OBJECTIVE: Osteoarthritis (OA) is currently diagnosed using clinical and radiographic findings. In recent years magnetic resonance imaging (MRI) use in OA has increasingly been studied. This study was conducted to determine the diagnostic utility of MRI in OA through a meta-analysis of published studies. METHODS: A systematic literature search was undertaken to include studies that used MRI to evaluate or detect OA. MRI was compared to various reference standards: histology, arthroscopy, radiography, CT, clinical evaluation, and direct visual inspection. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and receiver operating characteristic (ROC) area under the curve (AUC) were calculated. Random-effects models were used to pool results. RESULTS: Of 20 relevant studies identified from the literature, 16 reported complete data and were included in the meta-analysis, with a total of 1220 patients (1071 with OA and 149 without). Overall sensitivity from pooling data of all the included studies was 61% [95% confidence interval (CI) 53-68], specificity was 82% (95% CI 77-87), PPV was 85% (95% CI 80-88), and NPV was 57% (95% CI 43-70). The ROC showed an AUC of 0.804. There was significant heterogeneity in the above parameters (I(2)>83%). With histology as the reference standard, sensitivity increased to 74% and specificity decreased to 76% compared with all reference standards combined. When arthroscopy was used as the reference standard, sensitivity increased to 69% and specificity to 93% compared with all reference standards combined. CONCLUSION: MRI can detect OA with an overall high specificity and moderate sensitivity when compared with various reference standards, thus lending more utility to ruling out OA than ruling it in. The sensitivity of MRI is below the current clinical diagnostic standards. At this time standard clinical algorithm for OA diagnosis, aided by radiographs appears to be the most effective method for diagnosing OA.
OBJECTIVE:Osteoarthritis (OA) is currently diagnosed using clinical and radiographic findings. In recent years magnetic resonance imaging (MRI) use in OA has increasingly been studied. This study was conducted to determine the diagnostic utility of MRI in OA through a meta-analysis of published studies. METHODS: A systematic literature search was undertaken to include studies that used MRI to evaluate or detect OA. MRI was compared to various reference standards: histology, arthroscopy, radiography, CT, clinical evaluation, and direct visual inspection. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and receiver operating characteristic (ROC) area under the curve (AUC) were calculated. Random-effects models were used to pool results. RESULTS: Of 20 relevant studies identified from the literature, 16 reported complete data and were included in the meta-analysis, with a total of 1220 patients (1071 with OA and 149 without). Overall sensitivity from pooling data of all the included studies was 61% [95% confidence interval (CI) 53-68], specificity was 82% (95% CI 77-87), PPV was 85% (95% CI 80-88), and NPV was 57% (95% CI 43-70). The ROC showed an AUC of 0.804. There was significant heterogeneity in the above parameters (I(2)>83%). With histology as the reference standard, sensitivity increased to 74% and specificity decreased to 76% compared with all reference standards combined. When arthroscopy was used as the reference standard, sensitivity increased to 69% and specificity to 93% compared with all reference standards combined. CONCLUSION: MRI can detect OA with an overall high specificity and moderate sensitivity when compared with various reference standards, thus lending more utility to ruling out OA than ruling it in. The sensitivity of MRI is below the current clinical diagnostic standards. At this time standard clinical algorithm for OA diagnosis, aided by radiographs appears to be the most effective method for diagnosing OA.
Authors: R Altman; E Asch; D Bloch; G Bole; D Borenstein; K Brandt; W Christy; T D Cooke; R Greenwald; M Hochberg Journal: Arthritis Rheum Date: 1986-08
Authors: M P Recht; J Kramer; S Marcelis; M N Pathria; D Trudell; P Haghighi; D J Sartoris; D Resnick Journal: Radiology Date: 1993-05 Impact factor: 11.105
Authors: Hiroshi Yoshioka; Kathryn Stevens; Brian A Hargreaves; Daniel Steines; Mark Genovese; Michael F Dillingham; Carl S Winalski; Philipp Lang Journal: J Magn Reson Imaging Date: 2004-11 Impact factor: 4.813
Authors: Nima Befrui; Jens Elsner; Achim Flesser; Jacqueline Huvanandana; Oussama Jarrousse; Tuan Nam Le; Marcus Müller; Walther H W Schulze; Stefan Taing; Simon Weidert Journal: Med Biol Eng Comput Date: 2018-02-01 Impact factor: 2.602
Authors: D Kumar; D C Karampinos; T D MacLeod; W Lin; L Nardo; X Li; T M Link; S Majumdar; R B Souza Journal: Osteoarthritis Cartilage Date: 2013-12-20 Impact factor: 6.576
Authors: Pieter Van Dyck; Christoph Kenis; Filip M Vanhoenacker; Valérie Lambrecht; Kristien Wouters; Jan L Gielen; Lieven Dossche; Paul M Parizel Journal: Knee Surg Sports Traumatol Arthrosc Date: 2013-10-09 Impact factor: 4.342
Authors: Cyrus Cooper; Jonathan D Adachi; Thomas Bardin; Francis Berenbaum; Bruno Flamion; Helgi Jonsson; John A Kanis; Franz Pelousse; Willem F Lems; Jean-Pierre Pelletier; Johanne Martel-Pelletier; Susanne Reiter; Jean-Yves Reginster; René Rizzoli; Olivier Bruyère Journal: Curr Med Res Opin Date: 2013-04-17 Impact factor: 2.580