Evidence map›Paper›PMID 42116162›Full record

ReviewJournal of orthopaedic surgery and research2026

Research progress of diffusion tensor imaging in lumbar degenerative diseases: a narrative review.

Nan Zhang, Zemin Zhao, Jinlin Tian, Yang Xu

Abstract readReview
In one paragraph

Review in Journal of orthopaedic surgery and research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Nan Zhang *Medical Imaging Department, 82nd Group Army Hospital, People's Liberation Army, Baoding, 071000, Hebei, China.
Zemin Zhao *North China University of Technology, Tangshan, 063200, Hebei, China.
Jinlin TianMedical Imaging Department, 82nd Group Army Hospital, People's Liberation Army, Baoding, 071000, Hebei, China.
Yang XuMedical Imaging Department, 82nd Group Army Hospital, People's Liberation Army, Baoding, 071000, Hebei, China. 2315937450@qq.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Degenerative diseases of the lumbar spine are a common cause of chronic low back pain and neurological dysfunction. Their pathological basis involves not only microscopic structural damage to the intervertebral discs but also microscopic injury to adjacent nerves and muscle tissues. Diffusion tensor imaging (DTI), which relies on the anisotropic properties of water molecule diffusion, enables non-invasive, quantitative assessment of microscopic structural changes in intervertebral discs, nerve fiber bundles, and muscle tissues. Studies have shown that DTI-related parameters-fractional anisotropy (FA), apparent diffusion coefficient (ADC), and other parameters show a strong correlation with the degree of degeneration, nerve compression, and clinical symptoms in lumbar degenerative diseases such as intervertebral disc degeneration, lumbar disc herniation, and stenosis of the spinal canal and intervertebral foramen. These parameters can provide imaging evidence for identifying the affected segment and evaluating treatment efficacy. This review summarizes the recent advances in the application of DTI in lumbar degenerative diseases, with the aim of providing a reference for the clinical application of DTI and future research.

Indexed as

Biomedical ResearchDiffusion Tensor ImagingIntervertebral Disc DegenerationIntervertebral Disc DisplacementLumbar VertebraeHumansSpinal StenosisArtificial intelligenceDiffusion tensor imagingIntervertebral disc degenerationLumbar degenerative diseaseLumbar disc herniationLumbar foraminal stenosisLumbar spinal stenosisParaspinal muscle changes

Identifiers

PMID42116162
PMCPMC13430770

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

None linked

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 Socratic graph.