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An US Mathematical Model in Predicting Renal Transplant Rejection

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Read our disclaimer for details. Identifier: NCT03045731
Recruitment Status : Unknown
Verified April 2018 by Shanghai Zhongshan Hospital.
Recruitment status was:  Recruiting
First Posted : February 7, 2017
Last Update Posted : April 23, 2018
Information provided by (Responsible Party):
Shanghai Zhongshan Hospital

Brief Summary:
The purpose of this study is to establish an ultrasound mathematical model using acoustic radiation force impulse (ARFI) and contrast-enhanced ultrasonography (CEUS) for diagnosing the status of renal allografts.

Condition or disease
Kidney Transplantation

Detailed Description:
  • There are various reasons for renal failure after kidney transplantation, such as delayed graft function (DGF) and acute rejection, acute renal tubular necrosis, chronic rejection and toxicity of immunosuppressive drugs. The diagnosis of renal allografts dysfunction can determine the direction of therapy. Currently, the gold standard of diagnosing renal allografts status is biopsies. However, biopsy has several drawbacks. It is invasive and can cause serious complications. These drawbacks urge investigators to find an accurate and non-invasive method to detect renal function. Elastography is a new way to detect tissue elasticity and can evaluate the tissue elasticity quantitatively. This method is proved to be of great value in diagnosing hepatic fibrosis (≥stage 2). Even though the investigation about this method is relatively less in allograft, the recent research shows that tissue elasticity does have relationship with pathological changes of transplanted kidney. Another new method, contrast-enhanced ultrasonography (CEUS), can indicate the blood perfusion of organ microcirculation. The accuracy rate of diagnosis of acute rejection(AR) can be 80% by using this method. It also has advantage in diagnosing acute tubular necrosis(ATN) and CAN. In addition, it produces no radioactive contamination as well as renal toxicity. This method has no serious side effect so it will not influence the normal function of patients' bodies and it can be performed for many times easily.
  • The research information about Elastography and CEUS is still at the primary stage. The value of one single parameter in diagnosing renal failure is restricted. So the establishment of an integrated mathematical model got by combining traditional methods (such as ultrasonography and color Doppler flow imaging) with these two new methods (Elastography and CEUS) is required to provide a systematical, multi-parameter diagnosis of allograft rejection.
  • What investigators have investigated before shows that different pathological changes of renal allograft can lead to regular changes in shear wave speed (SWS) and hemodynamics. By in-depth study of these changes, investigators aim to develop a mathematical model to diagnose the status of renal allograft.
  • To achieve this goal, the following things will be done:

    1. Investigators plan to enroll 100 renal transplant recipients .
    2. Before biopsy, these things will be done : a. Normal ultrasonography will be performed on transplanted kidney to measure their size, cortical thickness and vertebral body. b. Color Doppler flow imaging will be performed to see blood supply of transplanted kidney and resistive index (RI) of renal seg-mental will be measured. c. Contrast enhanced ultrasonography examination will be performed using Philips iU-22 ultrasonic apparatus with a C5-1 probe (Philips,Amsterdam, theNetherlands)with an intravenous bolus injection of 0.6-1.0mL SonoVue (Bracco, Milan, Italy). Area under curve (AUC), peak intensity (PI), time-to-peak (TTP), rise time (RT) and mean transit time (MTT) will be measured on central cortex of transplanted kidney. d. Elastography will be performed with a Siemens Acuson S2000 ultrasound machine using a 1- to 4-MHzcurved array multifrequency transducer (4 C1) (Siemens,Munich, Germany).

      Shear wave velocity (SWV) will be measured.

    3. Statistical analysis will be performed on the 10 quantitative parameters we got before (AUC, PI.etc ). The correlation between these parameters and condition of transplanted kidney (got by renal biopsy) will be evaluated. Then screening indexes will be optimized. On this basis, a mathematical model in diagnosing transplanted kidney is supposed to be built up.
    4. A ROC curve will be used to analyze the accuracy, sensitivity and specificity of this mathematical model.
    5. Then the US model will be verified in another 80 renal transplant recipients. Investigators will compare the diagnosis efficacy of transplanted kidney status got by the US model with the kidney biopsy result. Any parameter can be adjusted according to the verification results.

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Study Type : Observational
Estimated Enrollment : 180 participants
Observational Model: Cohort
Time Perspective: Prospective
Official Title: An US Mathematical Model in Predicting Renal Transplant Rejection
Study Start Date : January 2016
Estimated Primary Completion Date : September 30, 2019
Estimated Study Completion Date : December 31, 2019

Resource links provided by the National Library of Medicine

Kidney transplant recipients
Patients who have received kidney transplantation in Zhongshan Hospital.

Primary Outcome Measures :
  1. The diagnosis of the status of kidney allografts from biopsy results [ Time Frame: 3 years ]

Information from the National Library of Medicine

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Ages Eligible for Study:   18 Years and older   (Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Sampling Method:   Probability Sample
Study Population
Adults (over 18) who have undergone renal transplant for at Zhongshan Hospital.

Inclusion Criteria:

  • Adults (over 18) who have undergone renal transplant at Zhongshan Hospital
  • Understanding the research situation
  • Signing informed consent voluntarily

Exclusion Criteria:

  • Urinary obstruction
  • Perirenal hematioma
  • Infection in operative sites

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its identifier (NCT number): NCT03045731

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Contact: Wanyuan He, MD, PhD 0086-0-13916237059

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China, Shanghai
Zhongshan Hospital Recruiting
Shanghai, Shanghai, China, 200032
Contact: Jia Fan   
Sponsors and Collaborators
Shanghai Zhongshan Hospital

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Responsible Party: Shanghai Zhongshan Hospital Identifier: NCT03045731    
Other Study ID Numbers: FDU-ZS-US-001
First Posted: February 7, 2017    Key Record Dates
Last Update Posted: April 23, 2018
Last Verified: April 2018
Keywords provided by Shanghai Zhongshan Hospital:
kidney transplantation
mathematical model