Simplified Universal Grading of Lumbar Spine MRI Degenerative Findings: Inter-Reader Agreement of Non-Radiologist Spine Experts

MRI evaluation of lumbar foraminal stenosis: correlation between a new quantitative evaluation and the qualitative Lee's classification

PURPOSE

Lumbar foraminal stenosis (LFS) accounts 8-11% of leg radiculopathy cases, typically assessed by MRI with qualitative classifications and more recently, quantitative ones. However, a combined surface area assessment of the foramen and exiting nerve root is lacking. We aimed to correlate the Nerve root/Foramen ratio (N/F ratio), a novel quantitative assessment for LFS, with Lee's classification.

METHODS

We studied lumbar spine MRI images of 36 patients eligible for degenerative lumbar spine surgery. Inclusion criteria comprised T2-weighted 3D images (120-210 slices) from L1 to S1 without artifacts. LFS severity was assessed using the N/F ratio and Lee's classification. Image analysis utilized sagittal reconstructions of T2-weighted 3D axial sequences using 3D slicer software. Quantitative analysis of 360 foramens was conducted using manual segmentation to calculate the N/F ratio from the cross-sectional areas of the foramen and exiting nerve root (higher score indicates more severe LFS). Qualitative LFS analysis was based on Lee's classification (grade 0 to 3).

RESULTS

LFS severity (N/F ratio and Lee's grade) increased in the craniocaudal direction. Stratified by level and side, the N/F ratio was significantly correlated with Lee's grade, except for the right L2L3 foramen. Applying a linear mixed model, a positive and significant association was found between Lee's classification and the N/F ratio (β = 0.10 [95%CI: 0.09 ; 0.10]; p < 0.001).

CONCLUSION

The N/F ratio emerges as an objective quantitative measure for LFS correlated to Lee's classification, integrating evaluation of perineural intraforaminal elements and exiting nerve root. Future automating manual segmentation could facilitate rapid LFS evaluation in daily clinic.

Artificial intelligence for segmentation and classification in lumbar spinal stenosis: an overview of current methods

PURPOSE

Lumbar spinal stenosis (LSS) is a frequently occurring condition defined by narrowing of the spinal or nerve root canal due to degenerative changes. Physicians use MRI scans to determine the severity of stenosis, occasionally complementing it with X-ray or CT scans during the diagnostic work-up. However, manual grading of stenosis is time-consuming and induces inter-reader variability as a standardized grading system is lacking. Machine Learning (ML) has the potential to aid physicians in this process by automating segmentation and classification of LSS. However, it is unclear what models currently exist to perform these tasks.

METHODS

A systematic review of literature was performed by searching the Cochrane Library, Embase, Emcare, PubMed, and Web of Science databases for studies describing an ML-based algorithm to perform segmentation or classification of the lumbar spine for LSS. Risk of bias was assessed through an adjusted version of the Newcastle-Ottawa Quality Assessment Scale that was more applicable to ML studies. Qualitative analyses were performed based on type of algorithm (conventional ML or Deep Learning (DL)) and task (segmentation or classification).

RESULTS

A total of 27 articles were included of which nine on segmentation, 16 on classification and 2 on both tasks. The majority of studies focused on algorithms for MRI analysis. There was wide variety among the outcome measures used to express model performance. Overall, ML algorithms are able to perform segmentation and classification tasks excellently. DL methods tend to demonstrate better performance than conventional ML models. For segmentation the best performing DL models were U-Net based. For classification U-Net and unspecified CNNs powered the models that performed the best for the majority of outcome metrics. The number of models with external validation was limited.

CONCLUSION

DL models achieve excellent performance for segmentation and classification tasks for LSS, outperforming conventional ML algorithms. However, comparisons between studies are challenging due to the variety in outcome measures and test datasets. Future studies should focus on the segmentation task using DL models and utilize a standardized set of outcome measures and publicly available test dataset to express model performance. In addition, these models need to be externally validated to assess generalizability.

Association Between Radiological Severity of Lumbar Spinal Stenosis and Spinopelvic Parameters in Adult Patients With Achondroplasia

BACKGROUND AND OBJECTIVES

Adults with achondroplasia are more vulnerable to suffer from neurogenic claudication because of a congenital narrow spinal canal, which makes them susceptible to lumbar spinal stenosis (LSS). The study aims to investigate the correlations between sagittal alignment parameters and the degree of LSS in patients with achondroplasia with LSS.

METHODS

The radiological data of adult achondroplasts presented to the neurosurgical clinic of our medical center from 2019 to 2022 were collected. Lumbar stenosis was graded using the Schizas scale, and the dural sac cross-sectional area (DSCA) was measured. The angles defining the spinopelvic parameters comprising lumbar lordosis, thoracolumbar kyphosis, sagittal vertical axis, pelvic tilt, sacral slope, and pelvic incidence were measured. Spearman or Pearson correlation was used to investigate the association between sagittal misalignment and LSS.

RESULTS

A total of 34 achondroplastics were enrolled, with a median age of 44.3 ± 15.5 years, ranging from 18.6 to 78.5 years. Larger thoracolumbar kyphosis was associated with more severe stenosis according to the Schizas scale of the L 12 lumbar level (r = 0.44, P = .020, 95% CI [0.08, 0.70]). Larger sagittal vertical axis correlated with a smaller DSCA at L 23 (r = -0.53, P = .036, 95% CI [-0.81, -0.04]) and L 45 (r = -0.66, P = .004, 95% CI [-0.87, -0.26]). Larger pelvic tilt was demonstrated to be associated with a smaller DSCA of the L 34 lumbar level (r = -0.42, P = .027, 95% CI [-0.68, -0.05]) and the L 45 lumbar level (r = -0.47, P = .011, 95% CI [-0.71, -0.12]).

CONCLUSION

The upper LSS may be attributed to an increased kyphosis of the thoracolumbar spine. On the contrary, the lower LSS seemed to be correlated with a more backward tilt of the pelvis.

Convolutional Neural Network Incorporating Multiple Attention Mechanisms for MRI Classification of Lumbar Spinal Stenosis

BACKGROUND

Lumbar spinal stenosis (LSS) is a common cause of low back pain, especially in the elderly, and accurate diagnosis is critical for effective treatment. However, manual diagnosis using MRI images is time consuming and subjective, leading to a need for automated methods.

OBJECTIVE

This study aims to develop a convolutional neural network (CNN)-based deep learning model integrated with multiple attention mechanisms to improve the accuracy and robustness of LSS classification via MRI images.

METHODS

The proposed model is trained on a standardized MRI dataset sourced from multiple institutions, encompassing various lumbar degenerative conditions. During preprocessing, techniques such as image normalization and data augmentation are employed to enhance the model's performance. The network incorporates a Multi-Headed Self-Attention Module, a Slot Attention Module, and a Channel and Spatial Attention Module, each contributing to better feature extraction and classification.

RESULTS

The model achieved 95.2% classification accuracy, 94.7% precision, 94.3% recall, and 94.5% F1 score on the validation set. Ablation experiments confirmed the significant impact of the attention mechanisms in improving the model's classification capabilities.

CONCLUSION

The integration of multiple attention mechanisms enhances the model's ability to accurately classify LSS in MRI images, demonstrating its potential as a tool for automated diagnosis. This study paves the way for future research in applying attention mechanisms to the automated diagnosis of lumbar spinal stenosis and other complex spinal conditions.

Prediction of transforaminal epidural injection success in sciatica (POTEISS): a protocol for the development of a multivariable prediction model for outcome after transforaminal epidural steroid injection in patients with lumbar radicular pain due to disc herniation or stenosis

BACKGROUND

Transforaminal epidural injections (TEI) can alleviate symptoms and help to maintain physical functioning and quality of life in patients with lumbar radicular pain. We aim to develop a prediction model for patient outcome after TEI in patients suffering from unilateral lumbar radicular pain due to lumbar disc herniation (LDH) or single-level spinal stenosis (LSS). The secondary aim is to estimate short-term patient outcome differences between LDH and LSS patients, the association between psychological variables and patient outcome, the rate of additional injections, surgery and complications, and to explore the short-term cost-effectiveness of TEI.

METHODS

This study is designed as a multi-centre, observational, prospective cohort study in two large regional hospitals in the Netherlands. Patients diagnosed with unilateral lumbar radicular pain secondary to LDH or LSS and congruent with MRI findings, who are referred for TEI along usual care pathways, are eligible for study participation. A total of 388 patients with LDH or LSS will be included. A pre-defined set of demographic, clinical and radiological variables will be used as the predictors in the model. The primary outcome measure is the Numerical Rating Scale (NRS) for leg pain. Secondary outcome measures include back pain, physical functioning, perceived recovery, pain coping strategies, anxiety and depression and use of analgesics and physical therapy. Patients will be evaluated at baseline, 2 weeks and 6 weeks after treatment. NRS leg pain and Likert perceived recovery data will be used as the dependent variables in a generalized linear mixed model for prediction of TEI outcome, with internal validation of performance (explained variation) by bootstrap resampling. Cost-effectiveness for a period of 6 weeks prior to and after treatment will be performed with decision-analytic modelling.

DISCUSSION

Patients with severe lumbar radicular pain often request additional treatment when conservative care is insufficient. TEI can offer relief of symptoms. Currently, it is not possible to predict responsiveness to this treatment for individual patients. This study is designed to explore predictors that can differentiate between patients that will and will not have a positive outcome after TEI. This information may support treatment strategies for this patient group.

TRIAL REGISTRATION

This study is registered at ClinicalTrials.gov database under registry number NCT04540068 on September 1, 2020.

Reporting of Facet Joint Inflammation in Lumbar Spine MRI Studies in Patients With Low Back Pain

STUDY DESIGN

Retrospective.

OBJECTIVE

We aimed to assess the frequency of facet joint inflammatory features noted in routine radiology reports of lumbar spine magnetic resonance imaging (MRI) studies among patients with chronic low back pain.

SUMMARY OF BACKGROUND DATA

Facet joint arthropathy is one of the most common causes of chronic low back pain. It may encompass various inflammatory imaging characteristics, such as facet joint effusion, bone marrow edema, and soft tissue edema. The extent to which radiology reports mention inflammatory features of the lumbar facet joints and the accuracy of these reports have not been investigated.

MATERIALS AND METHODS

The authors performed a chart review on 49 subjects with previous facet-related interventions ( i.e . medial branch blocks or intra-articular facet joint injection) and MRI available in the medical record. One senior musculoskeletal radiologist and a musculoskeletal radiology fellow graded the inflammatory features using a published facet joint inflammation grading system [Gold Standard (GS)]. The authors identified the inflammatory markers mentioned in the radiology reports and calculated the sensitivity and positive predictive value of the radiology reports compared with GS readings.

RESULTS

Compared with the GS, the sensitivity of radiology reports for facet joint effusion, bone marrow, and soft tissue edema ranged from 6% to 22%, and the positive predictive value ranged from 25% to 100%. L4/5 had the highest number of cases with inflammatory features noted on the reports.

CONCLUSION

Inflammatory findings, such as facet joint effusion, bone marrow edema, and soft tissue edema, are not commonly identified in radiology reports. Further investigations are needed to determine the clinical importance of MRI-detected lumbar facet joint inflammatory features as a potential mechanism of nociception and as a predictor of outcomes following injections or other therapies.

Comprehensive Grading System of Inflammatory Features of the Lumbar Facet Joints on Magnetic Resonance Imaging

STUDY DESIGN

Retrospective.

OBJECTIVE

We aimed to describe a magnetic resonance imaging (MRI)-based grading system of inflammatory features of the lumbar facet joints using an atlas and assess its reliability.

SUMMARY OF BACKGROUND DATA

Chronic low back pain is often caused by facet joint arthropathy. Inflammatory features are often evident on MRI. While several grading systems of facet arthropathy have been described, there is scant data on the reliability of these systems, and none focus exclusively on inflammatory features.

MATERIALS AND METHODS

We describe a grading system that assesses facet joint effusion, bone marrow edema, and soft tissue edema. Each feature was graded from 0 to 3 (facet edema) or 0 to 2 (bone marrow edema intensity and extent, soft tissue edema intensity and extent). Four spine experts graded MRIs of 50 subjects at the bilateral L3/4, L4/5, and L5/S1 levels. All subjects had symptomatic facet arthropathy and received therapeutic facet joint injections. We assessed the intra-reader and inter-reader reliability of each feature at each joint and summarized across all six joints.

RESULTS

The mean age of subjects was 56 years (SD = 17), and 48% were female. The injections occurred at the L3/4 level in 12% of cases, at L4/5 in 88%, and at L5/S1 in 80% of cases. The intra-reader reliability kappa's for each feature ranged from 0.42 to 0.81. In contrast, the inter-reader reliability kappa values for each feature ranged from 0.37 to 0.54.

CONCLUSION

MRI inflammatory features of the lumbar facet joints are often noted in patients with low back pain. The proposed grading system is reliable and could serve as a research tool for studies assessing the clinical relevance and prognostic value of these features.

Grading Systems of Lumbar Facet Joint Inflammatory Changes on Magnetic Resonance Imaging: A Scoping Review

STUDY DESIGN

A scoping review.

OBJECTIVE

We aimed to identify and characterize grading systems of the inflammatory features of the lumbar facet joints (FJs) noted on magnetic resonance imaging and summarize their reliability.

SUMMARY OF BACKGROUND DATA

Chronic low back pain is one of the most common causes of disability worldwide and is frequently accompanied by FJ osteoarthritis. Inflammatory changes in the lumbar FJs are commonly noted in imaging studies of patients with FJ osteoarthritis and low back pain. Several grading systems for these inflammatory changes have been developed. However, these grading system's features and reliability have yet to be reviewed.

MATERIALS AND METHODS

We performed a literature search of studies reporting grading systems for FJ inflammatory changes published in English or Spanish between 1985 and 2022. We collected data on reported interreader reliability measures of each grading system. Finally, we compared the features of inflammation described by each system.

RESULTS

Six studies met the inclusion criteria and were used in our analysis. Features commonly graded in these systems are the hyperintensity signal noted within the FJ, bone marrow edema, and the extent of the soft-tissue edema surrounding the FJs. We found that the interreader reliability measures ranged from 0.56 to 0.96.

CONCLUSIONS

Only 6 studies have reported methods for documenting inflammation in the FJs. Studies varied in the precise tissues and phenomena included in the grading systems. However, the systems were generally reliable. Future studies should document the reliability of these methods when independent investigators are not involved in developing the classification schemes. Further work might combine one or more of these measures to establish a standard and reliable grading system for inflammatory changes in the FJs, including signal intensity within the joint, bone marrow edema, and soft-tissue inflammation.

The current state of radiodiagnostics of degenerative changes in the lumbar spine (literature review)

Examination of the spine using radiological methods remains the most frequently conducted study in the outpatient practice of almost any radiologist. In most cases, changes in the spine are degenerative and dystrophic in nature. These changes in the spine are the leading cause of loss of activity among adults and the elderly, and cover a wide range of age-related structural changes. It is of great importance to understand the possibilities and limitations of radiological methods of diagnostics. The description of morphological changes observed in degenerative and dystrophic changes requires the use of unified terminology and classifications among clinicians and radiologists.The aim. To present modern concepts in the assessment of degenerative changes of the spine using radiological methods. A description of the standardized international nomenclature of intervertebral disc pathology and current classifications of spinal canal stenosis are presented.Material and methods. For literature search, we used electronic databases MEDLINE (PubMed), eLibrary, EMBASE and Cochrane Library with a selection of sources published from 2000 to 2021. We analyzed the works devoted to the diagnosis of degenerative changes in lumbar spine and to degenerative stenosis.Conclusion. The key to productive communication between physicians is the uniformity or standardization of terminology and definitions used. It is important that the protocol of description, its terms, semantic expressions be uniform and understandable to specialists who are involved in the diagnosis and treatment of the spine. Magnetic resonance imaging is a valuable method in the diagnosis of degenerative changes of the spinal column, but it has its limitations.

Standardized Classification of Lumbar Spine Degeneration on Magnetic Resonance Imaging Reduces Intra- and Inter-subspecialty Variability

BACKGROUND AND PURPOSE

To determine the efficacy of standardized definitions of degenerative change in reducing variability in interpretation of lumbar spine magnetic resonance imaging within and between groups of subspecialty-trained neuroradiologists (NR) and musculoskeletal radiologists (MSK).

MATERIALS AND METHODS

Six radiologists, three from both NR and MSK groups were trained on a standardized classification system of degenerative change. After an 11-month washout period, they independently re-interpreted fifty exams at the L4-L5 and L5-S1 levels. Responses were converted to a six-point ordinal scale for the assessment of neural foraminal stenosis and spinal canal stenosis (SCS), three-point scale for lateral recess stenosis, and four-point scale for facet osteoarthritis (FO). Intra-subspecialty and inter-subspecialty analysis was performed using the weighted Cohen's kappa with a binary matrix of all reader pairs.

RESULTS

Inter-subspecialty agreement improved from k=0.527 (moderate) to k=0.602 (substantial) for neural foraminal stenosis, from k=0.540 (moderate) to k=0.652 (substantial) for SCS, from k=0.0818 (slight) to k=0.337 (fair) for lateral recess stenosis, and from k=0.176 (slight) to k=0.495 (moderate) for FO. The NR group demonstrated improved intra-subspecialty agreement for the assessment of SCS, from k=0.368 (fair) to k=0.638 (substantial). The MSK group demonstrated improved intra-subspecialty agreement for the assessment of FO, from k=0.134 (slight) to k=0.413 (moderate). Intra-subspecialty agreement was similar for other parameters before and after training.

CONCLUSIONS

As result of the standardized definitions training, the NR and MSK groups each improved in one of the four parameters, while inter-subspecialty variability improved in all four parameters. These definitions may be useful in clinical practice across radiology subspecialties.