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

Study Overview
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Brief Summary
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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.

Official Title
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Establishment of a Feasibility Model for Predicting Natural Orifice Specimen Extraction Surgery (NOSES) Based on Machine Learning.

Conditions
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Machine Learning, Surgery, Rectosigmoid Cancer, Natural Orifice Specimen Extraction Surgery

Intervention / Treatment
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* Procedure: Natural Orifice Specimen Extraction Surgery


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Patients diagnosed with colorectal cancer or large adenoma who are suitable for laparoscopic colorectal surgery; Tumor staging ≤ T3 without invasion of surrounding organs; No abdominal seeding or distant organ metastasis; Clear and complete imaging data (CT, pelvic MRI) that can be processed by a computer; Feasible evaluation and determination for obtaining specimens through the rectal channel during preoperative and intraoperative assessments. Exclusion Criteria: Contraindications for laparoscopic colorectal surgery; Tumor staging is T4, or there are cancer nodules; Presence of metastasis or distant organ metastasis; Incomplete imaging data; Preoperative intestinal obstruction; Tumor or specimen diameter larger than the transverse diameter of the pelvic outlet; Previous rectal radiotherapy; Unsuitable evaluation and determination for obtaining specimens through the rectal channel during preoperative and intraoperative assessments.

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 80 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Training set<br>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<br>* 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.<br>* Other names: NOSES;|
| test set<br>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<br>* 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.<br>* Other names: NOSES;|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| The number of successful operations performed | Accuracy will be calculated by the number of successful operations performed | 3 years | 
| The number of successful operations actually completed. | Accuracy will be calculated by the number of successful operations actually completed. | 3 years |