Diagnostic accuracy in axial spondyloarthritis: a systematic evaluation of the role of clinical information in the interpretation of sacroiliac joint imaging

OBJECTIVES

Radiography and MRI of the sacroiliac joints (SIJ) are relevant for the diagnosis and classification of patients with axial spondyloarthritis (axSpA). This study aimed to evaluate the impact of clinical information (CI) on the accuracy of imaging interpretation.

METHODS

Out of 109 patients referred because of suspicion of axSpA with complete imaging sets (radiographs and MRI of SIJ), 61 were diagnosed with axSpA (56%). Images were independently evaluated by three radiologists in four consecutive reading campaigns: radiographs and radiographs+MRI without and with CI including demographic data, SpA features, physical activity and pregnancy. Radiographs were scored according to the modified New York criteria, and MRIs for inflammatory and structural changes compatible with axSpA (yes/no). The clinical diagnosis was taken as reference standard. The compatibility of imaging findings with a diagnosis of axSpA (precision) before and after the provision of CI and radiologists' confidence with their findings (0-10) were evaluated.

RESULTS

The precision of radiographs evaluation without versus with CI increased from 70% to 78% (p=0.008), and for radiographs+MRI from 81% to 82% (p=1.0), respectively. For CR alone, the sensitivity and specificity of radiologic findings were 51% and 94% without and 60% and 100% with CI, while, for radiographs+MRI, they were 74% and 90% vs 71% and 98%, respectively. The diagnostic confidence of radiologists increased from 5.2±1.9 to 6.0±1.7 with CI for radiographs, and from 6.7±1.6 to 7.2±1.6 for radiographs+MRI, respectively.

CONCLUSION

The precision, specificity and diagnostic confidence of radiologic evaluation increased when CI was provided.

[Diagnosis and classification of axial spondyloarthritis (axSpA) - the current status]

Axial spondyloarthritis (axSpA) is an inflammatory rheumatic disease typically characterized by inflammatory back pain (IBP). The term axSpA has largely replaced the long-used term ankylosing spondylitis (AS). IBP is caused by inflammation in the axial skeleton, with the sacroiliac joints (SIJ) being particularly frequently affected initially. The spine is usually added in later stages, which is then increasingly characterized structurally by the formation of new bone. The overall concept of spondyloarthritis includes other disease manifestations such as uveitis, psoriasis and colitis and comorbidities such as cardiovascular disease and osteoporosis.The ASAS classification criteria for axSpA, in place since 2009, have replaced the 1984 modified New York criteria. In the former, in addition to conventional X-rays, changes in the SIJ detected by magnetic resonance imaging (MRI) and also the detection of HLA B27 have, for the first time, played a role. It is important to note that these are not diagnostic criteria, as they do not exist. This paper outlines 10 points that should be considered when making a diagnosis.

Automatic segmentation of fat metaplasia on sacroiliac joint MRI using deep learning

OBJECTIVE

To develop a deep learning (DL) model for segmenting fat metaplasia (FM) on sacroiliac joint (SIJ) MRI and further develop a DL model for classifying axial spondyloarthritis (axSpA) and non-axSpA.

MATERIALS AND METHODS

This study retrospectively collected 706 patients with FM who underwent SIJ MRI from center 1 (462 axSpA and 186 non-axSpA) and center 2 (37 axSpA and 21 non-axSpA). Patients from center 1 were divided into the training, validation, and internal test sets (n = 455, 64, and 129). Patients from center 2 were used as the external test set. We developed a UNet-based model to segment FM. Based on segmentation results, a classification model was built to distinguish axSpA and non-axSpA. Dice Similarity Coefficients (DSC) and area under the curve (AUC) were used for model evaluation. Radiologists' performance without and with model assistance was compared to assess the clinical utility of the models.

RESULTS

Our segmentation model achieved satisfactory DSC of 81.86% ± 1.55% and 85.44% ± 6.09% on the internal cross-validation and external test sets. The classification model yielded AUCs of 0.876 (95% CI: 0.811-0.942) and 0.799 (95% CI: 0.696-0.902) on the internal and external test sets, respectively. With model assistance, segmentation performance was improved for the radiological resident (DSC, 75.70% vs. 82.87%, p < 0.05) and expert radiologist (DSC, 85.03% vs. 85.74%, p > 0.05).

CONCLUSIONS

DL is a novel method for automatic and accurate segmentation of FM on SIJ MRI and can effectively increase radiologist's performance, which might assist in improving diagnosis and progression of axSpA.

CRITICAL RELEVANCE STATEMENT

DL models allowed automatic and accurate segmentation of FM on sacroiliac joint MRI, which might facilitate quantitative analysis of FM and have the potential to improve diagnosis and prognosis of axSpA.

KEY POINTS

• Deep learning was used for automatic segmentation of fat metaplasia on MRI. • UNet-based models achieved automatic and accurate segmentation of fat metaplasia. • Automatic segmentation facilitates quantitative analysis of fat metaplasia to improve diagnosis and prognosis of axial spondyloarthritis.

Research on automatic recognition radiomics algorithm for early sacroiliac arthritis based on sacroiliac MRI imaging

OBJECTIVE

To create an automated machine learning model using sacroiliac joint MRI imaging for early sacroiliac arthritis detection, aiming to enhance diagnostic accuracy.

METHODS

We conducted a retrospective analysis involving 71 patients with early sacroiliac arthritis and 85 patients with normal sacroiliac joint MRI scans. Transverse T1WI and T2WI sequences were collected and subjected to radiomics analysis by two physicians. Patients were randomly divided into training and test groups at a 7:3 ratio. Initially, we extracted the region of interest on the sacroiliac joint surface using ITK-SNAP 3.6.0 software and extracted radiomic features. We retained features with an Intraclass Correlation Coefficient > 0.80, followed by filtering using max-relevance and min-redundancy (mRMR) and LASSO algorithms to establish an automatic identification model for sacroiliac joint surface injury. Receiver operating characteristic (ROC) curves were plotted, and the area under the ROC curve (AUC) was calculated. Model performance was assessed by accuracy, sensitivity, and specificity.

RESULTS

We evaluated model performance, achieving an AUC of 0.943 for the SVM-T1WI training group, with accuracy, sensitivity, and specificity values of 0.878, 0.836, and 0.943, respectively. The SVM-T1WI test group exhibited an AUC of 0.875, with corresponding accuracy, sensitivity, and specificity values of 0.909, 0.929, and 0.875, respectively. For the SVM-T2WI training group, the AUC was 0.975, with accuracy, sensitivity, and specificity values of 0.933, 0.889, and 0.750. The SVM-T2WI test group produced an AUC of 0.902, with accuracy, sensitivity, and specificity values of 0.864, 0.889, and 0.800. In the SVM-bimodal training group, we achieved an AUC of 0.974, with accuracy, sensitivity, and specificity values of 0.921, 0.889, and 0.971, respectively. The SVM-bimodal test group exhibited an AUC of 0.964, with accuracy, sensitivity, and specificity values of 0.955, 1.000, and 0.875, respectively.

CONCLUSION

The radiomics-based detection model demonstrates excellent automatic identification performance for early sacroiliitis.

The diagnostic value of morphological features of fat deposition of sacroiliac joint steatosis in axial spondyloarthritis

Background

Findings of fatty lesions in the context of other imaging manifestations, especially bone marrow edema and erosions can effectively assist in the diagnosis of axSpA. Chemical shift-encoded MRI is a sequence which allows for the quantification of fat signal and has been applied in the imaging evaluation of the SIJ in axSpA. The objective of this study was to investigate the diagnostic performance of morphological features of fatty lesions visualized by CSE-MRI in the imaging evaluation of SIJ in axSpA.

Methods

Fatty lesions with morphological features (subchondral, homogeneity and distinct border) were assessed and recorded as a binary variable in each quadrant of the SIJ. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were calculated for different morphological features as well as the anatomical distribution in patients with nr-axSpA and r-axSpA. T1-weighted images and CSE-MRI fat fraction maps were directly compared in the recognition of different morphological features.

Results

Eighty-two patients [non-SpA (n = 21), nr-axSpA (n = 23), r-axSpA (n = 38)] with lower back pain (LBP) were enrolled. Presence of the three morphological features of fatty lesions had a specificity of 90.48% in axSpA. The sensitivities of being subchondral, homogeneity and distinct border were 52.17, 39.13 and 39.13% in nr-axSpA on T1-weighted images. For patients with r-axSpA, the sensitivities reached 86.84, 76.32 and 57.89%. No significant difference was found in the distribution of fatty lesions between T1-weighted images and CSE-MRI. However, CSE-MRI fat fraction maps could detect significantly more fatty lesions with homogeneity (p = 0.0412) and distinct border (p = 0.0159) than T1-weighted images in the sacroiliac joint, but not subchondral lesions (p = 0.6831).

Conclusion

The homogeneity and distinct border are more relevant for the diagnosis of axSpA. Moreover, CSE-MRI could detect more typical morphological features of fatty lesions than T1-weighted images in showing these two features. The presence of all three features was more likely to be indicative of axSpA.

Significance of structural changes in the axial skeleton in patients with axial spondyloarthritis: how important are lesions in the sacroiliac joint?

Inflammatory back pain (IBP) is a characteristic clinical symptom of patients with axial spondyloarthritis (axSpA) that is caused by inflammation in the axial skeleton. In early disease stages the sacroiliac joints (SIJ) are most often affected, the spine usually at later stages. In many but clearly not all cases of axSpA new bone formation in form of syndesmophytes and ankylosis occur in the further course of the disease. Function and mobility may be impaired by both, inflammation and structural changes. In clinical trials outcome parameters most often used refer to pain, disease activity, function, mobility and global health but many researchers are also interested in radiographic progression in the axial skeleton of patients with axSpA. This viewpoint discusses the relevance of structural changes in the SIJ in comparison to the spine and in relation to functional outcomes and mobility.

Use of Imaging in Axial Spondyloarthritis for Diagnosis and Assessment of Disease Remission in the Year 2022

Medical imaging remains the cornerstone of diagnostics and follow-up of axial spondyloarthritis (axSpA) patients. With the lack of specific biomarkers allowing monitoring of disease activity and progression, clinicians refer to imaging modalities for accurate evaluation of the axSpA burden. Technological advances and increasing availability of modern imaging techniques such as MRI have enabled faster diagnosis of the disease, hence dramatically changed the diagnostic delay and improved the prognosis and functional outcomes for axSpA patients.Active sacroiliitis as visualized by MRI has been widely accepted as a diagnostic tool, and definitions of inflammatory and structural lesions within the axial skeleton have been developed. Recently, it has been acknowledged that bone marrow edema, suggestive of sacroiliitis, is a common finding among non-SpA patients, and could be attributed to mechanical loading or accumulate with age in healthy individuals. Therefore, it is crucial to distinguish between true pathological and concealing imaging findings, not only for diagnostic but also for disease remission purposes. New imaging modalities, aimed for in vivo visualization of specific molecular processes, could be employed to cross-validate findings from techniques used in daily clinical practice. This review critically evaluates the use of different imaging modalities for diagnosis and assessment of disease remission in axSpA in the year 2022.

The influence of age on the prevalence of inflammatory and structural MRI lesions in the SIJ of patients with and without axSpA

OBJECTIVE

To compare the influence of age on inflammatory (bone marrow oedema. BME) and structural (fat lesions (FL), erosions and ankylosis) MRI lesions in the SIJ of patients with and without axial spondyloarthritis (axSpA).

METHODS

In a retrospective study, SIJ MRI (STIR/T1 sequences) of consecutive patients with chronic back pain diagnosed with axSpA or non-SpA were evaluated based on SIJ quadrants (SIJ-Q). Two blinded readers evaluated BME and structural lesions. Reader agreement was evaluated for prevalence of MRI lesions related to age.

RESULTS

MRIs of 309 (175 axSpA, 134 non-SpA) patients were evaluated. Their mean age was 38.5 ± 11.4 vs 43.4 ± 13.8 years (y), 67% and 36% were male, CRP 1.6 ± 2.4 vs 1.1 ± 2.1 mg/dl, median symptom duration 48 and 60 months, respectively. SIJ-Q with BME and erosions were significantly more frequent in axSpA vs non-SpA patients independent of age, while this difference was seen for FL only in patients ≥50 y. The proportion of patients with ≥1 or ≥ 3 BME or chronic lesions except for FL increased with age in both groups, and was constantly higher in axSpA vs non-SpA. In univariate analyses, only female sex was significantly associated with more FL.

CONCLUSIONS

The proportion of patients with MRI lesions was high in both, axSpA and non-SpA patients. However, the prevalence of BME and erosions was significantly more frequent in patients with axSpA, was independent of age and also allowed for discrimination. FL occurred more frequently only in older age groups and were less reliable for discrimination vs. non-SpA patients.

Diagnostic evaluation of the sacroiliac joints for axial spondyloarthritis: should MRI replace radiography?

The possibility of detection of structural damage on magnetic resonance imaging (MRI) of sacroiliac joints raises the question of whether MRI can substitute radiographs for diagnostic evaluation and to a further extent for classification of axial spondyloarthritis (axSpA). In this viewpoint, we will argue that it is time to replace conventional radiographs with MRI for the assessment of structural changes in sacroiliac joints. This message is based on current data on the following questions: (1) How reliable are conventional radiographs in the diagnosis of axSpA overall and radiographic axSpA in particular? (2) How does T1-weighted MRI compare to radiographs in the detection of sacroiliitis? (3) Are there now other (better) MRI sequences than T1-weighted, which might be more suitable for the detection of structural lesions? (4) Which MRI sequences should be performed for the diagnostic evaluation of the sacroiliac joints? (5) Do we have data to define sacroiliitis based on structural changes detected by MRI?

Novel imaging techniques for sacroiliac joint assessment

PURPOSE OF REVIEW

Imaging of the sacroiliac joints is one of the cornerstones in the diagnosis and monitoring of axial spondyloarthritis. We aim to present an overview of the emerging imaging techniques for sacroiliac joint assessment and provide an insight into their relevant benefits and pitfalls.

RECENT FINDINGS

Evaluation of structural and active inflammatory lesions in sacroiliitis are both important for understanding the disease process. Dual-energy computed tomography (CT) can detect inflammatory bone marrow edema in the sacroiliac joints and provides an alternative for magnetic resonance imaging (MRI). Three-dimensional gradient echo sequences improve the visualization of erosions on MRI. Susceptibility weighted MRI and deep learning-based synthetic CT are innovative MRI techniques that allow for generating 'CT-like' images and better depict osseous structural lesions than routine MRI sequences.

SUMMARY

New imaging innovations and developments result in significant improvements in the imaging of spondyloarthritis. Advanced MRI techniques enhance its potential for the accurate detection of structural and active inflammatory lesions of sacroiliitis in one single imaging session.

Quantification of Fat Metaplasia in the Sacroiliac Joints of Patients With Axial Spondyloarthritis by Chemical Shift-Encoded MRI: A Diagnostic Trial

Objective

To study the diagnostic performance of chemical shift-encoded MRI (CSE-MRI) in the diagnosis of axial spondyloarthritis (axSpA).

Methods

CSE-MRI images were acquired for consecutive patients complaining of back pain as well as healthy volunteers. Proton density fat fraction (PDFF) values were measured independently by two readers. Diagnostic performance of CSE-MRI was analyzed by sensitivity analysis and ROC curve analysis. Logistic regression analysis was employed to investigate the risk factors of extensive fat deposition in the SIJs.

Results

A total of 52 r-axSpA patients, 37 nr-axSpA patients, 24 non-SpA patients and 34 healthy volunteers were included. Mean PDFF values in the SIJs of patients with r-axSpA and nr-axSpA (72.7% and 64.5%) were significantly higher than non-SpA patients and healthy volunteers (56.0% and 57.6%) (p<0.001). By defining extensive fat deposition in the SIJs as ≥8 ROIs with PDFF values over 70%, its sensitivity and specificity in diagnosing axSpA reached 72.47% and 86.21%%. By joining bone marrow edema (BME) with ≥8 ROIs (PDFF>70%), 22 (24.71%) and 23 (25.84%) more axSpA patients were classified as SIJ MRI (+) by reader 1 and 2, but specificities decreased by 15.52% and 10.34%. Multivariate logistic regression analysis confirmed longer disease duration as the independent risk factor of extensive fat deposition in SIJs (OR=1.15, 95%CI[1.03, 1.32]), while bDMARDs medication was a protective factor (OR=0.15, 95%CI[0.04, 0.51]).

Conclusion

CSE-MRI is a reliable tool to quantitively assess the fat metaplasia in the SIJs of axSpA patients. Extensive fat deposition in the SIJs could add incremental diagnostic value to BME, but at the cost of decreased specificities.

Distribution of Acute and Chronic Lesions in the Sacroiliac Joints of Patients with Axial Spondyloarthritis

Objective

In this study, we aimed to investigate whether there was a pattern of distribution of acute and chronic lesions in the sacroiliac joints (SIJ) of patients with axial spondyloarthritis (axSpA).

Methods

A total of 96 patients diagnosed as axSpA were retrospectively included in this study. The Spondyloarthritis Research Consortium of Canada sacroiliac joint inflammation score (SIS) and structural score (SSS) were used to evaluate the acute and chronic lesions in the SIJs. Scores representing the distribution of bone marrow edema, fatty lesions and erosions were extracted respectively. By dividing the SIJs into sacral or iliac sections, upper or lower sections, anterior and posterior levels, differences of scores representing acute and chronic lesions were analyzed by Kruskal Wallis’ tests.

Results

SIS scores were not significantly different in sacral or iliac sections, in upper or lower sections, on anterior or posterior levels. SSS scores were also not significantly different in different sections, except for higher occurrence rates of erosions in the iliac sections. Post-hoc analysis showed that there was a higher erosion score in the left ilium than left sacrum, as well as in right ilium than left sacrum.

Conclusion

There was no specific distribution pattern of acute or chronic lesions in the SIJs in patients with axSpA. A bigger study sample was needed to confirm the distribution of erosions in sacral or iliac sections.

MRI in axial spondyloarthritis: understanding an 'ASAS-positive MRI' and the ASAS classification criteria

In 2009, the Assessment of SpondyloArthritis international Society (ASAS) published a definition of 'active sacroiliitis on magnetic resonance imaging (MRI) for classification of axial spondyloarthritis'. This new definition of an 'ASAS-positive MRI' was integral to new classification criteria for axial spondyloarthritis that were published in the same year. The ASAS MRI definition had the considerable advantage of simplicity and the definition gained popularity as guidance for interpreting MRI of the sacroiliac joints in clinical practice. However, classification criteria are not designed for use in clinical practice with the consequence that overreliance on the presence of bone marrow edema, which is the principal determinant of an 'ASAS-positive MRI', may result in a tendency to overcall inflammatory sacroiliitis in the clinical setting. This article aims to inform the reader about the rationale behind the ASAS definition of a positive MRI and ASAS classification criteria, their proper use in research and why they should not be used in clinical practice. The article also contains guidance for an updated imaging protocol and interpretation of images including typical imaging findings, differential diagnosis, and common pitfalls.

[Answering epidemiologic rheumatologic questions by cooperation with the large population-based SHIP cohort-findings with relevance for the diagnosis of axial spondyloarthritis (axSpA)]

This article presents how, based on the availability of new imaging methods and medications, objectives regarding the rheumatic disease axial spondyloarthritis (axSpA) have developed over the course of more than two decades into a rheumatologic research group. During recent years, cooperation with the Study of Health in Pomerania (SHIP) cohort has given rise to new fundamental aspects. This involved intensive cooperation between the Ruhr University Bochum (Rheumazentrum Ruhrgebiet) and the Greifswald University Hospital (Community Medicine research collective). The design of the SHIP cohort was published 10 years ago and the cohort approach presented in the Bundesgesundheitsblatt, which also described central methodologic questions in detail. In 2014, a cooperation project between the Ruhr Rheumatology Center/Ruhr University Bochum and the SHIP Department of Clinical and Epidemiologic Research (Klinisch-Epidemiologische Forschung, KEF; SHIP-KEF) was established, which has already resulted in publication of interesting results in high-ranking journals. In order to stress the potential of such corporations, important contents thereof are presented herein, with a focus on MRI and consideration of historical aspects.

Imaging in Axial Spondyloarthritis: What is Relevant for Diagnosis in Daily Practice?

PURPOSE OF REVIEW

To explore how imaging may assist diagnosing axial spondyloarthritis in rheumatology practice.

RECENT FINDINGS

A diagnosis of axial spondyloarthritis is based on pattern recognition by synthesizing clinical, laboratory, and imaging findings. In health care settings providing low threshold access to advanced imaging, sacroiliac joint MRI is the preferred imaging modality in clinically suspected axial spondyloarthritis. In daily routine, the optimum protocol to assess suspected inflammatory back pain combines sacroiliac joint and spine MRI fitting a 30-min slot. Contextual assessment of concomitant structural and active MRI lesions is key to enhance diagnostic utility. In women with postpartum back pain suggestive of axial spondyloarthritis, recent reports advocate waiting 6-12 months after delivery before acquiring sacroiliac joint MRI. Major unmet needs are consistent MRI protocols, standardized training modules on how to evaluate axial MRI, and timely dissemination of imaging advances into mainstream practice both in rheumatology and in radiology. In rheumatology practice, MRI has become indispensable to help diagnose early axial spondyloarthritis. However, major gaps in training and knowledge transfer to daily care need to be closed.

Choose wisely: imaging for diagnosis of axial spondyloarthritis

Objective

To assess the diagnostic accuracy of radiography (X-ray, XR), CT and MRI of the sacroiliac joints for diagnosis of axial spondyloarthritis (axSpA).

Methods

163 patients (89 with axSpA; 74 with degenerative conditions) underwent XR, CT and MR. Three blinded experts categorised the imaging findings into axSpA, other diseases or normal in five separate reading rounds (XR, CT, MR, XR +MR, CT +MR). The clinical diagnosis served as reference standard. Sensitivity and specificity for axSpA and inter-rater reliability were compared.

Results

XR showed lower sensitivity (66.3%) than MR (82.0%) and CT (76.4%) and also an inferior specificity of 67.6% vs 86.5% (MR) and 97.3% (CT). XR +MR was similar to MR alone (sensitivity 77.5 %/specificity 87.8%) while CT+MR was superior (75.3 %/97.3%). CT had the best inter-rater reliability (kappa=0.875), followed by MR (0.665) and XR (0.517). XR +MR was similar (0.662) and CT+MR (0.732) superior to MR alone.

Conclusions

XR had inferior diagnostic accuracy and inter-rater reliability compared with cross-sectional imaging. MR alone was similar in diagnostic performance to XR+MR. CT had the best accuracy, strengthening the importance of structural lesions for the differential diagnosis in axSpA.