To compare the performance of dual-energy computed tomography(DECT) technologies and ultrasound(US) in detecting monosodium urate(MSU) deposition and assess the potential value of quantitative multiparameter derived from second-generation dual-layer spectral detector CT (dlDECT) in diagnostics of differential materials.

A total of 20 patients were consecutively enrolled and gout was diagnosed based on the 2015 EULAR/ACR criteria. All patients underwent both ultrasound and dlDECT examinations for diagnostic evaluation. The detection rate, differential diagnosis ability, and merits of each method were evaluated. The comparison of diagnosis efficiency between dlDECT and ultrasound detection was using McNemar’s test. The abilities of the spectral quantitative parameters were calculated, including the conventional CT values and six spectral CT parameters—Z Effective, MonoE 40keV, Uric Acid Removed, Electron Density, CaSupp-I 25, and CaSupp-I 70—in distinguishing MSU from bone and muscle tissues.

A total of 20 consecutive patients, encompassing 28 joints, met the inclusion criteria and were enrolled in this study. All patients were male, aged from 27 to 65 years; the disease duration ranged from 2 months to 14 years. Of the 28 joints, the most symptomatic joint or area was foot and ankle(50.00%), followed by knee (35.71%). the overall positivity of crystal deposition detected by dlDECT was similar to that by the US(52.14% vs. 42.14%，p=0.088), and the agreement between dlDECT and US in detecting MSU was just fair (к=0.177). Detection by dlDECT was significantly greater than the US in the upper limb (100% vs. 50%, p=0.008), while in the lower limb, the sensitivity of dlDECT and US was similar (45.97% vs. 41.13%, p=0.48). When using the Spectral CT multi-parameter analysis in dlDECT, All six spectral CT parameters provided some degree of differentiation between MSU, bone, and muscle (AUC = 0.55-1.00). the CaSupp-I 25 demonstrated the best AUC, offering optimal differentiation among the three materials (MSU vs. non-MSU, MSU vs. bone, MSU vs. muscle, and bone vs. muscle with AUC values of 0.992, 0.999, 0.985 and 0.980, respectively; (p<0.05)). Furthermore, the unique parameter characteristics of each patient, represented by histograms, scatter plots, and attenuation curves. Combining these characteristic graphs can enhance the efficiency of differentiating MSU from non-MSU in diagnostic assessments.

dlDECT has the potential value in detecting MSU deposits in gout arthritis, the combined analysis of the CaSupp-I 25 in dlDECT improves MSU diagnostic capabilities. dlDECT outperforms ultrasound in MSU detection, demonstrating its potential as a valuable diagnostic tool. Clinical implementation of multi-parameter analysis in dlDECT offers a powerful and improved alternative to ultrasound for MSU diagnosis and management.