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Peer-reviewedCC BY 4.0Frontiers in Medicine

Diffusion tensor imaging for rehabilitation and prevention of lumbar degenerative diseases: a narrative review

  • Nan Zhang1
  • Baohua Zhang1
  • Zemin Zhao2
  • Di Xu1
  • Yang Xu1
  1. 1Medical Imaging Department, 82nd Group Army Hospital, People’s Liberation Army, Baoding, Hebei, China
  2. 2North China University of Technology, Tangshan, Hebei, China
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Abstract

Although objective imaging markers for rehabilitation assessment are available, lumbar disc herniation (LDH) and lumbar spinal stenosis (LSS) remain two common causes of chronic low back pain (CLBP). Diffusion tensor imaging (DTI) is a non-invasive imaging modality that allows estimation of water-molecule anisotropy and assessment of the microstructure of nerve roots and paraspinal muscles. Postoperative monitoring, preoperative prognostic assessment, evaluation of conservative treatment, detection of paraspinal muscle degeneration, and prevention of injuries during military training are examples of DTI applications in the rehabilitation and prevention of lumbar degenerative disease (LDD). There are two aspects of “prevention”: primary prevention, which concerns early warning of training injuries; and secondary prevention, which concerns the quality of rehabilitation to avoid long-term disability. Initial results suggest that DTI has the potential to identify progressive recovery of fractional anisotropy (FA) following surgery, act as a preoperative outcome predictor, evaluate the efficacy of conservative treatment, and detect age- and disease-related changes in the paraspinal muscle. These results have particular implications for military personnel, where DTI could be used to monitor training load and help reduce non-combat casualties. However, most findings remain preliminary and need to be confirmed in military populations.

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Cite

BibTeXRIS
BibTeX
@article{zhang2026diffusion,
  title = {{Diffusion tensor imaging for rehabilitation and prevention of lumbar degenerative diseases: a narrative review}},
  author = {Nan Zhang and Baohua Zhang and Zemin Zhao and Di Xu and Yang Xu},
  journal = {Frontiers in Medicine},
  year = {2026},
  month = oct,
  doi = {10.3389/fmed.2026.1959293},
  url = {https://doi.org/10.3389/fmed.2026.1959293},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Diffusion tensor imaging for rehabilitation and prevention of lumbar degenerative diseases: a narrative review
AU  - Nan Zhang
AU  - Baohua Zhang
AU  - Zemin Zhao
AU  - Di Xu
AU  - Yang Xu
PY  - 2026
DA  - 2026/10/22
JO  - Frontiers in Medicine
DO  - 10.3389/fmed.2026.1959293
UR  - https://doi.org/10.3389/fmed.2026.1959293
AB  - Although objective imaging markers for rehabilitation assessment are available, lumbar disc herniation (LDH) and lumbar spinal stenosis (LSS) remain two common causes of chronic low back pain (CLBP). Diffusion tensor imaging (DTI) is a non-invasive imaging modality that allows estimation of water-molecule anisotropy and assessment of the microstructure of nerve roots and paraspinal muscles. Postoperative monitoring, preoperative prognostic assessment, evaluation of conservative treatment, detection of paraspinal muscle degeneration, and prevention of injuries during military training are examples of DTI applications in the rehabilitation and prevention of lumbar degenerative disease (LDD). There are two aspects of “prevention”: primary prevention, which concerns early warning of training injuries; and secondary prevention, which concerns the quality of rehabilitation to avoid long-term disability. Initial results suggest that DTI has the potential to identify progressive recovery of fractional anisotropy (FA) following surgery, act as a preoperative outcome predictor, evaluate the efficacy of conservative treatment, and detect age- and disease-related changes in the paraspinal muscle. These results have particular implications for military personnel, where DTI could be used to monitor training load and help reduce non-combat casualties. However, most findings remain preliminary and need to be confirmed in military populations.
SN  - 2296-858X
ER  -