Evidence map›Paper›PMID 38286908›Full record

ArticleEuropean spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society2024

Diagnostic efficacy of tract-specific diffusion tensor imaging in cervical spondylotic myelopathy with electrophysiological examination validation.

Yanming Fang, Sisi Li, Jinchao Wang, Zhenzhen Zhang, Wen Jiang, Chao Wang, Yuancheng Jiang, Hua Guo, Xiao Han, Wei Tian

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Article in 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. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
2.9field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Nomogram for predicting the postoperative outcomes in cervical spondylotic myelopathy based on apparent diffusion coefficient.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 · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 4 institutions in 1 country.

Yanming Fang *Beijing Jishuitan Hospital, Capital Medical University, Beijing, China.
Sisi Li *Center for Biomedical Imaging Research, Tsinghua University, Beijing, China.
Jinchao WangBeijing Jishuitan Hospital, Capital Medical University, Beijing, China.
Zhenzhen ZhangBeijing Jishuitan Hospital, Capital Medical University, Beijing, China.
Wen JiangBeijing Jishuitan Hospital, Capital Medical University, Beijing, China.
Chao WangBeijing Jishuitan Hospital, Capital Medical University, Beijing, China.
Yuancheng JiangCenter for Biomedical Imaging Research, Tsinghua University, Beijing, China.
Hua GuoCenter for Biomedical Imaging Research, Tsinghua University, Beijing, China.
Xiao HanBeijing Jishuitan Hospital, Capital Medical University, Beijing, China. hanxiaomd@vip.163.com.
Wei TianBeijing Jishuitan Hospital, Capital Medical University, Beijing, China. tianweispine@163.com.
Peking University · CNTsinghua University · CNCapital Medical University · CNBeijing Jishuitan Hospital · CN

Funding

Beijing Jishuitan Hospital Elite Young Scholar Programme XKGG202103Capital's Funds for Health Improvement and Research CFH2020-2-1121National Natural Science Foundation of China 11871459
6 · The paper itself

Abstract

purposeThis study aimed to investigate the effectiveness of tract-specific diffusion tensor imaging (DTI) metrics in identifying the responsible segments for neurological dysfunction in cervical spondylotic myelopathy (CSM).

methodsThe study encompassed nineteen participants diagnosed with CSM, including 10 males and 9 females. Additionally, a control group consisting of ten healthy caregivers (5 males and 5 females) were recruited with no symptoms and no compressions on magnetic resonance imaging (MRI). All participants underwent a comprehensive physical examination, MRI assessment, and DTI examination conducted by a senior chief physician. Several parameters were collected from the MR images, including the aspect ratio (defined as the anteroposterior diameter / the transverse diameter of the corresponding segment's spinal cord), transverse ratio (defined as the transverse diameter of the corresponding segment's spinal cord / the transverse diameter of the spinal cord at C2/3), and T2 high signal of the spinal cord. Furthermore, quantitative DTI metrics, such as axial diffusivity (AD), mean diffusivity (MD), radial diffusivity (RD), and fractional anisotropy (FA), were calculated using automatic region-of-interest (ROI) analysis for both whole spinal cord column and dorsal column. Receiver operating characteristic (ROC) curves were constructed to evaluate the diagnostic efficacy of the aspect ratio, transverse ratio, and DTI parameters. The area under the curve (AUC), sensitivity, and specificity were calculated. Intraoperative spinal cord electrophysiological examination was performed as the objective measure of spinal cord function during surgery.

resultsAs determined by electrophysiological examination, neurological dysfunction was found in 2 patients due to C3/4 compression, in 10 patients due to C4/5 compression, in 6 patients due to C5/6 compression, and in 1 patient due to C6/7 compression. The modified Japanese Orthopedic Association scale (mJOA) was 12.71 ± 1.55 in the CSM group, with 4.87 ± 0.72 for sensory nerve function and 5.05 ± 1.35 for motor nerve function. For the control group, none of the volunteers had neurological dysfunction. T2 high signal was found at the most stenotic segment in 13 patients of the CSM group. Considering all the cervical segments, the aspect ratio (AUC = 0.823, P = 0.001, Sensitivity = 68.42%, Specificity = 82.47%) was more capable of determining the responsible segment than transverse ratio (AUC = 0.661, P = 0.027, Sensitivity = 68.42%, Specificity = 67.01%). AD, MD, and RD were significantly higher while FA was significantly lower in the responsible segment than in the irresponsible segment (P < 0.05). The AUC of DTI-Dorsal column parameters (AD, MD, RD, FA) was larger than the corresponding parameters of the DTI (Whole spinal cord). AD of DTI-Dorsal Column possessed the greatest efficacy (AUC = 0.823, sensitivity = 84.21%, specificity = 77.32%) to determine the responsible segment, larger than AD of DTI-Whole spinal cord (AUC = 0.822, P = 0.001, Sensitivity = 89.47%, Specificity = 77.32%), aspect ratio (AUC = 0.823, P = 0.001, Sensitivity = 68.42%, Specificity = 82.47%) and transverse ratio (AUC = 0.661, P = 0.027, Sensitivity = 68.42%, Specificity = 67.01%). Subgroup analysis revealed that the diagnostic efficacy of DTI and MRI parameters was influenced by cervical spine segment.

conclusionsWhen considering all cervical segments, AD from the DTI-Dorsal Column exhibited the most significant potential in identifying responsible segments. This potential was found to be superior to that of DTI-Whole spinal cord, aspect ratio, the most stenotic segment, T2 high signals, transverse ratio, motor nerve dysfunction, and sensory nerve dysfunction. The diagnostic effectiveness of both DTI and MRI parameters was notably influenced by the specific cervical spine segment.

Indexed as

Spinal Cord DiseasesSpondylosisCervical VertebraeConstriction, PathologicDiffusion Magnetic Resonance ImagingDiffusion Tensor ImagingFemaleHumansMaleCervical spondylotic myelopathy (CSM)Diffusion tensor imaging (DTI)Receiver operating characteristicSomatosensory evoked potential (SSEP)Spinal cord electrophysiological examination

Identifiers

PMID38286908
OpenAlexW4391308978

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.