Automatic Segmentation Ultrasound-based Radiomics Technology in Diabetic Kidney Disease

February 15, 2022 updated by: Second Affiliated Hospital, School of Medicine, Zhejiang University

Noninvasive Detection of Diabetic Kidney Disease Based on Automatic Segmentation Ultrasound-based Radiomics Technology

Diabetic kidney disease is a common complication of diabetes and the main cause of end-stage renal disease. In this study, the investigator plan to enroll nearly 500 participant with/without DKD and to develop an automatic segmentation ultrasound based radiomics technology to differentiating participant with a non-invasive and an available way.

Study Overview

Status

Status

Indicates the current recruitment status or the expanded access status.
Completed

Conditions

Conditions

The disease, disorder, syndrome, illness, or injury that is being studied. On ClinicalTrials.gov, conditions may also include other health-related issues, such as lifespan, quality of life, and health risks.

Intervention / Treatment

Intervention / Treatment

A process or action that is the focus of a clinical study. Interventions include drugs, medical devices, procedures, vaccines, and other products that are either investigational or already available. Interventions can also include noninvasive approaches, such as education or modifying diet and exercise.

Detailed Description

Ultrasound examination is a convenient, cheap and non-invasive method for kidney examination. However, the ability of conventional ultrasound to distinguish diabetic kidney disease from normal kidney is limited, and it is difficult to accurately distinguish between diabetic kidney disease and normal kidney only with the naked eye. In recent years, computer science has developed rapidly and artificial intelligence has been developing continuously. Much progress has been made in applying artificial intelligence in data analysis. Machine learning is a direction of generalized artificial intelligence, its main characteristic is to make the machine autonomous prediction and create algorithm, so as to achieve autonomous learning. kidney disease and deep learning are two different approaches in the field of machine learning. In this study, image omics and deep learning were used to analyze the images. Image omics extracts traditional image features, including shape, gray scale, texture, etc., and uses machine learning (pattern recognition) models to classify and predict, such as support vector machine, random forest, XGBoost, etc. Deep learning directly uses the convolutional network CNN to extract features, and completes classification and prediction in combination with the full connection layer, etc.

This study aims to explore the detection of diabetic kidney disease and its pathological degree based on automatic segmentation ultraound-based radiomics technology, mining of internal information of ultrasound images, and form a set of non-invasive monitoring of diabetic kidney disease complications development system, especially in primary medical institutions, has a broad clinical application prospect.

Study Type

Study Type

Describes the nature of a clinical study. Study types include interventional studies (also called clinical trials), observational studies (including patient registries), and expanded access.
Observational

Enrollment (Actual)

Enrollment

The number of participants in a clinical study. The "anticipated" enrollment is the target number of participants that the researchers need for the study.
499

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • China
    • Anhui
      • Fuyang, Anhui, China, 236200
        • The People's Hospital of Yingshang
    • Tianjin
      • Tianjin, Tianjin, China, 300000
        • Tianjin Third Central Hospital
    • Zhejiang
      • Hangzhou, Zhejiang, China, 310000
        • Department of Ultrasound, Second Affiliated Hospital, School of Medicine, Zhejiang University

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Eligibility Criteria

The key requirements that people who want to participate in a clinical study must meet or the characteristics they must have. Eligibility criteria consist of both inclusion criteria (which are required for a person to participate in the study) and exclusion criteria (which prevent a person from participating). Types of eligibility criteria include whether a study accepts healthy volunteers, has age or age group requirements, or is limited by sex.

Ages Eligible for Study

18 years to 80 years (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Sampling Method

Non-Probability Sample

Study Population

  1. patients with diabetes
  2. patients with or without DKD

Description

Inclusion Criteria:

  • patients with clinical diagnosis of T2DM and DKD were enrolled.
  • patients with clear B mode ultrasound imaging in both side of kidney (left and right).
  • No missing value in the vital clinical data such as eGFR and UACR.

Exclusion Criteria:

  • Patients with large kidney space occupying disease such as kidney renal cyst and tumor were excluded.
  • Ultrasound images with severe shadow or incomplete kidney border were excluded.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort

Group / Cohort

A group or subgroup of participants in an observational study that is assessed for biomedical or health outcomes.
Intervention / Treatment

Intervention / Treatment

A process or action that is the focus of a clinical study. Interventions include drugs, medical devices, procedures, vaccines, and other products that are either investigational or already available. Interventions can also include noninvasive approaches, such as education or modifying diet and exercise.
Experimental group
Experimental group1：DKD patients with Type 2 diabetes patients with DKD Experimental group2：High level DKD patients with diabetic kidney disease Stage III and IV.
Diagnostic test: ultrasonic imaging
Two-dimensional ultrasound images of the patient's kidneys were obtained by ultrasound imaging.
Control group
Control1：T2DM patients with Type 2 diabetes Control2：Low level DKD patients with diabetic kidney disease Stage I and II.
Diagnostic test: ultrasonic imaging
Two-dimensional ultrasound images of the patient's kidneys were obtained by ultrasound imaging.

What is the study measuring?

Primary Outcome Measures

Primary Outcome Measures

In a clinical study's protocol, the planned outcome measure that is the most important for evaluating the effect of an intervention/treatment. Most clinical studies have one primary outcome measure, but some have more than one.
Outcome Measure
Measure Description
Time Frame
AUC
Time Frame: 6 months
The area under curve (AUC) of radiomics model for differentiating DKD and T2DM or high level and low level DKD patients
6 months

Secondary Outcome Measures

Secondary Outcome Measures

In a clinical study's protocol, a planned outcome measure that is not as important as the primary outcome measure for evaluating the effect of an intervention but is still of interest. Most clinical studies have more than one secondary outcome measure.
Outcome Measure
Measure Description
Time Frame
Miou
Time Frame: 6 months
The mean intersection over union (Miou) of DL-based auto-segmentation in different medical centers
6 months
mPA
Time Frame: 6 months
The mean pixel accuracy (mPA) of DL-based auto-segmentation in different medical centers
6 months

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Sponsor

The organization or person who initiates the study and who has authority and control over the study.
Second Affiliated Hospital, School of Medicine, Zhejiang University

Investigators

Investigators

A researcher involved in a clinical study. Related terms include site principal investigator, site sub-investigator, study chair, study director, and study principal investigator.
  • Study Chair: Pintong Huang, Department of Ultrasound, The Second Affiliated Hospital of Zhejiang University

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

Study Start

The actual date on which the first participant was enrolled in a clinical study. The "anticipated" study start date is the date that the researchers think will be the study start date.
June 1, 2021

Primary Completion (Actual)

Primary Completion

The date on which the last participant in a clinical study was examined or received an intervention to collect final data for the primary outcome measure. Whether the clinical study ended according to the protocol or was terminated does not affect this date. For clinical studies with more than one primary outcome measure with different completion dates, this term refers to the date on which data collection is completed for all the primary outcome measures. The "anticipated" primary completion date is the date that the researchers think will be the primary completion date for the study.
December 1, 2021

Study Completion (Actual)

Study Completion

The date on which the last participant in a clinical study was examined or received an intervention/treatment to collect final data for the primary outcome measures, secondary outcome measures, and adverse events (that is, the last participant's last visit). The "anticipated" study completion date is the date that the researchers think will be the study completion date.
December 1, 2021

Study Registration Dates

First Submitted

First Submitted

The date on which the study sponsor or investigator first submitted a study record to ClinicalTrials.gov. There is typically a delay of a few days between the first submitted date and the record's availability on ClinicalTrials.gov (the first posted date).
August 24, 2021

First Submitted That Met QC Criteria

First Submitted That Met QC Criteria

The date on which the study sponsor or investigator first submits a study record that is consistent with National Library of Medicine (NLM) quality control (QC) review criteria. The sponsor or investigator may need to revise and submit a study record one or more times before NLM's QC review criteria are met. It is the responsibility of the sponsor or investigator to ensure that the study record is consistent with the NLM QC review criteria.
August 24, 2021

First Posted (Actual)

First Posted

The date on which the study record was first available on ClinicalTrials.gov after National Library of Medicine (NLM) quality control (QC) review has concluded. There is typically a delay of a few days between the date the study sponsor or investigator submitted the study record and the first posted date.
August 27, 2021

Study Record Updates

Last Update Posted (Actual)

Last Update Posted

The most recent date on which changes to a study record were made available on ClinicalTrials.gov. There may be a delay between when the changes were submitted to ClinicalTrials.gov by the study's sponsor or investigator (the last update submitted date) and the last update posted date.
February 16, 2022

Last Update Submitted That Met QC Criteria

Last Update Submitted That Met QC Criteria

The most recent date on which the study sponsor or investigator submitted changes to a study record that are consistent with National Library of Medicine (NLM) quality control (QC) review criteria. It is the responsibility of the sponsor or investigator to ensure that the study record is consistent with the NLM QC review criteria.
February 15, 2022

Last Verified

Last Verified

The most recent date on which the study sponsor or investigator confirmed the information about a clinical study on ClinicalTrials.gov as accurate and current. If a study with a recruitment status of recruiting; not yet recruiting; or active, not recruiting has not been confirmed within the past 2 years, the study's recruitment status is shown as unknown.
August 1, 2021

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

Other Study ID Numbers

Identifiers or ID numbers other than the NCT number that are assigned to a clinical study by the study's sponsor, funders, or others. These numbers may include unique identifiers from other trial registries and National Institutes of Health grant numbers.
  • 2021-0465

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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