Understanding the impact of Lumbar Disc Degeneration (LDD) and recurrent pain

Introduction: Some people with Lumbar Disc Degeneration (LDD) experience recurrent low back pain (LBP) and others do not and it is unclear why. This thesis investigates the biomechanical differences between those with LDD and LBP and those without through the examination of intrinsic lumbar spine shape, postural adjustments and kinematic strategies. Methods: Patients and healthy controls were recruited and consented to our cross-sectional cohort (ethical approval reference13/LO/0793). T2 weighted images (L1-S1, 3T MRI) were acquired and groups identified based upon LDD grade (Modified Pfirrmann grading) and the presence of LBP. Intrinsic lumbar spine shape was investigated using Statistical Shape Modelling (SSM). Postural and kinematic strategies were examined during gait, sit-to-stand and bespoke perturbation tasks using surface electromyography (eight bilateral trunk and lower limb muscles) and a novel marker set, the ‘Imperial Spine’ (three segmented spine and bilateral lower limbs). Participant pain (NRS), depression and anxiety (HADS), quality of life (SF-36), disability (ODI) and total STarT Back scores (SBT) were recorded. Results: Intrinsic lumbar shape was significantly different between groups; the ‘LDD pain’ group had larger antero-posterior vertebral diameters (p=0.05) and a more even lumbar curvature with smaller L5/S1 intervertebral disc spaces (p=0.01) than the ‘no LDD no pain’ group. Significant differences in postural and kinematic strategy were observed between ‘LDD pain’ and ‘LDD no pain’ groups, particularly during the postural perturbation task (p=0.049-0.001). Depression, anxiety, disability and SBT scores were significantly higher and quality of life lower for the ‘LDD pain’ group when compared with the ‘LDD no pain’ group (p≤0.0001). Conclusions: This study provides new evidence that intrinsic lumbar shape is associated with LDD and LBP in adults. People with LDD and LBP use different postural and kinematic strategies and have different psychosocial profiles to those without LBP. Future management will need to reflect these biomechanical and psychosocial components.Open Acces

MRI-based Surgical Planning for Lumbar Spinal Stenosis

The most common reason for spinal surgery in elderly patients is lumbar spinal stenosis(LSS). For LSS, treatment decisions based on clinical and radiological information as well as personal experience of the surgeon shows large variance. Thus a standardized support system is of high value for a more objective and reproducible decision. In this work, we develop an automated algorithm to localize the stenosis causing the symptoms of the patient in magnetic resonance imaging (MRI). With 22 MRI features of each of five spinal levels of 321 patients, we show it is possible to predict the location of lesion triggering the symptoms. To support this hypothesis, we conduct an automated analysis of labeled and unlabeled MRI scans extracted from 788 patients. We confirm quantitatively the importance of radiological information and provide an algorithmic pipeline for working with raw MRI scans

Characterisation of Ovine and Human Vertebral Endplates using X-ray Microtomography: the Effects of Degeneration on Structure.

Back pain is a significant and debilitating problem worldwide. It can be caused by several factors, but the cause of pain is only identified successfully in a minority of cases. There has been significant evidence indicating that the vertebral endplate (VEP) plays a major role in low back pain. The VEP balances two conflicting biophysical functions: providing both a nutritional pathway and mechanical support to the disc, therefore making it prone to damage. However, the VEP is still poorly characterised. This thesis describes work undertaken to characterise the structure of normal and degenerative VEPs. Initially, ovine VEPs were used to investigate the effect of location along the spine on the structural properties of the VEP. Next, the network of canals within the VEP was characterised in terms of canal architecture, content and endings at the disc boundary. Finally, the effect of degeneration on the structural properties was investigated in human endplates. Sheep spines were used as a model for the human spine to develop experimental protocols, due to similarities in their morphological and biomechanical features. A protocol was developed, using micro-computed tomography (micro-CT), for the structural characterisation of sheep VEPs. This is the first time that simultaneous assessment of different structural properties of the same VEP has been reported, allowing the comparison of structural features at different VEP locations on the same spine. The central region of the VEP was thinner than the periphery at all spinal levels and this could be explained by the increased biochemical exchange with the central nucleus pulposus of the disc and by the requirement of strong anchorage of disc fibres for mechanical support in the peripheral regions. Cranial VEPs were thicker, more porous and showed higher bone mineral density than their caudal counterparts. VEPs at different spinal levels also exhibited different structural properties. The thickest VEP measured was 1.010 ± 0.014 mm at the anterior region at cranial side of L5/L6 and the thinnest VEP was 0.455 ± 0.025 mm at the central region at caudal side of L3/L4. A series of intricate 3D canal networks within the ovine VEP layer was analysed. These networks were found to connect the marrow spaces in the vertebra to the soft tissues of the disc. Evidence of the presence of blood within these canals was shown using photoacoustic imaging, and the ending of the vessels were identified as bud-like protrusions, emerging out of the VEP layer. The individual canals were characterised in terms of their length, cross-sectional diameter and orientation. A high density of canals perpendicular to the VEP surface and emerging out of the VEP boundary was seen in the central region, of up to 39 ± 8 canal openings/mm2 for the caudal VEP at the spinal level L3/L4, providing further evidence for the increased nutritional exchange with the nucleus pulposus. This study is the first to characterise the structure of the individual canals, and simultaneously investigate the contents and the endings of these canals. A novel approach was also developed for the comparison of the clinical assessments of disc degeneration, from magnetic resonance imaging (MRI) scans, to laboratory characterisation of the human VEP from micro-CT imaging, using samples from patients undergoing elective surgery. The results suggest that the hindered nutritional pathway within the VEP was more likely to be an initiating factor of disc degeneration, rather than the effect. The structural properties of the VEP were seen to change with levels of disc degeneration, assessed by Modic types, Pfirrmann grades and VEP erosion grades. The bone mineral density showed an increasing trend from Modic type I (0.108 ± 0.007 gcm-3) to type III (0.139 ± 0.004 gcm-3). The Pfirrmann grading system was found to be limited in its assessment of progressive degeneration, while advancing VEP erosion grades was correlated with increasing sizes of the canal openings on the VEP surface. The findings also showed that the sheep model, although useful for optimising testing protocols, was not a realistic representation of the human spine. This body of work shows the importance of the VEP in maintaining the healthy functioning of the disc, given its key role in providing nutrition and mechanical support to the disc. Evidence is also provided to correlate spinal degeneration with structural changes in the VEP. Equipped with knowledge of the structure and functions of the VEP, it will be possible to identify the areas prone to damage and therefore the aetiology of degeneration can be clarified.non

ISSLS PRIZE in Clinical Science 2023: comparison of degenerative MRI features of the intervertebral disc between those with and without chronic low back pain. An exploratory study of two large female populations using automated annotation

Objectives The relationship of degeneration to symptoms has been questioned. MRI detects apparently similar disc degeneration and degenerative changes in subjects both with and without back pain. We aimed to overcome these problems by re-annotating MRIs from asymptomatic and symptomatics groups onto the same grading system. Methods We analysed disc degeneration in pre-existing large MRI datasets. Their MRIs were all originally annotated on different scales. We re-annotated all MRIs independent of their initial grading system, using a verified, rapid automated MRI annotation system (SpineNet) which reported degeneration on the Pfirrmann (1–5) scale, and other degenerative features (herniation, endplate defects, marrow signs, spinal stenosis) as binary present/absent. We compared prevalence of degenerative features between symptomatics and asymptomatics. Results Pfirrmann degeneration grades in relation to age and spinal level were very similar for the two independent groups of symptomatics over all ages and spinal levels. Severe degenerative changes were significantly more prevalent in discs of symptomatics than asymptomatics in the caudal but not the rostral lumbar discs in subjects  Conclusions We confirmed age and disc level are significant in determining imaging differences between asymptomatic and symptomatic populations and should not be ignored. Automated analysis, by rapidly combining and comparing data from existing groups with MRIs and information on LBP, provides a way in which epidemiological and ‘big data’ analysis could be advanced without the expense of collecting new groups. Level of evidence I Diagnostic: individual cross-sectional studies with consistently applied reference standard and blinding

Assessment of Lumbar Spine Disc Degeneration in Coherence to Pfirrman Grades and Oswestry Disability Index

Introduction: Intervertebral disc (IVD) degeneration (IDD) is one of the main causes of low back pain (LBP). Standardized diagnostic algorithms for adequate estimation and classification of changes of lumbar discs are mandatory before starting with therapy.Methods: One hundred patients who were indicated for lumbar magnetic resonance imaging (MRI) were included in the study. Pfirrmann grading system was used for the determination of IDD, while the visual analog scale (VAS) is used for evaluation of the intensity of LBP. To quantification of disability for LBP, we used the Oswestry Disability Index (ODI).Result: Results showed higher Pfirrmann grades II and III for L2/L3 and L3/L4 lumbar levels and lower scores at L4/L5 and L5/S1. The analysis also showed low scores at the L2/3 and L3/4 lumbar level for Pfirrmann grades IV and V, and there was an increased at more inferior lumbosacral levels L4/5 and L5/S1. There was a significant correlation between Pfirrmann grades and ODI (p = 0.24) as well as VAS (p = 0.16).Conclusion: Higher Pfirrmann grades correlated with increased ODI and VAS. Therefore, MRI can be used as a strong indicator of clinical appearance, but it is important to take into consideration that LBP should be correlated with clinical features. By summing Pfirrmann grades of all lumbar intervertebral levels in each patient, we can get more accurate insight for the status of the lumbar spine

Learning-based fully automated prediction of lumbar disc degeneration progression with specified clinical parameters and preliminary validation

Background: Lumbar disc degeneration (LDD) may be related to aging, biomechanical and genetic factors. Despite the extensive work on understanding its etiology, there is currently no automated tool for accurate prediction of its progression. / Purpose: We aim to establish a novel deep learning-based pipeline to predict the progression of LDD-related findings using lumbar MRIs. / Materials and methods: We utilized our dataset with MRIs acquired from 1,343 individual participants (taken at the baseline and the 5-year follow-up timepoint), and progression assessments (the Schneiderman score, disc bulging, and Pfirrmann grading) that were labelled by spine specialists with over ten years clinical experience. Our new pipeline was realized by integrating the MRI-SegFlow and the Visual Geometry Group-Medium (VGG-M) for automated disc region detection and LDD progression prediction correspondingly. The LDD progression was quantified by comparing the Schneiderman score, disc bulging and Pfirrmann grading at the baseline and at follow-up. A fivefold cross-validation was conducted to assess the predictive performance of the new pipeline. / Results: Our pipeline achieved very good performances on the LDD progression prediction, with high progression prediction accuracy of the Schneiderman score (Accuracy: 90.2 ± 0.9%), disc bulging (Accuracy: 90.4% ± 1.1%), and Pfirrmann grading (Accuracy: 89.9% ± 2.1%). / Conclusion: This is the first attempt of using deep learning to predict LDD progression on a large dataset with 5-year follow-up. Requiring no human interference, our pipeline can potentially achieve similar predictive performances in new settings with minimal efforts

Generative models : an upcoming innovation in musculoskeletal radiology? A preliminary test in spine imaging

Background Deep learning is a ground-breaking technology that is revolutionising many research and industrial fields. Generative models are recently gaining interest. Here, we investigate their potential, namely conditional generative adversarial networks, in the field of magnetic resonance imaging (MRI) of the spine, by performing clinically relevant benchmark cases. Methods First, the enhancement of the resolution of T2-weighted (T2W) images (super-resolution) was tested. Then, automated image-to-image translation was tested in the following tasks: (1) from T1-weighted to T2W images of the lumbar spine and (2) vice versa; (3) from T2W to short time inversion-recovery (STIR) images; (4) from T2W to turbo inversion recovery magnitude (TIRM) images; (5) from sagittal standing x-ray projections to T2W images. Clinical and quantitative assessments of the outputs by means of image quality metrics were performed. The training of the models was performed on MRI and x-ray images from 989 patients. Results The performance of the models was generally positive and promising, but with several limitations. The number of disc protrusions or herniations showed good concordance (\u3ba = 0.691) between native and super-resolution images. Moderate-to-excellent concordance was found when translating T2W to STIR and TIRM images (\u3ba 65\u20090.842 regarding disc degeneration), while the agreement was poor when translating x-ray to T2W images. Conclusions Conditional generative adversarial networks are able to generate perceptually convincing synthetic images of the spine in super-resolution and image-to-image translation tasks. Taking into account the limitations of the study, deep learning-based generative methods showed the potential to be an upcoming innovation in musculoskeletal radiology