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Background: Dual-energy computed tomography (DECT) is purported to accurately distinguish uric acid stones from non-uric acid stones. However, whether DECT can accurately discriminate ammonium urate stones from uric acid stones remains unknown. Therefore, we aimed to explore whether they can be accurately identified by DECT and to develop a radiomics model to assist in distinguishing them.

Methods: This research included two steps. For the first purpose to evaluate the accuracy of DECT in the diagnosis of uric acid stones, 178 urolithiasis patients who underwent preoperative DECT between September 2016 and December 2019 were enrolled. For model construction, 93, 40, and 109 eligible urolithiasis patients treated between February 2013 and October 2022 were assigned to the training, internal validation, and external validation sets, respectively. Radiomics features were extracted from non-contrast CT images, and the least absolute shrinkage and selection operator (LASSO) algorithm was used to develop a radiomics signature. Then, a radiomics model incorporating the radiomics signature and clinical predictors was constructed. The performance of the model (discrimination, calibration, and clinical usefulness) was evaluated.

Results: When patients with ammonium urate stones were included in the analysis, the accuracy of DECT in the diagnosis of uric acid stones was significantly decreased. Sixty-two percent of ammonium urate stones were mistakenly diagnosed as uric acid stones by DECT. A radiomics model incorporating the radiomics signature, urine pH value, and urine white blood cell count was constructed. The model achieved good calibration and discrimination {area under the receiver operating characteristic curve (AUC; 95% confidence interval [CI]), 0.944 (0.899-0.989)}, which was internally and externally validated with AUCs of 0.895 (95% CI, 0.796-0.995) and 0.870 (95% CI, 0.769-0.972), respectively. Decision curve analysis revealed the clinical usefulness of the model.

Conclusions: DECT cannot accurately differentiate ammonium urate stones from uric acid stones. Our proposed radiomics model can serve as a complementary diagnostic tool for distinguishing them in vivo .

Titel:	Development of a radiomics model to discriminate ammonium urate stones from uric acid stones in vivo : A remedy for the diagnostic pitfall of dual-energy computed tomography.
Autor/in / Beteiligte Person:	Zheng, J ; Zhang, J ; Cai, J ; Yao, Y ; Lu, S ; Wu, Z ; Cai, Z ; Tuerxun, A ; Batur, J ; Huang, J ; Kong, J ; Lin, T
Link:	Zum Volltext
Zeitschrift:	Chinese medical journal, Jg. 137 (2024-05-05), Heft 9, S. 1095
Veröffentlichung:	<2015- > : Beijing : Chinese Medical Association ; produced by Wolters Kluwer ; <i>Original Publication</i>: Peking, Chinese Medical Assn., 2024
Medientyp:	academicJournal
ISSN:	2542-5641 (electronic)
DOI:	10.1097/CM9.0000000000002866
Schlagwort:	Humans Female Male Middle Aged Adult Urolithiasis diagnostic imaging Urolithiasis diagnosis Urinary Calculi diagnostic imaging Urinary Calculi chemistry ROC Curve Algorithms Aged Radiomics Uric Acid analysis Tomography, X-Ray Computed methods
Sonstiges:	Nachgewiesen in: MEDLINE Sprachen: English Publication Type: Journal Article Language: English [Chin Med J (Engl)] 2024 May 05; Vol. 137 (9), pp. 1095-1104. <i>Date of Electronic Publication: </i>2023 Nov 23. MeSH Terms: Uric Acid* / analysis ; Tomography, X-Ray Computed* / methods ; Humans ; Female ; Male ; Middle Aged ; Adult ; Urolithiasis / diagnostic imaging ; Urolithiasis / diagnosis ; Urinary Calculi / diagnostic imaging ; Urinary Calculi / chemistry ; ROC Curve ; Algorithms ; Aged ; Radiomics References: De Coninck V, Antonelli J, Chew B, Patterson JM, Skolarikos A, Bultitude M. Medical expulsive therapy for urinary stones: Future trends and knowledge gaps. Eur Urol 2019;76: 658–666. doi: 10.1016/j.eururo.2019.07.053. (PMID: 10.1016/j.eururo.2019.07.053) ; Thongprayoon C, Krambeck AE, Rule AD. Determining the true burden of kidney stone disease. Nat Rev Nephrol 2020;16: 736–746. doi: 10.1038/s41581-020-0320-7. 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Development of a radiomics model to discriminate ammonium urate stones from uric acid stones in vivo : A remedy for the diagnostic pitfall of dual-energy computed tomography.