An update on three-dimensional computed tomography reconstruction and its applications to lung segmentectomy: a narrative review

Introduction

Lung cancer remains a leading cause of cancer-related mortality, with an estimated 226,650 new cases and 130,200 deaths projected in 2025. However, lung cancer incidence has decreased in both genders due to increased awareness of smoking cessation and high-quality screening (1). Surgical resection remains the gold standard for early-stage lung cancer, with lobectomy established as the standard approach since 1960 (2). However, recent studies have fueled debate over the optimal surgical strategy for small peripheral non-small cell lung cancer (NSCLC), with evidence increasingly supporting segmentectomy as a viable alternative to lobectomy (3). National Comprehensive Cancer Network (NCCN) guidelines version 3, 2025 state that sublobar resection, either segmentectomy (preferred) or wedge resection, is suitable for select patients: (I) those who are not candidates for lobectomy and (II) those with a peripheral nodule of 2 cm or less that possesses very low-risk features. Segmentectomy or wedge resection should aim for parenchymal resection margins that are either (I) 2 cm or more or (II) the size of the nodule or larger (4).

Segmentectomy could be more technically challenging than a lobectomy because the anatomy of the pulmonary segments is more complex, and variations of vessels and bronchi are common (5). Technology improvements, from video-assisted thoracoscopic surgery to robotic surgery, appear to be associated with an increasing number of segmentectomies being performed (6). Nevertheless, an important field of innovation in preoperative planning involves three-dimensional (3D) computed tomography (CT) reconstruction. Retrospective studies showed that this technique is reliable and could reveal the anatomy of the pulmonary vessel branches and identify anatomic variations (7-9). Several software for preoperative planning of lung segmentectomy also estimate the distance from the tumor to the intersegmental plane, which is important to achieve adequate oncologic negative margins. Furthermore, some authors suggest that this technology could significantly reduce the operative time and intraoperative blood loss, decrease the number of stapler reloads, and prevent postoperative air leakage in thoracoscopic segmentectomy compared to standard chest CT (10,11). While retrospective studies suggest several benefits from this technology, the evidence is not definitive. The objective of this review is to evaluate the current role of 3D CT reconstruction in preoperative planning for lung segmentectomy, focusing on its clinical outcomes, educational utility, and potential cost-effectiveness. We present this article in accordance with the Narrative Review reporting checklist (available at https://asj.amegroups.com/article/view/10.21037/asj-25-47/rc).

3D CT reconstruction

3D reconstruction is a process that converts standard two-dimensional (2D) imaging data, such as CT scans, into detailed 3D models, in this case, of pulmonary anatomy. This is achieved through segmentation (12), a technique that isolates structures like bronchi, pulmonary vessels, and lung parenchyma using specialized software. Various semi-automatic and fully automated algorithms enhance segmentation accuracy by differentiating between tissues based on density and contrast patterns. Commercial software such as Synapse 3D (Fujifilm), Materialise Mimics, and IntelliSpace Portal (Philips) offer advanced tools for creating high-resolution reconstructions, but they can be costly. Open-source alternatives like 3D Slicer and ITK-SNAP provide viable, cost-effective options for generating 3D models, though they often require manual refinement. Once reconstructed, these models can be viewed on-screen, printed using 3D printing technology, or integrated into virtual reality simulations for surgical planning and education. By providing a patient-specific visualization of anatomical structures, 3D lung reconstruction enhances preoperative planning, facilitates minimally invasive surgical approaches, and improves procedural outcomes.

Methods

A literature search was conducted on March 1st, 2025, using four electronic databases: PubMed, Embase, Cochrane Library, and Scopus. The search included terms such as “Lung Neoplasms”, “Segmental Resection”, “Tomography”, and “Three-Dimensional Imaging” with free-text terms including “lung segmentectomy”, “3D CT reconstruction”, “three-dimensional imaging”, and “minimally invasive thoracic surgery”. Filters were applied to limit results to studies involving human subjects, published in English, between January 1st, 2005, and January 31st, 2025, and focused on adult populations (18 years and older). Nine studies that addressed the use of 3D reconstruction in lung segmentectomy were included in this narrative review. Studies were excluded if they were non-English, case reports with fewer than five patients, animal studies, editorials, or unrelated to pulmonary surgery. However, as a narrative review, this work does not follow a formal systematic methodology, such as predefined MeSH terms, inclusion/exclusion criteria, or quality assessment tools. This may introduce selection bias and limit the reproducibility of our findings, which should be interpreted accordingly. One independent reviewer (S.F.) conducted the screening and interpretation of titles and abstracts. No additional considerations were noted during the selection process (Table 1).

Surgical outcomes of lung segmentectomy with 3D CT reconstruction assistance

Operative time

Multiple studies about 3D reconstruction during the performance of segmentectomy have shown significant advantages in terms of locating nodules and identifying the variations of vessels and bronchi (10,13). A study comparing 3D reconstruction in complex segmentectomy of the lower lung lobes versus routine perioperative imaging found that 3D reconstruction might reduce the operation time (11). Currently, there is no data specific to the upper lung lobes. However, a recent randomized controlled trial (RCT) performed by Chen et al. didn’t show any benefits of 3D reconstruction in relation to decreasing operative time (5).

Intraoperative blood loss

Bleeding after thoracic surgery is of clinical importance, with an incidence between 4.1% and 10.5% (14-16). Given the variability in pulmonary anatomy, preoperative knowledge of broncho-vascular structures could help prevent intraoperative bleeding complications and reduce the need for conversion. While some studies suggest that 3D lung reconstructions improve surgical precision and reduce intraoperative blood loss (10,13), others have found no significant difference in bleeding outcomes (5,11). This discrepancy highlights the ongoing debate regarding the impact of 3D reconstruction on intraoperative bleeding.

Conversion to thoracotomy

Studies suggest that detailed preoperative imaging, including 3D lung reconstructions, may help reduce conversion rates (10,17) by providing enhanced visualization of pulmonary vasculature and bronchial anatomy, thereby improving surgical precision. Some case series have reported a complete success of minimally invasive segmentectomy without any cases converted to open with the use of 3D reconstruction (11,13,18). However, while some research supports the role of 3D reconstruction in minimizing conversions, other studies have not found a significant difference, indicating that additional factors, such as surgeon experience and intraoperative decision-making, also play a crucial role (5).

Surgery education and 3D CT reconstruction assistance

3D reconstruction software is increasingly recognized as a valuable tool in surgical education, particularly in thoracic surgery. By transforming conventional 2D CT images into interactive 3D models, these technologies provide residents with a more intuitive understanding of pulmonary anatomy, anatomical variations, and spatial relationships. A study demonstrated that integrating 3D reconstruction into training programs enhances the ability of surgical trainees to interpret imaging, plan procedures, and anticipate intraoperative challenges. Notably, senior residents appear to derive greater benefits from 3D reconstruction compared to junior trainees, likely due to their more advanced anatomical knowledge and clinical experience (19). While 3D reconstruction has shown promise in improving surgical education, its effectiveness depends on the learner’s foundational understanding of radiologic interpretation. Further research is needed to assess the long-term impact of 3D reconstruction on surgical competency and patient outcomes.

Economic impact

3D reconstruction technology has emerged as a valuable component of preoperative planning, with potential benefits in reducing intraoperative and postoperative complications, as mentioned before. From a financial perspective, studies have explored the cost-effectiveness of this technology. In head and neck surgery, for example, 3D reconstruction has been associated with reduced operative times and shorter lengths of hospital stay, suggesting a favorable economic impact (20). However, the heterogeneity of study designs and outcomes limits the generalizability of these findings. In the field of thoracic surgery, evidence on cost-effectiveness remains limited. Further research is needed to assess the financial and clinical value of integrating 3D reconstruction into preoperative planning for lung resections.

Our experience

Until recently, preoperative planning for segmentectomy at our institution relied solely on the standard axial, sagittal, and coronal CT scan views. While this approach was often sufficient, it occasionally led to unexpected intraoperative findings that necessitated conversion from a planned segmentectomy to a lobectomy. Over the past few months, we have implemented advanced 3D reconstruction software into our planning process. This technology allows for the precise selection of the pulmonary artery branches to be divided, ensuring an adequate oncologic margin around the target lesion. The software generates a detailed 3D model of the intrapulmonary anatomy, enabling accurate identification of the corresponding arterial, venous, and bronchial structures (Figure 1). This enhanced visualization has greatly improved our ability to correlate preoperative planning with intraoperative anatomy, facilitating more precise and confident execution of segmentectomies. The software also estimates the distance from the tumor to the intersegmental plane, and it correlates reliably with intraoperative demarcation after administration of indocyanine green (ICG) (Figure 2). This tool allows us to decide ahead of time which pulmonary artery branches and segmental bronchi should be divided to obtain at least a 2 cm margin free of tumor circumferentially.

Figure 1 Visualization of segmental anatomy and intraoperative dissection during right upper lobectomy. (A) 3D reconstruction of the pulmonary vasculature and bronchial anatomy. (B) Intraoperative view during division of the right upper lobe. The red circles highlight the posterior ascending artery. 3D, three-dimensional.

Figure 2 Fluorescence imaging to assess perfusion after posterior ascending artery division. (A) 3D reconstruction of the pulmonary vasculature and bronchial anatomy. (B) Intraoperative ICG fluorescence imaging following division of the posterior ascending pulmonary artery. 3D, three-dimensional; ICG, indocyanine green.

This review has several limitations. As a narrative synthesis, it is susceptible to selection bias and does not have the methodological rigor of a systematic review or meta-analysis. The variability among existing studies, including surgical approaches, imaging software, and surgeon experience, restricts direct comparisons and limits the generalizability of the findings. Moreover, much of the available literature consists of retrospective analyses and single-center experiences. Although early data indicate potential benefits of 3D CT reconstruction in preoperative planning, intraoperative precision, and education, further prospective, high-quality studies are necessary to establish its true clinical utility, impact on long-term outcomes, and cost-effectiveness in thoracic surgery.

Conclusions

3D reconstruction has emerged as a promising tool in thoracic surgery, offering potential benefits for both clinical practice and surgical education. Enhancing preoperative planning and 3D reconstruction may lead to improved surgical outcomes and facilitate minimally invasive approaches, especially in complex segmentectomies. Beyond surgical outcomes, 3D reconstruction is increasingly important in education, helping trainees master pulmonary anatomy and procedural planning. Furthermore, its application in patient education could enhance preoperative discussions and shared decision-making. While 3D reconstruction presents significant promise, ongoing research is essential to fully define its advantages, optimize its implementation, and explore its expanding role in thoracic surgery.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the Narrative Review reporting checklist. Available at https://asj.amegroups.com/article/view/10.21037/asj-25-47/rc

Peer Review File: Available at https://asj.amegroups.com/article/view/10.21037/asj-25-47/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://asj.amegroups.com/article/view/10.21037/asj-25-47/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All clinical procedures described in this study were performed in accordance with the ethical standards of the institutional and/or national research committee(s) and with the Declaration of Helsinki and its subsequent amendments. Written informed consent was obtained from the patient for the publication of this article and accompanying images.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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