AI-Assisted 3D Reconstruction for Lung Resection Planning
Trial statusNot yet recruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorS. Andrea Hospital
About this trial
This prospective observational study aims to validate an artificial intelligence (AI)-based system for automated three-dimensional (3D) reconstruction of pulmonary anatomy from preoperative chest computed tomography (CT) scans in patients undergoing lung resection.
The AI system will automatically identify and reconstruct relevant pulmonary anatomical structures, including pulmonary arteries, veins, bronchi, lobes, and segments. AI-generated 3D reconstructions will be compared with expert manual 3D reconstructions and with anatomical findings documented during surgery.
The primary objective is to assess the anatomical accuracy of AI-generated 3D reconstructions in identifying surgically relevant bronchovascular anatomy and anatomical variants. Secondary objectives include evaluating accuracy for individual anatomical structures, discrepancies between automated and manual reconstructions, concordance with intraoperative findings, and the time required to generate and review the automated reconstruction.
The study is observational and will not modify the planned surgical procedure or standard patient care.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
Age ≥18 years
Scheduled for anatomical lung resection (segmentectomy, lobectomy, bilobectomy, or pneumonectomy)
Availability of a preoperative contrast-enhanced chest CT scan suitable for 3D reconstruction, with slice thickness ≤1.5 mm.
Ability to provide informed consent.
Disqualifiers
Preoperative CT images of insufficient quality or technical characteristics for 3D reconstruction.
Cancellation of the planned surgical procedure before surgery.
Inability or unwillingness to provide informed consent.
Trial population
Adult patients undergoing anatomical lung resection at the Thoracic Surgery Unit of Sant'Andrea University Hospital who have a preoperative contrast-enhanced chest CT scan suitable for AI-based 3D reconstruction.
Trial design
Design model
Cohort
Time perspective
Prospective
Treatments tested in this trial
AI-Based 3D Reconstruction
Other interventionPreoperative contrast-enhanced chest CT images will be processed using an artificial intelligence-based segmentation system to automatically generate three-dimensional reconstructions of pulmonary anatomy, including pulmonary arteries, veins, bronchi, lobes, and segments when applicable. The AI-generated reconstructions will be evaluated against expert manual 3D reconstruction and intraoperative anatomical findings. The AI output will not determine or modify the planned surgical treatment.
Treatment groups
50 Participants
are divided into 1 treatment groupGroup A: Prospective Validation Cohort1 intervention
Trial outcomes
Primary outcomes
1
Patient-Level Anatomical Accuracy of AI-Generated 3D Reconstruction
Proportion of patients in whom the AI-generated 3D reconstruction correctly represents all predefined surgically relevant pulmonary arterial, venous, and bronchial structures and anatomical variants for the planned lung resection, without clinically relevant omissions or incorrectly represented structures. Accuracy will be assessed by comparison with expert manual 3D reconstruction and intraoperative anatomical findings.
Time frame
From preoperative CT imaging through completion of the surgical procedureSponsors and contacts
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Source ClinicalTrials.gov
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