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The combination of mean and maximum Hounsfield Unit allows more accurate prediction of uric acid stones

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Abstract

Based on mean Hounsfield Unit (HuMean), we aimed to evaluate the additional use of standard deviation of Hounsfield Unit (HuStd), minimum Hounsfield Unit (HuMin), and maximum Hounsfield Unit (HuMax) in noncontrast computed tomography (NCCT) to evaluate uric acid (UA) stones more accurately. The data of patients who underwent the NCCT examination and infrared spectroscopy in our hospital from August 2017 to December 2021 were analyzed retrospectively. Based on CT scans, the HuMean, HuStd, HuMin, and HuMax of all patients were measured. The patients were divided into groups according to the stone composition. The attenuation value of mixed stones was in the middle of their pure stones. Except for Str, statistically significant differences between UA stones and other pure stones were observed for HuMean, HuStd, HuMin, and HuMax. A moderate correlation was found between HuMean, HuStd, HuMin, and HuMax and UA stones (rs showed −0.585, −0.409, −0.492, and −0.577, respectively). Receiver operator characteristic (ROC) curve showed that the area under the curve (AUC) of HuMean and HuMax were higher than those of HuStd and HuMin (AUC = 0.896, AUC = 0.891 vs. AUC = 0.777, AUC = 0.833). Higher AUC (0.904), specificity (0.899) and positive predictive value (PPV) (0.712) can be obtained by combining HuMean and HuMax in the diagnosis of UA stones. In conclusion, HuMean and HuMax can better predict UA stones than HuStd and HuMin. The combined use of HuMean and HuMax can lead to higher accuracy.

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Acknowledgements

The authors are grateful to Xiaowen Fu, Wei Jin, Guoqiang Zhu and Xuan Yi for their methodology, formal analysis and investigation as well as Xiaowen Fu and Xuan Yi for their help in manuscript writing.

Funding

The study was funded by the Natural Science Foundation of Hunan Province (2020JJ4542), the Clinical Research Project of University of South China (USCKF201902K01) and the Hunan Provincial Clinical Medical Technology Innovation Guiding Project (2020SK51801).

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Authors and Affiliations

  1. The First Affiliated Hospital, Urology Department, Hengyang Medical School, University of South China, No. 69, chuanshan Road, Shigu District, Hengyang, 421001, Hunan Province, China

    Long Qin, Jianhua Zhou, Wei Hu, Hu Zhang, Yunhui Tang & Mingyong Li

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  1. Long Qin
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  2. Jianhua Zhou
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  3. Wei Hu
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  4. Hu Zhang
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  5. Yunhui Tang
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  6. Mingyong Li
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Contributions

Conceptualization: Long Qin, Wei Hu, and Mingyong Li; methodology: Long Qin, Jianhua Zhou, Hu Zhang, and Yunhui Tang; formal analysis and investigation: Long Qin and Hu Zhang; writing—original draft preparation: Long Qin, Hu Zhang, and Yunhui Tang; writing—review and editing: Long Qin, Wei Hu, and Mingyong Li; funding acquisition: Wei Hu and Mingyong Li; resources: Wei Hu and Mingyong Li; supervision: Wei Hu and Mingyong Li.

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Correspondence to Mingyong Li.

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Ethical approval

The study was approved by the Medical Ethics Committee of the First Affiliated Hospital of University of South China (No: USCKF201711K13).

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Informed consent was obtained from all individual participants included in the study.

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Qin, L., Zhou, J., Hu, W. et al. The combination of mean and maximum Hounsfield Unit allows more accurate prediction of uric acid stones. Urolithiasis 50, 589–597 (2022). https://doi.org/10.1007/s00240-022-01333-2

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  • DOI: https://doi.org/10.1007/s00240-022-01333-2

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