Literature DB >> 32185539

Is fractal dimension a reliable imaging biomarker for the quantitative classification of an intervertebral disk?

Junchao Ma1, Ruifeng Wang1, Yong Yu1, Xiaotong Xu1, Haifeng Duan1, Nan Yu2.   

Abstract

PURPOSE: This study aimed to explore the feasibility of the fractal method used in decoding disk heterogeneity, hoping to find a reliable imaging biomarker for the quantitative and continuous grading of intervertebral disks (IVDs).
METHODS: Totally, 180 IVDs in 65 low back pain patients (29 males, 36 female, 28-69 years) were examined with MRI. Each IVD was manually segmented on axial slice (at the mid-height layer of the disk). All disks were visually evaluated regarding degeneration grade, using Pfirrmann classification, by two experienced radiologists. Fractal dimension (FD) of the IVD was calculated from the defined regions of interest and correlated with Pfirrmann grade.
RESULTS: Fractal dimension differed significantly between any two groups (P < 0.01). The mean FDs for the four grades were as follows: Pfirrmann 1: 1.13 ± 0.02; Pfirrmann 2: 1.30 ± 0.05; Pfirrmann 3: 1.50 ± 0.05; and Pfirrmann 4: 1.65 ± 0.02. The well-hydrated IVDs displayed low fractal dimension. Degenerated IVDs displayed increased fractal dimension caused by disk heterogeneity, where the fractal dimension was shown to correlate strongly with Pfirrmann grade.
CONCLUSIONS: Fractal dimension associated well with IVD degeneration, determined with Pfirrmann grading, suggesting that the IVD fractal analysis was a suitable detection tool for the objective and continuous classification of IVD degeneration. These slides can be retrieved under Electronic Supplementary Material.

Entities:  

Keywords:  Classification; Degeneration; Fractal dimension; Intervertebral disks; MRI

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Year:  2020        PMID: 32185539     DOI: 10.1007/s00586-020-06370-2

Source DB:  PubMed          Journal:  Eur Spine J        ISSN: 0940-6719            Impact factor:   3.134


  2 in total

1.  Novel Methods to Measure Height and Volume in Healthy and Degenerated Lumbar Discs in MRIs: A Reliability Assessment Study.

Authors:  Nadya Guellil; Neha Argawal; Magnus Krieghoff; Ingmar Kaden; Christian Hohaus; Hans-Joerg Meisel; Philipp Schenk
Journal:  Diagnostics (Basel)       Date:  2022-06-10

2.  Deep learning-based high-accuracy quantitation for lumbar intervertebral disc degeneration from MRI.

Authors:  Hua-Dong Zheng; Yue-Li Sun; De-Wei Kong; Meng-Chen Yin; Jiang Chen; Yong-Peng Lin; Xue-Feng Ma; Hong-Shen Wang; Guang-Jie Yuan; Min Yao; Xue-Jun Cui; Ying-Zhong Tian; Yong-Jun Wang
Journal:  Nat Commun       Date:  2022-02-11       Impact factor: 14.919

  2 in total

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