Intraoperative imaging and margin control in sublobar resection: a new dimension of surgical precision

In the era of lung cancer screening, the widespread detection of subcentimetric pulmonary nodules has profoundly reshaped thoracic surgical practice. The growing use of segmentectomy and wedge resection reflects a paradigm shift toward parenchyma-sparing surgery. Yet, this evolution comes with a renewed challenge: ensuring adequate surgical margins and oncological completeness.

As thoracic surgeons, we all share this concern daily. Based on our experience with anatomical segmentectomies and 3D preoperative planning at the Ambroise Paré Hartmann Hospital, I am convinced that surgical precision and oncologic safety are inseparable goals. Pathology remains the gold standard for assessing margins, but intraoperative tools capable of providing real-time feedback could become essential decision-making allies.

Kitazawa et al. propose an elegant and innovative solution: intraoperative computed tomography (CT) of resected sublobar specimens (1). In their study of 52 patients, CT-derived margin distances were compared with final pathological evaluation. CT slightly overestimated the margin (mean difference 1.2 mm), with broad limits of agreement (−7.2 to +9.6 mm). Discrepancies were more frequent in subsolid and deep lesions, yet the method proved both feasible and informative.

These findings are particularly relevant, as defining an “adequate” margin remains a matter of debate. Previous work has shown that a parenchymal margin ≥10 mm or a margin-to-tumor ratio ≥1 correlates with improved local control, especially in spread through air spaces (STAS)-negative tumors (2). However, securing such margins is not always achievable—particularly for deep, small, or multifocal lesions where anatomical and functional constraints, rather than purely technical margin control, limit resection extent.

Recent evidence reinforces the prognostic importance of margin adequacy, especially in wedge resections. Mohiuddin et al. demonstrated that a margin ≥15 mm reduced the risk of local recurrence by nearly half (3). El-Sherif et al. similarly found that patients with margins <1 cm had almost double the recurrence rate compared to those with ≥1 cm (4). Large-scale analyses such as that of Ajmani et al. further revealed that only “high-quality” wedge resections—defined by negative margins and adequate lymph node sampling—were associated with improved survival (5).

These findings are in line with a recent review on the evolving role of wedge resection in early-stage non-small cell lung cancer (NSCLC), which emphasized the critical influence of margin width, lymph node dissection, and intraoperative quality control on long-term oncological outcomes (6).

International recommendations mirror these findings. The National Comprehensive Cancer Network (NCCN) guidelines advocate for a parenchymal margin of at least 2 cm or a distance equal to the tumor diameter, whichever is greater (7). The International Association for the Study of Lung Cancer (IASLC) classification defines a “complete resection” (R0) as one with negative microscopic margins, systematic lymph node dissection, and absence of extracapsular nodal extension (8). When any criterion is missing, the resection is deemed “uncertain” [R(un)], a status consistently linked to poorer survival (9).

In this light, intraoperative CT may represent a pragmatic bridge between the surgeon’s need for real-time feedback and the pathologist’s definitive judgment. In centers without frozen section availability, CT could offer an immediate and standardized method to estimate margin adequacy. However, the implementation of intraoperative CT may raise organizational and logistical challenges, including operating room workflow constraints and limited accessibility, as such technology is not available in all centers. Yet, the accuracy of such measurements depends on proper specimen orientation, inflation, and standardized imaging protocols—elements that must be harmonized through multicenter validation.

These considerations align with other advances in intraoperative imaging. Kamimura et al. demonstrated strong correlations between ex-vivo CT and macroscopic pathology (10), while Ueda et al. confirmed the accuracy of intraoperative cone-beam CT for evaluating resection planes (11). Similarly, Sato et al. explored radiofrequency identification (RFID)-based localization to guide precise resection of small nodules (12). Collectively, these innovations reflect the same ambition: to integrate imaging directly into the surgical workflow and enhance oncologic control without compromising function.

In this context, advances in intraoperative imaging should be viewed as complementary strategies aimed at improving spatial understanding and margin control during sublobar resection, particularly when tactile feedback is limited.

Nevertheless, intraoperative CT must be regarded as an adjunct, not a replacement, for pathological evaluation. Frozen section remains invaluable where available, yet it is not universally accessible—especially in smaller or non-academic institutions. In this context, intraoperative CT could serve as a complementary tool, or even a telepathology interface. The possibility of transmitting digital CT images to remote pathologists for immediate interpretation opens new perspectives, particularly in regions lacking on-site pathology coverage.

The complexity of correlating imaging with histopathology should not be underestimated. Differences in inflation, tissue deformation, and specimen handling can alter measurements. Moreover, in the presence of STAS, microscopic tumor cells can extend several millimeters beyond the visible tumor margin. Studies by Masai et al. and Shiono et al. have shown that both STAS and margin distance <1 cm independently predict recurrence (13,14). This underscores the inherent limitations of imaging alone and the continued necessity of histologic control when feasible.

Beyond parenchymal margins, completeness of resection also depends on lymph node assessment. Several studies have demonstrated that wedge resections frequently omit nodal dissection, resulting in pathological understaging and inferior survival outcomes. The CALGB 140503 trial highlighted the importance of intraoperative frozen section and conversion when margins or nodal status were inadequate (15). In our practice, systematic sampling of hilar and mediastinal nodes is a non-negotiable component of oncologic surgery, even in sublobar resections.

From a broader perspective, intraoperative CT could serve as a unifying platform for imaging, pathology, and surgical expertise. Its digital nature facilitates integration with artificial intelligence (AI) algorithms capable of automatically segmenting the tumor and mapping margin distances. Future applications may include automated detection of insufficient margins or AI-assisted prediction of STAS likelihood based on texture analysis.

Radiomics has already shown potential in predicting tumor aggressiveness and molecular status from preoperative CT. The fusion of such predictive imaging with intraoperative CT would close the loop between planning and real-time verification, aligning surgical action with tumor biology. This direction resonates deeply with the principles of “precision surgery”—a concept that we, as thoracic surgeons, must now embrace alongside precision oncology.

Finally, intraoperative CT may also hold educational value. For surgeons in training, visualizing resected specimens with CT can provide immediate feedback on resection planes and margin adequacy, accelerating the learning curve for sublobar techniques. In my experience, this combination of technology and anatomical understanding fosters both safety and confidence in performing complex segmentectomies.

In conclusion, Kitazawa et al. (1) provide convincing evidence that intraoperative CT of resected sublobar specimens is both feasible and clinically meaningful. When interpreted in light of existing literature on margin adequacy, lymph node evaluation, and STAS, their study points toward a future where intraoperative imaging becomes integral to surgical quality assurance.

As one of the authors of the recent review on wedge resection, I remain convinced that improving intraoperative margin assessment—through imaging, telepathology, or AI—will be central to safely expanding the indications for parenchyma-sparing surgery. Intraoperative CT represents not only a promising adjunct but a mindset of precision that will guide the next generation of thoracic surgeons.

Take-home message: intraoperative CT should complement, not replace, pathology. By providing rapid and objective margin evaluation, it may help surgeons ensure oncologic safety while preserving lung function—two imperatives that define modern thoracic surgery.

Acknowledgments

None.

Footnote

Provenance and Peer Review: This article was commissioned by the editorial office, Current Challenges in Thoracic Surgery. The article has undergone external peer review.

Peer Review File: Available at https://ccts.amegroups.com/article/view/10.21037/ccts-2025-1-58/prf

Funding: None.

Conflicts of Interest: The author has completed the ICMJE uniform disclosure form (available at https://ccts.amegroups.com/article/view/10.21037/ccts-2025-1-58/coif). The author has no conflicts of interest to declare.

Ethical Statement: The author is 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.

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/.

References

1. Kitazawa S, Bernards N, Sata Y, et al. Intraoperative Surgical Margin Assessment of Sublobar Lung Resection Specimens Using Computed Tomography. Ann Thorac Surg 2025; [Crossref]
2. Nagano M, Sato M. Impact of surgical margin after sublobar resection of lung cancer: a narrative review. J Thorac Dis 2023;15:5750-9. [Crossref] [PubMed]
3. Mohiuddin K, Haneuse S, Sofer T, et al. Relationship between margin distance and local recurrence among patients undergoing wedge resection for small (≤2 cm) non-small cell lung cancer. J Thorac Cardiovasc Surg 2014;147:1169-75; discussion 1175-7. [Crossref] [PubMed]
4. El-Sherif A, Fernando HC, Santos R, et al. Margin and local recurrence after sublobar resection of non-small cell lung cancer. Ann Surg Oncol 2007;14:2400-5. [Crossref] [PubMed]
5. Ajmani GS, Wang CH, Kim KW, et al. Surgical quality of wedge resection affects overall survival in patients with early stage non-small cell lung cancer. J Thorac Cardiovasc Surg 2018;156:380-391.e2. [Crossref] [PubMed]
6. Ceccarelli I, Durand M, Seguin-Givelet A. The evolving role of wedge resection in early-stage non-small cell lung cancer: a literature review. Transl Lung Cancer Res 2025;14:4078-94. [Crossref] [PubMed]
7. National Comprehensive Cancer Network. Non-Small Cell Lung Cancer (Version 3.2020). Available online: https://www2.trikobe.org/nccn/guideline/lung/english/non_small.pdf
8. Rami-Porta R, Wittekind C, Goldstraw P, et al. Complete resection in lung cancer surgery: proposed definition. Lung Cancer 2005;49:25-33. [Crossref] [PubMed]
9. Gagliasso M, Migliaretti G, Ardissone F. Assessing the prognostic impact of the International Association for the Study of Lung Cancer proposed definitions of complete, uncertain, and incomplete resection in non-small cell lung cancer surgery. Lung Cancer 2017;111:124-30. [Crossref] [PubMed]
10. Kamimura G, Ueda K, Suzuki S, et al. Intraoperative computed tomography of a resected lung inflated with air to verify safety surgical margin. Quant Imaging Med Surg 2022;12:1281-9. [Crossref] [PubMed]
11. Ueda K, Aoki M, Kamimura G, et al. Intraoperative cone-beam computed tomography to secure the surgical margin in pulmonary wedge resection for indistinct intrapulmonary lesions. JTCVS Tech 2022;13:219-28. [Crossref] [PubMed]
12. Sato T, Yutaka Y, Nakamura T, et al. First clinical application of radiofrequency identification (RFID) marking system-Precise localization of a small lung nodule. JTCVS Tech 2020;4:301-4. [Crossref] [PubMed]
13. Masai K, Sakurai H, Sukeda A, et al. Prognostic Impact of Margin Distance and Tumor Spread Through Air Spaces in Limited Resection for Primary Lung Cancer. J Thorac Oncol 2017;12:1788-97. [Crossref] [PubMed]
14. Shiono S, Endo M, Suzuki K, et al. Spread through air spaces affects survival and recurrence of patients with clinical stage IA non-small cell lung cancer after wedge resection. J Thorac Dis 2020;12:2247-60. [Crossref] [PubMed]
15. Altorki N, Wang X, Damman B, et al. Lobectomy, segmentectomy, or wedge resection for peripheral clinical T1aN0 non-small cell lung cancer: A post hoc analysis of CALGB 140503 (Alliance). J Thorac Cardiovasc Surg 2024;167:338-347.e1. [Crossref] [PubMed]