The incidental finding of soft tissue masses is a challenge for the radiologist. Benign and malignant lesions can be differentiated relying on patient history, symptoms and mostly with the help of imaging. Ultrasound (US), computed tomography (CT) and magnetic resonance imaging (MRI) become fundamental in order to distinguish these lesions but the radiologist needs to know the main characteristics of benign soft tissue masses and sarcomas. Herein, we present a pictorial review of lesions mimicking soft tissue sarcomas features.

The onset and progression of immune-mediated inflammatory arthritis, such as rheumatoid arthritis and spondyloarthritis, are linked to the IL23-IL17 immune axis, so that many therapeutic strategies aim at modulating this pathway. However, there is so far no possibility of an in vivo direct monitoring, without a biopsy, of the specific T cells involved in this modulation. Synovial perfusion, and thus synovial angiogenesis, has been recognized as a sensitive and early marker of inflammation that can be evaluated via quantitative analysis of contrast-enhanced ultrasound imaging data.

Contrast Enhanced Ultrasound (CEUS) is a sensitive imaging technique to assess tissue vascularity, that can be useful in the quantification of different perfusion patterns. This can particularly important in the early detection and differentiation of different types of arthritis. A Gamma-variate can accurately quantify synovial perfusion and it is flexible enough to describe many heterogeneous patterns. However, in some cases the heterogeneity of the kinetics can be such that even the Gamma model does not properly describe the curve, especially in presence of recirculation or of an additional slowflow component. In this work we apply to CEUS data both the Gamma-variate and the single compartment recirculation model (SCR) which takes explicitly into account an additional component of slow flow. The models are solved within a Bayesian framework. We also employed the perfusion estimates obtained with SCR to train a support vector machine classifier to distinguish different types of arthritis. When dividing the patients into two groups (rheumatoid arthritis and polyarticular RA-like psoriatic arthritis vs. other arthritis types), the slow component amplitude was significantly different across groups: mean values of a1 and its variability were statistically higher in RA and RA-like patients (131% increase in mean, p = 0.035 and 73% increase in standard deviation, p = 0.049 respectively). The SVM classifier achieved a balanced accuracy of 89%, with a sensitivity of 100% and a specificity of 78%.

Contrast Enhanced Ultrasound (CEUS) is a sensitive imaging technique to assess tissue vascularity, that can be useful in the quantification of different perfusion patterns. This can be particularly important in the early detection and staging of arthritis. In a recent study we have shown that a Gamma-variate can accurately quantify synovial perfusion and it is flexible enough to describe many heterogeneous patterns. Moreover, we have shown that through a pixel-by-pixel analysis the quantitative information gathered characterizes more effectively the perfusion. However, the SNR ratio of the data and the nonlinearity of the model makes the parameter estimation difficult. Using classical non-linear-leastsquares (NLLS) approach the number of unreliable estimates (those with an asymptotic coefficient of variation greater than a user-defined threshold) is significant, thus affecting the overall description of the perfusion kinetics and of its heterogeneity. In this work we propose to solve the parameter estimation at the pixel level within a Bayesian framework using Variational Bayes (VB), and an automatic and data-driven prior initialization. When evaluating the pixels for which both VB and NLLS provided reliable estimates, we demonstrated that the parameter values provided by the two methods are well correlated (Pearson’s correlation between 0.85 and 0.99). Moreover, the mean number of unreliable pixels drastically reduces from 54% (NLLS) to 26% (VB), without increasing the computational time (0.05 s/pixel for NLLS and 0.07 s/pixel for VB). When considering the efficiency of the algorithms as computational time per reliable estimate, VB outperforms NLLS (0.11 versus 0.25 seconds per reliable estimate respectively).

AIM:To establish the accuracy of magnetic resonance imaging (MRI) in distinguishing between benign and malignant lipomatous tumors; to evaluate the reproducibility of the MRI interpretation assessing the agreement between judgments of two radiologists with the same experience in soft-tissue sarcomas; to identify an association among MRI findings (size, depth, septa, nodules, signal homogeneity) and nature of the lesion.MATERIALS AND METHODS:A total of 54 patients (28 men and 26 women), with a mean age of 56 (range=27-84) were included years. All subjects followed-up by the Multidisciplinary Sarcoma Group. The following MRI findings were judged in a blind study by two radiologists: size, localization, septa, nodules and signal homogeneity. A diagnostic indication was then given from among lipoma, atypical lipomatous tumour (ALT) and liposarcoma. Accuracy in distinguishing between benign and malignant lesions, and between lipoma and ALT (Fisher's exact test), inter-operator agreement (Cohen's kappa), association of MRI findings and malignancy of the lesion (Fisher's exact test and odds ratio) were evaluated.RESULTS:The inter-operator agreement was complete (100%). The agreement between diagnostic hypothesis and histological diagnosis was statistically significant (p<0.05). Among the radiological findings taken into account, only septa and signal homogeneity were significantly associated with the malignancy of the lesion (p<0.05).CONCLUSION:MRI could be helpful in distinguishing lipomatous tumors, allowing biopsy to be avoided in some cases (negative predictive value=100%).

To develop quantitative imaging biomarkers of synovial tissue perfusion by pixel-based contrast-enhanced ultrasound (CEUS), we studied the relationship between CEUS synovial vascular perfusion and the frequencies of pathogenic T helper (Th)-17 cells in psoriatic arthritis (PsA) joints. Eight consecutive patients with PsA were enrolled in this study. Gray scale CEUS evaluation was performed on the same joint immediately after joint aspiration, by automatic assessment perfusion data, using a new quantification approach of pixel-based analysis and the gamma-variate model. The set of perfusional parameters considered by the time intensity curve includes the maximum value (peak) of the signal intensity curve, the blood volume index or area under the curve, (BVI, AUC) and the contrast mean transit time (MTT). The direct ex vivo analysis of the frequencies of SF IL17A-F(+)CD161(+)IL23(+) CD4(+) T cells subsets were quantified by fluorescence-activated cell sorter (FACS). In cross-sectional analyses, when tested for multiple comparison setting, a false discovery rate at 10%, a common pattern of correlations between CEUS Peak, AUC (BVI) and MTT parameters with the IL17A-F(+)IL23(+) - IL17A-F(+)CD161(+) - and IL17A-F(+)CD161(+)IL23(+) CD4(+) T cells subsets, as well as lack of correlation between both peak and AUC values and both CD4(+)T and CD4(+)IL23(+) T cells, was observed. The pixel-based CEUS assessment is a truly measure synovial inflammation, as a useful tool to develop quantitative imaging biomarker for monitoring target therapeutics in PsA.

Contrast Enhanced Ultrasound (CEUS) is a sensitive imaging technique to assess tissue vascularity and it can be particularly useful in early detection and grading of arthritis. In a recent study we have shown that a Gamma-variate can accurately quantify synovial perfusion and it is flexible enough to describe many heterogeneous patterns. However, in some cases the heterogeneity of the kinetics can be such that even the Gamma model does not properly describe the curve, with a high number of outliers. In this work we apply to CEUS data the single compartment recirculation model (SCR) which takes explicitly into account the trapping of the microbubbles contrast agent by adding to the single Gamma-variate model its integral. The SCR model, originally proposed for dynamic-susceptibility magnetic resonance imaging, is solved here at pixel level within a Bayesian framework using Variational Bayes (VB). We also include the automatic relevant determination (ARD) algorithm to automatically infer the model complexity (SCR vs. Gamma model) from the data. We demonstrate that the inclusion of trapping best describes the CEUS patterns in 50% of the pixels, with the other 50% best fitted by a single Gamma. Such results highlight the necessity of the use ARD, to automatically exclude the irreversible component where not supported by the data. VB with ARD returns precise estimates in the majority of the kinetics (88% of total percentage of pixels) in a limited computational time (on average, 3.6 min per subject). Moreover, the impact of the additional trapping component has been evaluated for the differentiation of rheumatoid and non-rheumatoid patients, by means of a support vector machine classifier with backward feature selection. The results show that the trapping parameter is always present in the selected feature set, and improves the classification.

The purpose of the study was to assess the relationship of the continuous mode contrast-enhanced harmonic ultrasound (CEUS) imaging with the histopathological and immunohistochemical (IHC) quantitative estimation of microvascular proliferation on synovial samples of patients affected by sustained psoriatic arthritis (PsA). A dedicated linear transducer was used in conjunction with a specific continuous mode contrast enhanced harmonic imaging technology with a second-generation sulfur hexafluoride-filled microbubbles C-agent. The examination was carried out within 1 week before arthroscopic biopsies in 32 active joints. Perfusional parameters were analyzed including regional blood flow (RBF); peak (PEAK) of the C-signal intensity, proportional to the regional blood volume (RBV); beta (β) perfusion frequency; slope (S), representing the inclination of the tangent in the origin; and the refilling time (RT), the reverse of beta. Arthroscopic synovial biopsies were targeted in the hypervascularity areas, as in the same knee recesses assessed by CEUS; the synovial cell infiltrate and vascularity (vessel density) was evaluated by IHC staining of CD45 (mononuclear cell) and CD31, CD105 (endothelial cell) markers, measured by computer-assisted morphometric analysis. In the CEUS area examined, the corresponding time-intensity curves demonstrated a slow rise time. Synovial histology showed slight increased layer lining thickness, perivascular lymphomonocyte cell infiltration, and microvascular remodeling, with marked vessel wall thickening with reduction of the vascular lumen. A significant correlation was found between RT and CD31+ as PEAK and CD105+ vessel density; RT was inversely correlated to RBF, PEAK, S, and β. The study demonstrated the association of the CEUS perfusion kinetics with the histopathological quantitative and morphologic estimation of synovial microvascular proliferation, suggesting that a CEUS imaging represents a reliable tool for the estimate of the synovial hypervascularity in PsA.

Purpose The purpose of this study was to evaluate the usefulness of contrast-enhanced ultrasonography (CEUS) in the bioptic sampling of soft tissue tumors (STT) compared with unenhanced ultrasonography alone.Methods This is a prospective longitudinal study of 40 patients subjected to ultrasonography (US)-guided core needle biopsy (CNB) to characterize a suspected STT. Three series of bioptic samplings were carried out on each patient, respectively using unenhanced US alone and CEUS in both the areas of the tumor enhanced or not by the contrast medium. All bioptic samples underwent a histological evaluation and the results were analyzed by comparing the histology of the biopsy with the definitive diagnosis in 15 surgically excised samples.Results 27 (67.5 %) of the 40 patients completed the entire study procedure; in 19 cases (70.3 %) the three bioptic samplings gave unanimous results, also when compared to the surgical specimen; in seven cases (25.9 %) use of CEUS allowed to obtain additional or more accurate information about the mass in question, compared to simple US guidance without contrast; in one patient (3.7 %) sampling obtained using unenhanced ultrasonography guidance and in the areas enhanced by the contrast agent had precisely the same results of the surgical specimen.Conclusions CEUS, due to its ability to evaluate microvascular areas, has proven to be a promising method in guiding bioptic sampling of soft tissue tumor, directing the needle to the most significant areas of the tumor. Given the small number of patients evaluated in our study, to achieve statistically significant results, it would be appropriate to obtain a larger sample size, since the very first results seem to be encouraging and to justify the increase of the population.

Inflammatory rheumatic diseases are the leading causes of disability and constitute a frequent medical disorder, leading to inability to work, high comorbidity, and increased mortality. The standard for diagnosing and differentiating arthritis is based on clinical examination, laboratory exams, and imaging findings, such as synovitis, bone edema, or joint erosions. Contrast-enhanced ultrasound (CEUS) examination of the small joints is emerging as a sensitive tool for assessing vascularization and disease activity. Quantitative assessment is mostly performed at the region of interest level, where the mean intensity curve is fitted with an exponential function. We showed that using a more physiologically motivated perfusion curve, and by estimating the kinetic parameters separately pixel by pixel, the quantitative information gathered is able to more effectively characterize the different perfusion patterns. In particular, we demonstrated that a random forest classifier based on pixelwise quantification of the kinetic contrast agent perfusion features can discriminate rheumatoid arthritis from different arthritis forms (psoriatic arthritis, spondyloarthritis, and arthritis in connective tissue disease) with an average accuracy of 97%. On the contrary, clinical evaluation (DAS28), semiquantitative CEUS assessment, serological markers, or region-based parameters do not allow such a high diagnostic accuracy.

Malgré l’efficacité des anti-TNF, la plupart des patients atteints d’un rhumatisme psoriasique (RP) maintiennent une activité résiduelle d’inflammation synoviale. Le but principal de cette étude était d’évaluer les effets du traitement par les bains de boue sur l’aspect clinique des patients atteints de RP recevant des anti-TNF. L’objectif secondaire était d’évaluer l’inflammation synoviale des mains en utilisant l’échographie de contraste. Les autres objectifs étaient de vérifier le risque de poussée d’arthrite et d’évaluer les effets du traitement par spa sur la fonction et la qualité de vie. Trente-six patients atteints de rhumatisme psoriasique, traités pendant au moins 6 mois par anti-TNF, étaient inclus. Après une randomisation 1:1, 18 patients (groupe A) avaient bénéficié d’un traitement par bains de boue (12 cataplasmes d’argile et 12 bains thermaux), tout en poursuivant leur traitement par anti-TNF et 18 patients (groupe B) avaient continué avec le traitement pharmacologique seul. La CRP, PASI, DAS28, nombre d’articulations douloureuses et gonflées, l’EVA douleur, le HAQ et le SF-36 étaient évalués à l’inclusion (T0) et après 45 jours (T1). L’inflammation synoviale détectée par échographie de contraste, analysée par logiciel informatique, a été évaluée. Une amélioration significative du PASI (p < 0,005), du DAS28 (p < 0,05), du nombre d’articulations gonflées et douloureuses (p < 0,001) et du HAQ (p < 0,001) entre T0 et T1 a été observée dans le groupe A. Aucun patient n’avait expérimenté de poussée de son arthrite. Les vidéos d’échographie avaient montré un retard d’apparition significatif (p < 0,05) et un washout plus rapide (p < 0,02) du produit de contraste dans le groupe A comparativement au groupe B. Ces données suggèrent une diminution de l’activité résiduelle d’inflammation synoviale et un bénéfice clinique du spa sur le rhumatisme psoriasique chez les patients traités par anti-TNF alpha.

Searchable abstracts of presentations at key conferences in endocrinology ISSN 1470-3947 (print) | ISSN 1479-6848 (online)

Great technologic and clinical progress have been made in the last two decades in identifying genetic defects of several neuromuscular diseases, as Spinal Muscular Atrophy, genetic muscular dystrophies and other genetic myopathies. The diagnosis is usually challenging, due to great variability in genetic abnormalities and clinical phenotypes and the poor specificity of complementary analyses, i.e., serum creatine kinase (CK) and electrophysiology. Muscle biopsy represents the gold standard for the diagnosis of genetic neuromuscular diseases, but clinical imaging of muscle tissue is an important diagnostic tool to identify and quantifyies muscle damage. Radiologic imaging is, indeed, increasingly used as a diagnostic tool to describe patterns and the extent of muscle involvement, thanks to modern techniques that enable to definethe definition of degrees of muscle atrophy and changes in connective tissue. They usually grade the severity of the disease process with greater accuracy than clinical scores. Clinical imaging is more than complementary to perform muscle biopsy, especially as ultrasound scans are often mandatory to identify the muscle to be biopsied. We will here detail and provide We will herein provide detailed examples of the radiologic methods that can be used in genetic and acquired neuromuscular disorders, stressing pros and cons.

Objectives: Despite the efficacy of TNF inhibitors, most patients with psoriatic arthritis maintain a residual synovial inflammation. The main aim of the study was to evaluate the effects of mud-bath therapy on clinical picture of PsA patients treated with TNF inhibitors. The secondary outcome was to assess synovial inflammation in hand joints detected by contrast-enhanced ultrasound. Other aims were to verify the risk of arthritis flare and to evaluate the effects of spa treatment on functional ability and on quality of life.Methods: Thirty-six patients with psoriatic arthritis, treated in the last 6 months with TNF inhibitors, were enrolled. After 1:1 randomisation, 18 patients (group A) underwent mud-bath therapy (12 mudpacks and 12 thermal baths), maintaining treatment with TNF inhibitors; 18 patients (group B) continued pharmacological therapy alone. CRP, PASI, DAS28, swollen and tender joint count, VAS pain, HAQ and SF-36 were evaluated at baseline (TO) and after 45 days (T1). Synovial inflammation detected by contrastenhanced ultrasound, analysed by a software system, was also assessed.Results: A significant improvement in PASI (P < 0.005), DAS28 (P < 0.05), swollen joint count and tender joint count (P < 0.001), and HAQ(P < 0.001) between TO and T1 was observed in group A. No patient underwent a flare-up of arthritis. Ultrasound videos demonstrated a significant appearance delay (P < 0.05) and faster washout (P < 0.02) of contrast dye in group A patients with respect to group B.Conclusions: These data suggest a decrease of residual synovial inflammation and a beneficial clinical effect of spa therapy in psoriatic arthritis patients treated with TNF inhibitors. (C) 2014 Societe francaise de rhumatologie. Published by Elsevier Masson SAS. All rights reserved.

Background Although both diseases are characterized by specific features the differentiation between rheumatoid arthritis (RA) and simil-rheumatoid psoriatic arthritis (srPsA) is extremely difficult except by hard-to-gain biopsy specimens (1). On contrast enhanced magnetic resonance imaging (CE-MRI) some extra-articular manifestations may direct diagnosis, but synovitis could not be discriminated between RA and srPsA in these studies (2-4). Contrast-enhanced ultrasound (CEUS) using “real” intravascular agents is believed to allow more accurate study of synovial vascularization. Objectives To determine the feasibility to discriminate between RA and srPsA using CEUS derived flow parameters by ad hoc developed software program for analysis of synovial vascularization. Methods 64 outclinic patients with polyarthritis of hands, 32 with RA and 32 with srPsA, were recruited. The most active joint was chosen for CEUS examination using a US device (Mylab70, Esaote) equipped with Contrast tuned Imaging (CnTI, Esaote), and as contrast agent sulfur hexafluoride microbubbles (SonoVue; Bracco International). Both the anatomical B-mode image and the CnTI cineloop video were digitally stored for subsequent software analysis. Image analysis was performed firstly applying a semi-automatic detection of synovial boundaries (5). Then, the contrast time-activity curve of all pixels belonging to the synovial and perisynovial region was analyzed fitting a gamma curve f(t) = A(t − t0)a $times$ e(t −t0)/b on the data. The statistics summarizing the distribution of the estimated kinetics parameters in the synovial and in the perisynovial tissue were computed and their difference between the two groups (RA and srPsA) analyzed, so to study the existence of different vascularization patterns. Finally, a supervised classifier (random forest) was trained to classify each patient through its CEUS-derived parameters, validating the classifier diagnostic power using a leave-one-out strategy. To further increase diagnostic power data about DAS28, CRP, ESR and autoantibodies were added. Results Vascularization pattern constituted of 40 flow parameters discriminated effectively RA from srPsA. Accuracy was 0.93 during training and 0.83 during test phase. Adding rheumatoid factor (RF) and anti-CCP increased diagnostic accuracy to 0.99 in training and 0.93 in test phase decreasing needed flow parameters to 28, whereas DAS28, CRP and ESR did not. Conclusions The Dynamic Automated Synovial Imaging (DASI) is actually the only imaging method that accurately discriminates RA from srPsA, especially in the presence of RF and anti-CCP data. References Kruithof E. Arthritis Res Ther 2005;7:569-80. Jevtic V. Handchir Mikrochir Plast Chir 2012;44:163-170. Cimmino MA. J Rheum 2012;39(89):43-8. Schoellnast H. AJR 2006;187:351-7. Veronese E. Med Eng Phys 2013; 35, 188–194. Disclosure of Interest None declared DOI 10.1136/annrheumdis-2014-eular.3779