Lung cancer (LC) remains the leading cause of cancer death, and it is the cancer with the highest incidence (1). In recent years, the detection rate of early non-small-cell lung cancer (NSCLC) has increased significantly with the introduction of thin-section and low-dose computed tomography (2). The application of segmentectomy, which is associated with less trauma, fewer complications, and less pain for patients than thin-section and low-dose computed tomography, is more conducive for patients with non-small-cell lung cancer (3). 3D computed tomography of lung segments can ensure the position of the lung tumor within the anatomical segment and assist in the prediction of surgical margins (4). However, whether preoperative 3D lung simulation is better than non-3D procedures in segmentectomy for lung cancer remains controversial.

Whether preoperative 3D lung simulation is better than non-3D procedures in segmentectomy for LC has not yet been confirmed by guidelines (5). Liu et al., Chen et al., and Xu et al. suggested that preoperative 3D simulations for the assessment of pulmonary vessel and bronchi branching patterns could improve surgical accuracy and safety (6–8). Similarly, Hu et al., Xue et al., She et al., and Qiu et al. all reported that preoperative 3D lung simulation shortened the operation time and reduced intraoperative blood loss and intraoperative and postoperative complications, especially in patients with stage IA NSCLC (9–12). However, Wu et al. suggested that conventional segmentectomy can obviously reduce the time of operation and can protect the lung from air leakage, although a sufficient resection margin and lymph node dissection might be ensured by preoperative 3D lung simulation (13).

To verify the reliability and safety of this method, we compared the intraoperative and postoperative indicators of the included patients for whom preoperative 3D lung simulation was performed with those of patients for whom it was not performed.

This meta-analysis followed the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) (Supplementary Table 1) (14). (PROSPERO Registration: CRD42021275020).

Currently, the leading cause of cancer-related mortality worldwide is still lung cancer (20). According to global epidemiological data, over 2 million individuals were affected by lung cancer in 2018 (21). At present, segmentectomy in combination with mediastinal lymph node (LN) dissection or sampling is still one of the main treatment options for patients with stage I non-small-cell lung cancer (NSCLC) (22–24). 3D imaging provides a stereoscopic view, and the visual information obtained through binocular visualization allows precise 3D preoperative planification (25). However, large-sample studies demonstrating the safety and efficacy of 3D system use are still lacking. This study is the first meta-analysis of preoperative 3D lung simulation compared with non-3D procedures during segmentectomy for lung cancer. Our results revealed that the 3D group had notably less blood loss, a shorter operative time, a lower conversion rate, a shorter postoperative hospital stay and a lower total number of complications than the non-3D group. Arrhythmia, pulmonary air leakage, atrial fibrillation, pulmonary infection and pneumonia were top 5 postoperative complications in the 3D group. The number of resected lymph nodes (LNs), postoperative drainage time, postoperative forced expiratory volume in the first second (post-op FEV1) and postoperative drainage volume were similar in the two groups.

For intraoperative outcomes, the patients in the 3D group showed an obvious improvement in blood loss, operative time, and conversion rate (conversion from segmentectomy to thoracotomy or lobectomy) compared with patients in the non-3D group. With the latest developments in 3D lung simulation imaging, the quality of imaging in a 3D system is similar to that in stereo vision. Because the 3D structure of the lung was examined adequately before surgery, the risk of bleeding during surgery was reduced. The surgeon obtained a better understanding of the anatomy of the nodule by watching the preoperative 3D lung simulation, which may have led to the shorter operation time. Similarly, with preoperative 3D lung simulation scanning, conversion to lobectomy was less likely. However, there were no differences in the number resected LNs between these two groups. Jiao et al. found that their 3D group had results that were similar to those of their traditional 2D procedure group (26). Regarding the number of resected lymph nodes, preoperative 3D lung simulation provided a better understanding of the position of LNs than traditional 2D procedures, thus increasing the number of resected LNs.

For postoperative outcomes, the postoperative hospital stay and total number of complications in the 3D group were better than those of the non-3D group (27). However, Hu W et al. found that the postoperative hospital stay and total number of complications such as pneumonia, hemoptysis, arrhythmia, and pulmonary air leakage were not significantly different between the two groups (9). Postoperative complications are often caused by multiple factors, usually intraoperative conditions, postoperative patient care and primary underlying disease. A study with a larger sample is needed to further confirm and clarify these findings. For the postoperative drainage time, postoperative FEV1 and postoperative drainage volume, we found little difference between the two groups. However, Xu et al. reported that their 3D group had notably different postoperative drainage times compared with their 2D group (28). On the one hand, the difference between the two studies might caused by differences in the condition of the patients, for example, the basic physical condition of the patients and the patients' other underlying diseases, as well as differences in clinical nursing practices (29). It is worth mentioning that the proficiency of the surgeons who performed segmentectomy for lung cancer also may be partly responsible for the difference between the two studies. On the other hand, preoperative 3D lung simulation improved preoperative preparation, which therefore may have reduced the risks of difficulties and accidents during the operation (30), resulting in the 3D group having better postoperative drainage times.

There are still many shortcomings in our research. First, the sample size was too small to allow credible conclusions to be drawn, and the number of patients was generally <100 in the 3D group (31). Second, only one study was a randomized controlled trial, and the remaining studies were cohort studies of lower quality than the RCT. In the future, more randomized controlled trials and studies with larger sample sizes are needed. Third, none of these 8 studies reported survival data, which is an important clinical result. However, this situation is likely due to the development of preoperative 3D lung simulation in recent years, which limits the availability of longer-term survival data at present and demands the accumulation of time and efforts. Fourth, all studies and patients were from China, which may lead to racial bias in the results, which may not be applicable to other regions and populations. Last, the indicators monitored were not consistent among the studies. Some studies focused on intraoperative indicators, but other studies tended to analyze postoperative indicators. A broad and unified standard is necessary to standardize and evaluate the two surgical methods.

Overall, preoperative 3D lung simulation showed a beneficial improvement in perioperative outcomes and postoperative outcomes compared with non-3D procedures for segmentectomy with lung cancer. The top 5 common complications in the 3D group were arrhythmia, pulmonary air leakage, atrial fibrillation, pulmonary infection and pneumonia. Because of the above limitations, our results should be verified in large-sample randomized controlled trials. Preoperative 3D lung simulation improves surgical accuracy and safety and is worthy of clinical promotion.

The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author/s.

ZX and WZ had full access to all of the data in the manuscript and takes responsibility for the integrity of the data and the accuracy of the data analysis. ZX, JX, and WZ: drafting of the manuscript. ZX, BW, XZ, NF, YW, and WZ: critical revision of the manuscript for important intellectual content. ZX, BW, XZ, and YW: statistical analysis. ZX and WZ: supervision. All authors: concept, design, acquisition, analysis, or interpretation of data. All authors contributed to the article and approved the submitted version.

This study was supported by Natural Science Foundation of Jiangxi Province (Grant number: 20212BAB206050), Science and technology planning project of Health Commission of Jiangxi Province (Grant number: 202110045) and Science and technology planning project of Jiangxi Administration of traditional Chinese Medicine (Grant number: 2020B0108). The funding had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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