European journal of radiology · 2024
Application of improved urate analysis algorithm based on spectral parameters in Podagra: A prospective study.
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Zhang Yiteng, Liu Yi, Zhao Yi, Zhang Yu, Xia Chunchao, Ye Zheng, Li Hanyu, Romman Zimam, Yao Hui, Li Zhenlin, Tang Jing
Аннотация
OBJECTIVES: To explore whether the improved urate analysis (IUA) algorithm based on spectral parameters can reduce false positives in CT gout images compared with current urate analysis (CUA) algorithm.
MATERIALS AND METHODS: This prospective study was performed from May 2022 to May 2023. Spectral feet CT images of suspected gout participants were reconstructed by IUA and CUA algorithm. Qualitative diagnosis of IUA and CUA images was recorded and compared with the reference standard (ultrasound + conventional CT). Artifacts on IUA and CUA images of non-gout participants were recorded and compared; the maximum cross-sectional area of the maximum tophi (SIT-max) on IUA and CUA images of participants with gout were measured and compared.
RESULTS: There are 65 participants (mean age, 43.9 years ± 13.1 [SD]; 65 men) with 114 feet studies in the gout group, and 33 participants (mean age, 43.4 years ± 15.0 [SD]; 30 men) with 65 feet studies in the non-gout group. For all 179 feet studies, IUA images had higher specificity (19.2-86.6 % vs. 1.3-44.3 %) and accuracy (63.1-88.8 % vs. 41.3-57.0 %) than CUA images (P < 0.001). In the non-gout group, the reduction rates of artifacts from the nail bed, skin, beam hardening, vascular structures, tendons, and total artifacts on the IUA images compared to the CUA images was 40.5 %, 48.9 %, 74.3 %, 99.2 %, 99.6 %, and 80.0 %, respectively (P < 0.001). For 82 feet studies with tophi, SIT-max was higher on CUA images than IUA images (P < 0.05).
CONCLUSION: The improved urate analysis algorithm based on spectral parameters can reduce image artifacts and improve diagnostic efficacy.
MATERIALS AND METHODS: This prospective study was performed from May 2022 to May 2023. Spectral feet CT images of suspected gout participants were reconstructed by IUA and CUA algorithm. Qualitative diagnosis of IUA and CUA images was recorded and compared with the reference standard (ultrasound + conventional CT). Artifacts on IUA and CUA images of non-gout participants were recorded and compared; the maximum cross-sectional area of the maximum tophi (SIT-max) on IUA and CUA images of participants with gout were measured and compared.
RESULTS: There are 65 participants (mean age, 43.9 years ± 13.1 [SD]; 65 men) with 114 feet studies in the gout group, and 33 participants (mean age, 43.4 years ± 15.0 [SD]; 30 men) with 65 feet studies in the non-gout group. For all 179 feet studies, IUA images had higher specificity (19.2-86.6 % vs. 1.3-44.3 %) and accuracy (63.1-88.8 % vs. 41.3-57.0 %) than CUA images (P < 0.001). In the non-gout group, the reduction rates of artifacts from the nail bed, skin, beam hardening, vascular structures, tendons, and total artifacts on the IUA images compared to the CUA images was 40.5 %, 48.9 %, 74.3 %, 99.2 %, 99.6 %, and 80.0 %, respectively (P < 0.001). For 82 feet studies with tophi, SIT-max was higher on CUA images than IUA images (P < 0.05).
CONCLUSION: The improved urate analysis algorithm based on spectral parameters can reduce image artifacts and improve diagnostic efficacy.