Philipp Sewerin

Glycosaminoglycan chemical exchange saturation transfer of lumbar intervertebral discs in patients with spondyloarthritis

To assess glycosaminoglycan (GAG) content of lumbar intervertebral discs (IVD) in patients with spondyloarthritis (SpA) using glycosaminoglycan chemical exchange saturation transfer (gagCEST).

Dynamic contrast-enhanced magnetic resonance imaging of metacarpophalangeal joints reflects histological signs of synovitis in rheumatoid arthritis

IntroductionSynovial inflammation and joint destruction in rheumatoid arthritis (RA) may progress despite clinical remission. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is increasingly used to detect synovial inflammation in RA. Although small joints such as metacarpophalangeal (MCP) joints are mainly affected by RA, MRI findings have never been directly compared to histological synovitis in MCP synovial tissue. The objective of the current study was therefore to analyse if DCE-MRI relates to histological signs of synovitis small RA joints.MethodsIn 9 RA patients, DCE-MRI (3 Tesla, dynamic 2D T1 weighted turbo-flash sequence) of the hand was performed prior to arthroscopically-guided synovial biopsies from the second MCP of the imaged hand. Maximum enhancement (ME), rate of early enhancement, and maximum rate of enhancement were assessed in the MCP. Synovial biopsies were stained for determination of sublining CD68 and the Synovitis Score. Correlations between MRI and histological data were calculated according to Spearman.ResultsME of the MCP significantly correlated to sublining CD68 staining (r = 0.750, P = 0.02), the Synovitis Score (r = 0.743, P = 0.02), and the subscores for lining layer hypertrophy (r = 0.789, P = 0.01) and cellular density (r = 0.842; P = 0.004).ConclusionsPerfusion imaging of synovial tissue in RA finger joints employing DCE-MRI reflects histological synovial inflammation. According to our study, ME is the most closely associated parameter amongst the measures considered.

Utility of combined high-resolution bone SPECT and MRI for the identification of rheumatoid arthritis patients with high-risk for erosive progression

OBJECTIVES To evaluate the utility of sequentially acquired, post hoc fused, magnetic resonance imaging (MRI) and multi-pinhole single photon emission computed tomography (MPH-SPECT) with technetium-99m-labeled disphosphonates (Tc99m-DPD) for the identification of finger joints with later erosive progression in early rheumatoid arthritis (ERA) patients. METHODS Ten consecutive ERA patients prospectively underwent MPH-SPECT and MRI of metacarpophalangeal (MCP) joints prior to and after 6 months methotrexate therapy. Tc99m-DPD uptake was measured at proximal and distal MCP sites using regional analysis. The course of joint pathologies was scored according to the Rheumatoid Arthritis MRI Score (RAMRIS) criteria. RESULTS The frequency of increased Tc99m-DPD uptake, synovitis and bone marrow edemadecreased under MTX therapy; but the number of bone erosions increased. Joints with progressive and new erosions on follow-up had a higher baseline Tc99m-DPD uptake (2.64 ± 1.23 vs. 1.43 ± 0.91) (p=0.02). CONCLUSIONS Joints with erosive progression are characterized by an early increased Tc99m-DPD uptake, even in absence of MRI bone pathologies. Tc99m-DPD MPH-SPECT might thus be of additional value to morphological MRI for the identification of RA patients with a high risk for erosive progression.

Prospective MRI score to predict negative EULAR response in patients with rheumatoid arthritis (RA) before therapy-escalation to a biological therapy

Dear Editor We read with great interest the article by Baker et al 1 who showed that early MRI measures independently predict erosive progression on X-ray and MRI after 1 and 2 years in therapy-naive patients with rheumatoid arthritis (RA) from the randomised-controlled GO-BEFORE trial. Due to these findings, we re-evaluated MRI data from the German REMISSION-PLUS Cohort2 ,3 at our centre to verify if a MRI score may predict negative response in patients with RA before therapy-escalation …

[Case-based interactive PACS learning: introduction of a new concept for radiological education of students].

PURPOSE Medical curricula are currently being reformed in order to establish superordinated learning objectives, including, e.g., diagnostic, therapeutic and preventive competences. This requires a shifting from traditional teaching methods towards interactive and case-based teaching concepts. Conceptions, initial experiences and student evaluations of a novel radiological course Co-operative Learning In Clinical Radiology (CLICR) are presented in this article. MATERIALS AND METHODS A novel radiological teaching course (CLICR course), which combines different innovative teaching elements, was established and integrated into the medical curriculum. Radiological case vignettes were created for three clinical teaching modules. By using a PC with PACS (Picture Archiving and Communication System) access, web-based databases and the CASUS platform, a problem-oriented, case-based and independent way of learning was supported as an adjunct to the well established radiological courses and lectures. Student evaluations of the novel CLICR course and the radiological block course were compared. RESULTS Student evaluations of the novel CLICR course were significantly better compared to the conventional radiological block course. Of the participating students 52% gave the highest rating for the novel CLICR course concerning the endpoint overall satisfaction as compared to 3% of students for the conventional block course. The innovative interactive concept of the course and the opportunity to use a web-based database were favorably accepted by the students. Of the students 95% rated the novel course concept as a substantial gain for the medical curriculum and 95% also commented that interactive working with the PACS and a web-based database (82%) promoted learning and understanding. CONCLUSION Interactive, case-based teaching concepts such as the presented CLICR course are considered by both students and teachers as useful extensions to the radiological course program. These concepts fit well into competence-oriented curricula.

Rheumatoid Arthritis Magnetic Resonance Imaging Score Predicts Therapy Response: Results of the German ArthroMark Cohort

Objective. Markers for treatment response in rheumatoid arthritis (RA) are lacking. The aim of the study was to assess the performance of the RA magnetic resonance imaging (MRI) scoring system (RAMRIS) in combination with serum biomarkers to predict response to methotrexate (MTX) treatment in therapy-naive patients with early RA by using high-field MRI. Methods. Twenty-eight patients with RA were prospectively assessed with baseline 3-T MRI of the clinical dominant hand, 3 and 6 months after MTX. The patients met the 2010 American College of Rheumatology/European League Against Rheumatism (EULAR) criteria [average age 56.8 yrs (range 39–74); positive for rheumatoid factor and/or anticyclic citrullinated peptide antibodies; disease duration < 6 mos (range 2–23 weeks)]. RAMRIS and serum biomarkers consisting of various experimental proteins including receptor activator of nuclear factor-κB ligand (RANKL) were obtained. Remission or treatment response was defined according to EULAR. To adjust for intrapersonal correlation, generalized linear mixed models were used. Results. Treatment response at 3 months was associated to low RAMRIS erosion subscores and low total RAMRIS scores (p = 0.019 and 0.03, respectively). Remission at 6 months was associated to low RANKL levels (p = 0.033). In multivariate analyses, response at 3 and 6 months was predicted more accurately with the inclusion of total RAMRIS score, RAMRIS synovitis subscore at the second metacarpophalangeal (MCP) joint, or a combination of the two (p value likelihood ratio test = 0.035, 0.035, and 0.041, respectively). Remission was more accurately predicted with inclusion of RANKL, with no significant predictive effect of MRI. Conclusion. Baseline total RAMRIS can predict EULAR response. RAMRIS synovitis subscore at the second MCP joint and RANKL are associated with response and remission, respectively.

Important but incomplete data analysis

We are grateful to the article about incidence and prevalence of psoriatic arthritis (PsA) in Denmark by Egeberg et al .1 The comprehensive health registers from Denmark and other Nordic countries have proven to yield many insights into the epidemiology of chronic diseases. The authors of the article provide very detailed information about the age-specific incidence of PsA, including its time trend. However, we have a question about reporting the overall age-specific incidence rate, combined for both sexes. Could the authors comment …

Fallbasiertes interaktives „PACS-learning“

PURPOSE Medical curricula are currently being reformed in order to establish superordinated learning objectives, including, e.g., diagnostic, therapeutic and preventive competences. This requires a shifting from traditional teaching methods towards interactive and case-based teaching concepts. Conceptions, initial experiences and student evaluations of a novel radiological course Co-operative Learning In Clinical Radiology (CLICR) are presented in this article. MATERIALS AND METHODS A novel radiological teaching course (CLICR course), which combines different innovative teaching elements, was established and integrated into the medical curriculum. Radiological case vignettes were created for three clinical teaching modules. By using a PC with PACS (Picture Archiving and Communication System) access, web-based databases and the CASUS platform, a problem-oriented, case-based and independent way of learning was supported as an adjunct to the well established radiological courses and lectures. Student evaluations of the novel CLICR course and the radiological block course were compared. RESULTS Student evaluations of the novel CLICR course were significantly better compared to the conventional radiological block course. Of the participating students 52% gave the highest rating for the novel CLICR course concerning the endpoint overall satisfaction as compared to 3% of students for the conventional block course. The innovative interactive concept of the course and the opportunity to use a web-based database were favorably accepted by the students. Of the students 95% rated the novel course concept as a substantial gain for the medical curriculum and 95% also commented that interactive working with the PACS and a web-based database (82%) promoted learning and understanding. CONCLUSION Interactive, case-based teaching concepts such as the presented CLICR course are considered by both students and teachers as useful extensions to the radiological course program. These concepts fit well into competence-oriented curricula.

Biomarker und Bildgebung zur Diagnose und Stratifizierung der rheumatoiden Arthritis und Spondylarthritis im BMBF-Verbund ArthroMark

ZusammenfassungRheumatische Erkrankungen gehören zu den häufigsten chronisch entzündlichen Krankheiten. Neben ausgeprägter Schmerzhaftigkeit und progredienter Gelenkzerstörung reduzieren die rheumatoide Arthritis (RA), die Spondyloarthritiden (SpA) und die Psoriasisarthritis (PsA) die Arbeitsfähigkeit, die Lebensqualität und bei unzureichender Behandlung auch die Lebenserwartung. Seit der Einführung der Biologika zur Therapie dieser Erkrankungen hat die Suche nach geeigneten Biomarkern zur Frühdiagnostik und Vorhersage des Therapieerfolgs zunehmend an Bedeutung gewonnen. Das Hauptziel des Verbundes ArthroMark ist, neue Biomarker zu identifizieren und moderne Bildgebungsverfahren einzusetzen mit dem Ziel, die Diagnose, die Verlaufskontrolle und die Stratifizierung von Patienten mit RA, SpA und PsA zu verbessern. Mit der Entwicklung geeigneter Biomarker für diese Erkrankungen trägt dieses Vorhaben zur Gesundheitsforschung im Bereich chronischer Erkrankungen des Bewegungsapparates bei. Durch die Zusammenarbeit verschiedener nationaler Zentren sollen standortspezifische Ressourcen wie Probenbanken und klinische Studien gemeinsam nutzbar gemacht werden und individuelle Schwerpunkte in der Biomarkeranalyse mit einem entsprechenden Mehrwert vernetzt werden. Gemeinsames Datenmanagement und Vereinheitlichung der Datenerhebung sowie bestmögliche Charakterisierung der Patienten durch neue Bildgebungsmethoden sollen die Qualität der Markerprüfung optimieren.AbstractRheumatic diseases are among the most common chronic inflammatory disorders. Besides severe pain and progressive destruction of the joints, rheumatoid arthritis (RA), spondyloarthritides (SpA) and psoriatic arthritis (PsA) impair working ability, reduce quality of life and if treated insufficiently may enhance mortality. With the introduction of biologics to treat these diseases, the demand for biomarkers of early diagnosis and therapeutic stratification has been growing continuously. The main goal of the consortium ArthroMark is to identify new biomarkers and to apply modern imaging technologies for diagnosis, follow-up assessment and stratification of patients with RA, SpA and PsA. With the development of new biomarkers for these diseases, the ArthroMark project contributes to research in chronic diseases of the musculoskeletal system. The cooperation between different national centers will utilize site-specific resources, such as biobanks and clinical studies for sharing and gainful networking of individual core areas in biomarker analysis. Joint data management and harmonization of data assessment as well as best practice characterization of patients with new imaging technologies will optimize quality of marker validation.

Big Data in der Bildgebung

ZusammenfassungDie großen wissenschaftlichen Fortschritte in der Medizin wurden bis heute hauptsächlich durch hypothesengetriebene Forschungsansätze im Rahmen von kontrollierten klinischen Studien erreicht. Hierbei können allerdings aufgrund der zahlreichen Variablen nur einzelne Fragestellungen untersucht werden, sodass diese nach wie vor sehr zeit- und kostenintensiv sind. Big Data bietet durch einen neuen datenbasierten Ansatz die Möglichkeit, mit sehr großen Datenmengen alle vorhandenen Variablen zu untersuchen, und öffnet somit neue Horizonte. Die Bildgebung scheint für solche Ansätze durch die weitestgehend flächendeckende Digitalisierung der Daten und der immer besseren Hard- und Softwarelösungen prädestiniert zu sein. Einige kleine Studien wiesen bereits nach, dass automatisierte Auswertungsalgorithmen und künstliche Intelligenz Pathologien mit höchster Präzision erkennen können. Auch in der rheumatologischen Bildgebung erscheinen solche automatisierten Systeme sinnvoll, da seit Langem nach personalisierter Risikostratifizierung für die Patienten gesucht wird. Bei all den vielversprechenden Möglichkeiten muss allerdings heute noch festgestellt werden, dass die Heterogenität der Daten und die sehr komplexen Datenschutzauflagen in Deutschland eine Big-Data-Lösung in der Bildgebung noch erschweren. Die enormen Chancen in der klinischen Versorgung und der Wissenschaft sind es aber wert, diese Herausforderungen anzunehmen.AbstractUntil now, most major medical advancements have been achieved through hypothesis-driven research within the scope of clinical trials. However, due to a multitude of variables, only a certain number of research questions could be addressed during a single study, thus rendering these studies expensive and time consuming. Big data acquisition enables a new data-based approach in which large volumes of data can be used to investigate all variables, thus opening new horizons. Due to universal digitalization of the data as well as ever-improving hard- and software solutions, imaging would appear to be predestined for such analyses. Several small studies have already demonstrated that automated analysis algorithms and artificial intelligence can identify pathologies with high precision. Such automated systems would also seem well suited for rheumatology imaging, since a method for individualized risk stratification has long been sought for these patients. However, despite all the promising options, the heterogeneity of the data and highly complex regulations covering data protection in Germany would still render a big data solution for imaging difficult today. Overcoming these boundaries is challenging, but the enormous potential advances in clinical management and science render pursuit of this goal worthwhile.Until now, most major medical advancements have been achieved through hypothesis-driven research within the scope of clinical trials. However, due to a multitude of variables, only a certain number of research questions could be addressed during a single study, thus rendering these studies expensive and time consuming. Big data acquisition enables a new data-based approach in which large volumes of data can be used to investigate all variables, thus opening new horizons. Due to universal digitalization of the data as well as ever-improving hard- and software solutions, imaging would appear to be predestined for such analyses. Several small studies have already demonstrated that automated analysis algorithms and artificial intelligence can identify pathologies with high precision. Such automated systems would also seem well suited for rheumatology imaging, since a method for individualized risk stratification has long been sought for these patients. However, despite all the promising options, the heterogeneity of the data and highly complex regulations covering data protection in Germany would still render a big data solution for imaging difficult today. Overcoming these boundaries is challenging, but the enormous potential advances in clinical management and science render pursuit of this goal worthwhile.