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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

Tracking Information
First Submitted Date January 14, 2017
First Posted Date February 7, 2017
Last Update Posted Date April 23, 2018
Study Start Date January 2016
Estimated Primary Completion Date September 30, 2019   (Final data collection date for primary outcome measure)
Current Primary Outcome Measures
 (submitted: February 4, 2017)
The diagnosis of the status of kidney allografts from biopsy results [ Time Frame: 3 years ]
Original Primary Outcome Measures Same as current
Change History
Current Secondary Outcome Measures Not Provided
Original Secondary Outcome Measures Not Provided
Current Other Pre-specified Outcome Measures Not Provided
Original Other Pre-specified Outcome Measures Not Provided
Descriptive Information
Brief Title An US Mathematical Model in Predicting Renal Transplant Rejection
Official Title An US Mathematical Model in Predicting Renal Transplant Rejection
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.
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.
Study Type Observational
Study Design Observational Model: Cohort
Time Perspective: Prospective
Target Follow-Up Duration Not Provided
Biospecimen Not Provided
Sampling Method Probability Sample
Study Population Adults (over 18) who have undergone renal transplant for at Zhongshan Hospital.
Condition Kidney Transplantation
Intervention Not Provided
Study Groups/Cohorts Kidney transplant recipients
Patients who have received kidney transplantation in Zhongshan Hospital.
Publications *

*   Includes publications given by the data provider as well as publications identified by Identifier (NCT Number) in Medline.
Recruitment Information
Recruitment Status Unknown status
Estimated Enrollment
 (submitted: February 4, 2017)
Original Estimated Enrollment Same as current
Estimated Study Completion Date December 31, 2019
Estimated Primary Completion Date September 30, 2019   (Final data collection date for primary outcome measure)
Eligibility Criteria

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
Sexes Eligible for Study: All
Ages 18 Years and older   (Adult, Older Adult)
Accepts Healthy Volunteers No
Contacts Contact information is only displayed when the study is recruiting subjects
Listed Location Countries China
Removed Location Countries  
Administrative Information
NCT Number NCT03045731
Other Study ID Numbers FDU-ZS-US-001
Has Data Monitoring Committee Not Provided
U.S. FDA-regulated Product Not Provided
IPD Sharing Statement Not Provided
Responsible Party Shanghai Zhongshan Hospital
Study Sponsor Shanghai Zhongshan Hospital
Collaborators Not Provided
Investigators Not Provided
PRS Account Shanghai Zhongshan Hospital
Verification Date April 2018