Comparative Study on Medical Artificial Intelligence Algorithm Assisted and Conventional Imaging Examination Methods

NCT07040527 | Not Yet Recruiting

• 1 other identifier: 20250521
• Study Type: observational
• Target: 100
• Locations: 0 countries
• Sites: N/A

Brief Summary

Chest wall tumors are one of the important diseases in thoracic surgery, and surgery remains the main method for treating this disease in clinical practice. The surgery for chest wall tumors requires extensive resection, and more importantly, precise resection. If the resection range is insufficient, it is easy to cause tumor recurrence and metastasis, which affects the patient's survival; If the resection range is too large, it will cause damage to the chest wall structure, affecting the patient's postoperative recovery and quality of life. At present, the determination of the surgical resection range mainly relies on the experience of the surgeon and the results of imaging examinations. Even if experienced surgeons still have multiple imaging examination results, there are still clinical difficulties of insufficient or excessive resection. Medical artificial intelligence is the in-depth application of artificial intelligence technology in the field of medicine. By processing and analyzing massive amounts of medical data, it can accurately locate tumors and optimize surgical plans. Therefore, it is proposed to compare the clinical effects of surgical resection of chest wall tumors using medical artificial intelligence algorithms and conventional imaging examination methods, in order to understand whether it can achieve more accurate tumor resection.

Conditions

Chest Wall Tumor

Outcome Measures

Primary Outcomes (1)

• Pathological results of surgical margins for chest wall tumors

  Pathological diagnosis of residual tissue cells after tumor resection

  3 years

Secondary Outcomes (4)

• Surgical margins planned by medical artificial intelligence

  3 years

• Surgical margins planned using conventional imaging techniques

  3 years

• recurrence-free survival， RFS

  3 years

• Disease-free survival，DFS

  3 years

Study Arms (2)

Medical Artificial Intelligence Algorithm Assistance Group

Before surgery, medical artificial intelligence algorithms are used to outline the resection range of chest wall tumors, while during the actual surgical process, the resection range is determined by intraoperative frozen pathology. Ultimately, the value of medical artificial intelligence algorithm assistance will be evaluated based on paraffin pathology of surgical margins.

Routine imaging examination group

Before surgery, conventional imaging methods are used to outline the resection range of chest wall tumors, while during the actual surgical process, the resection range is determined by intraoperative frozen pathology. The value of routine imaging examination was ultimately evaluated by paraffin pathology of the surgical margin.

Eligibility Criteria

• Age: 18 Years - 70 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

Patients with benign or malignant chest wall tumors require surgical treatment ,meanwhile they have good overall condition and no signs of metastasis,

You may qualify if:

• years old, male or female not limited Anesthesia ASA score I-II Malignant tumor of soft tissue in the chest Malignant tumors of ribs, rib cartilage, and sternum Tumors with uncertain or unknown properties of ribs, rib cartilage, and sternum Giant benign tumors of ribs, rib cartilage, and sternum The preoperative examination results indicate that the tumor has not undergone distant metastasis Willing to participate in the research and sign the informed consent form

You may not qualify if:

• Patients with distant metastasis detected during preoperative examination Inoperable tumor During the examination, it was discovered that the patient had another type of malignant tumor present ECOG 4 Suffering from active or chronic fungal/bacterial/viral infections History of allergy to anesthesia related drugs Heart and lung dysfunction, liver and kidney dysfunction, inability to tolerate surgery Patients with mental disorders who are unable to cooperate with treatment

Sponsors & Collaborators

• Shanghai Jiao Tong University Affiliated Sixth People's Hospital: lead

Study Design

• Study Type: observational
• Observational Model: OTHER
• Time Perspective: PROSPECTIVE
• Target Duration: 3 Years
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Thoracic Surgery

Study Record Dates

• First Submitted: June 19, 2025
• First Posted: June 27, 2025
• Study Start: July 1, 2025
• Primary Completion: July 30, 2025
• Study Completion (Estimated): December 31, 2028
• Last Updated: June 27, 2025

Record last verified: 2025-06

Data Sharing

• IPD Sharing: Will not share