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Clinical Article
Texture analysis based on MR T2WI single sequence for differentiating rheumatoid arthritis from gouty arthritis
LIU Xin  YANG Haitao  WANG Qiqi  ZHOU Suying  ZHAO Jie 

Cite this article as: Liu X, Yang HT, Wang QQ, et al. Texture analysis based on MR T2WI single sequence for differentiating rheumatoid arthritis from gouty arthritis[J]. Chin J Magn Reson Imaging, 2021, 12(5): 50-54. DOI:10.12015/issn.1674-8034.2021.05.011.


[Abstract] Objective To evaluate the feasibility of texture analysis based on MR T2WI for differentiating rheumatoid arthritis (RA) from gouty arthritis (GA). Materials andMethods The MRI imaging data of 81 joints with RA and 61 joints with GA were retrospectively analyzed.Texture features were extracted from T2WI fat saturated sequence image, and the texture features with good consistency (ICC>0.75) were selected for statistical analysis.Results There were significant differences in 10, 9, 6 and 5 texture features in the first order statistics, GLCM, GLRLM, and GLSZM (P<0.05), corresponding AUC value were 0.898, 0.826, 0.831 and 0.830, respectively.The AUC value of all texture feature sets combined analysis was 0.902. The minimum in the first order statistics showed the maximum AUC value (0.836) of all individual texture features.Conclusions Texture analysis based on MR TaWI fat saturated single sequence image could effectively identify RA from GA.Texture analysis of different texture feature sets displayed certain value for differentiating RA from GA, and the texture features in the first order statistics set showed the best identification efficiency.
[Keywords] rheumatoid arthritis;gouty arthritis;texture analysis;differential diagnosis;magnetic resonance imaging

LIU Xin   YANG Haitao*   WANG Qiqi   ZHOU Suying   ZHAO Jie  

Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China

Yang HT, E-mail: frankyang119@126.com

Conflicts of interest   None.

ACKNOWLEDGMENTS The 2020 Chongqing Science and Health Joint Medical Research Project (No. 2020MSXM034).
Received  2021-01-07
Accepted  2021-03-25
DOI: 10.12015/issn.1674-8034.2021.05.011
Cite this article as: Liu X, Yang HT, Wang QQ, et al. Texture analysis based on MR T2WI single sequence for differentiating rheumatoid arthritis from gouty arthritis[J]. Chin J Magn Reson Imaging, 2021, 12(5): 50-54. DOI:10.12015/issn.1674-8034.2021.05.011.

1
Reijnierse M, Helm-Mil AV, Eshed I, et al. Magnetic resonance imaging of rheumatoid arthritis: peripheral joints and spine[J]. Semin Musculoskelet Radiol, 2018, 22(2): 127-146. DOI: 10.1055/s-0038-1639474.
2
Teh J, Mcqueen F, Eshed I, et al. Advanced imaging in the diagnosis of gout and other crystal arthropathies[J]. Semin Musculoskelet Radiol, 2018, 22(2): 225-236. DOI: 10.1055/s-0038-1639484.
3
Salma K, Nessrine A, Krystel E, et al. Rheumatoid arthritis: seropositivity versus seronegativity: a comparative cross-sectional study arising from Moroccan context[J]. Curr Rheumatol Rev, 2020, 16(2): 143-148. DOI: 10.2174/1573397115666191018115337.
4
Fernandes EA, Bergamaschi SB, Rodrigues TC, et al. Relevant aspects of imaging in the diagnosis and management of gout[J]. Rev Bras Reumatol Engl Ed, 2017, 57(1): 64-72. DOI: 10.1016/j.rbre.2016.05.001.
5
Burke CJ, Alizai H, Beltran LS, et al. MRI of synovitis and joint fluid[J]. J Magn Reson Imaging, 2019, 49(6): 1512-1527. DOI: 10.1002/jmri.26618.
6
Hu S, Liang CH, Liu ZY, et al. The application and progress of texture analysis and radiomics in nonneoplastic lesion[J]. Chin J Radiol, 2019, 53(6): 526-529. DOI: 10.3760/cma.j.issn.1005-1201.2019.06.018.
7
Lubner MG, Smith AD, Sandrasegaran K, et al. CT texture analysis: definitions, applications, biologic correlates, and challenges[J]. Radiographics, 2017, 37(5): 1483-1503. DOI: 10.1148/rg.2017170056.
8
Varghese BA, Cen SY, Hwang DH, et al. Texture analysis of imaging: what radiologists need to know[J]. AJR Am J Roentgenol, 2019, 212(3): 520-528. DOI: 10.2214/AJR.18.20624.
9
Guermazi A, Hayashi D, Roemer FW, et al. Synovitis in knee osteoarthritis assessed by contrast-enhanced magnetic resonance imaging (MRI) is associated with radiographic tibiofemoral osteoarthritis and MRI-detected widespread cartilage damage: the MOST study[J]. J Rheumatol, 2014, 41 (3): 501-508. DOI: 10.3899/jrheum.130541.
10
Borrero CG, Mountz JM, Mountz JD. Emerging MRI methods in rheumatoid arthritis[J]. Nat Rev Rheumatol, 2011, 7(2): 85-95. DOI: 10.1038/nrrheum.2010.173.
11
Liang LF, Liu JJ. Diagnostic value of magnetic resonance imaging in synovial diseases[J]. Medical Recapitulate, 2019, 53(6): 526-529. DOI: 10.3969/j.issn.1006-2084.2012.15.046.
12
Sarazin J, Schiopu E, Namas R. Case series: monoarticular rheumatoid arthritis[J]. Eur J Rheumatol, 2017, 4(4): 264-267. DOI: 10.5152/eurjrheum.2017.17011.
13
Mcqueen FM, Doyle A, Reeves Q, et al. Bone erosions in patients with chronic gouty arthropathy are associated with tophi but not bone oedema or synovitis: new insights from a 3T MRI study[J]. Rheumatology (Oxford), 2014, 53 (1): 95-103. DOI: 10.1093/rheumatology/ket329.
14
Gamala M, Jacobs JWG, Linn-Rasker SF, et al. The performance of dual-energy CT in the classification criteria of gout: a prospective study in subjects with unclassified arthritis[J]. Rheumatology (Oxford), 2019, 59(4): 845-851. DOI: 10.1093/rheumatology/kez391.
15
Dalbeth N, Doyle A, McQueen FM. Imaging in gout: insights into the pathological features of disease[J]. Curr Opin Rheumatol, 2012, 24 (2): 132-138. DOI: 10.1097/BOR.0b013e32834ff5b1.
16
Liang LF. Analyses of MRI manifestations of synovial diseases of articulatio genu[J]. J Med Imaging, 2017, 27(4): 740-744. DOI: CNKI:SUN:XYXZ.0.2017-04-048.
17
Kim HK, Zbojniewicz AM, Merrow AC, et al. MR findings of synovial disease in children and young adults: Part 2[J]. Pediatr Radiol, 2011, 41(4): 495-511. DOI: 10.1007/s00247-011-1971-0.
18
Zhong Y, Liu X, Xiao YD, et al. Research progress of medical image texture analysis in musculoskeletal diseases[J]. Chin J Magn Reson Imaging, 2020, 11(5): 394-397. DOI: 10.12015/issn.1674-8034.2020.05.018.
19
Yoo HJ, Hong SH, Oh HY, et al. Diagnostic accuracy of a fluid-attenuated inversion-recovery sequence with fat suppression for assessment of peripatellar synovitis: preliminary results and comparison with contrast-enhanced MR imaging[J]. Radiology, 2017, 283(3): 769-778. DOI: 10.1148/radiol.2016160155.
20
Hilbert F, Holl-Wieden A, Sauer A, et al. Intravoxel incoherent motion magnetic resonance imaging of the knee joint in children with juvenile idiopathic arthritis[J]. Pediatr Radiol, 2017, 47(6): 681-690. DOI: 10.1007/s00247-017-3800-6.
21
Meng XH, Wang Z, Zhang XN, et al. Rheumatoid arthritis of knee joints: MRI-pathological correlation[J]. Orthop Surg, 2018, 10(3): 247- 254. DOI: 10.1111/os.12389.
22
Laukamp KR, Thiele F, Shakirin G, et al. Fully automated detection and segmentation of meningiomas using deep learning on routine multiparametric MRI[J]. Eur Radiol, 2019, 29(1): 124-132. DOI: 10.1007/s00330-018-5595-8.

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