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Detection of microvascular damage of membranous nephropathy by MicroFlow imaging: a novel ultrasound technique.
Lu, Renjie; Sun, Fangfang; Zhang, Lili; Zhang, Chao; Du, Jie; Hao, Jianxun; Zhao, Lirong.
Afiliação
  • Lu R; Department of Diagnostic Ultrasound Center, the First Hospital of Jilin University, Changchun, China.
  • Sun F; Department of Diagnostic Ultrasound Center, the First Hospital of Jilin University, Changchun, China.
  • Zhang L; Department of Diagnostic Ultrasound Center, the First Hospital of Jilin University, Changchun, China.
  • Zhang C; Department of Diagnostic Ultrasound Center, the First Hospital of Jilin University, Changchun, China.
  • Du J; Department of Diagnostic Ultrasound Center, the First Hospital of Jilin University, Changchun, China.
  • Hao J; Department of Diagnostic Ultrasound Center, the First Hospital of Jilin University, Changchun, China.
  • Zhao L; Department of Diagnostic Ultrasound Center, the First Hospital of Jilin University, Changchun, China.
Quant Imaging Med Surg ; 14(1): 958-971, 2024 Jan 03.
Article em En | MEDLINE | ID: mdl-38223077
ABSTRACT

Background:

MicroFlow imaging (MFI) is a novel noninvasive ultrasound (US) technique that depicts microcirculatory blood vessels in the kidney while filtering out tissue motion and enhancing blood flow signals. We aimed to investigate the value of MFI for the detection of renal microvascular perfusion in chronic kidney disease caused by stage I-II membranous nephropathy (MN).

Methods:

Seventy-six participants including biopsy-proven MN (n=38) and healthy volunteers (n=38) were prospectively examined using MFI from March 2020 to December 2020. In addition, patients with MN were subdivided into a mild group, a moderate group, and a severe group based on the results of vascular pathology evaluation. All MFI images were analyzed by Image Pro Plus to obtain a cortical vascular index (VI). Basic patient information, relative US parameters and laboratory results were then acquired for each participant. Finally, after the univariate analysis among multiple groups, binary logistic regression (forward LR) and ordered logistic regression were used for multivariate analysis. Significance was set at P<0.05.

Results:

VI was significantly lower in MN patients compared with that of healthy controls (0.65±0.09 vs. 0.35±0.18, P<0.001). After multivariate analysis, we found that the exploratory diagnostic performance of VI [area under the curve (AUC) 0.94; 95% confidence interval (CI) 0.89-0.99] outperformed that of serum creatinine (Scr) (AUC 0.87; 95% CI 0.79-0.95) in identifying MN. We also observed considerable differences among MN groups in parameters including VI (P=0.006), estimated glomerular filtration rate (eGFR) (P=0.037), shape (P=0.013), and impression (P=0.007). In addition, in the group with mild vascular damage, the exploratory diagnostic performance of VI (AUC 0.79; 95% CI 0.64-0.94) was better than other parameters, such as eGFR (AUC 0.63; 95% CI 0.43-0.84).

Conclusions:

MFI detected abnormal renal microvascular perfusion in patients with MN (particularly in those with early vascular damage or preserved renal function) without the use of a contrast agent. Combining MFI with B-mode US can improve the predictive performance of traditional kidney US.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article