A Novel Fluorescence Optical Imaging Scoring System for Hand Synovitis in Rheumatoid Arthritis - validity and agreement with ultrasound

[Can rheuma be scanned? : Review of the current study situation on fluorescence optical imaging]

BACKGROUND

The novel technique of indocyanine green (ICG)-based fluorescence optical imaging (FOI) using the Xiralite® system (Rheumascan) has been the subject of many different studies worldwide since approval for clinical use in the European Union (2009), USA (2014) and Asia. The FOI depicts the disturbed microcirculation in the joints of both hands caused by inflammation.

OBJECTIVE

The aim of this article is to provide an overview of the current state of studies on ICG-based FOI in different rheumatologic indications.

METHODS

A narrative literature review of publications on ICG-based FOI in the diagnosis of various inflammatory rheumatic joint diseases since 2010 is presented, its use in treatment monitoring is explained, and its value in systemic sclerosis is outlined.

RESULTS

In summary, studies have extensively demonstrated the accuracy of FOI in inflammation detection. Therefore, it can be concluded that FOI is a good supplement to existing imaging modalities. Due to characteristic patterns of both skin and nails, FOI is an indicated procedure especially in psoriatic arthritis and can be very helpful in the diagnostic process in early undifferentiated arthritis. The FOI has shown its usefulness in children (juvenile idiopathic arthritis), for monitoring the course of treatment, and for demonstrating disturbed microcirculation in patients with systemic sclerosis.

CONCLUSION

The presented data imply that FOI should be considered as a valuable complementary imaging tool in the diagnostic algorithm of daily rheumatologic practice, both for diagnosis and for follow-up monitoring. In particular, the automated analyses should be able in the future to objectify measurements of inflammatory activity as well as monitoring the response to treatment.

Distinct Fluorescence Optical Imaging Patient Clusters Emerge for Seropositive and Seronegative Rheumatoid Arthritis

OBJECTIVE

To investigate whether digital activity fluorescence optical imaging (FOI) patterns of inflammation can identify distinct rheumatoid arthritis (RA) phenotypes.

METHODS

The hands of newly diagnosed patients with RA were evaluated by clinical examination, musculoskeletal ultrasound, and FOI. Inflammation on FOI was defined when capillary leakage and/or fluorophore perfusion was present. The FOI composite image was quantified into a digital disease activity (DACT) score, using novel computerized algorithms. Unsupervised clustering on FOI inflammatory patterns was used to identify subgroups of patients relative to anticyclic citrullinated peptides (ACPA) and/or rheumatoid factor (RF).

RESULTS

Of 1326 examined hand joints in 39 patients with RA (72% female; 56% ever-smokers; 54% RF positive and 69% ACPA positive), 400 (30%) showed inflammation by FOI, and 95% (37 of 39) of patients had DACT-FOI scores greater than 1. Unsupervised analysis on FOI patterns revealed two patient clusters, cluster 1 (n = 29) and cluster 2 (n = 10). The proportion of seropositive patients was significantly higher in cluster 1 versus cluster 2 (90%, 26 of 29 vs. 30%, 3 of 10; P < 0.01), whereas C-reactive-protein levels (minimum-maximum) were significantly higher in cluster 2 (20 mg/l [1-102]) versus cluster 1 (2 mg/l [0-119]; P = 0.01). A wider variety and proportion of inflamed joints emerged for patients with RA in cluster 2 versus cluster 1, in which inflammation was more concentrated around the wrists and the right metacarpophalangeal 2 (MCP2), bilateral MCP3, and, to a lesser degree, left MCP2 and proximal interphalangeal joint and tendon regions. Cluster 1 displayed lower mean (±SD) DACT scores compared with cluster 2 (3.6 ± 2.1 vs. 5.4 ± 2.1; P = 0.03).

CONCLUSION

FOI-based digital quantification of hand joint inflammation revealed two distinct RA subpopulations with and without ACPA and RF related autoantibodies.

Fluorescence optical imaging feature selection with machine learning for differential diagnosis of selected rheumatic diseases

Background and objective

Accurate and fast diagnosis of rheumatic diseases affecting the hands is essential for further treatment decisions. Fluorescence optical imaging (FOI) visualizes inflammation-induced impaired microcirculation by increasing signal intensity, resulting in different image features. This analysis aimed to find specific image features in FOI that might be important for accurately diagnosing different rheumatic diseases.

Patients and methods

FOI images of the hands of patients with different types of rheumatic diseases, such as rheumatoid arthritis (RA), osteoarthritis (OA), and connective tissue diseases (CTD), were assessed in a reading of 20 different image features in three phases of the contrast agent dynamics, yielding 60 different features for each patient. The readings were analyzed for mutual differential diagnosis of the three diseases (One-vs-One) and each disease in all data (One-vs-Rest). In the first step, statistical tools and machine-learning-based methods were applied to reveal the importance rankings of the features, that is, to find features that contribute most to the model-based classification. In the second step machine learning with a stepwise increasing number of features was applied, sequentially adding at each step the most crucial remaining feature to extract a minimized subset that yields the highest diagnostic accuracy.

Results

In total, n = 605 FOI of both hands were analyzed (n = 235 with RA, n = 229 with OA, and n = 141 with CTD). All classification problems showed maximum accuracy with a reduced set of image features. For RA-vs.-OA, five features were needed for high accuracy. For RA-vs.-CTD ten, OA-vs.-CTD sixteen, RA-vs.-Rest five, OA-vs.-Rest eleven, and CTD-vs-Rest fifteen, features were needed, respectively. For all problems, the final importance ranking of the features with respect to the contrast agent dynamics was determined.

Conclusions

With the presented investigations, the set of features in FOI examinations relevant to the differential diagnosis of the selected rheumatic diseases could be remarkably reduced, providing helpful information for the physician.

Features Found in Indocyanine Green-Based Fluorescence Optical Imaging of Inflammatory Diseases of the Hands

Rheumatologists in Europe and the USA increasingly rely on fluorescence optical imaging (FOI, Xiralite) for the diagnosis of inflammatory diseases. Those include rheumatoid arthritis, psoriatic arthritis, and osteoarthritis, among others. Indocyanine green (ICG)-based FOI allows visualization of impaired microcirculation caused by inflammation in both hands in one examination. Thousands of patients are now documented and most literature focuses on inflammatory arthritides, which affect synovial joints and their related structures, making it a powerful tool in the diagnostic process of early undifferentiated arthritis and rheumatoid arthritis. However, it has become gradually clear that this technique has the potential to go even further than that. FOI allows visualization of other types of tissues. This means that FOI can also support the diagnostic process of vasculopathies, myositis, collagenoses, and other connective tissue diseases. This work summarizes the most prominent imaging features found in FOI examinations of inflammatory diseases, outlines the underlying anatomical structures, and introduces a nomenclature for the features and, thus, supports the idea that this tool is a useful part of the imaging repertoire in rheumatology clinical practice, particularly where other imaging methods are not easily available.

Fluorescence optical imaging: ready for prime time?

The novel technique of fluorescence optical imaging (FOI, Xiralite), which is approved in the European Union and the USA for clinical use, has been the object of studies since 2009. Indocyanine green-based FOI can demonstrate an impaired microcirculation caused by inflammation in both hands in one examination. Several studies have investigated FOI for detection of joint inflammation by comparing FOI to magnetic resonance imaging (MRI) and/or musculoskeletal ultrasound (MSUS). The results have shown a generally good agreement (>80%) between FOI and clinical examination, MRI and MSUS by power Doppler in inflammatory joint diseases. Moreover, characteristic enhancements in skin and nails are seen in PsA, which potentially can be useful in the diagnostic process of early undifferentiated arthritis. Furthermore, FOI has been investigated for the visualisation of a disturbed microcirculation in the hands and fingers of patients with systemic sclerosis (SSc), highlighting the potential of monitoring vascular changes in SSc and other vasculopathies. The available data indicate that it is time to consider FOI as a useful part of the imaging repertoire in rheumatology clinical practice, particularly where MSUS and MRI are not easily available.