Thyroid NoduleNCT03887611
Application of Ultrasound Artificial Intelligence and Elastography in Differential Diagnosis of Thyroid Nodules
An observational study of Thyroid Nodule, run by Xin-Wu Cui at 1 site in China.
Trial summary
The application of computer-aided diagnosis (CAD) technology "S-DetectTM" enables qualitative and quantitative automated analysis of ultrasound images to obtain objective, repeatable and more accurate diagnostic results. Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Thyroid Nodule
- What is being tested?
- Ultrasound diagnosis
- Type of treatment
- Medical device
- How many people
- 2,000 participants
- Where
- 1 siteChina
- Study dates
- 18 Jan 2019to 18 Mar 2020
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: Patients with thyroid nodules in large tertiary hospitals
Who may be able to join
- Had thyroid lesions detected by ultrasound
- Age 18 or older
- Upcoming FNAB or surgery
- Signing informed consent
Who cannot join
- Patients who had received a biopsy of thyroid lesion before the ultrasound examination
- Can not cooperate with the test operation
- Patients who were pregnant or lactating
- Patients who were undergoing neoadjuvant treatment.
Trial locations and contacts
1 site in 1 country.
China1 site, 1 recruiting
- Recruiting
Xin-Wu Cui
Wuhan, Hubei, 430030
Xin-Wu Cui, PhD,MD, 15927103161, cuixinwu@live.cn
You-Bin Deng, PhD,MD, 13871197838, ybdeng2007@hotmail.com
About this study
Official title: A Multi-center Study of Differential Diagnosis Thyroid Nodules by Ultrasound Artificial Intelligence and Ultrasound Elastography
The application of computer-aided diagnosis (CAD) technology "S-DetectTM" enables qualitative and quantitative automated analysis of ultrasound images to obtain objective, repeatable and more accurate diagnostic results. The Elastic Contrast Factor (ECI) technique, unlike conventional strain-elastic imaging techniques, can evaluate the elastic distribution in the region of interest. The purpose of the study was to evaluate the differential diagnosis value of ultrasound S-DetectTM technology for benign and malignant thyroid nodules and evaluate the consistency of ultrasound S-DetectTM technology and sonographer in the differential diagnosis of thyroid nodules and explore the differential diagnosis value of Samsung ultrasound ECI technology for benign and malignant thyroid nodules.
Read the detailed description
Thyroid nodules are one of the most common nodular lesions in adults, and their incidence is increasing. Clinical studies have found that about 10%-15% of adults have thyroid nodules, most of which are benign nodules, only 7% of thyroid nodules tend to be malignant, but if not treated promptly, 5% of patients will still from benign to malignant. The incidence of thyroid cancer increases with age. According to the National Cancer Research Center, about 64,300 new cases of thyroid cancer occurred in the world in 2016, and about 1,980 died of thyroid cancer. Timely and accurate detection of thyroid nodules and differentiation of benign and malignant are important for improving clinical treatment and improving patient prognosis.
S-Detect technology is a computer-aided (CAD) system recently developed by Samsung Medical Center for thyroid ultrasound to assist in morphological analysis based on the Thyroid Imaging Reporting and Data System (TI-RADS) description and final assessment.This provides a new way to identify the benign and malignant thyroid nodules.
The ECI technique, unlike conventional strain-elastic imaging technology, performs an elastic analysis of the entire two-dimensional image. Moreover, when measuring the elastic ratio, it is only necessary to place a region of interest (ROI) at the nodule. Compared with the average elasticity of the surrounding area, it is more reflective of the elastic ratio of the mass to the surrounding tissue.
- Conditions
- Thyroid Nodule
- Being tested
- Ultrasound diagnosis
- Keywords
- Artificial Intelligence; Ultrasound;Thyroid nodule; ECI
- Medical subject headings
- Thyroid Nodule
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Ultrasound diagnosisDevice
Ultrasound diagnosis of lesions with Samsung S-Detect and ECI technology
| Study group | Role | What they receive |
|---|---|---|
| thyroid nodules | Those with one or more breast nodules, age 18 or older, upcoming FNAB or surgery and signed informed consent.Those without adverse effects on the test or threatening other candidates, such as mental illness, pregnancy, poor ultrasound image quality, history of thyroid surgery or thyroid biopsy, simple cystic nodules, calcification, excessive mass or too small, the S-DetectTM system can not identify the boundary of the tumor, the basic information is incomplete. Receives: Device: Ultrasound diagnosis |
What is being measured
The primary outcome is the main question the study is designed to answer.
Benign or malignant lesions as determined by pathology
The pathological diagnosis of benign or malignant lesions from surgery samples
Measured: Before surgery or biopsy
Elastic ratio
Clear ECI value
Measured: Before surgery or biopsy
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted25 Mar 2019
- Study start18 Jan 2019
- Primary completion18 Jan 2020 (estimated)
- Study completion18 Mar 2020 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Thyroid NoduleStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case only
- Time perspective
- Prospective
- Enrolment
- 2,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Xin-Wu Cui
- Sponsor type
- University, hospital or other
- Collaborators
- Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Wuhan Hospital of Traditional Chinese Medicine, Macheng People's Hospital, Huangshi Central Hospital, Affiliated Hospital of Jiangsu University, The First People's Hospital of Yichang, Yichang Second People's Hospital, Xiangyang Central Hospital, The Second Hospital of Anhui Medical University, Anqing Municipal Hospital, Huainan People's Hospital, Taizhou Hospital, Wenzhou Central Hospital, Xuzhou First People's Hospital, The Central Hospital of Lishui City, Huai'an First People's Hospital, WISCO General Hospital, Jiangxia District First People's Hospital, Enshi State Central Hospital, Lianyungang Third People's Hospital, First People's Hospital of Xianyang
- Responsible party
- Sponsor-investigator, Xin-Wu Cui, Tongji Hospital
- Investigators
- Xin-Wu Cui, PhD,MD, Study chair, Tongji HospitalYou-Bin Deng, PhD,MD, Study chair, Tongji Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03887611
- Sponsor's protocol ID
- 2019(S074)
- Status last verified
- Mar 2019
- First submitted
- 21 Mar 2019
- Last updated
- 26 Mar 2019
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- Yes
- Individual data sharing
- No: Not public because of the personal information of the participants
Publications
Choi YJ, Baek JH, Park HS, Shim WH, Kim TY, Shong YK, Lee JH. A Computer-Aided Diagnosis System Using Artificial Intelligence for the Diagnosis and Characterization of Thyroid Nodules on Ultrasound: Initial Clinical Assessment. Thyroid. 2017 Apr;27(4):546-552. doi: 10.1089/thy.2016.0372. Epub 2017 Feb 28.
PubMed 28071987
Study at a glance
From the registry record, last updated by the sponsor on 26 Mar 2019. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Multi-center Study of Differential Diagnosis Thyroid Nodules by Ultrasound Artificial Intelligence and Ultrasound Elastography
- ClinicalTrials.gov ID
- NCT03887611
- Acronym / sponsor ID
- 2019(S074)
- Conditions
- Thyroid Nodule
- Keywords
- Artificial Intelligence; Ultrasound;Thyroid nodule; ECI
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 2,000 participants (estimated)
- Lead sponsor
- Xin-Wu CuiUniversity, hospital or other
- Collaborators
- Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Wuhan Hospital of Traditional Chinese Medicine, Macheng People's Hospital, Huangshi Central Hospital, Affiliated Hospital of Jiangsu University, The First People's Hospital of Yichang, Yichang Second People's Hospital, Xiangyang Central Hospital, The Second Hospital of Anhui Medical University, Anqing Municipal Hospital, Huainan People's Hospital, Taizhou Hospital, Wenzhou Central Hospital, Xuzhou First People's Hospital, The Central Hospital of Lishui City, Huai'an First People's Hospital, WISCO General Hospital, Jiangxia District First People's Hospital, Enshi State Central Hospital, Lianyungang Third People's Hospital, First People's Hospital of Xianyang
- Study start
- 18 Jan 2019 (actual)
- Primary completion
- 18 Jan 2020 (estimated)
- Study completion
- 18 Mar 2020 (estimated)
- First posted
- 25 Mar 2019 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The application of computer-aided diagnosis (CAD) technology "S-DetectTM" enables qualitative and quantitative automated analysis of ultrasound images to obtain objective, repeatable and more accurate diagnostic results. The Elastic Contrast Factor (ECI) technique, unlike conventional strain-elastic imaging techniques, can evaluate the elastic distribution in the region of interest. The purpose of the study was to evaluate the differential diagnosis value of ultrasound S-DetectTM technology for benign and malignant thyroid nodules and evaluate the consistency of ultrasound S-DetectTM technology and sonographer in the differential diagnosis of thyroid nodules and explore the differential diagnosis value of Samsung ultrasound ECI technology for benign and malignant thyroid nodules.
Detailed description
Thyroid nodules are one of the most common nodular lesions in adults, and their incidence is increasing. Clinical studies have found that about 10%-15% of adults have thyroid nodules, most of which are benign nodules, only 7% of thyroid nodules tend to be malignant, but if not treated promptly, 5% of patients will still from benign to malignant. The incidence of thyroid cancer increases with age. According to the National Cancer Research Center, about 64,300 new cases of thyroid cancer occurred in the world in 2016, and about 1,980 died of thyroid cancer. Timely and accurate detection of thyroid nodules and differentiation of benign and malignant are important for improving clinical treatment and improving patient prognosis.
S-Detect technology is a computer-aided (CAD) system recently developed by Samsung Medical Center for thyroid ultrasound to assist in morphological analysis based on the Thyroid Imaging Reporting and Data System (TI-RADS) description and final assessment.This provides a new way to identify the benign and malignant thyroid nodules.
The ECI technique, unlike conventional strain-elastic imaging technology, performs an elastic analysis of the entire two-dimensional image. Moreover, when measuring the elastic ratio, it is only necessary to place a region of interest (ROI) at the nodule. Compared with the average elasticity of the surrounding area, it is more reflective of the elastic ratio of the mass to the surrounding tissue.
Study design
- Observational model
- Case only
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| thyroid nodules | – | Device: Ultrasound diagnosisThose with one or more breast nodules, age 18 or older, upcoming FNAB or surgery and signed informed consent.Those without adverse effects on the test or threatening other candidates, such as mental illness, pregnancy, poor ultrasound image quality, history of thyroid surgery or thyroid biopsy, simple cystic nodules, calcification, excessive mass or too small, the S-DetectTM system can not identify the boundary of the tumor, the basic information is incomplete. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- Patients with thyroid nodules in large tertiary hospitals
Key inclusion criteria (4 listed)
- Had thyroid lesions detected by ultrasound
- Age 18 or older
- Upcoming FNAB or surgery
- Signing informed consent
Key exclusion criteria (4 listed)
- Patients who had received a biopsy of thyroid lesion before the ultrasound examination
- Can not cooperate with the test operation
- Patients who were pregnant or lactating
- Patients who were undergoing neoadjuvant treatment.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Ultrasound diagnosisUltrasound diagnosis of lesions with Samsung S-Detect and ECI technology | Device | thyroid nodules |
Primary outcome
Benign or malignant lesions as determined by pathology
Time frame: Before surgery or biopsy
The pathological diagnosis of benign or malignant lesions from surgery samples
Elastic ratio
Time frame: Before surgery or biopsy
Clear ECI value
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 26 Mar 2019.
- Results publication: PubMed 28071987Choi YJ, Baek JH, Park HS, Shim WH, Kim TY, Shong YK, Lee JH. A Computer-Aided Diagnosis System Using Artificial Intelligence for the Diagnosis and Characterization of Thyroid Nodules on Ultrasound: Initial Clinical Assessment. Thyroid. 2017 Apr;27(4):546-552. doi: 10.1089/thy.2016.0372. Epub 2017 Feb 28.
- Individual participant dataSharing planned: No. Not public because of the personal information of the participants
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Xin-Wu Cui, PhD,MD study chair
Tongji Hospital
You-Bin Deng, PhD,MD study chair
Tongji Hospital
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Thyroid Nodule, run by Xin-Wu Cui at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 4 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 26 Mar 2019. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Li-Qiang Zhou, MD (15387076275, zlq_1118@hust.edu.cn), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Benign or malignant lesions as determined by pathology (time frame: Before surgery or biopsy). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT03887611, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 26 Mar 2019; AzTrials last refreshed its copy on 6 Nov 2026.