Why Are Some Intervertebral Discs More Prone to Degeneration?

Cheung, Samuel Tin Yan; Cheung, Pty; Cheung, Jason Pui Yin

doi:10.1097/brs.0000000000004632

Cited by 3 publications

(1 citation statement)

References 40 publications

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“…We focused on the last three lumbar spine IVDs (L3/L4, L4/L5, and L5/S1) because they are more prone to injury than others. These IVDs bear the most weight and pressure from the upper body as well as higher twisting pressure due to the wider range of motion they need to support making it more susceptible to twisting and bending forces that can damage the discs [15,16].…”

Section: Introductionmentioning

confidence: 99%

Lumbar spine MRI annotation with intervertebral disc height and Pfirrmann grade predictions

Natalia,

Sudirman,

Ruslim

et al. 2024

PLoS ONE

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Many lumbar spine diseases are caused by defects or degeneration of lumbar intervertebral discs (IVD) and are usually diagnosed through inspection of the patient’s lumbar spine MRI. Efficient and accurate assessments of the lumbar spine are essential but a challenge due to the size of the clinical radiologist workforce not keeping pace with the demand for radiology services. In this paper, we present a methodology to automatically annotate lumbar spine IVDs with their height and degenerative state which is quantified using the Pfirrmann grading system. The method starts with semantic segmentation of a mid-sagittal MRI image into six distinct non-overlapping regions, including the IVD and vertebrae regions. Each IVD region is then located and assigned with its label. Using geometry, a line segment bisecting the IVD is determined and its Euclidean distance is used as the IVD height. We then extract an image feature, called self-similar color correlogram, from the nucleus of the IVD region as a representation of the region’s spatial pixel intensity distribution. We then use the IVD height data and machine learning classification process to predict the Pfirrmann grade of the IVD. We considered five different deep learning networks and six different machine learning algorithms in our experiment and found the ResNet-50 model and Ensemble of Decision Trees classifier to be the combination that gives the best results. When tested using a dataset containing 515 MRI studies, we achieved a mean accuracy of 88.1%.

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Section: Introductionmentioning

confidence: 99%

Lumbar spine MRI annotation with intervertebral disc height and Pfirrmann grade predictions

Natalia,

Sudirman,

Ruslim

et al. 2024

PLoS ONE

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Applying ultrasonic osteotome to treat thoracic ossification of ligamentum flavum combined with thoracic disc herniation: A case report

Kang,

Yang,

Zhang

et al. 2024

Asian Journal of Surgery

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Male spondyloarthritis patients and those with longer disease duration have less severe disc degeneration: propensity score-matched comparison

Cheung,

Tsang,

Cheung

et al. 2023

Rheumatology Advances in Practice

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Objective Using whole-spine sagittal T2 magnetic resonance imaging (MRI) we aimed to compare the severity and prevalence of disc degeneration (DD) in axial spondyloarthritis (SpA) patients versuss the general population, and to determine any association between spinal inflammation, structural changes, mobility and DD among SpA patients. Methods Two prospectively collected cohorts of SpA patients (n = 411) and general population (n = 2007) were recruited. Eventually 967 participants from the populational cohort and 304 participants from the SpA cohort were analysed. 219 match pairs were generated by propensity-score matching. Imaging parameters including Pfirrmann grading, disc herniation, high intensity zone (HIZ), Schmorl’s node (SN), Modic change (MC) and anterior marrow change were studied and compared from C2/3 to L5/S1. DD was defined with Pfirrmann grade 4 or 5. Demographic factors including age, sex and BMI were collected. Multivariable linear regression was used to determine association between spinal inflammation (Spondyloarthritis research consortium of Canada (SPARCC) spine MRI index), structural changes (Modified Stoke ankylosing spondylitis spinal score (mSASSS)), and mobility (Bath ankylosing spondylitis metrology index (BASMI)) with lumbar Pfirrmann score. Results SpA patients had lower prevalence of DD (p < 0.001). The disease-stage stratified regression model showed SPARCC spinal MRI index was associated with higher lumbar Pfirrmann scores in early disease (β = 0.196, p = 0.044), where mSASSS was associated with lower lumbar Pfirrmann scores in later disease (β=-0.138, p = 0.038). Male had higher mSASSS (p < 0.001) and lower odds of whole spine DD (OR = 0.622, p = 0.028). Conclusion SpA patients had lower DD severity than the population. Males had higher mSASSS scores, and increased mSASSS at later disease was associated with less severe DD.

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Why Are Some Intervertebral Discs More Prone to Degeneration?

Cited by 3 publications

References 40 publications

Lumbar spine MRI annotation with intervertebral disc height and Pfirrmann grade predictions

Lumbar spine MRI annotation with intervertebral disc height and Pfirrmann grade predictions

Applying ultrasonic osteotome to treat thoracic ossification of ligamentum flavum combined with thoracic disc herniation: A case report

Male spondyloarthritis patients and those with longer disease duration have less severe disc degeneration: propensity score-matched comparison

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