Artificial Intelligence Combined With 3D-Preformed Chest Wall Defection Reconstruction System in Chest Wall Tumor Surgery

NCT ID: NCT06978075

Last Updated: 2025-05-18

Basic Information

• Recruitment Status: NOT_YET_RECRUITING
• Clinical Phase: NA
• Total Enrollment: 50 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2025-07-01
• Study Completion Date: 2028-12-31

Brief Summary

Chest wall tumors should be completely resection as much as possible while malignant chest wall tumors should be extensively resection. If not completely resection, it will recur in the short time and affect the patient's survival. At present, the surgical resection range mainly relies on preoperative imaging examination and the experience of the surgeon. It lacks precise guidance. This can easily lead to incomplete resection. In addition, the reconstruction materials required for reconstruct the excised chest wall defection are often generated in a standardized manner, lacking intraoperative adjustability. To address this clinical issue, we plan to carry out the research on the application of artificial Intelligence (AI) assisted chest wall tumor resection combined with personalized 3D preformed chest wall defection reconstruction system in chest wall tumor surgery.

Detailed Description

Chest wall tumors should be completely removed as much as possible while malignant tumors should be extensively resection. Due to the lack of sensitivity of the vast majority of chest wall malignant tumors to current chemotherapy drugs, radiotherapy techniques, and even targeted drugs. If not completely resected, the tumor may recur in the short time and catastrophic consequences may occur. At present, the surgical resection range mainly relies on traditional imaging examinations before surgery and the clinical experience of the surgeon. It lacks precise instrument or equipment guidance. This can easily lead to incomplete surgical resection range. In addition, for the reconstruction materials required to reconstruct the chest wall defection after resection, they are often produced in a standardized manner and need to be adjusted according to the surgical situation. Even with 3D printed titanium alloy materials currently available, there is a possibility that they may not be usable once the lesion area exceeds preoperative assessment. To address this clinical issue, we plan to carry out of the research on the application of artificial intelligence (AI) assisted chest wall tumor research combined with a personalized 3D preformed chest wall defect reconstruction system in chest wall tumor surgery. Data will be imported into a computer to draw a 3D model of the tumor and construct an ideal resection range to ensuring sufficient surgical margins while avoiding damage to important nerve and vascular tissues in the chest. Preformed titanium plates will be prepared based on the calculated resection range and the titanium plates will be detachable assembly components through screws, which can be adjusted at any time according to the surgical situation.

Conditions

Chest Wall Tumor; Reconstruction Surgery

Study Design

• Allocation Method: NA
• Intervention Model: SINGLE_GROUP
• Primary Study Purpose: TREATMENT
• Blinding Strategy: NONE

Study Groups

chest wall tumor

Group Type: EXPERIMENTAL

Chest wall tumor resection by the artificial intelgent assistent

Intervention Type: DEVICE

we plan to carry out of the research on the application of artificial intelligence (AI) assisted chest wall tumor research combined with a personalized 3D preformed chest wall defect reconstruction system in chest wall tumor surgery. Data will be imported into a computer to draw a 3D model of the tumor and construct an ideal resection range to ensuring sufficient surgical margins while avoiding damage to important nerve and vascular tissues in the chest. Preformed titanium plates will be prepared based on the calculated resection range and the titanium plates will be detachable assembly components through screws, which can be adjusted at any time according to the surgical situation.

Interventions

Chest wall tumor resection by the artificial intelgent assistent

we plan to carry out of the research on the application of artificial intelligence (AI) assisted chest wall tumor research combined with a personalized 3D preformed chest wall defect reconstruction system in chest wall tumor surgery. Data will be imported into a computer to draw a 3D model of the tumor and construct an ideal resection range to ensuring sufficient surgical margins while avoiding damage to important nerve and vascular tissues in the chest. Preformed titanium plates will be prepared based on the calculated resection range and the titanium plates will be detachable assembly components through screws, which can be adjusted at any time according to the surgical situation.

Intervention Type: DEVICE

Eligibility Criteria

Inclusion Criteria

1. 18-70 years old, male or female not limited

2. Anesthesia ASA score I-II

3. Malignant tumor of soft tissue in the chest

4. Malignant tumors of ribs, rib cartilage, and sternum

5. Tumors with uncertain or unknown properties of ribs, rib cartilage, and sternum

6. Giant benign tumors of ribs, rib cartilage, and sternum

7. The preoperative examination results indicate that the tumor has not undergone distant metastasis

8. Willing to participate in the research and sign the informed consent form

Exclusion Criteria

1. Patients with distant metastasis detected during preoperative examination

2. Inoperable tumor

3. During the examination, it was discovered that the patient had another type of malignant tumor present

4. ECOG 4

5. Suffering from active or chronic fungal/bacterial/viral infections

6. History of allergy to anesthesia related drugs

7. Heart and lung dysfunction, liver and kidney dysfunction, inability to tolerate surgery

8. Patients with mental disorders who are unable to cooperate with treatment

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 80 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Wu Weiming

OTHER

Sponsor Role: lead

Responsible Party

Wu Weiming

Shanghai Jiao Tong University Affiliated Sixth People's Hospital of medicine

Responsibility Role: SPONSOR_INVESTIGATOR

Other Identifiers

20240910

Identifier Type: -

Identifier Source: org_study_id