Tumor necrosis factor inhibitor therapy but not standard therapy is associated with resolution of erosion in the sacroiliac joints of patients with axial spondyloarthritis

INTRODUCTION: Radiography is an unreliable and insensitive tool for the assessment of structural lesions in the sacroiliac joints (SIJ). Magnetic resonance imaging (MRI) detects a wider spectrum of structural lesions but has undergone minimal validation in prospective studies. The Spondyloarthritis Research Consortium of Canada (SPARCC) MRI Sacroiliac Joint (SIJ) Structural Score (SSS) assesses a spectrum of structural lesions (erosion, fat metaplasia, backfill, ankylosis) and its potential to discriminate between therapies requires evaluation. METHODS: The SSS score assesses five consecutive coronal slices through the cartilaginous portion of the joint on T1-weighted sequences starting from the transitional slice between cartilaginous and ligamentous portions of the joint. Lesions are scored dichotomously (present/absent) in SIJ quadrants (fat metaplasia, erosion) or halves (backfill, ankylosis). Two readers independently scored 147 pairs (baseline, 2 years) of scans from a prospective cohort of patients with SpA who received either standard (n = 69) or tumor necrosis factor alpha (TNFα) inhibitor (n = 78) therapy. Smallest detectable change (SDC) was calculated using analysis of variance (ANOVA), discrimination was assessed using Guyatt’s effect size, and treatment group differences were assessed using t-tests and the Mann–Whitney test. We identified baseline demographic and structural damage variables associated with change in SSS score by univariate analysis and analyzed the effect of treatment by multivariate stepwise regression adjusted for severity of baseline structural damage and demographic variables. RESULTS: A significant increase in mean SSS score for fat metaplasia (P = 0.017) and decrease in mean SSS score for erosion (P = 0.017) was noted in anti-TNFα treated patients compared to those on standard therapy. Effect size for this change in SSS fat metaplasia and erosion score was moderate (0.5 and 0.6, respectively). Treatment and baseline SSS score for erosion were independently associated with change in SSS erosion score (β = 1.75, P = 0.003 and β = 0.40, P < 0.0001, respectively). Change in ASDAS (β = −0.46, P = 0.006), SPARCC MRI SIJ inflammation (β = −0.077, P = 0.019), and baseline SSS score for fat metaplasia (β = 0.085, P = 0.034) were independently associated with new fat metaplasia. CONCLUSION: The SPARCC SSS method for assessment of structural lesions has discriminative capacity in demonstrating significantly greater reduction in erosion and new fat metaplasia in patients receiving anti-TNFα therapy

Weakly Supervised Medical Image Segmentation With Soft Labels and Noise Robust Loss

Recent advances in deep learning algorithms have led to significant benefits for solving many medical image analysis problems. Training deep learning models commonly requires large datasets with expert-labeled annotations. However, acquiring expert-labeled annotation is not only expensive but also is subjective, error-prone, and inter-/intra- observer variability introduces noise to labels. This is particularly a problem when using deep learning models for segmenting medical images due to the ambiguous anatomical boundaries. Image-based medical diagnosis tools using deep learning models trained with incorrect segmentation labels can lead to false diagnoses and treatment suggestions. Multi-rater annotations might be better suited to train deep learning models with small training sets compared to single-rater annotations. The aim of this paper was to develop and evaluate a method to generate probabilistic labels based on multi-rater annotations and anatomical knowledge of the lesion features in MRI and a method to train segmentation models using probabilistic labels using normalized active-passive loss as a "noise-tolerant loss" function. The model was evaluated by comparing it to binary ground truth for 17 knees MRI scans for clinical segmentation and detection of bone marrow lesions (BML). The proposed method successfully improved precision 14, recall 22, and Dice score 8 percent compared to a binary cross-entropy loss function. Overall, the results of this work suggest that the proposed normalized active-passive loss using soft labels successfully mitigated the effects of noisy labels

Validation of SPARCC MRI-RETIC e-tools for increasing scoring proficiency of MRI sacroiliac joint lesions in axial spondyloarthritis

BACKGROUND The Spondyloarthritis Research Consortium of Canada (SPARCC) developers have created web-based calibration modules for the SPARCC MRI sacroiliac joint (SIJ) scoring methods. We aimed to test the impact of applying these e-modules on the feasibility and reliability of these methods. METHODS The SPARCC-SIJ $_{RETIC}$ e-modules contain cases with baseline and follow-up scans and an online scoring interface. Visual real-time feedback regarding concordance/discordance of scoring with expert readers is provided by a colour-coding scheme. Reliability is assessed in real time by intraclass correlation coefficient (ICC), cases being scored until ICC targets are attained. Participating readers (n=17) from the EuroSpA Imaging project were randomised to one of two reader calibration strategies that each comprised three stages. Baseline and follow-up scans from 25 cases were scored after each stage was completed. Reliability was compared with a SPARCC developer, and the System Usability Scale (SUS) assessed feasibility. RESULTS The reliability of readers for scoring bone marrow oedema was high after the first stage of calibration, and only minor improvement was noted following the use of the inflammation module. Greater enhancement of reader reliability was evident after the use of the structural module and was most consistently evident for the scoring of erosion (ICC status/change: stage 1 (0.42/0.20) to stage 3 (0.50/0.38)) and backfill (ICC status/change: stage 1 (0.51/0.19) to stage 3 (0.69/0.41)). The feasibility of both e-modules was evident by high SUS scores. CONCLUSION The SPARCC-SIJ $_{RETIC}$ e-modules are feasible, effective knowledge transfer tools, and their use is recommended before using the SPARCC methods for clinical research and tria

MRI evidence of structural changes in the sacroiliac joints of patients with non-radiographic axial spondyloarthritis even in the absence of MRI inflammation

Abstract Background Studies have shown that structural lesions may be present in patients with non-radiographic axial spondyloarthritis (nr-axSpA). However, the relevance of structural lesions in these patients is unclear, particularly without signs of inflammation on magnetic resonance imaging (MRI). We assessed the presence of structural lesions at baseline on MRI in the sacroiliac joints (SIJ) of patients with nr-axSpA with and without SIJ inflammation on MRI. Methods Bone marrow edema (BME) was assessed on short tau inversion recovery (STIR) scans from 185 patients with nr-axSpA, by two independent readers at baseline using the Spondyloarthritis Research Consortium of Canada (SPARCC) score. Structural lesions were evaluated on T1 weighted spin echo scans, with readers blinded to STIR scans, using the SPARCC MRI SIJ structural score. Disease characteristics and structural lesions were compared in patients with SIJ BME (score ≥2) and without SIJ BME (score <2). Results Both SIJ BME and structural lesions scores were available for 183 patients; 128/183 (69.9%) patients had SIJ BME scores ≥2 and 55/183 (30.1%) had scores <2. Frequencies of MRI structural lesions in patients with vs without SIJ BME were: erosions (45.3% vs 10.9%, P < 0.001), backfill (20.3% vs 0%, P < 0.001), fat metaplasia (10.9% vs 1.8%, P = 0.04), and ankylosis (2.3% vs 1.8%, P = ns). Significantly more patients with both SIJ BME and structural lesions were male and/or HLA-B27 positive than patients with only SIJ BME. Mean (SD) spinal scores (23 discovertebral units) were significantly higher in patients with SIJ structural lesions than without: 6.5 (11.5) vs 3.3 (5.1), respectively, P = 0.01. Conclusions In patients with nr-axSpA, SIJ structural lesions, particularly erosions, may be present on MRI when radiographs are normal or inconclusive, even in patients negative for MRI SIJ inflammation. They may reflect more severe disease with greater spinal inflammation. Trial Registration ClinicalTrials.gov, NCT01258738 . Registered on 9 December 2010

Circulating protein fragments of cartilage and connective tissue degradation are diagnostic and prognostic markers of rheumatoid arthritis and ankylosing spondylitis.

Inflammation driven connective tissue turnover is key in rheumatic diseases, such as ankylosing spondylitis (AS). Few biomarkers are available for measuring disease prognosis or the efficacy of interventions applied in these tissue-related conditions. Type II collagen is the primary structural protein of cartilage and type III collagen of connective tissues, and obvious targets for the collagenalytic, which increase during tissue inflammation. The objective of the study was to investigate the diagnostic and prognostic utility of cartilage, C2M, and synovial, C3M, turnover biomarkers in AS. Serum samples were retrieved from patients suffering from AS (n = 103), RA (n = 47) and healthy controls (n = 56). AS progressors were defined as having new vertebral syndesmophytes or more that 3 unit change in mSASSS over a two-year period. Type II collagen degradation markers in serum were measured by the C2M ELISA, and type III collagen degradation by the C3M ELISA. Logistic regression and dichotomized decision tree were used to analyze the prognostic value of the markers individually or in combination. Both C2M and C3M levels were significantly higher in RA patients than in healthy controls (p<0.0001). Diagnostic utility was analyzed by ROC and areas under the curve (AUCs) were 72% and 89% for C2M and C3M, respectively. Both C2M and C3M, were significantly higher in serum samples from AS patient than from healthy controls (p<0.0001). The AUCs of C2M and C3M, respectively, were 70% and 81% for AS. A combination of C2M and C3M, dichotomized according to best cut-offs for individual markers, could correctly identify 80% of the progressors and 61% of the non-progressors. The present study is the first to show that specific biomarkers of cartilage and connective tissue degradation facilitate both diagnosis and prediction of progression of RA and AS

2D/3D ultrasound diagnosis of pediatric distal radius fractures by human readers vs artificial intelligence

Abstract Wrist trauma is common in children and generally requires radiography for exclusion of fractures, subjecting children to radiation and long wait times in the emergency department. Ultrasound (US) has potential to be a safer, faster diagnostic tool. This study aimed to determine how reliably US could detect distal radius fractures in children, to contrast the accuracy of 2DUS to 3DUS, and to assess the utility of artificial intelligence for image interpretation. 127 children were scanned with 2DUS and 3DUS on the affected wrist. US scans were then read by 7 blinded human readers and an AI model. With radiographs used as the gold standard, expert human readers obtained a mean sensitivity of 0.97 and 0.98 for 2DUS and 3DUS respectively. The AI model sensitivity was 0.91 and 1.00 for 2DUS and 3DUS respectively. Study data suggests that 2DUS is comparable to 3DUS and AI diagnosis is comparable to human experts

Additional file 2: of MRI evidence of structural changes in the sacroiliac joints of patients with non-radiographic axial spondyloarthritis even in the absence of MRI inflammation

Lesions seen on T1 weighted spin echo MRI. (PDF 128 kb

Comparative validation of the knee inflammation MRI scoring system and the MRI osteoarthritis knee score for semi-quantitative assessment of bone marrow lesions and synovitis-effusion in osteoarthritis: an international multi-reader exercise

Background: Bone marrow lesions (BMLs) and synovitis on magnetic resonance imaging (MRI) are associated with symptoms and predict degeneration of articular cartilage in osteoarthritis (OA). Validated methods for their semiquantitative assessment on MRI are available, but they all have similar scoring designs and questionable sensitivity to change. New scoring methods with completely different designs need to be developed and compared to existing methods. Objectives: To compare the performance of new web-based versions of the Knee Inflammation MRI Scoring System (KIMRISS) with the MRI OA Knee Score (MOAKS) for quantification of BMLs and synovitis-effusion (S-E). Design: Retrospective follow-up cohort. Methods: We designed web-based overlays outlining regions in the knee that are scored for BML in MOAKS and KIMRISS. For KIMRISS, both BML and S-E are scored on consecutive sagittal slices. The performance of these methods was compared in an international reading exercise of 8 readers evaluating 60 pairs of scans conducted 1 year apart from cases recruited to the OA Initiative (OAI) cohort. Interobserver reliability for baseline status and baseline to 1 year change in BML and S-E was assessed by intra-class correlation coefficient (ICC) and smallest detectable change (SDC). Feasibility was assessed using the System Usability Scale (SUS). Results: Mean change in BML and S-E was minimal over 1 year. Pre-specified targets for acceptable reliability (ICC ⩾ 0.80 and ⩾ 0.70 for status and change scores, respectively) were achieved more frequently for KIMRISS for both BML and synovitis. Mean (95% CI) ICC for change in BML was 0.88 (0.83–0.92) and 0.69 (0.60–0.78) for KIMRISS and MOAKS, respectively. KIMRISS mean SUS usability score was 85.7 and at the 95th centile of ranking for usability versus a score of 55.4 and 20th centile for MOAKS. Conclusion: KIMRISS had superior performance metrics to MOAKS for quantification of BML and S-E. Both methods should be further compared in trials of new therapies for OA