Breast DiseasesNCT04535466
Diagnosis Predictive Modle for Dense Density Breast Tissue Based on Radiomics
An observational study of Breast Diseases and Artificial Intelligence, run by Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University at 1 site in China.
Trial summary
It is a prospective, observational cohort study of patients with dense breast tissue. The study was based on the radiomics and other clinicopathological information of patients to establish the diagnostic system for breast disease by using artificial intelligence. Read more about this study
- Who is it for?
- Ages 18 to 80 years, women only
- Conditions the study is for
- Breast Diseases, Artificial Intelligence, Dense Breast Density
- How many people
- 1,000 participants
- Where
- 1 siteChina
- Study dates
- 1 Sep 2020to 1 Sep 2020
- How long will I take part?
- 2 Years
- 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 to 80 years
- Women only
- No healthy volunteers
- Adult, Older adult
Study population: Female patients aged 18-80 were included in our study who were diagnosed and treated at Sun Yat-sen memorial hospital .
Who may be able to join
- Female patients with dense breast density tissue
- Digital breast tomosynthesis was performed
- Breast ultrasound examination was performed
- Pathologic examination of breast lesions was performed
Who cannot join
- Incomplete clinicopathologic data
- Female patients with fatty glands of the breast
Trial locations and contacts
1 site in 1 country.
China1 site, 1 recruiting
- Recruiting
Breast tumor center of Sun Yat-sen Memorial Hospital
Guangzhou, Guangdong, 510120
Yaping yang, Doctor, 0086-020-34071145, yangyap2@mail.sysu.edu.cn
Herui Yao, Doctor
About this study
Official title: Development of an Artificial Intelligence Precise Diagnosis Predictive Modle for Dense Density Breast Tissue Based on Radiomics
It is a prospective, observational cohort study of patients with dense breast tissue. The study was based on the radiomics and other clinicopathological information of patients to establish the diagnostic system for breast disease by using artificial intelligence.
- Medical subject headings
- Breast Diseases
What is being measured
The primary outcome is the main question the study is designed to answer.
the predictive model's area under curve(AUC)
To assess the predictive accuracy of the radiomic-based and clinical-based model by using operating characteristic curve (ROC) analysis and calculating the area under the curves (AUC).
Measured: follow up for 2 year for individuals
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted2 Sep 2020
- Study start1 Sep 2020 (estimated)
- Primary completion1 Sep 2020 (estimated)
- Study completion1 Sep 2020 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Breast DiseasesStudies 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
- Cohort
- Time perspective
- Prospective
- Enrolment
- 1,000 participants (estimated)
- Target duration
- 2 Years
Sponsor and investigators
- Lead sponsor
- Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Yaping yang, Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04535466
- Sponsor's protocol ID
- SYSU_AI01
- Status last verified
- Aug 2020
- First submitted
- 21 Aug 2020
- Last updated
- 2 Sep 2020
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 2 Sep 2020. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Development of an Artificial Intelligence Precise Diagnosis Predictive Modle for Dense Density Breast Tissue Based on Radiomics
- ClinicalTrials.gov ID
- NCT04535466
- Acronym / sponsor ID
- SYSU_AI01
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 1,000 participants (estimated)
- Lead sponsor
- Sun Yat-Sen Memorial Hospital of Sun Yat-Sen UniversityUniversity, hospital or other
- Study start
- 1 Sep 2020 (estimated)
- Primary completion
- 1 Sep 2020 (estimated)
- Study completion
- 1 Sep 2020 (estimated)
- First posted
- 2 Sep 2020 (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.
It is a prospective, observational cohort study of patients with dense breast tissue. The study was based on the radiomics and other clinicopathological information of patients to establish the diagnostic system for breast disease by using artificial intelligence.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Target follow-up
- 2 Years
Who may qualify
- Ages
- 18 to 80 years
- Sex
- Female only
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Female patients aged 18-80 were included in our study who were diagnosed and treated at Sun Yat-sen memorial hospital .
Key inclusion criteria (4 listed)
- Female patients with dense breast density tissue
- Digital breast tomosynthesis was performed
- Breast ultrasound examination was performed
- Pathologic examination of breast lesions was performed
Key exclusion criteria (2 listed)
- Incomplete clinicopathologic data
- Female patients with fatty glands of the breast
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
the predictive model's area under curve(AUC)
Time frame: follow up for 2 year for individuals
To assess the predictive accuracy of the radiomic-based and clinical-based model by using operating characteristic curve (ROC) analysis and calculating the area under the curves (AUC).
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 2 Sep 2020.
Related trials for Breast Diseases
Active, not recruitingPhase 2
Tamoxifen Citrate or Z-Endoxifen Hydrochloride in Treating Patients With Locally Advanced or Metastatic, Estrogen Receptor-Positive, HER2-Negative Breast Cancer
Recurrent Breast Carcinoma, Stage III Breast Cancer AJCC v7
RecruitingPhase 1/2
A Study to Evaluate the Effect of GDC-4198 Alone and in Combination With Giredestrant Versus Abemaciclib and Giredestrant in Participants With Locally Advanced or Metastatic Estrogen Receptor-Positive (ER+), Human Epidermal Growth Factor Receptor-Negative (HER2-) Breast Cancer
Breast Cancer
Not yet recruiting
Podcast-Based Psychosocial Support for Women Newly Diagnosed With Breast Cancer
Breast Cancer
Recruiting
A Study of Skipping Radiation Therapy in People With Breast Cancer
HER2-positive Breast Cancer, Breast Cancer
Active, not recruiting
Dance Study for Post-surgical Pain in Breast Cancer Survivors
Breast Cancer, Survivorship
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.
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 Breast Diseases and Artificial Intelligence, run by Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University 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 2 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 2 Sep 2020. 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 Yaping Yang, Doctor (86020-34071145, yangyap2@mail.sysu.edu.cn), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
the predictive model's area under curve(AUC) (time frame: follow up for 2 year for individuals). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 2 Sep 2020.