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Spectral computed tomography parameters could be surrogate imaging markers to detect early perfusion changes in diabetic kidneys

BACKGROUND: Kidney microvasculopathy is the baseline pathophysiological feature of diabetic kidney disease (DKD). We aimed to evaluate the spectral computed tomography (CT) parameters for detecting renal perfusion changes among diabetic patients. METHODS: From August 2020 to June 2022, 34 patients (...

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Detalles Bibliográficos
Autores principales: Zheng, Wei, Mu, Ronghua, Qin, Xiaoyan, Li, Xin, Liu, Fuzhen, Zhuang, Zeyu, Yang, Peng, Liang, Yahui, Zhu, Xiqi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10498262/
https://www.ncbi.nlm.nih.gov/pubmed/37711810
http://dx.doi.org/10.21037/qims-22-1400
Descripción
Sumario:BACKGROUND: Kidney microvasculopathy is the baseline pathophysiological feature of diabetic kidney disease (DKD). We aimed to evaluate the spectral computed tomography (CT) parameters for detecting renal perfusion changes among diabetic patients. METHODS: From August 2020 to June 2022, 34 patients (age, 57.7±10.7 years; male, 20) clinically diagnosed with type 2 diabetes mellitus (DM) and 19 DM-free individuals (age, 48.1±16.9 years; male, 12) were selected for analysis. The series participants formed the DM group and control group, respectively. Spectral parameters, including effective atomic number (Z(eff)), iodine density (ID), normalized iodine density (NID) and the slope of the energy spectrum curves (λ), between the 2 groups were analyzed using independent samples t-test. Receiver operator characteristic (ROC) curves were used to evaluate the diagnostic performance of spectral parameters for detecting renal perfusion changes. RESULTS: The results indicate that in both cortical and medullary phases, the values of Z(eff), ID, NID, and λ(40–70) for the renal cortex of the DM group were significantly higher than those in the control group (P<0.05). In the cortex phase, the diagnostic efficacy of cortical spectral CT parameters discriminating DM patients from controls was as follows: the area under ROC curve (AUC) of ID value was 0.816 [95% confidence interval (CI): 0.679–0.921] at the optimal cutoff value 4.14, the AUC of Z(eff) value was 0.800 (95% CI: 0.668–0.901) at the optimal cutoff value 9.26, the AUC of λ(40–70) value was 0.822 (95% CI: 0.675–0.918) at the optimal cutoff value 8.26, and the AUC of NID value was 0.851 (95% CI: 0.684–0.926) at the optimal cutoff value 0.37. In medullary phase: the AUC of ID value was 0.769 (95% CI: 0.617–0.846) at the optimal cutoff value 5.08, the AUC of Z(eff) value was 0.763 (95% CI: 0.614–0.837) at the optimal cutoff value 9.58, the AUC of λ(40–70) value was 0.766 (95% CI: 0.617–0.839) at the optimal cutoff value 10.07, and the AUC of NID value was 0.79 (95% CI: 0.623–0.855) at the optimal cutoff value 1.37. CONCLUSIONS: Spectral CT could serve as an alternative protocol for the early identification of kidney injury in diabetic patients.