateral pulls to the waist while treadmill walking. Walking biomechanics data were collected from 10 PwDCM (F=6) and 10 non-myelopathic controls (F=7) using an 8 camera Vicon System (Vicon MX T-Series). Electromyography was collected from lower limb muscles. Participants walked on an instrumented treadmill and received lateral pulls at random intervals and in randomized direction at 5% and 2.5% body mass. Participants walked at 3 prescribed foot placements to control for effects of the size of base of support. RESULTS As compared with controls, the perturbation-related positional change of the center of mass motion (ΔCOM) was increased in PwDCM (p=0.001) with similar changes in foot placement (p>0.05). Change in gluteus medius electromyography, however, was less in PwDCM than in controls (p<0.001). SIGNIFICANCE After experimentally controlling step width, people with mild-to-moderate degenerative cervical myelopathy at least 3 months following cervical spine surgery have impaired reactive balance during walking likely coupled with reduced gluteus medius electromyographic responses. Rehabilitation programs focusing on reactive balance and power are likely necessary for this population.
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Affiliation(s)
| | - Learon McGinn
- Department of Physical Therapy, Marquette University, USA
| | - Megan Bellman
- Department of Neurosurgery, Medical College of Wisconsin, USA
| | - Marjorie C Wang
- Department of Neurosurgery, Medical College of Wisconsin, USA
| | - Brian D Schmit
- Department of Biomedical Engineering, Marquette University, USA
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Wang Y, Zhao R, Zhu D, Fu X, Sun F, Cai Y, Ma J, Guo X, Zhang J, Xue Y. Voxel- and tensor-based morphometry with machine learning techniques identifying characteristic brain impairment in patients with cervical spondylotic myelopathy. Front Neurol 2024; 15:1267349. [PMID: 38419699 PMCID: PMC10899699 DOI: 10.3389/fneur.2024.1267349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Accepted: 01/24/2024] [Indexed: 03/02/2024] Open
Abstract
Aim The diagnosis of cervical spondylotic myelopathy (CSM) relies on several methods, including x-rays, computed tomography, and magnetic resonance imaging (MRI). Although MRI is the most useful diagnostic tool, strategies to improve the precise and independent diagnosis of CSM using novel MRI imaging techniques are urgently needed. This study aimed to explore potential brain biomarkers to improve the precise diagnosis of CSM through the combination of voxel-based morphometry (VBM) and tensor-based morphometry (TBM) with machine learning techniques. Methods In this retrospective study, 57 patients with CSM and 57 healthy controls (HCs) were enrolled. The structural changes in the gray matter volume and white matter volume were determined by VBM. Gray and white matter deformations were measured by TBM. The support vector machine (SVM) was used for the classification of CSM patients from HCs based on the structural features of VBM and TBM. Results CSM patients exhibited characteristic structural abnormalities in the sensorimotor, visual, cognitive, and subcortical regions, as well as in the anterior corona radiata and the corpus callosum [P < 0.05, false discovery rate (FDR) corrected]. A multivariate pattern classification analysis revealed that VBM and TBM could successfully identify CSM patients and HCs [classification accuracy: 81.58%, area under the curve (AUC): 0.85; P < 0.005, Bonferroni corrected] through characteristic gray matter and white matter impairments. Conclusion CSM may cause widespread and remote impairments in brain structures. This study provided a valuable reference for developing novel diagnostic strategies to identify CSM.
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Affiliation(s)
- Yang Wang
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China
- Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Rui Zhao
- Department of Orthopedics Surgery, Tianjin Medical University General Hospital, Tianjin, China
| | - Dan Zhu
- Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
- Department of Radiology, Tianjin Medical University General Hospital Airport Hospital, Tianjin, China
| | - Xiuwei Fu
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China
- Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Fengyu Sun
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Yuezeng Cai
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Juanwei Ma
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China
- Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Xing Guo
- Department of Orthopedics Surgery, Tianjin Medical University General Hospital, Tianjin, China
| | - Jing Zhang
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China
- Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Yuan Xue
- Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
- Tianjin Key Laboratory of Spine and Spinal Cord, Tianjin Medical University General Hospital, Tianjin, China
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Costa F, Anania CD, Agrillo U, Roberto A, Claudio B, Simona B, Daniele B, Carlo B, Barbara C, Ardico C, Battista CG, Raffaele DF, Andrea DR, Carlo DV, Mauro D, Vito F, Diego G, Giancarlo G, Corrado I, Claudio I, Michele I, Innocenzi G, Alessandro L, Giancarlo L, Giuseppe M, Ciro M, Rosario M, Vincenzo M, Nicola M, Pierpaolo N, Andrea P, Giovanni P, Federico PP, Armando R, Alessandro R, Rossella R, Stefano R, Sbaffi PF, Teresa S, Enrico T, Matteo V, Zerbi A, Gianluigi Z, Barbanera A. Cervical Spondylotic Myelopathy: From the World Federation of Neurosurgical Societies (WFNS) to the Italian Neurosurgical Society (SINch) Recommendations. Neurospine 2023; 20:415-429. [PMID: 37401060 PMCID: PMC10323338 DOI: 10.14245/ns.2244996.498] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Revised: 01/13/2023] [Accepted: 02/05/2023] [Indexed: 07/05/2023] Open
Abstract
Cervical spondylotic myelopathy (CSM) is a progressively growing pathology to afford by a spinal surgeon due to the aging of the population, associated with better treatment management and the best diagnosis and treatment solutions are greatly discussed. Nowadays that scientific literature is progressively increasing to identify the gold standard in diagnosis and treatment can be very challenging. This is particularly evident in spinal surgery with many different indications not only in different countries but also in the same local reality. In this scenario, many neurosurgical societies works to identify some guideline or recommendations to help spinal surgeons in daily practice. Furthermore, in an era in which legal issues are increasingly present in clinical practice to have some indications globally accepted can be very useful. World Federation of Neurosurgical Societies (WFNS) few years ago starts this process creating a list of recommendations originating from a worldwide steering committee to respect all the local reality. The spinal section of Italian Neurosurgical Society decides to adopt the WFNS recommendations with some revision basing on Italian scenario. The steering committee of the Spinal Section of Italian Neurosurgical Society identify 7 groups to review the literature of the last 10 years about different topics on CSM and to analyses the WFNS recommendations to adapt it to the Italian daily practice. The statements were discussed and voted in 2 sessions to obtain the final version. A list of recommendations on natural course and clinical presentation; diagnostic tests; conservative and surgical treatment; anterior, posterior and combined surgical treatment; role of neurophysiological monitoring and follow-up and outcome was created with only few new or revised statements respect the ones of WFNS. The Spine Section of Italian Neurosurgical Society create a list of recommendations that represent the more contemporary treatment concepts for CSM as presented in the highest quality clinical literature and best clinical practices available on this subject.
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Affiliation(s)
- Francesco Costa
- Spine Surgery Unit, Department of Neurosurgery, Fondazione IRCCS Istituto Nazionale Neurologico C. Besta, Milan, Italy
| | | | | | - Assietti Roberto
- Unit of Neurosurgery, Azienda Socio Sanitaria Territoriale Fatebenefratelli Sacco, Fatebenefratelli Hospital, Milan, Italy
| | - Bernucci Claudio
- Department of Neurosurgery, ASST Papa Giovanni XXIII Hospital, Bergamo, Italy
| | | | - Bongetta Daniele
- Unit of Neurosurgery, Azienda Socio Sanitaria Territoriale Fatebenefratelli Sacco, Fatebenefratelli Hospital, Milan, Italy
| | - Brembilla Carlo
- Department of Neurosurgery, ASST Papa Giovanni XXIII Hospital, Bergamo, Italy
| | - Cappelletto Barbara
- Section of Spine and Spinal Cord Surgery, Department of Neurological Sciences, ASUFC University Hospital of Udine, Udine, Italy
| | - Cocciaro Ardico
- Department of Neurosurgery, Azienda Ospedaliera Universitaria Pisana (AUOP), University of Pisa, Pisa, Italy
| | | | - De Falco Raffaele
- Department of Neurosurgery, P.O. Santa Maria delle Grazie, Pozzuoli (NA), Italy
| | - De Rosa Andrea
- Division of Neurosurgery, Department of Neurosciences, Reproductive and Odontostomatological Sciences, Università degli Studi di Napoli Federico II, Naples, Italy
| | | | - Dobran Mauro
- Department of Neurosurgery, Università Politecnica delle Marche, Azienda Ospedali Riuniti, Ancona, Italy
| | - Fiorenza Vito
- Department of Neurosurgery, A.R.N.A.S. “Civico Di Cristina Benfratelli” Hospital, Palermo, Italy
| | - Garbossa Diego
- Department of Neuroscience “Rita Levi Montalcini”, Neurosurgery Unit, University of Turin, Turin, Italy
| | | | - Iaccarino Corrado
- Division of Neurosurgery, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena University Hospital, Modena, Italy
| | - Irace Claudio
- Department of Neurosurgery, Hospital Igea, Milan, Italy
| | | | | | | | | | - Maida Giuseppe
- Department of Spine Surgery, Multidisciplinary Spine Center, Santa Maria Maddalena Hospital, Occhiobello (RO), Italy
| | - Mastrantuoni Ciro
- Department of Neurosurgery, P.O. Santa Maria delle Grazie, Pozzuoli (NA), Italy
| | - Maugeri Rosario
- Department of Experimental Biomedicine and Clinical Neurosciences, School of Medicine, Unit of Neurosurgery, AOUP “Paolo Giaccone”, Palermo, Italy
| | - Meglio Vincenzo
- Division of Neurosurgery, Department of Neurosciences, Reproductive and Odontostomatological Sciences, Università degli Studi di Napoli Federico II, Naples, Italy
| | - Montemurro Nicola
- Department of Neurosurgery, Azienda Ospedaliera Universitaria Pisana (AUOP), University of Pisa, Pisa, Italy
| | - Nina Pierpaolo
- Neurosurgical Unit of San Giovanni Bosco Hospital, Naples, Italy
| | | | | | | | - Rapanà Armando
- Neurosurgery Unit, Lorenzo Bonomo Hospital, Andria, Italy
| | - Ricci Alessandro
- Unit of Neurosurgery, Ospedale Civile San Salvatore, L'Aquila, Italy
| | - Rispoli Rossella
- Section of Spine and Spinal Cord Surgery, Department of Neurological Sciences, ASUFC University Hospital of Udine, Udine, Italy
| | - Romoli Stefano
- Unit of Spine Surgery, Careggi University Hospital, Florence, Italy
| | | | - Somma Teresa
- Division of Neurosurgery, Department of Neurosciences, Reproductive and Odontostomatological Sciences, Università degli Studi di Napoli Federico II, Naples, Italy
| | - Tessitore Enrico
- Neurosurgical Unit, Faculty of Medicine, Geneva University Hospitals, Geneva, Switzerland
| | - Vitali Matteo
- Department of Neurosurgery, SS Antonio e Biagio e Cesare Arrigo Alessandria Hospital, Alessandria, Italy
| | - Alberto Zerbi
- Fondazione Iseni Y Nervi, Istititi Clinici Iseni, Lonate Pozzolo, Italy
| | - Zona Gianluigi
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics and Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
- Department of Neurosurgery, IRCCS San Martino University Hospital, Genoa, Italy
| | - Andrea Barbanera
- Department of Neurosurgery, SS Antonio e Biagio e Cesare Arrigo Alessandria Hospital, Alessandria, Italy
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Zhang JK, Javeed S, Greenberg JK, Dibble CF, Song SK, Ray WZ. Diffusion Basis Spectrum Imaging Identifies Clinically Relevant Disease Phenotypes of Cervical Spondylotic Myelopathy. Clin Spine Surg 2023; 36:134-142. [PMID: 36959182 PMCID: PMC10042585 DOI: 10.1097/bsd.0000000000001451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 01/29/2023] [Indexed: 03/25/2023]
Abstract
STUDY DESIGN Prospective cohort study. OBJECTIVE Apply a machine learning clustering algorithm to baseline imaging data to identify clinically relevant cervical spondylotic myelopathy (CSM) patient phenotypes. SUMMARY OF BACKGROUND DATA A major shortcoming in improving care for CSM patients is the lack of robust quantitative imaging tools to guide surgical decision-making. Advanced diffusion-weighted magnetic resonance imaging (MRI) techniques, such as diffusion basis spectrum imaging (DBSI), may help address this limitation by providing detailed evaluations of white matter injury in CSM. METHODS Fifty CSM patients underwent comprehensive clinical assessments and diffusion-weighted MRI, followed by DBSI modeling. DBSI metrics included fractional anisotropy, axial and radial diffusivity, fiber fraction, extra-axonal fraction, restricted fraction, and nonrestricted fraction. Neurofunctional status was assessed by the modified Japanese Orthopedic Association, myelopathic disability index, and disabilities of the arm, shoulder, and hand. Quality-of-life was measured by the 36-Item Short Form Survey physical component summary and mental component summary. The neck disability index was used to measure self-reported neck pain. K-means clustering was applied to baseline DBSI measures to identify 3 clinically relevant CSM disease phenotypes. Baseline demographic, clinical, radiographic, and patient-reported outcome measures were compared among clusters using one-way analysis of variance (ANOVA). RESULTS Twenty-three (55%) mild, 9 (21%) moderate, and 10 (24%) severe myelopathy patients were enrolled. Eight patients were excluded due to MRI data of insufficient quality. Of the remaining 42 patients, 3 groups were generated by k-means clustering. When compared with clusters 1 and 2, cluster 3 performed significantly worse on the modified Japanese Orthopedic Association and all patient-reported outcome measures (P<0.001), except the 36-Item Short Form Survey mental component summary (P>0.05). Cluster 3 also possessed the highest proportion of non-Caucasian patients (43%, P=0.04), the worst hand dynamometer measurements (P<0.05), and significantly higher intra-axonal axial diffusivity and extra-axonal fraction values (P<0.001). CONCLUSIONS Using baseline imaging data, we delineated a clinically meaningful CSM disease phenotype, characterized by worse neurofunctional status, quality-of-life, and pain, and more severe imaging markers of vasogenic edema. LEVEL OF EVIDENCE II.
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Affiliation(s)
- Justin K. Zhang
- Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, Missouri, 63110, USA
| | - Saad Javeed
- Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, Missouri, 63110, USA
| | - Jacob K. Greenberg
- Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, Missouri, 63110, USA
| | - Christopher F. Dibble
- Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, Missouri, 63110, USA
| | - Sheng-Kwei Song
- Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, Missouri, 63110, USA
| | - Wilson Z. Ray
- Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, Missouri, 63110, USA
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Ouyang Z, Zhang N, Li M, Hong T, Ouyang T, Meng W. A meta-analysis of the role of diffusion tensor imaging in cervical spinal cord compression. J Neuroimaging 2023. [PMID: 36914383 DOI: 10.1111/jon.13093] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 02/08/2023] [Accepted: 02/08/2023] [Indexed: 03/14/2023] Open
Abstract
BACKGROUND AND PURPOSE At present, the role of diffusion tensor imaging (DTI) remains controversial. This study aimed to confirm the role of DTI by comparing the differences in fractional anisotropy (FA) values between patients with cervical spinal cord compression (CSCC) and healthy individuals. METHODS A systematic and comprehensive literature search was conducted using the Web of Science, Embase, PubMed, and Cochrane Library databases to compare the mean FA values of patients with CSCC and healthy controls across all compression levels in the cervical spinal cord. Essential data from the literature, such as demographic information, imaging parameters, and DTI analysis method, were extracted. Fixed- or random-effect models based on I2 heterogeneity were applied to the pooled and subgroup analyses. RESULTS Ten studies containing 445 patients and 197 healthy volunteers were eligible. The pooled results demonstrated a decrease in mean FA values across all compression levels in the experiment group compared to those in healthy controls (standardized mean difference = -1.54; 95% confidence interval = [-1.95, -1.14]; p < .001). Meta-regression revealed that the scanner field strength and DTI analysis method had a significant effect on heterogeneity. CONCLUSIONS Our results show that FA values in the spinal cord decline in patients with CSCC, thus confirming the crucial role of DTI in CSCC.
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Affiliation(s)
- Ziqiang Ouyang
- Department of Neurosurgery, The First Affiliated Hospital of Nanchang University, Nanchang, China.,Department of the First Clinical Medical College, Nanchang University, Jiangxi Province, China
| | - Na Zhang
- Department of Neurology, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Meihua Li
- Department of Neurosurgery, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Tao Hong
- Department of Neurosurgery, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Taohui Ouyang
- Department of Neurosurgery, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Wei Meng
- Department of Neurosurgery, The First Affiliated Hospital of Nanchang University, Nanchang, China
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11
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Zhang JK, Jayasekera D, Song C, Greenberg JK, Javeed S, Dibble CF, Blum J, Sun P, Song SK, Ray WZ. Diffusion Basis Spectrum Imaging Provides Insights Into Cervical Spondylotic Myelopathy Pathology. Neurosurgery 2023; 92:102-109. [PMID: 36519861 PMCID: PMC10158908 DOI: 10.1227/neu.0000000000002183] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Accepted: 08/11/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Diffusion basis spectrum imaging (DBSI) is a noninvasive quantitative imaging modality that may improve understanding of cervical spondylotic myelopathy (CSM) pathology through detailed evaluations of spinal cord microstructural compartments. OBJECTIVE To determine the utility of DBSI as a biomarker of CSM disease severity. METHODS A single-center prospective cohort study enrolled 50 patients with CSM and 20 controls from 2018 to 2020. All patients underwent clinical evaluation and diffusion-weighted MRI, followed by diffusion tensor imaging and DBSI analyses. Diffusion-weighted MRI metrics assessed white matter integrity by fractional anisotropy, axial diffusivity, radial diffusivity, and fiber fraction. In addition, DBSI further evaluates extra-axonal changes by isotropic restricted and nonrestricted fraction. Including an intra-axonal diffusion compartment, DBSI improves estimations of axonal injury through intra-axonal axial diffusivity. Patients were categorized into mild, moderate, and severe CSM using modified Japanese Orthopedic Association classifications. Imaging parameters were compared among patient groups using independent samples t tests and ANOVA. RESULTS Twenty controls, 27 mild (modified Japanese Orthopedic Association 15-17), 12 moderate (12-14), and 11 severe (0-11) patients with CSM were enrolled. Diffusion tensor imaging and DBSI fractional anisotropy, axial diffusivity, and radial diffusivity were significantly different between control and patients with CSM ( P < .05). DBSI fiber fraction, restricted fraction, and nonrestricted fraction were significantly different between groups ( P < .01). DBSI intra-axonal axial diffusivity was lower in mild compared with moderate (mean difference [95% CI]: 1.1 [0.3-2.1], P < .01) and severe (1.9 [1.3-2.4], P < .001) CSM. CONCLUSION DBSI offers granular data on white matter tract integrity in CSM that provide novel insights into disease pathology, supporting its potential utility as a biomarker of CSM disease progression.
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Affiliation(s)
- Justin K. Zhang
- Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, Missouri, USA
| | - Dinal Jayasekera
- Department of Biomedical Engineering, Washington University in St. Louis McKelvey School of Engineering, Saint Louis, Missouri, USA
| | - Chunyu Song
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Jacob K. Greenberg
- Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, Missouri, USA
| | - Saad Javeed
- Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, Missouri, USA
| | - Christopher F. Dibble
- Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, Missouri, USA
| | - Jacob Blum
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Peng Sun
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Sheng-Kwei Song
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Wilson Z. Ray
- Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, Missouri, USA
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12
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Zhang JK, Sun P, Jayasekera D, Greenberg JK, Javeed S, Dibble CF, Blum J, Song C, Song SK, Ray WZ. Utility of Diffusion Basis Spectrum Imaging in Quantifying Baseline Disease Severity and Prognosis of Cervical Spondylotic Myelopathy. Spine (Phila Pa 1976) 2022; 47:1687-1693. [PMID: 35969006 PMCID: PMC9712150 DOI: 10.1097/brs.0000000000004456] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Accepted: 07/20/2022] [Indexed: 02/01/2023]
Abstract
STUDY DESIGN Prospective cohort study. OBJECTIVE The aim was to assess the association between diffusion tensor imaging (DTI) and diffusion basis spectrum imaging (DBSI) measures and cervical spondylotic myelopathy (CSM) clinical assessments at baseline and two-year follow-up. SUMMARY OF BACKGROUND DATA Despite advancements in diffusion-weighted imaging, few studies have examined associations between diffusion magnetic resonance imaging (MRI) markers and CSM-specific clinical domains at baseline and long-term follow-up. MATERIALS AND METHODS A single-center prospective cohort study enrolled 50 CSM patients who underwent surgical decompression and 20 controls from 2018 to 2020. At initial evaluation, all patients underwent diffusion-weighted MRI acquisition, followed by DTI and DBSI analyses. Diffusion-weighted MRI metrics assessed white matter integrity by fractional anisotropy, axial diffusivity, radial diffusivity, and fiber fraction. To improve estimations of intra-axonal anisotropic diffusion, DBSI measures intra-/extra-axonal fraction and intra-axonal axial diffusivity. DBSI also evaluates extra-axonal isotropic diffusion by restricted and nonrestricted fraction. Clinical assessments were performed at baseline and two-year follow-up and included the modified Japanese Orthopedic Association (mJOA); 36-Item Short Form Survey physical component summary (SF-36 PCS); SF-36 mental component summary; neck disability index; myelopathy disability index; and disability of the arm, shoulder, and hand. Pearson correlation coefficients were computed to compare associations between DTI/DBSI and clinical measures. A False Discovery Rate correction was applied for multiple comparisons testing. RESULTS At baseline presentation, of 36 correlations analyzed between DTI metrics and CSM clinical measures, only DTI fractional anisotropy showed a positive correlation with SF-36 PCS ( r =0.36, P =0.02). In comparison, there were 30/81 (37%) significant correlations among DBSI and clinical measures. Increased DBSI axial diffusivity, intra-axonal axial diffusivity, intra-axonal fraction, restricted fraction, and extra-axonal anisotropic fraction were associated with worse clinical presentation (decreased mJOA; SF-36 PCS/mental component summary; and increased neck disability index; myelopathy disability index; disability of the arm, shoulder, and hand). At latest follow-up, increased preoperative DBSI intra-axonal axial diffusivity and extra-axonal anisotropic fraction were significantly correlated with improved mJOA. CONCLUSIONS This findings demonstrate that DBSI measures may reflect baseline disease burden and long-term prognosis of CSM as compared with DTI. With further validation, DBSI may serve as a noninvasive biomarker following decompressive surgery. LEVEL OF EVIDENCE 3.
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Affiliation(s)
- Justin K. Zhang
- Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, Missouri, 63110, USA
| | - Peng Sun
- Department of Imaging Physics, UT MD Anderson Cancer Center, Houston, Texas, 77030, USA
| | - Dinal Jayasekera
- Department of Biomedical Engineering, Washington University in St. Louis McKelvey School of Engineering, Saint Louis, Missouri, 63130, USA
| | - Jacob K. Greenberg
- Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, Missouri, 63110, USA
| | - Saad Javeed
- Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, Missouri, 63110, USA
| | - Christopher F. Dibble
- Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, Missouri, 63110, USA
| | - Jacob Blum
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri
| | - Chunyu Song
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri
| | - Sheng-Kwei Song
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri
| | - Wilson Z. Ray
- Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, Missouri, 63110, USA
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Jayasekera D, Zhang JK, Blum J, Jakes R, Sun P, Javeed S, Greenberg JK, Song SK, Ray WZ. Analysis of combined clinical and diffusion basis spectrum imaging metrics to predict the outcome of chronic cervical spondylotic myelopathy following cervical decompression surgery. J Neurosurg Spine 2022; 37:588-598. [PMID: 35523255 PMCID: PMC10629375 DOI: 10.3171/2022.3.spine2294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Accepted: 03/24/2022] [Indexed: 11/06/2022]
Abstract
OBJECTIVE Cervical spondylotic myelopathy (CSM) is the most common cause of chronic spinal cord injury, a significant public health problem. Diffusion tensor imaging (DTI) is a neuroimaging technique widely used to assess CNS tissue pathology and is increasingly used in CSM. However, DTI lacks the needed accuracy, precision, and recall to image pathologies of spinal cord injury as the disease progresses. Thus, the authors used diffusion basis spectrum imaging (DBSI) to delineate white matter injury more accurately in the setting of spinal cord compression. It was hypothesized that the profiles of multiple DBSI metrics can serve as imaging outcome predictors to accurately predict a patient's response to therapy and his or her long-term prognosis. This hypothesis was tested by using DBSI metrics as input features in a support vector machine (SVM) algorithm. METHODS Fifty patients with CSM and 20 healthy controls were recruited to receive diffusion-weighted MRI examinations. All spinal cord white matter was identified as the region of interest (ROI). DBSI and DTI metrics were extracted from all voxels in the ROI and the median value of each patient was used in analyses. An SVM with optimized hyperparameters was trained using clinical and imaging metrics separately and collectively to predict patient outcomes. Patient outcomes were determined by calculating changes between pre- and postoperative modified Japanese Orthopaedic Association (mJOA) scale scores. RESULTS Accuracy, precision, recall, and F1 score were reported for each SVM iteration. The highest performance was observed when a combination of clinical and DBSI metrics was used to train an SVM. When assessing patient outcomes using mJOA scale scores, the SVM trained with clinical and DBSI metrics achieved accuracy and an area under the curve of 88.1% and 0.95, compared with 66.7% and 0.65, respectively, when clinical and DTI metrics were used together. CONCLUSIONS The accuracy and efficacy of the SVM incorporating clinical and DBSI metrics show promise for clinical applications in predicting patient outcomes. These results suggest that DBSI metrics, along with the clinical presentation, could serve as a surrogate in prognosticating outcomes of patients with CSM.
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Affiliation(s)
- Dinal Jayasekera
- Department of Biomedical Engineering, Washington University in St. Louis McKelvey School of Engineering, St. Louis
| | - Justin K. Zhang
- Department of Neurosurgery, Washington University School of Medicine, St. Louis
| | - Jacob Blum
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri
| | - Rachel Jakes
- Department of Biomedical Engineering, Case School of Engineering, Cleveland, Ohio
| | - Peng Sun
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Saad Javeed
- Department of Neurosurgery, Washington University School of Medicine, St. Louis
| | - Jacob K. Greenberg
- Department of Neurosurgery, Washington University School of Medicine, St. Louis
| | - Sheng-Kwei Song
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri
| | - Wilson Z. Ray
- Department of Biomedical Engineering, Washington University in St. Louis McKelvey School of Engineering, St. Louis
- Department of Neurosurgery, Washington University School of Medicine, St. Louis
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Valošek J, Bednařík P, Keřkovský M, Hluštík P, Bednařík J, Svatkova A. Quantitative MR Markers in Non-Myelopathic Spinal Cord Compression: A Narrative Review. J Clin Med 2022; 11:2301. [PMID: 35566426 PMCID: PMC9105390 DOI: 10.3390/jcm11092301] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Revised: 04/11/2022] [Accepted: 04/12/2022] [Indexed: 02/01/2023] Open
Abstract
Degenerative spinal cord compression is a frequent pathological condition with increasing prevalence throughout aging. Initial non-myelopathic cervical spinal cord compression (NMDC) might progress over time into potentially irreversible degenerative cervical myelopathy (DCM). While quantitative MRI (qMRI) techniques demonstrated the ability to depict intrinsic tissue properties, longitudinal in-vivo biomarkers to identify NMDC patients who will eventually develop DCM are still missing. Thus, we aim to review the ability of qMRI techniques (such as diffusion MRI, diffusion tensor imaging (DTI), magnetization transfer (MT) imaging, and magnetic resonance spectroscopy (1H-MRS)) to serve as prognostic markers in NMDC. While DTI in NMDC patients consistently detected lower fractional anisotropy and higher mean diffusivity at compressed levels, caused by demyelination and axonal injury, MT and 1H-MRS, along with advanced and tract-specific diffusion MRI, recently revealed microstructural alterations, also rostrally pointing to Wallerian degeneration. Recent studies also disclosed a significant relationship between microstructural damage and functional deficits, as assessed by qMRI and electrophysiology, respectively. Thus, tract-specific qMRI, in combination with electrophysiology, critically extends our understanding of the underlying pathophysiology of degenerative spinal cord compression and may provide predictive markers of DCM development for accurate patient management. However, the prognostic value must be validated in longitudinal studies.
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Affiliation(s)
- Jan Valošek
- Department of Neurology, Faculty of Medicine and Dentistry, Palacký University Olomouc, 779 00 Olomouc, Czech Republic; (J.V.); (P.H.)
- Department of Radiology, Faculty of Medicine and Dentistry, Palacký University Olomouc, 779 00 Olomouc, Czech Republic
- Department of Biomedical Engineering, University Hospital Olomouc, 779 00 Olomouc, Czech Republic
| | - Petr Bednařík
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, 2650 Hvidovre, Denmark;
- Department of Radiology, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, 2650 Hvidovre, Denmark
| | - Miloš Keřkovský
- Faculty of Medicine, Masaryk University, 625 00 Brno, Czech Republic; (M.K.); (J.B.)
- Department of Radiology and Nuclear Medicine, University Hospital Brno, 625 00 Brno, Czech Republic
| | - Petr Hluštík
- Department of Neurology, Faculty of Medicine and Dentistry, Palacký University Olomouc, 779 00 Olomouc, Czech Republic; (J.V.); (P.H.)
- Department of Neurology, University Hospital Olomouc, 779 00 Olomouc, Czech Republic
| | - Josef Bednařík
- Faculty of Medicine, Masaryk University, 625 00 Brno, Czech Republic; (M.K.); (J.B.)
- Department of Neurology, University Hospital Brno, 625 00 Brno, Czech Republic
- Central European Institute of Technology, Masaryk University, 625 00 Brno, Czech Republic
| | - Alena Svatkova
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, 2650 Hvidovre, Denmark;
- Department of Radiology, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, 2650 Hvidovre, Denmark
- Department of Medicine III, Clinical Division of Endocrinology and Metabolism, Medical University of Vienna, 1090 Vienna, Austria
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Abstract
In the evaluation of spinal trauma, diagnostic imaging is of paramount importance. Computed tomography (CT), flexion/extension radiographs, and MRI are complementary modalities. CT is typically obtained in the initial setting of spinal trauma and provides detailed information about osseous structures. MRI provides detailed information about structural injury to the spinal cord. Diffusion tensor imaging provides microstructural information about the integrity of the axons and myelin sheaths, but its clinical use is limited. Novel imaging techniques may be better suited for the acute clinical setting and are under development for potential future clinical use.
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Zhang H, Guan L, Hai Y, Liu Y, Ding H, Chen X. Multi-shot echo-planar diffusion tensor imaging in cervical spondylotic myelopathy. Bone Joint J 2020; 102-B:1210-1218. [PMID: 32862690 DOI: 10.1302/0301-620x.102b9.bjj-2020-0468.r1] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
AIMS The aim of this study was to use diffusion tensor imaging (DTI) to investigate changes in diffusion metrics in patients with cervical spondylotic myelopathy (CSM) up to five years after decompressive surgery. We correlated these changes with clinical outcomes as scored by the Modified Japanese Orthopedic Association (mJOA) method, Neck Disability Index (NDI), and Visual Analogue Scale (VAS). METHODS We used multi-shot, high-resolution, diffusion tensor imaging (ms-DTI) in patients with cervical spondylotic myelopathy (CSM) to investigate the change in diffusion metrics and clinical outcomes up to five years after anterior cervical interbody discectomy and fusion (ACDF). High signal intensity was identified on T2-weighted imaging, along with DTI metrics such as fractional anisotropy (FA). MJOA, NDI, and VAS scores were also collected and compared at each follow-up point. Spearman correlations identified correspondence between FA and clinical outcome scores. RESULTS Significant differences in mJOA scores and FA values were found between preoperative and postoperative timepoints up to two years after surgery. FA at the level of maximum cord compression (MCL) preoperatively was significantly correlated with the preoperative mJOA score. FA postoperatively was also significantly correlated with the postoperative mJOA score. There was no statistical relationship between NDI and mJOA or VAS. CONCLUSION ms-DTI can detect microstructural changes in affected cord segments and reflect functional improvement. Both FA values and mJOA scores showed maximum recovery two years after surgery. The DTI metrics are significantly associated with pre- and postoperative mJOA scores. DTI metrics are a more sensitive, timely, and quantifiable surrogate for evaluating patients with CSM and a potential quantifiable biomarker for spinal cord dysfunction. Cite this article: Bone Joint J 2020;102-B(9):1210-1218.
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Affiliation(s)
- Hanwen Zhang
- Department of Orthopedic Surgery, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Li Guan
- Department of Orthopedic Surgery, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Yong Hai
- Department of Orthopedic Surgery, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Yuzeng Liu
- Department of Orthopedic Surgery, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Hongtao Ding
- Department of Orthopedic Surgery, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Xiaolong Chen
- Department of Orthopedic Surgery, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
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Degenerative Cervical Myelopathy: How to Identify the Best Responders to Surgery? J Clin Med 2020; 9:jcm9030759. [PMID: 32168833 PMCID: PMC7141260 DOI: 10.3390/jcm9030759] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2020] [Revised: 02/29/2020] [Accepted: 03/05/2020] [Indexed: 11/16/2022] Open
Abstract
Surgery is the only definitive treatment for degenerative cervical myelopathy (DCM), however, the degree of neurological recovery is often unpredictable. Here, we assess the utility of a multidimensional diagnostic approach, consisting of clinical, neurophysiological, and radiological parameters, to identify patients likely to benefit most from surgery. Thirty-six consecutive patients were prospectively analyzed using the modified Japanese Orthopedic Association (mJOA) score, MEPs/SSEPs and advance and conventional MRI parameters, at baseline, and 3- and 12-month postoperatively. Patients were subdivided into “normal” and “best” responders (<50%, ≥50% improvement in mJOA), and correlation between Diffusion Tensor Imaging (DTI) parameters, mJOA, and MEP/SSEP latencies were examined. Twenty patients were “best” responders and 16 were “normal responders”, but there were no statistical differences in age, T2 hyperintensity, and midsagittal diameter between them. There was a significant inverse correlation between the MEPs central conduction time and mJOA in the preoperative period (p = 0.0004), and a positive correlation between fractional anisotropy (FA) and mJOA during all the phases of the study, and statistically significant at 1-year (r = 0.66, p = 0.0005). FA was significantly higher amongst “best responders” compared to “normal responders” preoperatively and at 1-year (p = 0.02 and p = 0.009). A preoperative FA > 0.55 was predictor of a better postoperative outcome. Overall, these results support the concept of a multidisciplinary approach in the assessment and management of DCM.
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The Effect of Surgical Decompression on Functional Balance Testing in Patients With Cervical Spondylotic Myelopathy. Clin Spine Surg 2019; 32:369-376. [PMID: 31498275 DOI: 10.1097/bsd.0000000000000889] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
STUDY DESIGN A prospective cohort study. OBJECTIVE Quantify the extent of change in dynamic balance and stability in a group of patients with cervical spondylotic myelopathy (CSM) after cervical decompression surgery and to compare them with matched healthy controls. SUMMARY OF BACKGROUND DATA CSM is a naturally progressive degenerative condition that commonly results in loss of fine motor control in the hands and upper extremities and in gait imbalance. Whereas this was previously thought of as an irreversible condition, more recent studies are demonstrating postoperative improvements in balance and stability. MATERIALS AND METHODS Thirty subjects with symptomatic CSM and 25 matched asymptomatic controls between the ages of 45 and 75 years underwent functional balance testing using a 3D motion capture system to gather kinematic and spatiotemporal parameters. CSM subjects underwent testing 1 week before surgery and again 3 months postoperatively. RESULTS Patients with CSM exhibited markedly diminished balance as indicated by increased sway on a Romberg test and requiring significantly more time and a wider stance to complete tandem gait tests. The surgical intervention resulted in improved balance at the 3-month postoperative time point; however, kinematic and spatiotemporal parameters did not completely normalize to the levels observed in asymptomatic controls. CONCLUSIONS Human motion video capture can be used to robustly quantify balance parameters in the setting of CSM. Compared with healthy controls, such patients exhibited increased standing sway and poorer performance on a tandem gait task. The surgical intervention resulted in significant improvement in many of the measures of functional balance, but overall profiles had not completely returned to normal when measured 3 months after surgery. These data reinforce the importance of operative intervention in the treatment of symptomatic CSM with the goal of halting disease progress but the expectation that balance may actually improve postoperatively.
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Shabani S, Kaushal M, Budde M, Schmit B, Wang MC, Kurpad S. Comparison between quantitative measurements of diffusion tensor imaging and T2 signal intensity in a large series of cervical spondylotic myelopathy patients for assessment of disease severity and prognostication of recovery. J Neurosurg Spine 2019; 31:473-479. [PMID: 31174184 DOI: 10.3171/2019.3.spine181328] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2018] [Accepted: 03/20/2019] [Indexed: 11/06/2022]
Abstract
OBJECTIVE Cervical spondylotic myelopathy (CSM) is a common cause of spinal cord dysfunction. Recently, it has been shown that diffusion tensor imaging (DTI) may be a better biomarker than T2-weighted signal intensity (T2SI) on MRI for CSM. However, there is very little literature on a comparison between the quantitative measurements of DTI and T2SI in the CSM patient population to determine disease severity and recovery. METHODS A prospective analysis of 46 patients with both preoperative DTI and T2-weighted MRI was undertaken. Normalized T2SI (NT2SI), regardless of the presence or absence of T2SI at the level of maximum compression (LMC), was determined by calculating the T2SI at the LMC/T2SI at the level of the foramen magnum. Regression analysis was performed to determine the relationship of fractional anisotropy (FA), a quantitative measure derived from DTI, and NT2SI individually as well their combination with baseline preoperative modified Japanese Orthopaedic Association (mJOA) score and ∆mJOA score at the 3-, 6-, 12-, and 24-month follow-ups. Goodness-of-fit analysis was done using residual diagnostics. In addition, mixed-effects regression analysis was used to evaluate the impact of FA and NT2SI individually. A p value < 0.05 was selected to indicate statistical significance. RESULTS Regression analysis showed a significant positive correlation between FA at the LMC and preoperative mJOA score (p = 0.041) but a significant negative correlation between FA at the LMC and the ΔmJOA score at the 12-month follow-up (p = 0.010). All other relationships between FA at the LMC and the baseline preoperative mJOA score or ∆mJOA score at the 3-, 6-, and 24-month follow-ups were not statistically significant. For NT2SI and the combination of FA and NT2SI, no significant relationships with preoperative mJOA score or ∆mJOA at 3, 6, and 24 months were seen on regression analysis. However, there was a significant correlation of combined FA and NT2SI with ∆mJOA score at the 12-month follow-up. Mixed-effects regression revealed that FA measured at the LMC was the only significant predictor of ΔmJOA score (p = 0.03), whereas NT2SI and time were not. Goodness-of-fit analysis did not show any evidence of lack of fit. CONCLUSIONS In this large prospective study of CSM patients, FA at LMC appears to be a better biomarker for determining long-term outcomes following surgery in CSM patients than NT2SI or the combination values at LMC.
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Affiliation(s)
- Saman Shabani
- 1Department of Neurosurgery, Medical College of Wisconsin; and
| | - Mayank Kaushal
- 1Department of Neurosurgery, Medical College of Wisconsin; and
| | - Matthew Budde
- 1Department of Neurosurgery, Medical College of Wisconsin; and
| | - Brian Schmit
- 2Department of Biomedical Engineering, Marquette University, Milwaukee, Wisconsin
| | - Marjorie C Wang
- 1Department of Neurosurgery, Medical College of Wisconsin; and
| | - Shekar Kurpad
- 1Department of Neurosurgery, Medical College of Wisconsin; and
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Zileli M, Maheshwari S, Kale SS, Garg K, Menon SK, Parthiban J. Outcome Measures and Variables Affecting Prognosis of Cervical Spondylotic Myelopathy: WFNS Spine Committee Recommendations. Neurospine 2019; 16:435-447. [PMID: 31607075 PMCID: PMC6790741 DOI: 10.14245/ns.1938196.098] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2019] [Accepted: 08/16/2018] [Indexed: 12/28/2022] Open
Abstract
This study is conducted to review the literature systematically to determine most reliable outcome measures, important clinical and radiological variables affecting the prognosis in cervical spondylotic myelopathy patients. A literature search was performed for articles published during the last 10 years. As functional outcome measures we recommend to use modified Japanese Orthopaedic Association scale, Nurick’s grade, and Myelopathy Disability Index. Three clinical variables that affect the outcomes are age, duration of symptoms, and severity of the myelopathy. Examination findings require more detailed study to validate their effect on the outcomes. The predictive variables affecting the outcomes are hand atrophy, leg spasticity, clonus, and Babinski’s sign. Among the radiological variables, the curvature of the cervical spine is the most important predictor of prognosis. Patients with instability are expected to have a poor surgical outcome. Spinal cord compression ratio is a critical factor for prognosis. High signal intensity on T2-weighted magnetic resonance images is a negative predictor for prognosis. The most important predictors of outcome are preoperative severity and duration of symptoms. T2 hyperintensity and cord compression ratio can also predict outcomes. New radiological tests may give promising results in the future.
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Affiliation(s)
- Mehmet Zileli
- Department of Neurosurgery, Ege University, Izmir, Turkey
| | - Shradha Maheshwari
- Department of Neurosurgery, LTMG Hospital & LTM Medical College, Mumbai, India
| | | | | | | | - Jutty Parthiban
- Department Neurosurgery and Spine Unit, Kovai Medical Center and Hospital, Tamilnadu, India
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Jin R, Luk KD, Cheung JPY, Hu Y. Prognosis of cervical myelopathy based on diffusion tensor imaging with artificial intelligence methods. NMR IN BIOMEDICINE 2019; 32:e4114. [PMID: 31131933 DOI: 10.1002/nbm.4114] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/15/2018] [Revised: 04/20/2019] [Accepted: 04/22/2019] [Indexed: 06/09/2023]
Abstract
Diffusion tensor imaging (DTI) has been proposed for the prognosis of cervical myelopathy (CM), but the manual analysis of DTI features is complicated and time consuming. This study evaluated the potential of artificial intelligence (AI) methods in the analysis of DTI for the prognosis of CM. Seventy-five patients who underwent surgical treatment for CM were recruited for DTI imaging and were divided into two groups based on their one-year follow-up recovery. The DTI features of fractional anisotropy, axial diffusivity, radial diffusivity, and mean diffusivity were extracted from DTI maps of all cervical levels. Conventional AI models using logistic regression (LR), k-nearest neighbors (KNN), and a radial basis function kernel support vector machine (RBF-SVM) were built using these DTI features. In addition, a deep learning model was applied to the DTI maps. Their performances were compared using 50 repeated 10-fold cross-validations. The accuracy of the classifications reached 74.2% ± 1.6% for LR, 85.6% ± 1.4% for KNN, 89.7% ± 1.6% for RBF-SVM, and 59.2% ± 3.8% for the deep leaning model. The RBF-SVM algorithm achieved the best accuracy, with sensitivity and specificity of 85.0% ± 3.4% and 92.4% ± 1.9% respectively. This finding indicates that AI methods are feasible and effective for DTI analysis for the prognosis of CM.
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Affiliation(s)
- Richu Jin
- Department of Orthopaedics and Traumatology, The University of Hong Kong, Pokfulam, Hong Kong
| | - Keith Dk Luk
- Department of Orthopaedics and Traumatology, The University of Hong Kong, Pokfulam, Hong Kong
| | - Jason Pui Yin Cheung
- Department of Orthopaedics and Traumatology, The University of Hong Kong, Pokfulam, Hong Kong
| | - Yong Hu
- Department of Orthopaedics and Traumatology, The University of Hong Kong, Pokfulam, Hong Kong
- Shenzhen Key Laboratory for Innovative Technology in Orthopaedic Trauma, Department of Orthopaedics and Traumatology, The University of Hong Kong-Shenzhen Hospital, Shenzhen, China
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Tempest-Mitchell J, Hilton B, Davies BM, Nouri A, Hutchinson PJ, Scoffings DJ, Mannion RJ, Trivedi R, Timofeev I, Crawford JR, Hay D, Laing RJ, Kotter MRN. A comparison of radiological descriptions of spinal cord compression with quantitative measures, and their role in non-specialist clinical management. PLoS One 2019; 14:e0219380. [PMID: 31329621 PMCID: PMC6645712 DOI: 10.1371/journal.pone.0219380] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2019] [Accepted: 06/23/2019] [Indexed: 11/28/2022] Open
Abstract
INTRODUCTION Magnetic resonance imaging (MRI) is gold-standard for investigating Degenerative Cervical Myelopathy (DCM), a disabling disease triggered by compression of the spinal cord following degenerative changes of adjacent structures. Quantifiable compression correlates poorly with disease and language describing compression in radiological reports is un-standardised. STUDY DESIGN Retrospective chart review. OBJECTIVES 1) Identify terminology in radiological reporting of cord compression and elucidate relationships between language and quantitative measures 2) Evaluate language's ability to distinguish myelopathic from asymptomatic compression 3) Explore correlations between quantitative or qualitative features and symptom severity 4) Investigate the influence of quantitative and qualitative measures on surgical referrals. METHODS From all cervical spine MRIs conducted during one year at a tertiary centre (N = 1123), 166 patients had reported cord compression. For each spinal level deemed compressed by radiologists (N = 218), four quantitative measurements were calculated: 'Maximum Canal Compromise (MCC); 'Maximum Spinal Cord Compression' (MSCC); 'Spinal Canal Occupation Ratio' (SCOR) and 'Compression Ratio' (CR). These were compared to associated radiological reporting terminology. RESULTS 1) Terminology in radiological reports was varied. Objective measures of compromise correlated poorly with language. "Compressed" was used for more severe cord compromise as measured by MCC (p<0.001), MSCC (p<0.001), and CR (p = 0.002). 2) Greater compromise was seen in cords with a myelopathy diagnosis across MCC (p<0.001); MSCC (p = 0.002) and CR (p<0.001). "Compress" (p<0.001) and "Flatten" (p<0.001) were used more commonly for myelopathy-diagnosis levels. 3) Measurements of cord compromise (MCC: p = 0.304; MSCC: p = 0.217; SCOR: p = 0.503; CR: p = 0.256) and descriptive terms (p = 0.591) did not correlate with i-mJOA score. 4) The only variables affecting spinal surgery referral were increased MSCC (p = 0.001) and use of 'Compressed' (p = 0.045). CONCLUSIONS Radiological reporting in DCM is variable and language is not fully predictive of the degree of quantitative cord compression. Additionally, terminology may influence surgical referrals.
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Affiliation(s)
| | - Bryn Hilton
- School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Benjamin M. Davies
- Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
| | - Aria Nouri
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada
| | - Peter J. Hutchinson
- Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
| | - Daniel J. Scoffings
- Department of Radiology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - Richard J. Mannion
- Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
| | - Rikin Trivedi
- Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
| | - Ivan Timofeev
- Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
| | - John R. Crawford
- Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
| | - Douglas Hay
- Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
| | - Rodney J. Laing
- Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
| | - Mark R. N. Kotter
- Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
- Anne McLaren Laboratory for Regenerative Medicine, Welcome Trust MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, United Kingdom
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Affiliation(s)
- Jacob M Buchowski
- Department of Orthopaedic Surgery, Washington University School of Medicine, St. Louis, Missouri
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