Cervical CancerNCT06448897
Development of an Imaging Prediction Model for Pelvic Lymph Node Metastasis of Cervical Cancer Using Artificial Intelligence Techniques.
An observational study of Cervical Cancer and Lymph Node Metastasis, run by Obstetrics & Gynecology Hospital of Fudan University at 1 site in China.
Trial summary
This study is a retrospective exploratory trial conducted at a single center, aiming to develop and validate a preoperative lymphatic metastasis model for cervical cancer using artificial intelligence deep learning. Read more about this study
- Who is it for?
- Ages 18 to 80 years, women only
- Conditions the study is for
- Cervical Cancer, Lymph Node Metastasis, Artificial Intelligence
- How many people
- 4,000 participants
- Where
- 1 siteChina
- Study dates
- 1 Feb 2024to Dec 2025
- 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: All patient information and imaging data were collected from the Obstetrics and Gynecology Hospital of Fudan University. This hospital is a specialized tertiary care facility and is recognized as the leading Obstetrics and Gynecology hospital in China.
Who may be able to join
- patients with preoperative diagnosis of invasive cervical cancer stage I-III, with any type of pathology, and patients who underwent radical/modified radical cervical cancer surgery + pelvic lymph node dissection in our hospital.
- Age ≥18 years old and ≤80 years old
- patients with complete preoperative pelvic MRI images and postoperative pathology and clinical data in our hospital
Who cannot join
- Patients during pregnancy or breastfeeding, patients within 42 days of abortion
- Patients who have received neoadjuvant chemotherapy or radiotherapy before surgery for this previous cervical cancer
- Patients with other malignant tumors within 5 years
- Combination of other underlying diseases that may lead to enlarged pelvic lymph nodes
- Imaging report more than 1 month prior to surgery
- Poor image quality and unrecognizable
Trial locations and contacts
1 site in 1 country.
China1 site, 1 recruiting
- Recruiting
The Obstetrics and Gynecology Hospital of Fudan University
Shanghai, Shanghai Municipality, 200090
Xin Wu, 8613764046908, wuxin_fc@fudan.edu.cn
Xin Wu
About this study
This study is a retrospective exploratory trial conducted at a single center, aiming to develop and validate a preoperative lymphatic metastasis model for cervical cancer using artificial intelligence deep learning. The model is trained using preoperative imaging and postoperative pathological findings of cervical cancer patients, with the goal of enhancing the accuracy of lymphatic metastasis prediction through preoperative imaging and offering insights for treatment decisions.
- Keywords
- Cervical Cancer, Lymph Node Metastasis, Artificial Interlligence
- Medical subject headings
- Uterine Cervical Neoplasms, Lymphatic Metastasis
What is being measured
The primary outcome is the main question the study is designed to answer.
A model for identifying pelvic lymph node metastases on preoperative imaging
Artificial intelligence (AI) technology was utilized to develop a model for identifying pelvic lymph node metastasis from preoperative images in order to enhance the accuracy of preoperative lymph node metastasis detection in cervical cancer. The model was validated with the main diagnostic focus on determining the status of lymph node metastasis.
Measured: From enrollment to the end of development of model at 24 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted7 Jun 2024
- Study start1 Feb 2024
- Primary completionDec 2025 (estimated)
- Study completionDec 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Cervical CancerStudies 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
- Other
- Time perspective
- Retrospective
- Enrolment
- 4,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Obstetrics & Gynecology Hospital of Fudan University
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06448897
- Sponsor's protocol ID
- FUOBGY2024-33
- Status last verified
- Jun 2024
- First submitted
- 3 Jun 2024
- Last updated
- 7 Jun 2024
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 7 Jun 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Development of an Imaging Prediction Model for Pelvic Lymph Node Metastasis of Cervical Cancer Using Artificial Intelligence Techniques.
- ClinicalTrials.gov ID
- NCT06448897
- Acronym / sponsor ID
- FUOBGY2024-33
- Keywords
- Cervical Cancer, Lymph Node Metastasis, Artificial Interlligence
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 4,000 participants (estimated)
- Lead sponsor
- Obstetrics & Gynecology Hospital of Fudan UniversityUniversity, hospital or other
- Study start
- 1 Feb 2024 (actual)
- Primary completion
- Dec 2025 (estimated)
- Study completion
- Dec 2025 (estimated)
- First posted
- 7 Jun 2024 (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.
This study is a retrospective exploratory trial conducted at a single center, aiming to develop and validate a preoperative lymphatic metastasis model for cervical cancer using artificial intelligence deep learning. The model is trained using preoperative imaging and postoperative pathological findings of cervical cancer patients, with the goal of enhancing the accuracy of lymphatic metastasis prediction through preoperative imaging and offering insights for treatment decisions.
Study design
- Observational model
- Other
- Time perspective
- Retrospective
Who may qualify
- Ages
- 18 to 80 years
- Sex
- Female only
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- All patient information and imaging data were collected from the Obstetrics and Gynecology Hospital of Fudan University. This hospital is a specialized tertiary care facility and is recognized as the leading Obstetrics and Gynecology hospital in China.
Key inclusion criteria (3 listed)
- patients with preoperative diagnosis of invasive cervical cancer stage I-III, with any type of pathology, and patients who underwent radical/modified radical cervical cancer surgery + pelvic lymph node dissection in our hospital.
- Age ≥18 years old and ≤80 years old
- patients with complete preoperative pelvic MRI images and postoperative pathology and clinical data in our hospital
Key exclusion criteria (6 listed)
- Patients during pregnancy or breastfeeding, patients within 42 days of abortion
- Patients who have received neoadjuvant chemotherapy or radiotherapy before surgery for this previous cervical cancer
- Patients with other malignant tumors within 5 years
- Combination of other underlying diseases that may lead to enlarged pelvic lymph nodes
- Imaging report more than 1 month prior to surgery
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
A model for identifying pelvic lymph node metastases on preoperative imaging
Time frame: From enrollment to the end of development of model at 24 months
Artificial intelligence (AI) technology was utilized to develop a model for identifying pelvic lymph node metastasis from preoperative images in order to enhance the accuracy of preoperative lymph node metastasis detection in cervical cancer. The model was validated with the main diagnostic focus on determining the status of lymph node metastasis.
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 7 Jun 2024.
- Individual participant dataSharing planned: No
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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.
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 Cervical Cancer and Lymph Node Metastasis, run by Obstetrics & Gynecology Hospital of Fudan 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 3 inclusion and 6 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 7 Jun 2024. 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 Xin Wu ((021)33189900, wuxin_fc@fudan.edu.cn), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
A model for identifying pelvic lymph node metastases on preoperative imaging (time frame: From enrollment to the end of development of model at 24 months). 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 7 Jun 2024.