Degenerative lumbar spinal canal stenosis: intra- and inter-reader agreement for magnetic resonance imaging parameters

Inter-observer variability in the classification of lumbar foraminal stenosis in magnetic resonance imaging using different evaluation scales

BACKGROUND

The evaluation of lumbar spine degeneration on magnetic resonance imaging (MRI) is prone to inter-reader variability, including when assessing foraminal changes. This variability, often due to subjective criteria and inconsistent terminology, may affect clinical correlations. Standardized criteria could help improve agreement among readers.

MATERIALS AND METHODS

MRI of the lumbar spine of 50 randomly selected patients were evaluated by 12 independent readers. Foraminal stenosis was assessed using four different rating scales for each patient. The first scale classified stenosis as presence/absence of neurologic compromise of the spinal nerve root at the foramen, the second scale classified stenosis as absent/mild/moderate/severe, the third scale as normal/contact of disk or osteophyte with the nerve root/deviation of the nerve root/compression of the nerve root, and the fourth scale utilized the Lee et al. criteria. Agreement analysis was performed using Fleiss' kappa coefficients.

RESULTS

Agreement was moderate using the first scale (k = 0.439), and significantly lower using the second, third and fourth scales (k = 0.310, k = 0.311, k = 0.295, respectively). When comparing the agreements obtained between board certified neuroradiologists and between neuroradiology residents, there was statistically significant differences when using the third and fourth scales, where the agreement for board certified neuroradiologists was higher, but still only fair. Individual kappas showed that in the second, third, and fourth scales the levels of agreement were higher in the extremes of the scale, namely, when there was no stenosis or when the stenosis was maximal with nerve compression.

CONCLUSIONS

Levels of agreement can differ depending on the scale used. Simpler dichotomous scales may return higher levels of agreement compared to more complex ones. For the non-dichotomous scales, using different scales may not result in overall different levels of agreement. Given the overall low inter-rater agreements observed, there is probably significant potential to enhance agreement through more rigorous training and consensus-building.

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.

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.

Axial T1-weighted imaging of the lumbar spine: a redundancy or an asset?

OBJECTIVE

To determine the diagnostic value of axial T1-weighted imaging for patients suffering from lower back pain.

MATERIALS AND METHODS

In this retrospective study, 100 consecutive lumbar spine MRIs obtained in patients with chronic low back pain were reviewed in two sessions: First, readers viewed core sequences (sagittal T1-weighted, STIR and T2-weighted, and axial T2-weighted) with axial T1-weighted sequences, and second, readers viewed cores sequences alone. Readers recorded the presence of disc degeneration, nerve root compromise, facet joint arthritis, and stenosis at each lumbar spine level as well as the presence of lipoma of filum terminale (LFT), spondylolisthesis, transitional vertebrae, and fractures. The McNemar, Wilcoxon signed-rank, and student T tests were utilized.

RESULTS

For 100 studies, 5 spine levels were evaluated (L1-L2 through L5-S1). There were cases of disc disease (444/500 bulges, 56/500 herniations), nerve root compromise (1/500 nerve enlargement, 36/500 contact only, 20/500 displacement or compression), facet arthritis (438/500), stenosis (58/500 central canal, 64/500 lateral recess, 137/500 neuroforaminal), 6/100 LFTs, and other abnormalities (58/500 spondylolisthesis, 10/100 transitional vertebrae, 10/500 fracture/spondylolysis). There was no difference in diagnostic performance between the interpretation sessions (with and without axial T1-weighted imaging) at any level (p > 0.05), although four small additional LFTs were identified with axial T1-weighted imaging availability.

CONCLUSION

There was no clinically significant difference in the interpretation of lumbar spine MRI viewed with and without axial T1-weighted imaging, suggesting that the axial T1-weighted sequence does not add diagnostic value to routine lumbar spine MRI.

Effectiveness of X-stop Interspinous Distractor Device Versus Laminectomy for Treatment of Lumbar Stenosis: A Systematic Review and Meta-Analysis

Lumbar spinal stenosis refers to the narrowing of the spinal canal in the lumbar region. There is an increasing need to determine the treatment modality for lumbar spinal stenosis by comparing the outcomes of X-stop interspinous distractors and laminectomy. The objective of this study is to determine the effectiveness of the X-stop interspinous distractor compared to laminectomy. This systematic review fundamentally abides by the procedures delineated in the Cochrane methodology while the reporting is done according to the Preferred Reporting Items for Systematic Review and Meta-Analyses guidelines. Three databases searched generated a total of 943 studies, with PubMed being the source for the bulk of the articles. Six studies were selected for inclusion in this study. The effectiveness of the interspinous distractor devices and laminectomy can be determined through their impact on the quality of life, rates of complications, and the amount of money utilized. This meta-analysis fundamentally emphasizes that laminectomy is a more effective intervention for the treatment of lumbar spinal stenosis as it is more cost-effective and results in fewer complications in the long term.

The reliability, correlation with clinical symptoms and surgical outcomes of dural sac cross-sectional area, nerve root sedimentation sign and morphological grade for lumbar spinal stenosis

BACKGROUND

No study had directly compared the reliability, correlation with clinical symptoms, and surgical outcomes of dural sac cross-sectional area (DCSA), nerve root sedimentation sign (SedSign), and morphological grade for lumbar spinal stenosis (LSS).

METHODS

From January 2017 to December 2020, 202 patients with LSS were retrospectively analyzed. The narrowest segments were assessed via T2-weighted cross-sectional images using DCSA, morphological grade, and SedSign by two independent observers. Three classifications' reliabilities were evaluated. Correlations between three classifications and between each of the classifications and symptoms or surgical outcomes 12 months postoperatively were evaluated.

RESULTS

There were 144 males and 58 females; 23, 52, and 127 patients had the narrowest segment in L2-3, L3-4, and L4-5, respectively. The intra-observer reliability of DCSA ranged from 0.91 to 0.93, and the inter-observer reliability was 0.90. The intra-observer reliability of SedSign ranged from 0.83 to 0.85, and the inter-observer reliability was 0.75. The intra-observer reliability of morphological grade ranged from 0.72 to 0.78, and the inter-observer reliability was 0.61. Each of these classifications was correlated with the other two (P < 0.01). For preoperative symptoms, DCSA was correlated with leg pain (LP) (r =  - 0.14), Oswestry Disability Index (ODI) (r =  - 0.17), and claudication (r =  - 0.19). Morphological grade was correlated with LP (r = 0.19) and claudication (r = 0.27). SedSign was correlated with ODI (r = 0.23). For postoperative outcomes, morphological grade was correlated with LP (r =  - 0.14), and SedSign was correlated with ODI (r = 0.17).

CONCLUSIONS

Substantial to almost perfect intra and inter-observer reliabilities for the three classifications were found; however, these classifications had either weak correlations with symptoms and surgical outcomes or none at all. Based on our findings, using one of them without conducting other tests for LSS will have limited or uncertain value in surgical decision-making or evaluating the prognostic value.

The Effect of Paraspinal Fatty Muscle Infiltration and Cumulative Lumbar Spine Degeneration on the Outcome of Patients With Lumbar Spinal Canal Stenosis: Analysis of the Lumbar Stenosis Outcome Study (LSOS) Data

STUDY DESIGN

Prospective.

OBJECTIVE

To investigate the influence of paraspinal fatty muscle infiltration (FMI) and cumulative lumbar spine degeneration as assessed by magnetic resonance imaging on long-term clinical outcome measures in patients with lumbar spinal canal stenosis (LSCS) of the Lumbar Stenosis Outcome Study (LSOS) cohort.

SUMMARY OF BACKGROUND DATA

Past studies have tried to establish correlations of morphologic imaging findings in LSCS with clinical endpoints. However, the impact of FMI and overall lumbar spinal degeneration load has not been examined yet.

MATERIALS AND METHODS

Patients from the LSOS cohort with moderate to severe LSCS were included. Two radiologists assessed the degree of LSCS as well as cumulative degeneration of the lumbar spine. FMI was graded using the Goutallier scoring system. Spinal Stenosis Measure (SSM) was used to measure the severity level of symptoms and disability. European Quality of Life 5 Dimensions 3 Level Version (EQ-5D-3L) was used to measure health-related quality of life.

RESULTS

The nonsurgically treated group consisted of 116 patients (age 74.8±8.5 yr), whereas the surgically treated group included 300 patients (age 72.3±8.2 yr). Paraspinal FMI was significantly different between the groups (54.3% vs. 32.0% for Goutallier grade ≥2; P <0.001). Total degeneration score was comparable in both groups (9.5±2.0 vs. 9.3±2.0; P =0.418). FMI was associated with lower SSM function and lower EQ-5D-3L (all P <0.05), but not with SSM symptoms. Total degeneration of the lumbar spine was associated neither with SSM symptoms, nor with SSM function, nor with EQ-5D-3L (all P >0.05).

CONCLUSIONS

FMI is associated with higher disability and worse health-related quality of life of LSCS patients in the LSOS cohort. There was no significant association between total cumulative lumbar spine degeneration and the outcome of either surgically or nonsurgically treated patients.

LEVEL OF EVIDENCE

3.

Japanese Orthopaedic Association (JOA) clinical practice guidelines on the management of lumbar spinal stenosis, 2021 - Secondary publication

BACKGROUND

The Japanese Orthopaedic Association (JOA) guideline for the management of lumbar spinal stenosis (LSS) was first published in 2011. Since then, the medical care system for LSS has changed and many new articles regarding the epidemiology and diagnostics of LSS, conservative treatments such as new pharmacotherapy and physical therapy, and surgical treatments including minimally invasive surgery have been published. In addition, various issues need to be examined, such as verification of patient-reported outcome measures, and the economic effect of revised medical management of patients with lumbar spinal disorders. Accordingly, in 2019 the JOA clinical guidelines committee decided to update the guideline and consequently established a formulation committee. The purpose of this study was to describe the formulation we implemented for the revision of the guideline, incorporating the recent advances of evidence-based medicine.

METHODS

The JOA LSS guideline formulation committee revised the previous guideline based on the method for preparing clinical guidelines in Japan proposed by the Medical Information Network Distribution Service in 2017. Background and clinical questions were determined followed by a literature search related to each question. Appropriate articles based on keywords were selected from all the searched literature. Using prepared structured abstracts, systematic reviews and meta-analyses were performed. The strength of evidence and recommendations for each clinical question was decided by the committee members.

RESULTS

Eight background and 15 clinical questions were determined. Answers and explanations were described for the background questions. For each clinical question, the strength of evidence and the recommendation were both decided, and an explanation was provided.

CONCLUSIONS

The 2021 clinical practice guideline for the management of LSS was completed according to the latest evidence-based medicine. We expect that this guideline will be useful for all medical providers as an index in daily medical care, as well as for patients with LSS.

Added value of ultra-short echo time and fast field echo using restricted echo-spacing MR imaging in the assessment of the osseous cervical spine

PURPOSE

To evaluate the added value of ultra-short echo time (UTE) and fast field echo resembling a CT using restricted echo-spacing (FRACTURE) MR sequences in the assessment of the osseous cervical spine using CT as reference.

MATERIALS AND METHODS

Twenty-seven subjects underwent postmortem CT and MRI within 48 h. Datasets were anonymized and analyzed retrospectively by two radiologists. Morphological cervical spine alterations were rated on CT, UTE and FRACTURE images. Afterward, neural foraminal stenosis was graded on standard MR and again after viewing additional UTE/FRACTURE sequences. To evaluate interreader and intermodality reliability, intra-class correlation coefficients (ICC) and for stenosis grading Wilcoxon-matched-pairs testing with multiple comparison correction were calculated.

RESULTS

Moderate interreader reliability (ICC = 0.48-0.71) was observed concerning morphological findings on all modalities. Intermodality reliability was good between modalities regarding degenerative vertebral and joint alterations (ICC = 0.69-0.91). Compared to CT neural stenosis grades were more often considered as nonsignificant on all analyzed MR sequences. Neural stenosis grading scores differed also significantly between specific bone imaging sequences, UTE and FRACTURE, to standard MR sequences. However, no significant difference was observed between UTE and FRACTURE sequences.

CONCLUSION

Compared to CT as reference, UTE or FRACTURE sequence added to standard MR sequences can deliver comparable information on osseous cervical spine status. Both led to changes in clinically significant stenosis gradings when added to standard MR, mainly reducing the severity of neural foramina stenosis.

External validation of the deep learning system "SpineNet" for grading radiological features of degeneration on MRIs of the lumbar spine

BACKGROUND

Magnetic resonance imaging (MRI) is used to detect degenerative changes of the lumbar spine. SpineNet (SN), a computer vision-based system, performs an automated analysis of degenerative features in MRI scans aiming to provide high accuracy, consistency and objectivity. This study evaluated SN's ratings compared with those of an expert radiologist.

METHOD

MRIs of 882 patients (mean age, 72 ± 8.8 years) with degenerative spinal disorders from two previous trials carried out in our spine center between 2011 and 2019, were analyzed by an expert radiologist. Lumbar segments (L1/2-L5/S1) were graded for Pfirrmann Grades (PG), Spondylolisthesis (SL) and Central Canal Stenosis (CCS). SN's analysis for the equivalent parameters was generated. Agreement between methods was analyzed using kappa (κ), Spearman correlation (ρ) and Lin's concordance correlation (ρ_c) coefficients and class average accuracy (CAA).

RESULTS

4410 lumbar segments were analyzed. κ statistics showed moderate to substantial agreement in PG between the radiologist and SN depending on spinal level (range κ 0.63-0.77, all levels together 0.72; range CAA 45-68%, all levels 55%), slight to substantial agreement for SL (range κ 0.07-0.60, all levels 0.63; range CAA 47-57%, all levels 56%) and CCS (range κ 0.17-0.57, all levels 0.60; range CAA 35-41%, all levels 43%). SN tended to record more pathological features in PG than did the radiologist whereas the contrary was the case for CCS. SL showed an even distribution between methods.

CONCLUSION

SN is a robust and reliable tool with the ability to grade degenerative features such as PG, SL or CCS in lumbar MRIs with moderate to substantial agreement compared to the current gold-standard, the radiologist. It is a valuable alternative for analyzing MRIs from large cohorts for diagnostic and research purposes.

Reliability of preoperative MRI findings in patients with lumbar spinal stenosis

Background

Magnetic Resonance Imaging (MRI) is an important tool in preoperative evaluation of patients with lumbar spinal stenosis (LSS). Reported reliability of various MRI findings in LSS varies from fair to excellent. There are inconsistencies in the evaluated parameters and the methodology of the studies. The purpose of this study was to evaluate the reliability of the preoperative MRI findings in patients with LSS between musculoskeletal radiologists and orthopaedic spine surgeons, using established evaluation methods and imaging data from a prospective trial.

Methods

Consecutive lumbar MRI examinations of candidates for surgical treatment of LSS from the Norwegian Spinal Stenosis and Degenerative Spondylolisthesis (NORDSTEN) study were independently evaluated by two musculoskeletal radiologists and two orthopaedic spine surgeons. The observers had a range of experience between six and 13 years and rated five categorical parameters (foraminal and central canal stenosis, facet joint osteoarthritis, redundant nerve roots and intraspinal synovial cysts) and one continuous parameter (dural sac cross-sectional area). All parameters were re-rated after 6 weeks by all the observers. Inter- and intraobserver agreement was assessed by Gwet’s agreement coefficient (AC1) for categorical parameters and Intraclass Correlation Coefficient (ICC) for the dural sac cross-sectional area.

Results

MRI examinations of 102 patients (mean age 66 ± 8 years, 53 men) were evaluated. The overall interobserver agreement was substantial or almost perfect for all categorical parameters (AC1 range 0.67 to 0.98), except for facet joint osteoarthritis, where the agreement was moderate (AC1 0.39). For the dural sac cross-sectional area, the overall interobserver agreement was good or excellent (ICC range 0.86 to 0.96). The intraobserver agreement was substantial or almost perfect/ excellent for all parameters (AC1 range 0.63 to 1.0 and ICC range 0.93 to 1.0).

Conclusions

There is high inter- and intraobserver agreement between radiologists and spine surgeons for preoperative MRI findings of LSS. However, the interobserver agreement is not optimal for evaluation of facet joint osteoarthritis.

Trial registration

www.ClinicalTrials.gov identifier: NCT02007083, registered December 2013.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12891-021-04949-4.

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.

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

OBJECTIVE

1) To describe a simplified multidisciplinary grading system for the most clinically relevant lumbar spine degenerative changes. 2) To measure the inter-reader variability among non-radiologist spine experts in their use of the classification system for interpretation of a consecutive series of lumbar spine magnetic resonance imaging (MRI) examinations.

METHODS

ATS multidisciplinary and collaborative standardized grading of spinal stenosis, foraminal stenosis, lateral recess stenosis, and facet arthropathy was developed. Our institution's picture archiving and communication system was searched for 50 consecutive patients who underwent non-contrast MRI of the lumbar spine for chronic back pain, radiculopathy, or symptoms of spinal stenosis. Three fellowship-trained spine subspecialists from neurosurgery, orthopedic surgery, and physiatry interpreted the 50 exams using the classification at the L4-L5 and L5-S1 levels. Inter-reader agreement was assessed with Cohen's kappa coefficient.

RESULTS

For spinal stenosis, the readers demonstrated substantial agreement (κ = 0.702). For foraminal stenosis and facet arthropathy, the three readers demonstrated moderate agreement (κ = 0.544, and 0.557, respectively). For lateral recess stenosis, there was fair agreement (κ = 0.323).

CONCLUSIONS

A simplified universal grading system of lumbar spine MRI degenerative findings is newly described. Use of this multidisciplinary grading system in the assessment of clinically relevant degenerative changes revealed moderate to substantial agreement among non-radiologist spine physicians. This standardized grading system could serve as a foundation for interdisciplinary communication.

The Composite Severity Score for Lumbar Spine MRI: a Metric of Cumulative Degenerative Disease Predicts Time Spent on Interpretation and Reporting

Conventional measures of radiologist efficiency, such as the relative value unit, fail to account for variations in the complexity and difficulty of a given study. For lumbar spine MRI (LMRI), an ideal performance metric should account for the global severity of lumbar degenerative disease (LSDD) which may influence reporting time (RT), thereby affecting clinical productivity. This study aims to derive a global LSDD metric and estimate its effect on RT. A 10-year archive of LMRI reports comprising 13,388 exams was reviewed. Objective reporting timestamps were used to calculate RT. A natural language processing (NLP) tool was used to extract radiologist-assigned stenosis severity using a 6-point scale (0 = "normal" to 5 = "severe") at each lumbar level. The composite severity score (CSS) was calculated as the sum of each of 18 stenosis grades. The predictive values of CSS, sex, age, radiologist identity, and referring service on RT were examined with multiple regression models. The NLP tool accurately classified LSDD in 94.8% of cases in a validation set. The CSS increased with patient age and differed between men and women. In a univariable model, CSS was a significant predictor of mean RT (R2 = 0.38, p < 0.001) and independent predictor of mean RT (p < 0.001) controlling for patient sex, patient age, service location, and interpreting radiologist. The predictive strength of CSS was stronger for the low CSS range (CSS = 0-25, R2 = 0.83, p < 0.001) compared to higher CSS values (CSS > 25, R2 = 0.15, p = 0.05). Individual radiologist study volume was negatively correlated with mean RT (Pearson's R =  - 0.35, p < 0.001). The composite severity score predicts radiologist reporting efficiency in LMRI, providing a quantitative measure of case complexity which may be useful for workflow planning and performance evaluation.

Can T2-weighted Dixon fat-only images replace T1-weighted images in degenerative disc disease with Modic changes on lumbar spine MRI?

OBJECTIVES

To evaluate the diagnostic performance and interobserver agreement of a magnetic resonance imaging (MRI) protocol that only includes sagittal T2-weighted Dixon fat and water images as an alternative to a standard protocol that includes both sagittal T1-weighted sequence and T2-weighted Dixon water images as reference standard in lumbar degenerative disc disease with Modic changes.

METHODS

From February 2017 to March 2019, 114 patients who underwent lumbar spine MRI for low back pain were included in this retrospective study. All MRI showed Modic changes at least at one vertebral level. Two radiologists read the standard protocol and 1 month later the alternative protocol. All MRI were assessed for Modic changes (types, location, extension) as well as structural changes (endplate defects, facet arthropathy, spinal stenosis, foraminal stenosis, Schmorl nodes, spondylolisthesis, disc bulges, and degeneration). Interobserver agreement was assessed, as well as diagnostic performance using the standard protocol as reference standard.

RESULTS

Interobserver agreement was moderate to excellent (kappa ranging from 0.51 to 0.92). Diagnostic performance of the alternative protocol was good for detection of any Modic change (sensitivity = 100.00% [95% CI, 99.03-100.00]; specificity = 98.89% [95% CI, 98.02-99.44]), as well as for detection of each Modic subtype and structural variables (sensitivity respectively 100% and ranging from 88.43 to 99.75% ; specificity ranging respectively from 97.62 to 100% and 99.58 to 99.91% ).

CONCLUSIONS

Combined with T2-weighted Dixon water images, T2-weighted Dixon fat images provide good diagnostic performance compared to T1-weighted images in lumbar degenerative disc disease with Modic changes, and could therefore allow for a shortened protocol.

KEY POINTS

• Combined with T2-weighted Dixon water images, T2-weighted Dixon fat images (in comparison to T1-weighted sequence) can provide good diagnostic performance in lumbar degenerative disc disease with Modic changes. • Interobserver agreement of the alternative protocol including sagittal T2-weighted Dixon fat and water images was substantial to excellent for every studied variable except for facet arthropathy. • A shortened MRI protocol including T2-weighted Dixon sequence without T1-weighted sequence could be proposed in this clinical setting.

Predictability of the effects of epidural injection in lumbar spinal stenosis by assessment of lumbar MRI scans

BACKGROUND

Numerous classification systems have been proposed to interpret lumbar MRI scans. The clinical impact of the measured parameters remains unclear. To evaluate the clinical significance of imaging results in patients with multisegmental degenerative pathologies, treating specialists can perform image-guided local injections to target defined areas such as the epidural space.

OBJECTIVE

The aim of this retrospective study was to evaluate the correlation between lumbar spinal stenosis measurements obtained by MRI and improvement obtained through local epidural injection.

METHODS

In this retrospective study various measurement and classification systems for lumbar spinal stenosis were applied to MRI scans of 100 patients with this pathological condition. The reported effect of epidural bupivacaine/triamcinolone injections at the site was recorded in these patients and a comparative analysis performed.

RESULTS

MRI features assessed in this study did not show any relevant correlation with reported pain relief after epidural injection in patients with chronic lumbar stenosis, with the exception of posterior disc height with a weak Kendall's tau of -0.187 (p= 0.009).

CONCLUSIONS

Although MRI is crucial for evaluating lumbar spinal stenosis, it cannot replace but is rather complementary to a good patient history and clinical examination or the results of local diagnostic injections.

Differentiating epidural fibrosis from disc herniation on contrast-enhanced and unenhanced MRI in the postoperative lumbar spine

OBJECTIVE

To determine diagnostic confidence and inter-observer/intra-observer agreement in differentiating epidural fibrosis from disc herniation and lumbar spinal stenosis parameters on magnetic resonance images (MRI) in postoperative lumbar spines with (Gad-MRI) and without (unenhanced MRI) intravenous gadolinium-based contrast agent.

SUBJECTS AND METHODS

N = 124 lumbar spine MRI examinations of four groups were included: 1-6 months, 7-18 months, 19-36 months, more than 37 months between lumbar spine surgery and imaging. Two radiologists evaluated Gad-MRI and unenhanced MRI: diagnostic confidence was determined as confident or unconfident. Inter-observer and intra-observer agreement were assessed in differentiating epidural fibrosis from disc herniation and for lumbar spinal stenosis parameters on MRI. Fisher's exact test and Cohen's kappa served for statistics.

RESULTS

Diagnostic confidence in differentiating epidural fibrosis from disc herniation was significantly higher on Gad-MR images compared with unenhanced MRI at 1-18 months for observer 1 and at 1-6 months postoperatively for observer 2 (p values: 0.01-0.025). Inter-observer agreement at 1-6 months postoperatively for identification of epidural fibrosis was higher on Gad-MRI (kappa values: 0.53 versus 0.24). Inter-observer and intra-observer agreement for identification of disc herniation and for assessment of lumbar spinal stenosis parameters revealed inconsistent data, without a trend for higher inter-observer or intra-observer agreement on Gad-MRI compared with unenhanced MRI (kappa values: 0.17-0.75).

CONCLUSION

Gad-MR images compared with unenhanced MRI improved diagnostic confidence and agreement in differentiating epidural fibrosis from disc herniation for both observers in the first 6 months and for one observer in the first 18 months after lumbar spine surgery. After 18 months, Gad-MR images compared with unenhanced MRI did neither improve confidence nor agreement.

Natural Course and Diagnosis of Lumbar Spinal Stenosis: WFNS Spine Committee Recommendations

Lumbar spinal stenosis (LSS) is defined as a degenerative disorder showing a narrowing of the spinal canal. The diagnosis is straightforward in cases with typical neurogenic claudication symptoms and unequivocal imaging findings. However, not all patients present with typical symptoms, and there is obviously no correlation between the severity of stenosis and clinical complaint. The radiologic diagnosis of LSS is widely discussed in the literature. The best diagnostic test for the diagnosis of LSS is magnetic resonance imaging (MRI). However, canal diameter measurements have not gained much consensus from radiologists, whereas qualitative measures, such as cerebrospinal fluid space obliteration, have achieved greater consensus. Instability can best be defined by standing lateral radiograms and flexion-extension radiograms. For cases showing typical neurogenic claudication symptoms and unequivocal imaging findings, the diagnosis is straightforward. However, not all patients present with typical symptoms, and there is obviously no correlation between the severity of stenosis (computed tomography and MRI) and clinical complaint. In fact, recent MRI studies have shown that mild-to-moderate stenosis can also be found in asymptomatic individuals. Routine electrophysiological tests such as lower extremity electromyography, nerve conduction studies, F-wave, and H-reflex are not helpful in the diagnosis and outcome prediction of LSS. The electrophysiological recordings are complementary to the neurologic examination and can provide confirmatory information in less obvious clinical complaints. However, in the absence of reliable evidence, imaging studies should be considered as a first-line diagnostic test in the diagnosis of degenerative LSS.

Current applications and future directions of deep learning in musculoskeletal radiology

Deep learning with convolutional neural networks (CNN) is a rapidly advancing subset of artificial intelligence that is ideally suited to solving image-based problems. There are an increasing number of musculoskeletal applications of deep learning, which can be conceptually divided into the categories of lesion detection, classification, segmentation, and non-interpretive tasks. Numerous examples of deep learning achieving expert-level performance in specific tasks in all four categories have been demonstrated in the past few years, although comprehensive interpretation of imaging examinations has not yet been achieved. It is important for the practicing musculoskeletal radiologist to understand the current scope of deep learning as it relates to musculoskeletal radiology. Interest in deep learning from researchers, radiology leadership, and industry continues to increase, and it is likely that these developments will impact the daily practice of musculoskeletal radiology in the near future.

Intra- and Intersubspecialty Variability in Lumbar Spine MRI Interpretation: A Multireader Study Comparing Musculoskeletal Radiologists and Neuroradiologists

BACKGROUND AND PURPOSE

The purpose of this study is to assess the differences in degenerative spine MRI reporting between subspecialty-trained attending neuroradiologists and musculoskeletal radiologists (MSK) at a single institution, academic medical center.

MATERIALS AND METHODS

Fifty consecutive outpatient noncontrast lumbar spine examinations were selected from the Picture Archiving and Communication System. Three MSK and 3 neuroradiologists (NR) independently reviewed and interpreted the exams at the L4-L5 and L5-S1 levels in the same manner as in clinical practice. The assessment of neural foraminal stenosis (NFS) and spinal canal stenosis (SCS) was converted to a 5-point ordinal scale. The assessment of lateral recess stenosis (LRS) and facet osteoarthritis (FO) was recorded as present/absent. Intersubspecialty and intrasubspecialty analysis was performed using Cohen's kappa coefficient with a binary matrix of all reader pairs.

RESULTS

There was moderate intersubspecialty agreement (k = 0.527) for NFS and SCS (k = 0.540). Intersubspecialty agreement was slight for LRS (k = 0.0818) and FO (k = 0.176). The MSK group demonstrated greater intrasubspecialty agreement in assessment of NFS and SCS compared to the NR group, with nonoverlapping confidence intervals. The NR group demonstrated greater nominal intrasubspecialty agreement in the assessment of both LRS and FO, although with nonoverlapping confidence intervals.

CONCLUSION

There is moderate intersubspecialty agreement between MSK radiologists and neuroradiologists in reporting the severity of NFS and SCS, although MSK radiologists demonstrated greater intrasubspecialty agreement. There is slight intersubspecialty agreement for LRS and FO. The demonstration of differences in inter-reader agreement is a crucial first step to attempt to ameliorate these variabilities.

Challenges Related to Artificial Intelligence Research in Medical Imaging and the Importance of Image Analysis Competitions

In recent years, there has been enormous interest in applying artificial intelligence (AI) to radiology. Although some of this interest may have been driven by exaggerated expectations that the technology can outperform radiologists in some tasks, there is a growing body of evidence that illustrates its limitations in medical imaging. The true potential of the technique probably lies somewhere in the middle, and AI will ultimately play a key role in medical imaging in the future. The limitless power of computers makes AI an ideal candidate to provide the standardization, consistency, and dependability needed to support radiologists in their mission to provide excellent patient care. However, important roadblocks currently limit the expansion of this field in medical imaging. This article reviews some of the challenges and potential solutions to advance the field forward, with focus on the experience gained by hosting image-based competitions.

The MIST Guidelines: The Lumbar Spinal Stenosis Consensus Group Guidelines for Minimally Invasive Spine Treatment

BACKGROUND

Lumbar spinal stenosis (LSS) can lead to compression of neural elements and manifest as low back and leg pain. LSS has traditionally been treated with a variety of conservative (pain medications, physical therapy, epidural spinal injections) and invasive (surgical decompression) options. Recently, several minimally invasive procedures have expanded the treatment options.

METHODS

The Lumbar Spinal Stenosis Consensus Group convened to evaluate the peer-reviewed literature as the basis for making minimally invasive spine treatment (MIST) recommendations. Eleven consensus points were clearly defined with evidence strength, recommendation grade, and consensus level using U.S. Preventive Services Task Force criteria. The Consensus Group also created a treatment algorithm. Literature searches yielded 9 studies (2 randomized controlled trials [RCTs]; 7 observational studies, 4 prospective and 3 retrospective) of minimally invasive spine treatments, and 1 RCT for spacers.

RESULTS

The LSS treatment choice is dependent on the degree of stenosis; spinal or anatomic level; architecture of the stenosis; severity of the symptoms; failed, past, less invasive treatments; previous fusions or other open surgical approaches; and patient comorbidities. There is Level I evidence for percutaneous image-guided lumbar decompression as superior to lumbar epidural steroid injection, and 1 RCT supported spacer use in a noninferiority study comparing 2 spacer products currently available.

CONCLUSIONS

MISTs should be used in a judicious and algorithmic fashion to treat LSS, based on the evidence of efficacy and safety in the peer-reviewed literature. The MIST Consensus Group recommend that these procedures be used in a multimodal fashion as part of an evidence-based decision algorithm.

Texture analysis of paraspinal musculature in MRI of the lumbar spine: analysis of the lumbar stenosis outcome study (LSOS) data

OBJECTIVE

To evaluate association of fatty infiltration in paraspinal musculature with clinical outcomes in patients suffering from lumbar spinal stenosis (LSS) using qualitative and quantitative grading in magnetic resonance imaging (MRI).

MATERIALS AND METHODS

In this retrospective study, texture analysis (TA) was performed on postprocessed axial T2 weighted (w) MR images at level L3/4 using dedicated software (MaZda) in 62 patients with LSS. Associations in fatty infiltration between qualitative Goutallier and quantitative TA findings with two clinical outcome measures, Spinal stenosis measure (SSM) score and walking distance, at baseline and regarding change over time were assessed using machine learning algorithms and multiple logistic regression models.

RESULTS

Quantitative assessment of fatty infiltration using the histogram TA feature "mean" showed higher interreader reliability (ICC 0.83-0.97) compared to the Goutallier staging (κ = 0.69-0.93). No correlation between Goutallier staging and clinical outcome measures was observed. Among 151 TA features, only TA feature "mean" of the spinotransverse group showed a significant but weak correlation with worsened SSM (p = 0.046). TA feature "S(3,3) entropy" showed a significant but weak association with worsened WD over 12 months (p = 0.046).

CONCLUSION

MR TA is a reproducible tool to quantitatively assess paraspinal fatty infiltration, but there is no clear association with the clinical outcome in asymptomatic LSS patients.

Reliability of standing weight-bearing (0.25T) MR imaging findings and positional changes in the lumbar spine

OBJECTIVE

To test the reliability and absolute agreement of common degenerative findings in standing positional magnetic resonance imaging (pMRI).

METHODS AND MATERIALS

Low back pain patients with and without sciatica were consecutively enrolled to undergo a supine and standing pMRI. Three readers independently evaluated the standing pMRI for herniation, spinal stenosis, spondylolisthesis, HIZ lesions and facet joint effusion. The evaluation included a semi-quantitative grading of spinal stenosis, foraminal stenosis and spinal nerve root compression. The standing pMRI images were evaluated with full access to supine MRI. In case lower grades or the degenerative findings were not present in the supine images, this was reported separately as position-dependent changes. A subsample of 20 pMRI examinations was reevaluated after two months. The reproducibility was assessed by inter- and intra-reader reliability (kappa statistic) and absolute agreement between readers.

RESULTS

Fifty-six patients were included in this study. There was fair-to-substantial inter-reader reliability (κ 0.47 to 0.82) and high absolute agreement (72.3% to 99.1%) for the pMRI findings. The intra-reader assessment showed similar reliability and agreement (κ 0.36 to 0.85; absolute agreement: 62.5% to 98.8%). Positional changes between the supine and standing position showed a fair-to-moderate inter- and intra-reader reliability (κ 0.25 to 0.52; absolute agreement: 97.0% to 99.1).

CONCLUSION

Evaluation of the lumbar spine for degenerative findings by standing pMRI has acceptable reproducibility; however, positional changes from the supine to the standing position as an independent outcome should be interpreted with caution because of lower reliability, which calls for further standardisation.

Influence of Paravertebral Muscle Quality on Treatment Efficacy of Epidural Steroid Infiltration or Surgical Decompression in Lumbar Spinal Stenosis-Analysis of the Lumbar Spinal Outcome Study (LSOS) Data: A Swiss Prospective Multicenter Cohort Study

STUDY DESIGN

Prospective multicenter cohort study.

OBJECTIVE

To study the question whether paravertebral muscle quality may affect the clinical outcome of epidural steroid infiltration (ESI) or surgical decompression in patients with symptomatic lumbar spinal stenosis (LSS).

SUMMARY OF BACKGROUND DATA

To the present, the impact of paravertebral muscle quality on clinical outcome of ESI or surgical decompression in patients with LSS has not been clarified.

METHODS

The Lumbar Stenosis Outcome Study was used as database. Patients with symptomatic LSS who received an ESI (group I) or lumbar decompression surgery (group II), had a follow-up of at least 12 months and a pretreatment lumbar magnetic resonance imaging were included (n = 205). Paravertebral muscle quality was quantified by the degree of fatty degeneration (according to Goutallier) on the level L3. Clinical outcome was assessed using the Spinal Stenosis Measure, Numeric Rating Scale, Roland and Morris Disability Questionnaire, and EQ-5D-3L sum score. Reinfiltration, surgery following infiltration, or revision was defined as treatment failure.

RESULTS

ESI (group I) and surgical treatment (group II) were associated with a failure rate of 60% and 12.7%, respectively. In group I, there was a tendency for the rate of reintervention to be less in patients with bad muscle quality (P = 0.22). In group II, improvements in the clinical outcomes up to 12 months did not differ between Goutallier stage ≤1 and ≥2. Patients with Goutallier stage ≤1 had more improvement in Spinal Stenosis Measure symptoms (P = 0.04).

CONCLUSION

Relevant fatty degeneration of the paravertebral musculature, as a sign of low muscle quality, has low impact on clinical outcome and the high failure rates with conservative treatment by ESI compared to surgical decompression. Therefore fatty degeneration has no relevant prognostic value for LSS treatment.

LEVEL OF EVIDENCE

2.