The value of a repeat MRI examination of the sacroiliac joints following an inconclusive initial examination.

OBJECTIVE: Assess the diagnostic utility of repeat sacroiliac joint (SIJ) magnetic resonance imaging (MRI) examinations following an inconclusive initial examination performed for suspected sacroiliitis. METHOD: Subjects with > 1 SIJ MRI examinations, an inconclusive first scan and at least 6 months interval between scans, were included. All scans were evaluated for the presence of structural/active SIJ lesions as well as any other pathology. Clinical data was extracted from the patients' clinical files, and any missing data was obtained by a telephone interview. Diagnosis and active/structural scores were compared between first and follow-up examinations (t test). RESULTS: Seventy-one subjects were included in the study, 77.4% females, mean age 41.0 ± 15 years, mean time interval between exams 30.4 ± 25.24 months. Twelve subjects performed > 2 scans. In only two subjects (2.81%), both females, MRI diagnosis changed from inconclusive to definite sacroiliitis. None of the subjects with > 2 scans had evidence of sacroiliitis in any of the following MRI examinations. Significant differences were observed between the scores of active SIJ lesion of the first and follow-up MRI (1.51/1.62, p = 0.02) but not for scores of structural lesions (1.22/1.68, p = 0.2). CONCLUSIONS: Repeat SIJ MRI when the first MRI is inconclusive for sacroiliitis is more valuable in ruling out than in securing diagnosis of sacroiliitis. We suggest that when MRI findings are inconclusive, decision-making should be based on clinical data.

Sacroiliitis diagnosis based on interpretable features and multi-task learning.

Objective.Sacroiliitis is an early pathological manifestation of ankylosing spondylitis (AS), and a positive sacroiliitis test on imaging may help clinical practitioners diagnose AS early. Deep learning based automatic diagnosis algorithms can deliver grading findings for sacroiliitis, however, it requires a large amount of data with precise labels to train the model and lacks grading features visualization. In this paper, we aimed to propose a radiomics and deep learning based deep feature visualization positive diagnosis algorithm for sacroiliitis on CT scans. Visualization of grading features can enhance clinical interpretability with visual grading features, which assist doctors in diagnosis and treatment more effectively.Approach.The region of interest (ROI) is identified by segmenting the sacroiliac joint (SIJ) 3D CT images using a combination of the U-net model and certain statistical approaches. Then, in addition to extracting spatial and frequency domain features from ROI according to the radiographic manifestations of sacroiliitis, the radiomics features have also been integrated into the proposed encoder module to obtain a powerful encoder and extract features effectively. Finally, a multi-task learning technique and five-class labels are utilized to help with performing positive tests to reduce discrepancies in the evaluation of several radiologists.Main results.On our private dataset, proposed methods have obtained an accuracy rate of 87.3%, which is 9.8% higher than the baseline and consistent with assessments made by qualified medical professionals.Significance.The results of the ablation experiment and interpreting analysis demonstrated that the proposed methods are applied in automatic CT scan sacroiliitis diagnosis due to their excellently interpretable and portable advantages.

Artificial intelligence for the detection of sacroiliitis on magnetic resonance imaging in patients with axial spondyloarthritis.

Background: Magnetic resonance imaging (MRI) is important for the early detection of axial spondyloarthritis (axSpA). We developed an artificial intelligence (AI) model for detecting sacroiliitis in patients with axSpA using MRI. Methods: This study included MRI examinations of patients who underwent semi-coronal MRI scans of the sacroiliac joints owing to chronic back pain with short tau inversion recovery (STIR) sequences between January 2010 and December 2021. Sacroiliitis was defined as a positive MRI finding according to the ASAS classification criteria for axSpA. We developed a two-stage framework. First, the Faster R-CNN network extracted regions of interest (ROIs) to localize the sacroiliac joints. Maximum intensity projection (MIP) of three consecutive slices was used to mimic the reading of two adjacent slices. Second, the VGG-19 network determined the presence of sacroiliitis in localized ROIs. We augmented the positive dataset six-fold. The sacroiliitis classification performance was measured using the sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC). The prediction models were evaluated using three-round three-fold cross-validation. Results: A total of 296 participants with 4,746 MRI slices were included in the study. Sacroiliitis was identified in 864 MRI slices of 119 participants. The mean sensitivity, specificity, and AUROC for the detection of sacroiliitis were 0.725 (95% CI, 0.705-0.745), 0.936 (95% CI, 0.924-0.947), and 0.830 (95%CI, 0.792-0.868), respectively, at the image level and 0.947 (95% CI, 0.912-0.982), 0.691 (95% CI, 0.603-0.779), and 0.816 (95% CI, 0.776-0.856), respectively, at the patient level. In the original model, without using MIP and dataset augmentation, the mean sensitivity, specificity, and AUROC were 0.517 (95% CI, 0.493-0.780), 0.944 (95% CI, 0.933-0.955), and 0.731 (95% CI, 0.681-0.780), respectively, at the image level and 0.806 (95% CI, 0.729-0.883), 0.617 (95% CI, 0.523-0.711), and 0.711 (95% CI, 0.660-0.763), respectively, at the patient level. The performance was improved by MIP techniques and data augmentation. Conclusion: An AI model was developed for the detection of sacroiliitis using MRI, compatible with the ASAS criteria for axSpA, with the potential to aid MRI application in a wider clinical setting.

Current Role of Conventional Radiography of Sacroiliac Joints in Adults and Juveniles with Suspected Axial Spondyloarthritis: Opinion from the ESSR Arthritis and Pediatric Subcommittees.

This opinion article by the European Society of Musculoskeletal Radiology Arthritis and Pediatric Subcommittees discusses the current use of conventional radiography (CR) of the sacroiliac joints in adults and juveniles with suspected axial spondyloarthritis (axSpA). The strengths and limitations of CR compared with magnetic resonance imaging (MRI) and computed tomography (CT) are presented.Based on the current literature and expert opinions, the subcommittees recognize the superior sensitivity of MRI to detect early sacroiliitis. In adults, supplementary pelvic radiography, low-dose CT, or synthetic CT may be needed to evaluate differential diagnoses. CR remains the method of choice to detect structural changes in patients with suspected late-stage axSpA or established disease and in patients with suspected concomitant hip or pubic symphysis involvement. In children, MRI is the imaging modality of choice because it can detect active as well as structural changes and is radiation free.

Machine Learning Pipeline for Predicting Bone Marrow Edema Along the Sacroiliac Joints on Magnetic Resonance Imaging.

OBJECTIVE: We aimed to develop and validate a fully automated machine learning (ML) algorithm that predicts bone marrow edema (BME) on a quadrant level in sacroiliac (SI) joint magnetic resonance imaging (MRI). METHODS: A computer vision workflow automatically locates the SI joints, segments regions of interest (ilium and sacrum), performs objective quadrant extraction, and predicts presence of BME, suggestive of inflammatory lesions, on a quadrant level in semicoronal slices of T1/T2-weighted MRI scans. Ground truth was determined by consensus among human readers. The inflammation classifier was trained using a ResNet18 backbone and five-fold cross-validated on scans of patients with spondyloarthritis (SpA) (n = 279), postpartum individuals (n = 71), and healthy subjects (n = 114). Independent SpA patient MRI scans (n = 243) served as test data set. Patient-level predictions were derived from aggregating quadrant-level predictions, ie, at least one positive quadrant. RESULTS: The algorithm automatically detects the SI joints with a precision of 98.4% and segments ilium/sacrum with an intersection over union of 85.6% and 67.9%, respectively. The inflammation classifier performed well in cross-validation: area under the curve (AUC) 94.5%, balanced accuracy (B-ACC) 80.5%, and F1 score 64.1%. In the test data set, AUC was 88.2%, B-ACC 72.1%, and F1 score 50.8%. On a patient level, the model achieved a B-ACC of 81.6% and 81.4% in the cross-validation and test data set, respectively. CONCLUSION: We propose a fully automated ML pipeline that enables objective and standardized evaluation of BME along the SI joints on MRI. This method has the potential to screen large numbers of patients with (suspected) SpA and is a step closer towards artificial intelligence-assisted diagnosis and follow-up.

Two-year imaging outcomes from a phase 3 randomized trial of secukinumab in patients with non-radiographic axial spondyloarthritis.

BACKGROUND: Radiographic progression and course of inflammation over 2 years in patients with non-radiographic axial spondyloarthritis (nr-axSpA) from the phase 3, randomized, PREVENT study are reported here. METHODS: In the PREVENT study, adult patients fulfilling the Assessment of SpondyloArthritis International Society classification criteria for nr-axSpA with elevated CRP and/or MRI inflammation received secukinumab 150 mg or placebo. All patients received open-label secukinumab from week 52 onward. Sacroiliac (SI) joint and spinal radiographs were scored using the modified New York (mNY) grading (total sacroiliitis score; range, 0-8) and modified Stoke Ankylosing Spondylitis Spine Score (mSASSS; range, 0-72), respectively. SI joint bone marrow edema (BME) was assessed using the Berlin Active Inflammatory Lesions Scoring (0-24) and spinal MRI using the Berlin modification of the AS spine MRI (ASspiMRI) scoring (0-69). RESULTS: Overall, 78.9% (438/555) of patients completed week 104 of the study. Over 2 years, minimal changes were observed in total radiographic SI joint scores (mean [SD] change, - 0.04 [0.49] and 0.04 [0.36]) and mSASSS scores (0.04 [0.47] and 0.07 [0.36]) in the secukinumab and placebo-secukinumab groups. Most of the patients showed no structural progression (increase ≤ smallest detectable change) in SI joint score (87.7% and 85.6%) and mSASSS score (97.5% and 97.1%) in the secukinumab and placebo-secukinumab groups. Only 3.3% (n = 7) and 2.9% (n = 3) of patients in the secukinumab and placebo-secukinumab groups, respectively, who were mNY-negative at baseline were scored as mNY-positive at week 104. Overall, 1.7% and 3.4% of patients with no syndesmophytes at baseline in the secukinumab and placebo-secukinumab group, respectively, developed ≥ 1 new syndesmophyte over 2 years. Reduction in SI joint BME observed at week 16 with secukinumab (mean [SD], - 1.23 [2.81] vs - 0.37 [1.90] with placebo) was sustained through week 104 (- 1.73 [3.49]). Spinal inflammation on MRI was low at baseline (mean score, 0.82 and 1.07 in the secukinumab and placebo groups, respectively) and remained low (mean score, 0.56 at week 104). CONCLUSION: Structural damage was low at baseline and most patients showed no radiographic progression in SI joints and spine over 2 years in the secukinumab and placebo-secukinumab groups. Secukinumab reduced SI joint inflammation, which was sustained over 2 years. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02696031.

Early Identification of Sacroiliitis in Patients with Suspected Spondyloarthritis: A Challenging Task.

OBJECTIVE: The purpose of this study was to assess the performance of computed tomography (CT) scan and magnetic resonance imaging (MRI) for detecting sacroiliitis in nonradiographic SpA (nr-SpA). METHODS: This cross-sectional monocentric double-blind study included 63 patients consulting for symptoms suggestive of SpA between February 2014 and February 2017. Patients with conventional radiographs showing a confirmed sacroiliitis (grade 3 or 4) were not included. Eligible patients underwent CT and MRI of sacroiliac joints (SIJ). CT and MR images were interpreted by 2 experienced musculoskeletal radiologists blinded to clinical and laboratory data. Two professors in rheumatology blinded to radiologists' conclusions analyzed clinical data, laboratory tests, HLA typing, X-rays, CT and MRI images, and divided the patients into 2 groups: confirmed nr-SpA or no SpA. This classification was considered the gold standard when analyzing the results. RESULTS: 46 women and 17 men were included in this study. 47 patients were classified as confirmed nr-SpA (74.6%) and 16 patients as no SpA (25.4%). Sensitivity, specificity, and positive and negative predictive values of CT and MRI for detecting sacroiliitis were, respectively, estimated at 71.7%, 71.4%, 89.2%, 43.5%, and 51.2%, 100%, 100%, and 40%. CT and MRI findings were found to be statistically associated (p<0.001). CONCLUSION: SIJ MRI is a highly specific method in the detection of sacroiliitis, but with a moderate sensitivity. SIJ CT scan, usually known as the third option after radiography and MRI, has much greater diagnostic utility than it has been documented previously.

Neural network algorithm for detection of erosions and ankylosis on CT of the sacroiliac joints: multicentre development and validation of diagnostic accuracy.

OBJECTIVES: To evaluate the feasibility and diagnostic accuracy of a deep learning network for detection of structural lesions of sacroiliitis on multicentre pelvic CT scans. METHODS: Pelvic CT scans of 145 patients (81 female, 121 Ghent University/24 Alberta University, 18-87 years old, mean 40 ± 13 years, 2005-2021) with a clinical suspicion of sacroiliitis were retrospectively included. After manual sacroiliac joint (SIJ) segmentation and structural lesion annotation, a U-Net for SIJ segmentation and two separate convolutional neural networks (CNN) for erosion and ankylosis detection were trained. In-training validation and tenfold validation testing (U-Net-n = 10 × 58; CNN-n = 10 × 29) on a test dataset were performed to assess performance on a slice-by-slice and patient level (dice coefficient/accuracy/sensitivity/specificity/positive and negative predictive value/ROC AUC). Patient-level optimisation was applied to increase the performance regarding predefined statistical metrics. Gradient-weighted class activation mapping (Grad-CAM++) heatmap explainability analysis highlighted image parts with statistically important regions for algorithmic decisions. RESULTS: Regarding SIJ segmentation, a dice coefficient of 0.75 was obtained in the test dataset. For slice-by-slice structural lesion detection, a sensitivity/specificity/ROC AUC of 95%/89%/0.92 and 93%/91%/0.91 were obtained in the test dataset for erosion and ankylosis detection, respectively. For patient-level lesion detection after pipeline optimisation for predefined statistical metrics, a sensitivity/specificity of 95%/85% and 82%/97% were obtained for erosion and ankylosis detection, respectively. Grad-CAM++ explainability analysis highlighted cortical edges as focus for pipeline decisions. CONCLUSIONS: An optimised deep learning pipeline, including an explainability analysis, detects structural lesions of sacroiliitis on pelvic CT scans with excellent statistical performance on a slice-by-slice and patient level. CLINICAL RELEVANCE STATEMENT: An optimised deep learning pipeline, including a robust explainability analysis, detects structural lesions of sacroiliitis on pelvic CT scans with excellent statistical metrics on a slice-by-slice and patient level. KEY POINTS: • Structural lesions of sacroiliitis can be detected automatically in pelvic CT scans. • Both automatic segmentation and disease detection yield excellent statistical outcome metrics. • The algorithm takes decisions based on cortical edges, rendering an explainable solution.

Anatomical Variants of the Sacroiliac Joint.

Anatomical variants are frequently encountered when assessing the sacroiliac joints (SIJ) using magnetic resonance imaging. When not located in the weight-bearing part of the SIJ, variants associated with structural and edematous changes can be misinterpreted as sacroiliitis. Their correct identification is necessary to avoid radiologic pitfalls. This article reviews five SIJ variants involved in the dorsal ligamentous space (accessory SIJ, iliosacral complex, semicircular defect, bipartite iliac bony plate, and crescent iliac bony plate) and three SIJ variants involved in the cartilaginous part of the SIJ (posterior dysmorphic SIJ, isolated synostosis, and unfused ossification centers).

Consensus-Driven Definition for Unequivocal Sacroiliitis on Radiographs in Juvenile Spondyloarthritis.

OBJECTIVE: Radiography is still used worldwide for the detection of sacroiliitis in juvenile spondyloarthritis (JSpA), despite its low sensitivity and reliability. We aimed to define unequivocal evidence of sacroiliitis on pelvic radiography in skeletally immature youth for use in classification criteria when magnetic resonance imaging (MRI) is unavailable. METHODS: Subjects were a retrospective cohort of juvenile patients with spondyloarthritis with a radiograph and MRI as part of a diagnostic evaluation for axial disease. Six musculoskeletal imaging experts underwent an iterative consensus process to define unequivocal sacroiliitis on radiography in skeletally immature youth. Radiographs were graded using the modified New York (mNY) criteria and the unequivocal sacroiliitis criteria. Interrater agreement was assessed with the Fleiss [Formula: see text] statistic. Specificity, area under the receiver operator characteristic curve (AUROC), and sensitivity of the 2 measures were tested using 2 MRI reference standards. RESULTS: A total of 112 subjects, with a median age of 14.9 (range 6.7-20.1) years, were included. The Fleiss [Formula: see text] was fair for the mNY criteria (0.54, 95% CI 0.42-0.67) and the unequivocal sacroiliitis criteria (0.58, 95% CI 0.46-0.69). The unequivocal sacroiliitis criteria achieved > 90% specificity using both MRI reference standards. Sensitivity (59.26 and 57.14 vs 44.83 and 43.33) and AUROC (0.76 and 0.76 vs 0.71 and 0.71) were higher, for both reference standards, for the unequivocal sacroiliitis in youth definition than for the mNY criteria, respectively. CONCLUSION: In this study, we propose the first consensus-derived definition to our knowledge of unequivocal sacroiliitis by radiography in skeletally immature youth. This definition achieved excellent specificity and had higher AUROC and sensitivity values than the mNY criteria using both MRI reference standards. This definition has applicability to the JSpA axial disease classification imaging criterion when MRI is unavailable.

Evolution of Magnetic Resonance Imaging Lesions at the Sacroiliac Joints During and After Pregnancy by Serial Magnetic Resonance Imaging From Gestational Week Twenty to Twelve Months Postpartum.

OBJECTIVE: Sacroiliac (SI) joint magnetic resonance imaging (MRI) findings simulating sacroiliitis related to axial spondyloarthritis (SpA) may occur in women before and after birth. This study was undertaken to explore the prevalence, evolution, and topography of SI joint MRI lesions in pregnant and postpartum women. METHODS: A prospective cohort study included 103 first-time mothers who underwent up to 5 serial SI joint MRI between gestational week 20 and 12 months postpartum. After calibration, 3 assessors independently evaluated bone marrow edema (BME), including sacroiliitis according to the Assessment of SpondyloArthritis international Society (ASAS), as well as structural lesions, using the Spondyloarthritis Research Consortium of Canada (SPARCC) and a novel 2-plane assessment method. RESULTS: BME was frequent both during pregnancy and the postpartum period, peaking at 3 months postpartum with a prevalence of 69% (SPARCC) and 80% (2-plane method), but still present in 54% (SPARCC) and 58% (2-plane method) of subjects at 12 months postpartum. At 12 months postpartum, sacroiliitis according to the current ASAS definition was met in 41%, while 21% and 14% of women fulfilled the newly proposed ASAS MRI thresholds for active and structural SI joint lesions, respectively. BME clustered in the anterior middle joint portions at all time points, and ligamentous BME was rare. At 12 months postpartum, SPARCC erosion scores ≥3 (ASAS threshold) were observed in only 2.8% of women. CONCLUSION: At 12 months postpartum, 41% of women met the current ASAS sacroiliitis definition, which may result in false-positive assignments of axial SpA diagnosis in postpartum women with back pain. The topographical BME distribution and virtually absent erosions (ASAS threshold) at 12 months postpartum may help discriminate postpartum strain-related conditions from axial SpA-related sacroiliitis.

Ultrasound guided corticosteroids sacroiliac joint injections (SIJIs) in the management of active sacroiliitis: a real-life prospective experience.

INTRODUCTION: Active sacroiliitis represents the hallmark of axial spondyloarthritis (axSpA) and manifests as inflammatory low back pain associated with morning stiffness (MS). Sometimes, the combination of non-steroidal anti-inflammatory drugs (NSAIDs) and biological disease modifying drugs (bDMARDs) proves unsatisfactory in achieving a remission. MATERIALS AND METHODS: We enrolled patients affected with active sacroiliitis confirmed via magnetic resonance imaging (MRI) and treated with a corticosteroid sacroiliac joint injection (SIJI) via ultrasound guidance. After SIJI, we evaluated visual-analogue scale (VAS) and MS pain changes. As controls, we selected axSpA patients starting bDMARDs. RESULTS: We enrolled 26 patients (mean age 55 ± 14 years; 25 females and 1 male; > 95% treated with NSAIDs; 46% on bDMARDs; 75.82 ± 123 months) and examined a total of 47 treated joints. We detected a 48% reduction in VAS pain after 24 h. Moreover, we observed a significant reduction (p < 0.0001) of VAS pain between the baseline and every subsequent follow-up visit. Further, a significant difference in VAS pain compared to the baseline in the controls was observed starting from week 12. There was a significant reduction in MS after 1 week due to SIJIs, while in the controls the first significant change from the baseline in MS was detected after 12 weeks. The efficacy of infiltrative therapy lasted up to 6 months: persistent VAS as well as MS pain reduction was observed. CONCLUSIONS: US-guided SIJI represents an effective and safe technique for patients who have active sacroiliitis yet are ineligible for biologic treatment or who experience unsatisfactory disease control despite receiving therapy.

Response to netakimab in radiographic axial spondyloarthritis patients with different baseline C-reactive protein, sacroiliitis evaluated by MRI and peripheral joint involvement status: a post-hoc analysis of the ASTERA study.

OBJECTIVES: Netakimab is a humanised camelid-derived monoclonal antibody targeting interleukin-17A. Here, we report the results of post-hoc analysis of the ASTERA phase 3 study (NCT03447704, February 27, 2018) in patients with active radiographic axial spondyloarthritis (r-axSpA) grouped by baseline C-reactive protein (CRP), baseline sacroiliac joint (SIJ) inflammation through magnetic resonance imaging (MRI) or presence of peripheral arthritis (PA). METHODS: In this double-blinded, multicentre, randomised, placebo-controlled, phase 3 ASTERA study, 228 adult patients with active r-axSpA received 120 mg of subcutaneous netakimab or placebo at weeks 0, 1, 2, and thereafter every other week. For the subanalysis, 16-week data of 114 netakimab-treated patients with the available baseline CRP and SIJ MRI were grouped by normal (<5 mg/L) or abnormal (≥5 mg/L) CRP, by the grade of sacroiliitis (SI) based on the SPARCC MRI score <2 (MRI-SI-) or ≥2 (MRI-SI+), or by the presence of PA. ASAS-recommended activity, spinal mobility, and function endpoints for r-axSpA were analysed. RESULTS: At week 16, an improvement in all the outcomes was similar for MRI-SI- and MRI-SI+ patients, except for a change in ASspi-MRI-a which was significantly greater in MRI-SI+. Netakimab was effective regardless of baseline CRP and PA. For patients with CRP ≥5 mg/L, a more pronounced decline in r-axSpA activity was observed with a trend towards the most prominent improvement in ASDAS-CRP and BASDAI for patients with CRP >20 mg/L. CONCLUSIONS: Subcutaneous netakimab is effective in patients with r-axSpA irrespective of baseline CRP and inflammation on SIJ MRI. The benefit in patients with high CRP (>20 mg/L) was more pronounced.

Presence of axial spondyloarthritis associated sacroiliitis and structural changes on MR enterography: A direct comparison with sacroiliac joint MRI.

INTRODUCTION: To investigate the acute inflammatory and structural changes of sacroiliitis as auxiliary findings on magnetic resonance enterography (MRE) and their presence on closely timed conventional magnetic resonance imaging of the sacroiliac joint (SI joint MRI). MATERIALS AND METHODS: We screened axial spondyloarthritis patients for the simultaneous presence of MREs and SI joint MRIs. Two blinded radiologists evaluated SI joint MRIs and MREs on two separate occasions. We used the Assessment of SpondyloArthritis International Society (ASAS)/Outcome Measures in Rheumatology Network (OMERACT) definitions for SI joint MRI. We implemented previously published standard definitions for osteitis, erosion, sclerosis, and fatty infiltration of SI joint in MREs that contain T1w and T1w post-gadolinium sequences. RESULTS: SI joint MRI and MRE images were present in 43 patients. The median time between the two modalities was 14 (0-89) days. Twelve patients had ASAS-defined positive SI joint MRI. Radiologist-1 and radiologist-2 detected osteitis on MRE in nine and eight out of these 12 patients, respectively. The two radiologists detected ankylosis and fatty metaplasia with a complete agreement and sclerosis with an almost perfect agreement. Both radiologists agreed on erosions on SI joint MRI in the same 10 cases. Radiologists did not identify acute inflammatory or structural changes on MRE in patients with a negative SI joint MRI for these lesions. CONCLUSION: Along with intestinal findings, additional reporting of acute inflammatory and structural changes of the SI joint on a MRE is valuable and may alert physicians to the presence of previously not diagnosed axial spondyloarthritis.

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?

Evaluation of active inflammation, chronic structural damage, and response to treatment of sacroiliitis in axial spondyloarthritis using the Spondyloarthritis research consortium of Canada scoring system.

BACKGROUND: Axial spondyloarthritis (axSpA) is a chronic inflammatory rheumatic disease affecting the spine and sacroiliac joints. To investigate whether there are differences in inflammatory and chronic structural damages, as assessed by a semiquantitative MRI scoring method, between non-radiographic axial spondyloarthritis (nr-axSpA) and ankylosing spondylitis (AS) patients with active inflammation at baseline, and to evaluate the treatment response in these patients after 3 months of tumor necrosis factor-alpha (TNF-α) inhibitor treatment. METHODS: Fifty-eight axSpA patients with active inflammation were included in the study. The patients were divided into nr-axSpA group and AS group. MRI examinations of the sacroiliac joints were performed before and after treatment. Inflammatory and structural damages in these patients were assessed using the established Spondyloarthritis Research Consortium of Canada (SPARCC) inflammation and sacroiliac joint structural (SSS) scoring methods, which are two MRI-based scoring methods. The SPARCC score, SSS score, erythrocyte sedimentation rate (ESR), and C-reactive protein (CRP) level were compared between the two groups. RESULTS: At baseline, SPARCC scores for patients in the nr-axSpA and AS groups did not differ significantly (P > 0.05); however, SSS scores for fat metaplasia, erosion, and backfill for patients in the AS group were significantly higher (P < 0.001). Compared with baseline, SPARCC scores were significantly decreased in both groups after treatment (P < 0.001); however, after treatment, no statistically significant difference was found regarding SPARCC scores between the AS and nr-axSpA groups. Compared with baseline, a significant increase in the SSS scores for fat metaplasia and backfill (P < 0.001) and a significant decrease in the SSS scores for erosion (P < 0.001) were observed in all axSpA patients. Changes in the SPARCC score was inversely correlated with the changes in the SSS score for fat metaplasia (r = - 0.634, P < 0.001). Changes in the SSS score for backfill were positively correlated with the changes in the SSS score for fat metaplasia (r = 0.277, P < 0.05) and inversely correlated with those for erosion (r = - 0.443, P < 0.001). CONCLUSION: The SPARCC and SSS scoring systems can be used to assess inflammatory and chronic structural damages as well as treatment responses in patients with axSpA. More severe structural damages were seen in AS patients. TNF-α inhibitor treatment for 3 months could effectively reduce inflammation in axSpA patients.