Clincosm LogoSign in Get a demo

Establishment of a Feasibility Model for NOSE Surgery Based on Machine Learning

Sponsor
Sixth Affiliated Hospital, Sun Yat-sen University (Other)
Overall Status
Not yet recruiting
CT.gov ID
NCT05797064
Collaborator
(none)
460
Enrollment
1
Location
36
Anticipated Duration (Months)
12.8
Patients Per Site Per Month

Study Details

Study Description

Brief Summary

The goal of this observational study is to test in patients with resectable rectosigmoid cancers. The main question it aims to answer is establishment of a feasibility model for predicting natural orifice specimen extraction surgery (NOSES) based on machine learning.

Condition or Disease Intervention/Treatment Phase
  • Procedure: Natural Orifice Specimen Extraction Surgery

Study Design

Study Type:
Observational
Anticipated Enrollment :
460 participants
Observational Model:
Cohort
Time Perspective:
Prospective
Official Title:
Establishment of a Feasibility Model for Predicting Natural Orifice Specimen Extraction Surgery (NOSES) Based on Machine Learning.
Anticipated Study Start Date :
Jun 1, 2023
Anticipated Primary Completion Date :
Jun 1, 2026
Anticipated Study Completion Date :
Jun 1, 2026

Arms and Interventions

Arm Intervention/Treatment
Training set

The training set is a dataset used to train the model, which includes randomly enrolled patients with colon and rectal cancer. The inputs include data such as gender, age, height, weight, BMI, tumor stage, tumor pathology type, and the output information is whether NOSES surgery was successful or not. During training, the model learns from this dataset to make predictions on whether new patients with colon and rectal cancer can undergo NOSES surgery successfully.

Procedure: Natural Orifice Specimen Extraction Surgery
Natural Orifice Specimen Extraction Surgery (NOSES) is a minimally invasive surgical technique that aims to reduce the size and number of incisions required during certain surgeries. In NOSES, the surgical specimen (such as a diseased organ or tumor) is removed from the body through a natural orifice (such as the mouth, anus, or vagina), rather than through an incision in the abdominal wall. In this trial, we will extract surgical specimens from the rectum to reduce trauma to the abdominal wall.
Other Names:
  • NOSES

    		•
    test set

    The test set is a dataset used to evaluate the performance of a trained machine learning model. It includes another randomly enrolled group of patients with colon and rectal cancer, as well as their clinical and pathological data and surgical outcomes. The outputs are not used during training, but are used to test the trained model to evaluate its predictive ability on unknown data. The purpose is to evaluate the model's generalization ability, that is, its performance on new and unknown data.

    Procedure: Natural Orifice Specimen Extraction Surgery
    Natural Orifice Specimen Extraction Surgery (NOSES) is a minimally invasive surgical technique that aims to reduce the size and number of incisions required during certain surgeries. In NOSES, the surgical specimen (such as a diseased organ or tumor) is removed from the body through a natural orifice (such as the mouth, anus, or vagina), rather than through an incision in the abdominal wall. In this trial, we will extract surgical specimens from the rectum to reduce trauma to the abdominal wall.
    Other Names:
  • NOSES

    		•

    Outcome Measures

    Primary Outcome Measures

    1. The number of successful operations performed [3 years]

      Accuracy will be calculated by the number of successful operations performed

    2. The number of successful operations actually completed. [3 years]

      Accuracy will be calculated by the number of successful operations actually completed.

    Eligibility Criteria

    Criteria

    Ages Eligible for Study:
    18 Years to 80 Years
    Sexes Eligible for Study:
    All
    Accepts Healthy Volunteers:
    No
    Inclusion Criteria:

    1. Patients diagnosed with colorectal cancer or large adenoma who are suitable for laparoscopic colorectal surgery;

    2. Tumor staging ≤ T3 without invasion of surrounding organs;

    3. No abdominal seeding or distant organ metastasis;

    4. Clear and complete imaging data (CT, pelvic MRI) that can be processed by a computer;

    5. Feasible evaluation and determination for obtaining specimens through the rectal channel during preoperative and intraoperative assessments.

    Exclusion Criteria:

    1. Contraindications for laparoscopic colorectal surgery;

    2. Tumor staging is T4, or there are cancer nodules;

    3. Presence of metastasis or distant organ metastasis;

    4. Incomplete imaging data;

    5. Preoperative intestinal obstruction;

    6. Tumor or specimen diameter larger than the transverse diameter of the pelvic outlet;

    7. Previous rectal radiotherapy;

    8. Unsuitable evaluation and determination for obtaining specimens through the rectal channel during preoperative and intraoperative assessments.

    Contacts and Locations

    Locations

    Site City State Country Postal Code
    1 The Sixth Affiliate Hospital of Sun Yat-Sen University GuangZhou Guangdong China

    Sponsors and Collaborators

    • Sixth Affiliated Hospital, Sun Yat-sen University

    Investigators

    None specified.

    Study Documents (Full-Text)

    None provided.

    More Information

    Publications

    None provided.
    Responsible Party:
    Yanxin Luo,MD, Principal Investigator, Sixth Affiliated Hospital, Sun Yat-sen University
    ClinicalTrials.gov Identifier:
    NCT05797064
    Other Study ID Numbers:
    • 1010PY(2022)-09
    First Posted:
    Apr 4, 2023
    Last Update Posted:
    Apr 4, 2023
    Last Verified:
    Apr 1, 2023
    Individual Participant Data (IPD) Sharing Statement:
    Undecided
    Plan to Share IPD:
    Undecided
    Studies a U.S. FDA-regulated Drug Product:
    No
    Studies a U.S. FDA-regulated Device Product:
    No

    Study Results

    No Results Posted as of Apr 4, 2023