Identification of Intraarticular and Periarticular Uric Acid Crystals with Dual-Energy CT: Initial Evaluation

Radiology ◽  
2011 ◽  
Vol 261 (2) ◽  
pp. 516-524 ◽  
Author(s):  
Katrina N. Glazebrook ◽  
Luis S. Guimarães ◽  
Naveen S. Murthy ◽  
David F. Black ◽  
Tim Bongartz ◽  
...  
2019 ◽  
Vol 45 (4) ◽  
pp. 1092-1099
Author(s):  
Roberto Cannella ◽  
Mohammed Shahait ◽  
Alessandro Furlan ◽  
Feng Zhang ◽  
Joel D. Bigley ◽  
...  

2009 ◽  
Vol 35 (5) ◽  
pp. 629-635 ◽  
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Paul Stolzmann ◽  
Marko Kozomara ◽  
Natalie Chuck ◽  
Michael Müntener ◽  
Sebastian Leschka ◽  
...  

Radiology ◽  
2010 ◽  
Vol 257 (2) ◽  
pp. 402-409 ◽  
Author(s):  
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Martin Heuschmid ◽  
David Schilling ◽  
Dominik Ketelsen ◽  
Ilias Tsiflikas ◽  
...  

2016 ◽  
Vol 43 (6Part27) ◽  
pp. 3665-3665
Author(s):  
J Miller ◽  
J Huang ◽  
T Szczykutowicz ◽  
J Bayouth

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1763.1-1764
Author(s):  
M. Gamala ◽  
J. W. G. Jacobs ◽  
S. Linn-Rasker ◽  
M. Nix ◽  
B. Heggelman ◽  
...  

Background:Classification criteria are used for classifying groups of patients, especially for clinical trials, and diagnostic criteria for diagnosis in individual patients.Objectives:to establish the performance of the 2015 ACR/EULAR gout classification criteria for the diagnosis gout in patients with undifferentiated arthritis. Secondary, to explore the use and efficacy of uric acid lowering therapy (ULT) in daily clinical practice in new gout patients.Methods:1-year follow-up study was performed in subjects with unclassified arthritis, who had been classified as gout patients or not, according the gout classification criteria, including imaging with dual-energy CT, but without ultrasonography and joint X-rays.(1) The reference was the clinical diagnosis (gout yes/no) after 1-year follow-up.Results:71 patients were included; their demographic and clinical characteristics are summarized in Table 1. All 63/71 patients classified as having gout at baseline also had a clinical gout diagnosis after one year, and of the patients not classified, none had the clinical diagnosis of gout at one year.Table 1.Characteristics of the 71subjects included in analysesDiagnosis**gout (n=63)no gout (n=8)Age in years, mean (SD)62 (14)59 (14)Male gender, N (%)53 (84)5 (63)Symptom duration* at baseline in months, median (IQR)12 (1-48)8 (0.5-33)Joint involvement at baseline N patients (%):MTP,33 (52)1 (12)ankle/midfoot12 (19)1 (12)other joint18 (29)6 (76)SUA intercritical in umol/l, mean (SD)484 (63)337 (71)2015 ACR/EULAR criteria baseline score, mean (SD)***10.3 (2.5)2.6 (1.5)2015 ACR/EULAR criteria ≥8 points, N patients (%)***57 (90)0 (0)MSU crystal positive joint aspiration, N patients (%)44 (70)0 (0)DECT positive, N patients (%)49 (78)0 (0)* self-reported, intermittent symptoms; ** all patients classified with gout at baseline also had a clinical gout diagnosis after one yea; *** using a somewhat limited set, see methodsMTP, metatarsophalangeal joints; SUA, serum uric acid; DECT, dual-energy CT; MSU, monosodium urate;.Sensitivity, specificity, positive and negative predictive value, and accuracy values (95% CI) of the classification criteria set we used were 0.91 (0.80-0.96); 1 (0.63-1); 1; 0.57 (0.38-0.74) and 0.92 (0.83-0.97), respectively. The area under the receiver operating characteristics curve (95% CI) was 0.95 (0.91-0.99).ULT was started in 49/63 (78%) of gout patients; 45/49 (92%) of them had serum uric acid levels ≤ 360 μmol/l and no recurrent gout attack during one-year follow-up.Conclusion:The 2015 ACR-EULAR gout classification criteria performed well for the diagnosis gout in clinical practice. Most gout patients had been treated successfully, according to current guidelines.References:[1]Gamala M, Jacobs JWG, Linn-Rasker SF, Nix M, Heggelman BGF, Pasker-de Jong PCM, et al. The performance of dual-energy CT in the classification criteria of gout: a prospective study in subjects with unclassified arthritis. Rheumatology 2019 Sep (Epub ahead print).Disclosure of Interests:Mihaela Gamala: None declared, Johannes W. G. Jacobs Grant/research support from: Roche, Suzanne Linn-Rasker: None declared, Maarten Nix: None declared, Ben Heggelman: None declared, Pieternel Pasker: None declared, Jacob M. van Laar Grant/research support from: MSD, Genentech, Consultant of: MSD, Roche, Pfizer, Eli Lilly, BMS, Ruth Klaasen: None declared


Author(s):  
Johan Jendeberg ◽  
Per Thunberg ◽  
Marcin Popiolek ◽  
Mats Lidén

Abstract Objectives To prospectively validate three quantitative single-energy CT (SE-CT) methods for classifying uric acid (UA) and non-uric acid (non-UA) stones. Methods Between September 2018 and September 2019, 116 study participants were prospectively included in the study if they had at least one 3–20-mm urinary stone on an initial urinary tract SE-CT scan. An additional dual-energy CT (DE-CT) scan was performed, limited to the stone of interest. Additionally, to include a sufficient number of UA stones, eight participants with confirmed UA stone on DE-CT were retrospectively included. The SE-CT stone features used in the prediction models were (1) maximum attenuation (maxHU) and (2) the peak point Laplacian (ppLapl) calculated at the position in the stone with maxHU. Two prediction models were previously published methods (ppLapl-maxHU and maxHU) and the third was derived from the previous results based on the k-nearest neighbors (kNN) algorithm (kNN-ppLapl-maxHU). The three methods were evaluated on this new independent stone dataset. The reference standard was the CT vendor’s DE-CT application for kidney stones. Results Altogether 124 participants (59 ± 14 years, 91 men) with 106 non-UA and 37 UA stones were evaluated. For classification of UA and non-UA stones, the sensitivity, specificity, and accuracy were 100% (37/37), 97% (103/106), and 98% (140/143), respectively, for kNN-ppLapl-maxHU; 95% (35/37), 98% (104/106), and 97% (139/143) for ppLapl-maxHU; and 92% (34/37), 94% (100/106), and 94% (134/143) for maxHU. Conclusion A quantitative SE-CT method (kNN-ppLapl-maxHU) can classify UA stones with accuracy comparable to DE-CT. Key Points • Single-energy CT is the first-line diagnostic tool for suspected renal colic. • A single-energy CT method based on the internal urinary stone attenuation distribution can classify urinary stones into uric acid and non-uric acid stones with high accuracy. • This immensely increases the availability of in vivo stone analysis.


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