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

Official title

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

Overview

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.

Interventions

• Device 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 prepare

Primary outcome measures

• the tumor status of surgical margin [Time frame: 3 year]

Secondary outcome measures (1)

• Stability after chest wall reconstruction [Time frame: 3 year]

Eligibility criteria

Inclusion criteria

• 18-70 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

Exclusion criteria

• 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

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Allocation

N/A

Model

Single group

Masking

Open label

Primary purpose

Treatment

Study locations

Center list to be confirmed — check the primary protocol.

Identifiers

NCT: NCT06978075 · 20240910

Primary sources (government registries)

• ClinicalTrials.gov (US NIH)

View this study on ClinicalTrials.gov ↗