Clinical trial NCT03887611: Application of Ultrasound Artificial Intelligence and Elastography in Differential Diagnosis of Thyroid Nodules
Official title: A Multi-center Study of Differential Diagnosis Thyroid Nodules by Ultrasound Artificial Intelligence and Ultrasound Elastography
Study type: OBSERVATIONAL
Overall status: UNKNOWN
Conditions: Thyroid Nodule
Keywords: Artificial Intelligence; Ultrasound;Thyroid nodule; ECI
Lead sponsor: Tongji Hospital
Sponsor class: OTHER
Collaborators: name: Xinhua Hospital, Shanghai Jiao Tong University School of Medicine
name: Wuhan Hospital of Traditional Chinese Medicine
name: Macheng People's Hospital
name: Huangshi Central Hospital, China
name: Affiliated Hospital of Jiangsu University
name: The First People's Hospital of Yichang
name: The Second People's Hospital of Yichang
name: Xiangyang Central Hospital
name: The Second Hospital of Anhui Medical University
name: Anqing People's Hospital
name: Huainan People's Hospital
name: Taizhou Hospital
name: Wenzhou Central Hospital
name: Xuzhou First People's Hospital
name: The Central Hospital of Lishui City
name: Huai'an First People's Hospital
name: WISCO General Hospital
name: Jiangxia District First People's Hospital
name: Enshi State Central Hospital
name: Lianyungang Third People's Hospital
name: First People's Hospital of Xianyang
First posted: 2019-03-25
Enrollment: 2000
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: CASE_ONLY
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Patients with thyroid nodules in large tertiary hospitals

Brief 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. 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.

Eligibility criteria: Inclusion Criteria:

1. Had thyroid lesions detected by ultrasound
2. Age 18 or older
3. Upcoming FNAB or surgery
4. Signing informed consent

Exclusion Criteria:

1. Patients who had received a biopsy of thyroid lesion before the ultrasound examination
2. Can not cooperate with the test operation
3. Patients who were pregnant or lactating
4. Patients who were undergoing neoadjuvant treatment.

Primary outcomes:
measure: Benign or malignant lesions as determined by pathology
timeFrame: Before surgery or biopsy
measure: Elastic ratio
timeFrame: Before surgery or biopsy
Secondary outcomes:
Other outcomes:
Locations:
city: Wuhan
country: China
facility: Xin-Wu Cui
state: Hubei
Study officials:
affiliation: Tongji Hospital
name: Xin-Wu Cui, PhD,MD
role: STUDY_CHAIR
affiliation: Tongji Hospital
name: You-Bin Deng, PhD,MD
role: STUDY_CHAIR
References:
citation: 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.