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  1. Home
  3. A Nomogram Based On Contrast-enhanced Ultrasound For Evaluating The Glomerulosclerosis Rate In Transplanted Kidneys.
  1. Home
  3. A Nomogram Based On Contrast-enhanced Ultrasound For Evaluating The Glomerulosclerosis Rate In Transplanted Kidneys.

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A nomogram based on contrast-enhanced ultrasound for evaluating the glomerulosclerosis rate in transplanted kidneys.

Nan Xu1, Dandan Wang1, Yi Hong2

  • 1Department of Ultrasound, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.

Quantitative Imaging in Medicine and Surgery
|April 15, 2024

View abstract on PubMed

Summary
This summary is machine-generated.

Contrast-enhanced ultrasound (CEUS) can predict glomerulosclerosis in transplanted kidneys. This novel imaging biomarker shows potential for early detection and improved patient outcomes.

Keywords:
Transplanted kidneyscontrast-enhanced ultrasound (CEUS)glomerulosclerosis ratenomogram

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Area of Science:

  • Nephrology
  • Radiology
  • Transplant Medicine

Background:

  • High glomerulosclerosis rates in transplanted kidneys indicate poor prognosis.
  • Early prediction of glomerulosclerosis is crucial for managing kidney transplant recipients.
  • Contrast-enhanced ultrasound (CEUS) is explored as a novel imaging biomarker.

Purpose of the Study:

  • To evaluate CEUS for early prediction of glomerulosclerosis rate in renal allografts.
  • To assess the efficacy of CEUS parameters in identifying high glomerulosclerosis rates.
  • To develop a predictive model for glomerulosclerosis in kidney transplant recipients.

Main Methods:

  • Retrospective analysis of 143 kidney transplant recipients with confirmed pathology.
  • Conventional ultrasound (CUS) and CEUS examinations were performed.
  • Multivariate logistic analysis and nomogram construction were used to identify predictors.

    • Main Results:

    • Significant differences in CEUS parameters (PI, ATTP, TTP) were observed between groups with >50% and ≤50% glomerulosclerosis.
    • Peak intensity, interlobar artery PSV, cortical echogenicity, and time since transplantation were independent predictors.
    • The developed nomogram demonstrated high predictive accuracy (AUC 0.914 in training, 0.909 in validation).

    Conclusions:

    • A nomogram combining CUS, CEUS, and clinical data effectively predicts glomerulosclerosis rate in transplanted kidneys.
    • CEUS shows potential as a non-invasive imaging biomarker for early detection.
    • This predictive model may enhance clinical decision-making in kidney transplant management.