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.

Training data distribution significantly impacts the estimation of tissue microstructure with machine learning.

PURPOSE: Supervised machine learning (ML) provides a compelling alternative to traditional model fitting for parameter mapping in quantitative MRI. The aim of this work is to demonstrate and quantify the effect of different training data distributions on the accuracy and precision of parameter estimates when supervised ML is used for fitting. METHODS: We fit a two- and three-compartment biophysical model to diffusion measurements from in-vivo human brain, as well as simulated diffusion data, using both traditional model fitting and supervised ML. For supervised ML, we train several artificial neural networks, as well as random forest regressors, on different distributions of ground truth parameters. We compare the accuracy and precision of parameter estimates obtained from the different estimation approaches using synthetic test data. RESULTS: When the distribution of parameter combinations in the training set matches those observed in healthy human data sets, we observe high precision, but inaccurate estimates for atypical parameter combinations. In contrast, when training data is sampled uniformly from the entire plausible parameter space, estimates tend to be more accurate for atypical parameter combinations but may have lower precision for typical parameter combinations. CONCLUSION: This work highlights that estimation of model parameters using supervised ML depends strongly on the training-set distribution. We show that high precision obtained using ML may mask strong bias, and visual assessment of the parameter maps is not sufficient for evaluating the quality of the estimates.

Comparative analysis of signal models for microscopic fractional anisotropy estimation using q-space trajectory encoding.

Microscopic diffusion anisotropy imaging using diffusion-weighted MRI and multidimensional diffusion encoding is a promising method for quantifying clinically and scientifically relevant microstructural properties of neural tissue. Several methods for estimating microscopic fractional anisotropy (µFA), a normalized measure of microscopic diffusion anisotropy, have been introduced but the differences between the methods have received little attention thus far. In this study, the accuracy and precision of µFA estimation using q-space trajectory encoding and different signal models were assessed using imaging experiments and simulations. Three healthy volunteers and a microfibre phantom were imaged with five non-zero b-values and gradient waveforms encoding linear and spherical b-tensors. Since the ground-truth µFA was unknown in the imaging experiments, Monte Carlo random walk simulations were performed using axon-mimicking fibres for which the ground truth was known. Furthermore, parameter bias due to time-dependent diffusion was quantified by repeating the simulations with tuned waveforms, which have similar power spectra, and with triple diffusion encoding, which, unlike q-space trajectory encoding, is not based on the assumption of time-independent diffusion. The truncated cumulant expansion of the powder-averaged signal, gamma-distributed diffusivities assumption, and q-space trajectory imaging, a generalization of the truncated cumulant expansion to individual signals, were used to estimate µFA. The gamma-distributed diffusivities assumption consistently resulted in greater µFA values than the second order cumulant expansion, 0.1 greater when averaged over the whole brain. In the simulations, the generalized cumulant expansion provided the most accurate estimates. Importantly, although time-dependent diffusion caused significant overestimation of µFA using all the studied methods, the simulations suggest that the resulting bias in µFA is less than 0.1 in human white matter.

On the potential for mapping apparent neural soma density via a clinically viable diffusion MRI protocol.

Diffusion MRI is a valuable tool for probing tissue microstructure in the brain noninvasively. Today, model-based techniques are widely available and used for white matter characterisation where their development is relatively mature. Conversely, tissue modelling in grey matter is more challenging, and no generally accepted models exist. With advances in measurement technology and modelling efforts, a clinically viable technique that reveals salient features of grey matter microstructure, such as the density of quasi-spherical cell bodies and quasi-cylindrical cell projections, is an exciting prospect. As a step towards capturing the microscopic architecture of grey matter in clinically feasible settings, this work uses a biophysical model that is designed to disentangle the diffusion signatures of spherical and cylindrical structures in the presence of orientation heterogeneity, and takes advantage of B-tensor encoding measurements, which provide additional sensitivity compared to standard single diffusion encoding sequences. For the fast and robust estimation of microstructural parameters, we leverage recent advances in machine learning and replace conventional fitting techniques with an artificial neural network that fits complex biophysical models within seconds. Our results demonstrate apparent markers of spherical and cylindrical geometries in healthy human subjects, and in particular an increased volume fraction of spherical compartments in grey matter compared to white matter. We evaluate the extent to which spherical and cylindrical geometries may be interpreted as correlates of neural soma and neural projections, respectively, and quantify parameter estimation errors in the presence of various departures from the modelling assumptions. While further work is necessary to translate the ideas presented in this work to the clinic, we suggest that biomarkers focussing on quasi-spherical cellular geometries may be valuable for the enhanced assessment of neurodevelopmental disorders and neurodegenerative diseases.

Modeling Fibrillogenesis of Collagen-Mimetic Molecules.

One of the most robust examples of self-assembly in living organisms is the formation of collagen architectures. Collagen type I molecules are a crucial component of the extracellular matrix, where they self-assemble into fibrils of well-defined axial striped patterns. This striped fibrillar pattern is preserved across the animal kingdom and is important for the determination of cell phenotype, cell adhesion, and tissue regulation and signaling. The understanding of the physical processes that determine such a robust morphology of self-assembled collagen fibrils is currently almost completely missing. Here, we develop a minimal coarse-grained computational model to identify the physical principles of the assembly of collagen-mimetic molecules. We find that screened electrostatic interactions can drive the formation of collagen-like filaments of well-defined striped morphologies. The fibril axial pattern is determined solely by the distribution of charges on the molecule and is robust to the changes in protein concentration, monomer rigidity, and environmental conditions. We show that the striped fibrillar pattern cannot be easily predicted from the interactions between two monomers but is an emergent result of multibody interactions. Our results can help address collagen remodeling in diseases and aging and guide the design of collagen scaffolds for biotechnological applications.

Microscopic susceptibility anisotropy imaging.

PURPOSE: The gradient-echo MR signal in brain white matter depends on the orientation of the fibers with respect to the external magnetic field. To map microstructure-specific magnetic susceptibility in orientationally heterogeneous material, it is thus imperative to regress out unwanted orientation effects. METHODS: This work introduces a novel framework, referred to as microscopic susceptibility anisotropy imaging, that disentangles the 2 principal effects conflated in gradient-echo measurements, (a) the susceptibility properties of tissue microenvironments, especially the myelin microstructure, and (b) the axon orientation distribution relative to the magnetic field. Specifically, we utilize information about the orientational tissue structure inferred from diffusion MRI data to factor out the B0 -direction dependence of the frequency difference signal. RESULTS: A human pilot study at 3 T demonstrates proxy maps of microscopic susceptibility anisotropy unconfounded by fiber crossings and orientation dispersion as well as magnetic field direction. The developed technique requires only a dual-echo gradient-echo scan acquired at 1 or 2 head orientations with respect to the magnetic field and a 2-shell diffusion protocol achievable on standard scanners within practical scan times. CONCLUSIONS: The quantitative recovery of microscopic susceptibility features in the presence of orientational heterogeneity potentially improves the assessment of microstructural tissue integrity.

Predictors of persistent disease activity and long quiescence in systemic lupus erythematosus: results from the Hopkins Lupus Cohort.

OBJECTIVES: The aim of this study is to identify prognostic factors of persistent disease activity and long quiescence in systemic lupus erythematosus (SLE). METHODS: Patients enrolled in the Hopkins Lupus Cohort from 1987 to 2012, who attended at least three visits per year during 3 consecutive years following baseline and had available information on disease activity were included. Patterns of SLE disease activity over the 3-year period were defined as: persistent long quiescent (pLQ), persistent relapsing-remitting (pRR), persistent chronic active (pCA) and mixed based on Modified SLE Disease Activity Index (M-SLEDAI). Possible predictors of pCA (vs pLQ, pRR and mixed) and pLQ (vs pCA, pRR and mixed) were identified by univariate and multivariate logistic regression analyses. RESULTS: 916 patients were included. In the multivariate analysis, use of hydroxychloroquine (OR: 0.45, 95% CI 0.22 to 0.92, p=0.03), African American ethnicity (OR: 2.36, 95% CI 1.15 to 4.85, p=0.02) and baseline SLEDAI (OR: 1.10, 95% CI 1.03 to 1.17, p=0.005) remained significant predictors of pCA. Higher education (>12 years; OR. 2.07, 95% CI 1.07 to 4.03, p=0.03) and lower baseline SLEDAI (OR: 0.67, 95% CI 0.56 to 0.82, p<0.001) were significant predictors of pLQ, while African American (OR: 0.38, 95% CI 0.17 to 0.83, p=0.02) and female patients (OR: 0.26, 95% CI 0.12 to 0.57, p<0.001) were less likely to achieve pLQ. CONCLUSION: African American ethnicity and high disease activity at baseline predict chronic activity in SLE, regardless of treatment, years of education and income. Higher education, low disease activity at baseline and male sex predict long quiescence. The use of hydroxychloroquine is independently associated with a lower risk of chronically active disease.

Disease activity patterns over time in patients with SLE: analysis of the Hopkins Lupus Cohort.

OBJECTIVE: To describe SLE disease activity patterns in the Hopkins Lupus Cohort. METHODS: Disease activity was studied in 1886 patients followed-up for 1-28 years. Disease activity patterns were defined using (1) Physician Global Assessment (PGA) and (2) modified SLE Disease Activity Index (M-SLEDAI) as follows: long quiescent (LQ), M-SLEDAI=0/PGA=0 at all visits; relapsing-remitting (RR), periods of activity (M-SLEDAI>0/PGA>0) interspersed with inactivity (M-SLEDAI=0/PGA=0); chronic active (CA), M-SLEDAI>0/PGA>0 at all visits. The pattern of first 3 consecutive follow-up years was determined in 916 patients as: persistent LQ (pLQ), persistent RR (pRR) and persistent CA (pCA), LQ, RR and CA pattern in each of the 3 years, respectively; mixed, at least two different pattern types were identified. RESULTS: The RR pattern accounted for the greatest proportion of follow-up time both by M-SLEDAI and PGA, representing 53.8% and 49.9% of total patient-years, respectively. The second most frequent pattern was LQ based on M-SLEDAI (30.7%) and CA based on PGA (40.4%). For the first 3-year intervals, the mixed pattern type was the most common (56.6%). The pRR was the second most frequent (M-SLEDAI 33.3%, PGA 26.5%), while pLQ (M-SLEDAI 6.4%, PGA 0.7%) and pCA were less frequent (M-SLEDAI 3.7%, PGA 16.3%). CONCLUSIONS: The RR pattern was the most prevalent pattern. LQ was achieved in a subset of patients, using the M-SLEDAI. However, the PGA captured mild activity missed on the M-SLEDAI in these patients. Over a 3-year perspective, less than half of patients maintained their original pattern.

A framework for remission in SLE: consensus findings from a large international task force on definitions of remission in SLE (DORIS).

OBJECTIVES: Treat-to-target recommendations have identified 'remission' as a target in systemic lupus erythematosus (SLE), but recognise that there is no universally accepted definition for this. Therefore, we initiated a process to achieve consensus on potential definitions for remission in SLE. METHODS: An international task force of 60 specialists and patient representatives participated in preparatory exercises, a face-to-face meeting and follow-up electronic voting. The level for agreement was set at 90%. RESULTS: The task force agreed on eight key statements regarding remission in SLE and three principles to guide the further development of remission definitions:1. Definitions of remission will be worded as follows: remission in SLE is a durable state characterised by …………………. (reference to symptoms, signs, routine labs).2. For defining remission, a validated index must be used, for example, clinical systemic lupus erythematosus disease activity index (SLEDAI)=0, British Isles lupus assessment group (BILAG) 2004 D/E only, clinical European consensus lupus outcome measure (ECLAM)=0; with routine laboratory assessments included, and supplemented with physician's global assessment.3. Distinction is made between remission off and on therapy: remission off therapy requires the patient to be on no other treatment for SLE than maintenance antimalarials; and remission on therapy allows patients to be on stable maintenance antimalarials, low-dose corticosteroids (prednisone ≤5 mg/day), maintenance immunosuppressives and/or maintenance biologics.The task force also agreed that the most appropriate outcomes (dependent variables) for testing the prognostic value (construct validity) of potential remission definitions are: death, damage, flares and measures of health-related quality of life. CONCLUSIONS: The work of this international task force provides a framework for testing different definitions of remission against long-term outcomes.

Induction maintenance with tumour necrosis factor-inhibitor combination therapy with discontinuation versus methotrexate monotherapy in early rheumatoid arthritis: a systematic review and meta-analysis of efficacy in randomised controlled trials.

OBJECTIVE: To determine whether an induction-maintenance strategy of combined therapy (methotrexate (MTX)+tumour necrosis factor (TNF) inhibitor (TNFi)) followed by withdrawal of TNFi could yield better long-term results than a strategy with MTX monotherapy, since it is unclear if the benefits from an induction phase with combined therapy are sustained if TNFi is withdrawn. METHODS: We performed a meta-analysis of trials using the initial combination of MTX+TNFi in conventional synthetic disease-modifying antirheumatic drug-naïve patients with early rheumatoid arthritis (RA). A systematic literature search was performed for induction-maintenance randomised controlled trials (RCTs) where initial combination therapy was compared with MTX monotherapy in patients with clinically active early RA. Our primary outcome was the proportion of patients who achieved low disease activity (LDA; Disease Activity Score (DAS)28<3.2) and/or remission (DAS28<2.6) at 12-76 weeks of follow-up. A random-effects model was used to pool the risk ratio (RR) for LDA and remission and heterogeneity was explored by subgroup analyses. RESULTS: We identified 6 published RCTs, 4 of them where MTX+adalimumab was given as initial therapy and where adalimumab was withdrawn in a subset of patients after LDA/remission had been achieved. 2 additional trials used MTX+infliximab as combination therapy. The pooled RRs for achieving LDA and clinical remission at follow-up after withdrawal of TNFi were 1.41 (95% CI 1.05 to 1.89) and 1.34 (95% CI 0.95 to 1.89), respectively. There was significant heterogeneity between trials due to different treatment strategies, which was a limitation to this study. CONCLUSIONS: Initial therapy with MTX+TNFi is associated with a higher chance of retaining LDA and/or remission even after discontinuation of TNFi.

Detection of clinically manifest and silent synovitis in the hands and wrists by fluorescence optical imaging.

OBJECTIVES: The correct identification of synovitis is critical for achieving optimal therapy results. Fluorescence optical imaging (FOI) is a novel modality based on the use of an intravenous fluorophore, which enables fluorescent imaging of the hands and wrists with increased focal optical signal intensities in areas of high perfusion and/or capillary leakage. The study objective was to determine the diagnostic utility of FOI in detecting apparent and clinically non-apparent active synovitis. METHODS: Bilateral hand and wrist joints (n=872) of 26 patients with inflammatory arthritis assessed by standard clinical examination, musculoskeletal ultrasound (MSUS) and FOI were studied. Synovitis was defined as tender and swollen joints on clinical examination, presence of synovial thickening and intra-articular Doppler signals on MSUS, and abnormal focal optical signal intensities on FOI, respectively. Subclinical synovitis was defined as being clinically non-apparent, but positively inflamed on MSUS. RESULTS: Depending on the standard used to define inflammation, FOI ranged from 73-83% sensitive and 83-95% specific for detecting manifest synovitis. For detecting clinically silent synovitis, the sensitivity, specificity and positive and negative predictive values of FOI were 80%, 96%, 77% and 97%, respectively. CONCLUSIONS: The high degree of agreement between MSUS and FOI suggest its use in clinical practice, especially when MSUS is not available, in order to identify synovitis earlier and with greater confidence. FOI may be particularly useful in identifying patients with clinically non-apparent joint inflammation of the hands and/or wrists.

Diagnostic utility of musculoskeletal ultrasound in patients with suspected arthritis--a probabilistic approach.

INTRODUCTION: This study aimed to assess the utility of musculoskeletal ultrasound (MSUS) in patients with joint symptoms using a probabilistic approach. METHODS: One hundred and three patients without prior rheumatologic diagnosis and referred to our clinic for evaluation of inflammatory arthritis were included. Patients were assessed clinically including joint examination, laboratory testing including acute-phase reactants, rheumatoid factor (RF) and anti citrulinated protein antibody (ACPA), and radiographs of hands and feet if clinically indicated. A diagnostic assessment was then performed by the responsible rheumatologist where the probability of a) any inflammatory arthritis and b) rheumatoid arthritis was given on a 5-point scale ranging from 0 to 20% up to 80 to 100% probability. Subsequently, an ultrasound examination of the wrist, metacarpophalangeal (MCP), proximal interphalangeal (PIP) joints 2 to 5 in both hands, metatarsophalangeal (MTP) joints 2 to 5 in both feet and any symptomatic joints was performed and the results presented to the same rheumatologist. The latter then assessed the diagnostic probabilities again, using the same scale. RESULTS: The rheumatologists' certainty for presence/absence of inflammatory arthritis and rheumatoid arthritis was increased significantly following ultrasound performance. The proportion of patient for whom diagnostic certainty for inflammatory arthritis was maximal was 33.0% before and 71.8% after musculoskeletal ultrasound (P <0.001). With regard to a diagnosis of RA, the proportions were 31.1% pre-test and 61.2% post-test (P <0.001). MSUS findings agreed with the final diagnosis in 95% of patients. CONCLUSION: Musculoskeletal ultrasound, when added to routine rheumatologic investigation, greatly increases the diagnostic certainty in patients referred for the evaluation of inflammatory arthritis. The changes from pre-test to post-test probability quantify the diagnostic utility of musculoskeletal ultrasound in probabilistic terms.