Non-small cell lung cancer is one of the cancers with the highest incidence and mortality rate in the world, and precise prognostic models can guide clinical treatment plans. With the continuous upgrading of computer technology, deep learning as a breakthrough technology of artificial intelligence has shown good performance and great potential in the application of non-small cell lung cancer prognosis model. The research on the application of deep learning in survival and recurrence prediction, efficacy prediction, distant metastasis prediction, and complication prediction of non-small cell lung cancer has made some progress, and it shows a trend of multi-omics and multi-modal joint, but there are still shortcomings, which should be further explored in the future to strengthen model verification and solve practical problems in clinical practice.
Objective To compare the effect of three-dimensional visual (3DV) model, three-dimensional printing (3DP) model and computer-aided design (CAD) modified 3DP model in video-assisted thoracoscopic surgery (VATS) sublobular resection. MethodsThe clinical data of patients who underwent VATS sublobular resection in the Affiliated Hospital of Hebei University from November 2021 to August 2022 were retrospectively analyzed. The patients were divided into 3 groups including a 3DV group, a 3DP group and a CAD-3DP group according to the tools used. The perioperative indexes and subjective evaluation of operators, patients and their families were compared. ResultsA total of 22 patients were included. There were 5 males and 17 females aged 32-77 (56.95±12.50) years. There were 9 patients in the 3DV group, 6 patients in the 3DP group, and 7 patients in the CAD-3DP group. There was no statistical difference in the operation time, intraoperative blood loss, drainage volume, hospital stay time or postoperative complications among the groups (P>0.05). Based on the subjective evaluations of 4 surgeons, the CAD-3DP group was better than the 3DV group in the preoperative planning efficiency (P=0.025), intuitiveness (P=0.045) and doctor-patient communication difficulty (P=0.034); the CAD-3DP group was also better than the 3DP group in the overall satisfaction (P=0.023), preoperative planning difficulty (P=0.046) and efficiency (P=0.014). Based on the subjective evaluations of patients and their families, the CAD-3DP group was better than the 3DP group in helping understand the vessel around the tumor (P=0.016), surgical procedure (P=0.020), procedure selection (P=0.029), and overall satisfaction (P=0.048); the CAD-3DP group was better than the 3DV group in helping understand the tumor size (P=0.038). ConclusionCAD-modified 3DP model has certain advantages in pre-planning, intraoperative navigation and doctor-patient communication in the VATS sublobectomy.