F W Roemer1, D J Hunter2, M D Crema3, C K Kwoh4, E Ochoa-Albiztegui5, A Guermazi6. 1. Quantitative Imaging Center (QIC), Department of Radiology, Boston University School of Medicine, Boston, MA, USA; Department of Radiology, University of Erlangen-Nuremberg, Erlangen, Germany. Electronic address: froemer@bu.edu. 2. Institute of Bone and Joint Research, Kolling Institute, University of Sydney, Sydney, Australia; Rheumatology Department, Royal North Shore Hospital, Australia. 3. Quantitative Imaging Center (QIC), Department of Radiology, Boston University School of Medicine, Boston, MA, USA; Department of Radiology, Hospital do Coração (HCor), São Paulo-SP, Brazil; Teleimagem, São Paulo-SP, Brazil. 4. University of Arizona Arthritis Center & University of Arizona College of Medicine, Tucson, AZ, USA. 5. Department of Radiology and Molecular Medicine, The American British Cowdray Medical Center, I.A.P., Mexico City, Mexico. 6. Quantitative Imaging Center (QIC), Department of Radiology, Boston University School of Medicine, Boston, MA, USA.
Abstract
OBJECTIVE: To introduce the most popular magnetic resonance imaging (MRI) osteoarthritis (OA) semi-quantitative (SQ) scoring systems to a broader audience with a focus on the most commonly applied scores, i.e., the MOAKS and WORMS system and illustrate similarities and differences. DESIGN: While the main structure and methodology of each scoring system are publicly available, the core of this overview will be an illustrative imaging atlas section including image examples from multiple OA studies applying MRI in regard to different features assessed, show specific examples of different grades and point out pitfalls and specifics of SQ assessment including artifacts, blinding to time point of acquisition and within-grade evaluation. RESULTS: Similarities and differences between different scoring systems are presented. Technical considerations are followed by a brief description of the most commonly utilized SQ scoring systems including their responsiveness and reliability. The second part is comprised of the atlas section presenting illustrative image examples. CONCLUSIONS: Evidence suggests that SQ assessment of OA by expert MRI readers is valid, reliable and responsive, which helps investigators to understand the natural history of this complex disease and to evaluate potential new drugs in OA clinical trials. Researchers have to be aware of the differences and specifics of the different systems to be able to engage in imaging assessment and interpretation of imaging-based data. SQ scoring has enabled us to explain associations of structural tissue damage with clinical manifestations of the disease and with morphological alterations thought to represent disease progression.
OBJECTIVE: To introduce the most popular magnetic resonance imaging (MRI) osteoarthritis (OA) semi-quantitative (SQ) scoring systems to a broader audience with a focus on the most commonly applied scores, i.e., the MOAKS and WORMS system and illustrate similarities and differences. DESIGN: While the main structure and methodology of each scoring system are publicly available, the core of this overview will be an illustrative imaging atlas section including image examples from multiple OA studies applying MRI in regard to different features assessed, show specific examples of different grades and point out pitfalls and specifics of SQ assessment including artifacts, blinding to time point of acquisition and within-grade evaluation. RESULTS: Similarities and differences between different scoring systems are presented. Technical considerations are followed by a brief description of the most commonly utilized SQ scoring systems including their responsiveness and reliability. The second part is comprised of the atlas section presenting illustrative image examples. CONCLUSIONS: Evidence suggests that SQ assessment of OA by expert MRI readers is valid, reliable and responsive, which helps investigators to understand the natural history of this complex disease and to evaluate potential new drugs in OA clinical trials. Researchers have to be aware of the differences and specifics of the different systems to be able to engage in imaging assessment and interpretation of imaging-based data. SQ scoring has enabled us to explain associations of structural tissue damage with clinical manifestations of the disease and with morphological alterations thought to represent disease progression.
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