Common incidental findings on sacroiliac joint MRI: Added value of MRI-based synthetic CT

A multipurpose, adolescent idiopathic scoliosis-specific, short MRI protocol: A feasibility study in volunteers

INTRODUCTION

Visualization of scoliosis typically requires ionizing radiation (radiography and CT) to visualize bony anatomy. MRI is often additionally performed to screen for neural axis abnormalities. We propose a 14-minutes radiation-free scoliosis-specific MRI protocol, which combines MRI and MRI-based synthetic CT images to visualize soft and osseous structures in one examination. We assess the ability of the protocol to visualize landmarks needed to detect 3D patho-anatomical changes, screen for neural axis abnormalities, and perform surgical planning and navigation.

METHODS

18 adult volunteers were scanned on 1.5 T MR-scanner using 3D T2-weighted and synthetic CT sequences. A predefined checklist of relevant landmarks was used for the parameter assessment by three readers. Parameters included Cobb angles, rotation, torsion, segmental height, area and centroids of Nucleus Pulposus and Intervertebral Disc. Precision, reliability and agreement between the readers measurements were evaluated.

RESULTS

91 % of Likert-based questions scored ≥ 4, indicating moderate to high confidence. Precision of 3D dot positioning was 1.0 mm. Precision of angle measurement was 0.6° (ICC 0.98). Precision of vertebral and IVD height measurements was 0.4 mm (ICC 0.99). Precision of area measurement for NP was 8 mm2 (ICC 0.55) and for IVD 18 mm2 (ICC 0.62) for IVD. Precision of centroid measurement for NP was 1.3 mm (ICC 0.88-0.92) and for IVD 1.1 mm (ICC 0.88-91).

CONCLUSIONS

The proposed MRI protocol with synthetic CT reconstructions, has high precision, reliability and agreement between the readers for multiple scoliosis-specific measurements. It can be used to study scoliosis etiopathogenesis and to assess 3D spinal morphology.

Artificial intelligence to analyze magnetic resonance imaging in rheumatology

Rheumatic disorders present a global health challenge, marked by inflammation and damage to joints, bones, and connective tissues. Accurate, timely diagnosis and appropriate management are crucial for favorable patient outcomes. Magnetic resonance imaging (MRI) has become indispensable in rheumatology, but interpretation remains laborious and variable. Artificial intelligence (AI), including machine learning (ML) and deep learning (DL), offers a means to improve and advance MRI analysis. This review examines current AI applications in rheumatology MRI analysis, addressing diagnostic support, disease classification, activity assessment, and progression monitoring. AI demonstrates promise, with high sensitivity, specificity, and accuracy, achieving or surpassing expert performance. The review also discusses clinical implementation challenges and future research directions to enhance rheumatic disease diagnosis and management.

The sacroiliac joint across ages - what is normal?

The anatomy of the sacroiliac joint (SIJ) is complex with wide variations inter-individually as well as intra-individually (right versus left) and a frequent occurrence of anatomical variants. Besides, the joints are subject to strain, which may elicit non-inflammatory subchondral changes such as bone marrow edema (BME), sclerosis, and fat deposition simulating inflammatory SIJ changes. Furthermore, normal physiological changes during skeletal maturation can make interpretation of SIJ magnetic resonance imaging in children challenging. Knowledge about the wide range of normal findings is therefore important to avoid misinterpretation of findings as pathological. This review describes the current knowledge about normal SIJ findings across all ages.

MRI-based synthetic CT: a new method for structural damage assessment in the spine in patients with axial spondyloarthritis - a comparison with low-dose CT and radiography

OBJECTIVE

To investigate the ability of MRI-based synthetic CT (sCT), low-dose CT (ldCT) and radiography to detect spinal new bone formation (NBF) in patients with axial spondyloarthritis (axSpA).

METHODS

Radiography of lumbar and cervical spine, ldCT and sCT of the entire spine were performed in 17 patients with axSpA. sCT was reconstructed using the BoneMRI application (V.1.6, MRIGuidance BV, Utrecht, NL), a quantitative three-dimensional MRI-technique based on a dual-echo gradient sequence and a machine learning processing pipeline that can generate CT-like MR images. Images were anonymised and scored by four readers blinded to other imaging/clinical information, applying the Canada-Denmark NBF assessment system.

RESULTS

Mean scores of NBF lesions for the four readers were 188/209/37 for ldCT/sCT/radiography. Most NBF findings were at anterior vertebral corners with means 163 on ldCT, 166 on sCT and 35 on radiography. With ldCT of the entire spine as reference standard, the sensitivity to detect NBF was 0.67/0.13 for sCT/radiography; both with specificities >0.95. For levels that were assessable on radiography (C2-T1 and T12-S1), the sensitivity was 0.61/0.48 for sCT/radiography, specificities >0.90. For facet joints, the sensitivity was 0.46/0.03 for sCT/radiography, specificities >0.94. The mean inter-reader agreements (kappa) for all locations were 0.68/0.58/0.56 for ldCT/sCT/radiography, best for anterior corners.

CONCLUSION

With ldCT as reference standard, MRI-based sCT of the spine showed very high specificity and a sensitivity much higher than radiography, despite limited reader training. sCT could become highly valuable for detecting/monitoring structural spine damage in axSpA, not the least in clinical trials.

Implementation of artificial intelligence models in magnetic resonance imaging with focus on diagnosis of rheumatoid arthritis and axial spondyloarthritis: narrative review

Early diagnosis in rheumatoid arthritis (RA) and axial spondyloarthritis (axSpA) is essential to initiate timely interventions, such as medication and lifestyle changes, preventing irreversible joint damage, reducing symptoms, and improving long-term outcomes for patients. Since magnetic resonance imaging (MRI) of the wrist and hand, in case of RA and MRI of the sacroiliac joints (SIJ) in case of axSpA can identify inflammation before it is clinically discernible, this modality may be crucial for early diagnosis. Artificial intelligence (AI) techniques, together with machine learning (ML) and deep learning (DL) have quickly evolved in the medical field, having an important role in improving diagnosis, prognosis, in evaluating the effectiveness of treatment and monitoring the activity of rheumatic diseases through MRI. The improvements of AI techniques in the last years regarding imaging interpretation have demonstrated that a computer-based analysis can equal and even exceed the human eye. The studies in the field of AI have investigated how specific algorithms could distinguish between tissues, diagnose rheumatic pathology and grade different signs of early inflammation, all of them being crucial for tracking disease activity. The aim of this paper is to highlight the implementation of AI models in MRI with focus on diagnosis of RA and axSpA through a literature review.

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.