Semiautomatic Assessment of Facet Tropism From Lumbar Spine MRI Using Deep Learning: A Northern Finland Birth Cohort Study.

STUDY DESIGN: This is a retrospective, cross-sectional, population-based study that automatically measured the facet joint (FJ) angles from T2-weighted axial magnetic resonance imagings (MRIs) of the lumbar spine using deep learning (DL). OBJECTIVE: This work aimed to introduce a semiautomatic framework that measures the FJ angles using DL and study facet tropism (FT) in a large Finnish population-based cohort. SUMMARY OF DATA: T2-weighted axial MRIs of the lumbar spine (L3/4 through L5/S1) for (n=1288) in the NFBC1966 Finnish population-based cohort were used for this study. MATERIALS AND METHODS: A DL model was developed and trained on 430 participants' MRI images. The authors computed FJ angles from the model's prediction for each level, that is, L3/4 through L5/S1, for the male and female subgroups. Inter-rater and intrarater reliability was analyzed for 60 participants using annotations made by two radiologists and a musculoskeletal researcher. With the developed method, we examined FT in the entire NFBC1966 cohort, adopting the literature definitions of FT thresholds at 7° and 10°. The rater agreement was evaluated both for the annotations and the FJ angles computed based on the annotations. FJ asymmetry ( - was used to evaluate the agreement and correlation between the raters. Bland-Altman analysis was used to assess the agreement and systemic bias in the FJ asymmetry. The authors used the Dice score as the metric to compare the annotations between the raters. The authors evaluated the model predictions on the independent test set and compared them against the ground truth annotations. RESULTS: This model scored Dice (92.7±0.1) and intersection over union (87.1±0.2) aggregated across all the regions of interest, that is, vertebral body (VB), FJs, and posterior arch (PA). The mean FJ angles measured for the male and female subgroups were in agreement with the literature findings. Intrarater reliability was high, with a Dice score of VB (97.3), FJ (82.5), and PA (90.3). The inter-rater reliability was better between the radiologists with a Dice score of VB (96.4), FJ (75.5), and PA (85.8) than between the radiologists and the musculoskeletal researcher. The prevalence of FT was higher in the male subgroup, with L4/5 found to be the most affected region. CONCLUSION: The authors developed a DL-based framework that enabled us to study FT in a large cohort. Using the proposed method, the authors present the prevalence of FT in a Finnish population-based cohort.

Cartilaginous endplates: A comprehensive review on a neglected structure in intervertebral disc research.

The cartilaginous endplates (CEP) are key components of the intervertebral disc (IVD) necessary for sustaining the nutrition of the disc while distributing mechanical loads and preventing the disc from bulging into the adjacent vertebral body. The size, shape, and composition of the CEP are essential in maintaining its function, and degeneration of the CEP is considered a contributor to early IVD degeneration. In addition, the CEP is implicated in Modic changes, which are often associated with low back pain. This review aims to tackle the current knowledge of the CEP regarding its structure, composition, permeability, and mechanical role in a healthy disc, how they change with degeneration, and how they connect to IVD degeneration and low back pain. Additionally, the authors suggest a standardized naming convention regarding the CEP and bony endplate and suggest avoiding the term vertebral endplate. Currently, there is limited data on the CEP itself as reported data is often a combination of CEP and bony endplate, or the CEP is considered as articular cartilage. However, it is clear the CEP is a unique tissue type that differs from articular cartilage, bony endplate, and other IVD tissues. Thus, future research should investigate the CEP separately to fully understand its role in healthy and degenerated IVDs. Further, most IVD regeneration therapies in development failed to address, or even considered the CEP, despite its key role in nutrition and mechanical stability within the IVD. Thus, the CEP should be considered and potentially targeted for future sustainable treatments.

Are current machine learning applications comparable to radiologist classification of degenerate and herniated discs and Modic change? A systematic review and meta-analysis.

INTRODUCTION: Low back pain is the leading contributor to disability burden globally. It is commonly due to degeneration of the lumbar intervertebral discs (LDD). Magnetic resonance imaging (MRI) is the current best tool to visualize and diagnose LDD, but places high time demands on clinical radiologists. Automated reading of spine MRIs could improve speed, accuracy, reliability and cost effectiveness in radiology departments. The aim of this review and meta-analysis was to determine if current machine learning algorithms perform well identifying disc degeneration, herniation, bulge and Modic change compared to radiologists. METHODS: A PRISMA systematic review protocol was developed and four electronic databases and reference lists were searched. Strict inclusion and exclusion criteria were defined. A PROBAST risk of bias and applicability analysis was performed. RESULTS: 1350 articles were extracted. Duplicates were removed and title and abstract searching identified original research articles that used machine learning (ML) algorithms to identify disc degeneration, herniation, bulge and Modic change from MRIs. 27 studies were included in the review; 25 and 14 studies were included multi-variate and bivariate meta-analysis, respectively. Studies used machine learning algorithms to assess LDD, disc herniation, bulge and Modic change. Models using deep learning, support vector machine, k-nearest neighbors, random forest and naïve Bayes algorithms were included. Meta-analyses found no differences in algorithm or classification performance. When algorithms were tested in replication or external validation studies, they did not perform as well as when assessed in developmental studies. Data augmentation improved algorithm performance when compared to models used with smaller datasets, there were no performance differences between augmented data and large datasets. DISCUSSION: This review highlights several shortcomings of current approaches, including few validation attempts or use of large sample sizes. To the best of the authors' knowledge, this is the first systematic review to explore this topic. We suggest the utilization of deep learning coupled with semi- or unsupervised learning approaches. Use of all information contained in MRI data will improve accuracy. Clear and complete reporting of study design, statistics and results will improve the reliability and quality of published literature.

External Validation of SpineNet, an Open-Source Deep Learning Model for Grading Lumbar Disk Degeneration MRI Features, Using the Northern Finland Birth Cohort 1966.

STUDY DESIGN: This is a retrospective observational study to externally validate a deep learning image classification model. OBJECTIVE: Deep learning models such as SpineNet offer the possibility of automating the process of disk degeneration (DD) classification from magnetic resonance imaging (MRI). External validation is an essential step to their development. The aim of this study was to externally validate SpineNet predictions for DD using Pfirrmann classification and Modic changes (MCs) on data from the Northern Finland Birth Cohort 1966 (NFBC1966). SUMMARY OF DATA: We validated SpineNet using data from 1331 NFBC1966 participants for whom both lumbar spine MRI data and consensus DD gradings were available. MATERIALS AND METHODS: SpineNet returned Pfirrmann grade and MC presence from T2-weighted sagittal lumbar MRI sequences from NFBC1966, a data set geographically and temporally separated from its training data set. A range of agreement and reliability metrics were used to compare predictions with expert radiologists. Subsets of data that match SpineNet training data more closely were also tested. RESULTS: Balanced accuracy for DD was 78% (77%-79%) and for MC 86% (85%-86%). Interrater reliability for Pfirrmann grading was Lin concordance correlation coefficient=0.86 (0.85-0.87) and Cohen κ=0.68 (0.67-0.69). In a low back pain subset, these reliability metrics remained largely unchanged. In total, 20.83% of disks were rated differently by SpineNet compared with the human raters, but only 0.85% of disks had a grade difference >1. Interrater reliability for MC detection was κ=0.74 (0.72-0.75). In the low back pain subset, this metric was almost unchanged at κ=0.76 (0.73-0.79). CONCLUSIONS: In this study, SpineNet has been benchmarked against expert human raters in the research setting. It has matched human reliability and demonstrates robust performance despite the multiple challenges facing model generalizability.

Immediate effects and associations between interoceptive accuracy and range of motion after a HVLA thrust on the thoracolumbar junction: A randomised controlled trial.

BACKGROUND: There is paucity in the literature regarding the role of interoceptive accuracy (IAc) at predicting the effectiveness of osteopathic techniques which increase spinal mobility when directed specifically at the thoracolumbar junction (TLJ). AIMS: The study aimed to explore whether a high velocity, low amplitude (HVLA) thrust of the TLJ would increase spinal mobility (measured through Range of Motion; ROM) and change IAc. Also, whether baseline IAc correlated with the post-ROM measures and change in ROM. METHOD: 21 asymptomatic participants were allocated into three conditions in a randomised order. These were; (1) a high velocity low amplitude manipulation of the TLJ; (2) sham (basic touch); and (3) a control (laying supine on a plinth). Before and following each intervention, the participants' spinal ROM was measured using an Acumar digital inclinometer. In addition to this an ECG was used to measure their pre and post condition IAc. RESULTS: There were significant increases in ROM for all condition, however, the HVLA thrust led to a significantly greater increase in ROM (p < 0.001) when compared to the control and sham. Baseline IAc was inversely associated with post-ROM but there was no association with change in ROM. The HVLA thrust did not significantly change IAc scores from pre to post intervention. CONCLUSIONS: HVLA thrust over the TLJ is a useful intervention for increasing spinal ROM. IAc maybe a useful predictor for intervention effectiveness of this technique and spinal area which could in the future be utilised by osteopaths as part of their diagnostics.

Immediate biomechanical, systemic, and interoceptive effects of myofascial release on the thoracic spine: A randomised controlled trial.

BACKGROUND: Myofascial release (MFR) is used to restore tissue extensibility of the fascia tissue and is considered to be useful in a number of clinical settings such as low back pain, ankle injuries, fibromyalgia, and headaches. There is, however, despite the popularity of MFR in manual therapy, little consensus on whether it leads to biomechanical, systemic or interoceptive outcomes. AIMS: This study aimed to explore the immediate biomechanical (increased elasticity for increased range of motion), systemic (local vs. distal areas of pain threshold) and bodily awareness effects (interoception) of a myofascial release technique on the thoracic spine. METHOD: Twelve healthy participants took part in this triple-bind, repeated measures, cross-over design study, and were randomised into counterbalanced sequences of three conditions; a control, a sham, and the MFR condition. The outcome measures used were; range of motion (ROM), pain pressure thresholds (PPT), and interoceptive sensitivity (IS) to assess biomechanical, systemic, and interoceptive effects of MFR. RESULTS: There were significant increases in ROM and PPT (both local and distal) post MFR intervention. There was also a positive correlation between baseline interoceptive sensitivity and post-MFR ROM and a negative correlation for baseline interoceptive sensitivity and post-MRF PPT. Interoceptive sensitivity did increase post-MFR but this was non-significant. CONCLUSIONS: The increase in ROM suggests that the MFR may have caused a biomechanical change in tissue elasticity creating an increase in tissue flexibility. The increase in both local and distal sites of the PPT suggest an overall systemic response to the therapy. The correlation between baseline IS and post-MFR ROM and PPT suggest that IS may be usefully applied as a predictor for ROM and PPT post-MFR.

The immediate effects of sigmoid colon manipulation on pressure pain thresholds in the lumbar spine.

Visceral manual therapy is increasingly used by UK osteopaths and manual therapists, but there is a paucity of research investigating its underlying mechanisms, and in particular in relation to hypoalgesia. The aim of this study was to investigate the immediate effects of osteopathic visceral mobilisation on pressure pain thresholds. A single-blinded, randomised, within subjects, repeated measures design was conducted on 15 asymptomatic subjects. Pressure pain thresholds were measured at the L1 paraspinal musculature and 1st dorsal interossei before and after osteopathic visceral mobilisation of the sigmoid colon. The results demonstrated a statistically significant improvement in pressure pain thresholds immediately after the intervention (P<0.001). This effect was not observed to be systemic, affecting only the L1 paraspinal musculature. This novel study provides new experimental evidence that visceral manual therapy can produce immediate hypoalgesia in somatic structures segmentally related to the organ being mobilised, in asymptomatic subjects.