Cone beam computed tomography for navigational bronchoscopy
Review Article

Cone beam computed tomography for navigational bronchoscopy

Aniek R. C. Bruinen, Roel L. J. Verhoeven, Erik H. F. M. van der Heijden

Department of Pulmonary Medicine, Radboud University Medical Center, Nijmegen, The Netherlands

Contributions: (I) Conception and design: All authors; (II) Administrative support: All authors; (III) Provision of study materials or patients: None; (IV) Collection and assembly of data: All authors; (V) Data analysis and interpretation: None; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.

Correspondence to: Prof. dr. Erik H. F. M. van der Heijden, MD, PhD. Professor of Interventional Pulmonology, Department of Pulmonary Medicine, Radboud University Medical Center, PO Box 9101, 6500 HB, Nijmegen, The Netherlands. Email: Erik.vanderHeijden@radboudumc.nl.

Abstract: Cone beam computed tomography (CBCT) is a revolutionary technology that is increasingly being used in interventional pulmonology for the diagnosis and treatment of pulmonary lesions, specifically small peripheral pulmonary lesions (PPLs). CBCT systems can provide detailed three-dimensional (3D) imaging, allowing for 3D lesion as well as instrument positioning information. Currently, only the fixed CBCT systems have been studied as a tool to not only provide 3D scanning information but also allow overlaying information on live fluoroscopy by a feature called augmented fluoroscopy. Using this combination of scanning and augmentation, CBCT can be used as a modality that provides both imaging and guidance in navigation to target lesions in navigation bronchoscopy. Studies have shown that the addition of CBCT to navigation bronchoscopy using other primary navigation guidance techniques can further increase the diagnostic yield of these technologies. The combination of CBCT with robotic assisted bronchoscopy (RAB) is one of the most promising combinations, allowing pulmonologists to navigate complex airways with distal tip control along with detailed 3D positioning information to obtain biopsies and correct for computed tomography (CT)-to-body divergence. It is important for physicians to be properly trained in the use of CBCT, in order to obtain a high diagnostic yield with a low complication rate and to limit radiation exposure to the patient and employees. While further research is needed to fully examine its potential and address challenges, CBCT will likely become the standard of care technology for a wide range of diagnostic and therapeutic procedures in interventional pulmonology. More research needs to be done on the added value and need of CBCT in combination with advanced procedural guidance techniques such as RAB.

Keywords: Cone beam computed tomography (CBCT); peripheral pulmonary lesions (PPLs); navigation bronchoscopy; lung cancer; robotic assisted bronchoscopy (RAB)


Submitted Oct 28, 2024. Accepted for publication Jun 26, 2025. Published online Jul 15, 2025.

doi: 10.21037/jtd-24-1828


Introduction

The continuous development of minimally invasive instruments and technologies has created new possibilities in pulmonology. The accuracy of diagnostic and therapeutic procedures in interventional pulmonology has been significantly increased by advanced imaging modalities and technological innovations. While interventional pulmonologists routinely use endoscopic video imaging to navigate central airways during bronchoscopy, accessing small peripheral pulmonary lesion (PPLs) for diagnosis and treatment necessitates supplementary guidance technologies and/or advanced imaging techniques. PPLs often present a diagnostic challenge, especially small (<20 mm) lesions. The size of the lesions is the biggest factor for the diagnostic yield (1). Potentially, nodules >20 mm allow an up to 20% higher diagnostic yield (2). Kops et al. (2023) also conducted an explorative subgroup analysis in their meta-analysis and found that there is indeed a significantly higher diagnostic yield in larger nodules and nodules with a bronchus sign (3). Successfully navigating beyond the central airways to access, localize, diagnose, and/or perform interventions in the lung periphery requires a detailed understanding of the required bronchial anatomy to assess the correct pathway. The 3D relationship between the target area, biopsy/treatment instruments and surrounding tissue structures is crucial. PPLs, particularly those at the end of or beyond existing bronchi, demand detailed and precise 3D information for accurate instrument positioning. Historically, 2D X-ray fluoroscopy was the only available—and therefore preferred—adjunct imaging technology. Immediately following the development of flexible bronchoscopes, Tsuboi already showed in 1967 that instruments could be advanced beyond the conventional bronchoscopic view under 2D X-ray fluoroscopy guidance, facilitating diagnostic biopsies of suspicious peripheral pulmonary lesions or segments with interstitial pathology (4). However, 2D X-ray fluoroscopy logically has a limited resolution for guiding bronchoscopic interventions. Stretching out instruments beyond the working channel of the bronchoscope and its video-scopic imaging capabilities means 3D positioning knowledge is required if meticulous positioning is the goal.

Several new advanced technologies, such as electromagnetic tracking, virtual endoscopic guidance and shape-sensing technologies have emerged to provide intraprocedural guidance for targeting these PPLs. These technologies, which often rely on preprocedural diagnostic CT scans to allow intra-procedural guidance, have demonstrated substantial improvements in diagnostic performance [i.e., (5-7)]. Yet, as multiple studies have reported, relying on pre-procedural imaging might cause CT-to-body-divergence (6-8). CT-to-body-divergence indicates the difference between intra-procedural lesion positioning and that hypothesized based on pre-procedural imaging.

In this review, we focus on a technological innovation in Interventional Pulmonology, which might help remove this divergence through allowing intra-operative imaging, cone beam CT.

We will review its performance as a stand-alone means to guide navigation bronchoscopy, as well as review its performance in small (<20 mm) lesions when combined with robotic assisted bronchoscopy (RAB) systems.


CBCT is an imaging technique that creates 3D representations of anatomical structures and is helpful for the proceduralist to guide to PPLs using intra-procedural positioning information. Currently, there are several CBCT imaging systems available. There are fixed [floor and ceiling-mounted (Figure 1)] and mobile CBCT systems.

Figure 1 Examples of fixed CBCT systems. CBCT, cone beam computed tomography.

The current advantage of fixed CBCT systems is that the majority of these systems have the ability of augmented fluoroscopy (AF, Figure 2). The fixed systems can generally be considered the top-of-the-line systems feature wise and have a generous amount of features that allow minimization of radiation exposure, ease-of-use and optimal image quality. AF allows visualization of segmented and/or marked lesions and points of interest as intra-procedurally obtained in the 3D CBCT scans onto live 2D fluoroscopy as overlays. This technique is useful for marking PPLs as well as overlaying a targeted navigation routing.

Figure 2 Overlay augmented fluoroscopy while using the shape-sensing robotic bronchoscope for diagnostic sampling of a right upper lobe nodule (blue, CBCT segmented nodule; purple dot, end of bronchoscope during breath hold). Often, additional dots or ‘bread crumbs’ can be positioned at landmarks along the navigation trajectory to help guide the endoscopist. CBCT, cone beam computed tomography.

Advanced navigation without any other secondary form of technological directional support requires using a CBCT system with 3D imaging and preferably such AF features. In one such approach, a regular therapeutic bronchoscope and a precurved extended working channel (Medtronic EWC Minneapolis USA, Figure 3), or i.e., an ultrathin bronchoscope can be used to navigate through the tortuous bronchial anatomy under AF guidance. After initial introduction of the EWC or ultrathin bronchoscope in the subsegmental bronchi based upon the pre-procedurally hypothesized correct segment, subsequent scanning can be performed to allow 3D segmentation of the lesion and pathway on a work-station situated outside the room. The segmented lesion and pathway are subsequently overlaid on fluoroscopy with AF in every fluoroscopy angle and can be used to navigate to the lesion. An ultrathin bronchoscope can be actively angulated, while a precurved catheter is torsionally stiff and can only be rotated to align the curvature with the proposed pathway and perform correct turn-by-turn navigation based on the AF suggested pathway. The detailed step-by-step clinical workflow of a CBCT-AF based EWC navigation bronchoscopy is published by Beyaz et al. with illustrative images and videos (9).

Figure 3 A combination of a regular therapeutic bronchoscope with precurved extended working channel fixated on the bronchoscope working channel (Edge Extended working channel, Medtronic, Minneapolis, USA). The precurved catheter is available in different curvatures (180 and 210 degree) which can be selected based on the needed angulation. Images by Medtronic, Minneapolis, USA.

Fixed CBCT systems have been predominantly available to surgical, cardial and radiological specialties over the past decade. Recent technological developments have, however, made CBCT imaging available to the wider public by transforming the conventional mobile C-arm into a 3D CBCT capable system. At a lower cost and requiring fewer operating theatre adjustments, these mobile C-arm systems capable of 3D imaging are increasingly used in the intervential pulmonology (IP) community and beyond. Unlike fixed CBCT systems that are limited to a single room, their mobility allows that they can easily be used at different locations (including the endoscopy suite). Until recently, no mobile CBCT system was commercially available to facilitate AF, but since last year the OEC 3D of GE HealthCare is available, and capable of supporting AF. However, since mobile CBCT systems are meant as cost-effective alternative to fixed and not ideated as replacement, currently available versions lack some advanced features, such as the ability to adjust detector distance which can limit image quality and increase radiation dose during fluoroscopy. Mobile CBCT systems furthermore also have a limited power supply, which results in longer scanning times in comparison with fixed CBCT systems. Nevertheless, these limitations are likely to be improved by future technological advancements and upgrades. The mobile system can be used to make 3D scans and confirm tools are in the correct location and support navigation tools like robotic bronchoscopy systems, as discussed later. The flexibility and lower cost of mobile CBCT systems make them an interesting option for clinicians, particularly when used with other navigation technologies like electromagnetic or robotic bronchoscopy systems. The ION® system (Intuitive, Sunnyvale, USA), demonstrates this integration by combining its shape-sensing robotic system with a Siemens Cios Spin mobile CBCT system® (Forchheim, Germany). It enables adjustments to navigation planning based on the 3D information obtained from the CBCT scan. Furthermore, the OEC 3D mobile CBCT system (GE HealthCare, Chicago, USA) has recently been similarly enhanced with an integration that enables the automatic transfer of CBCT images upon reconstruction to the ION® system, like the Siemens Cios Spin system, thereby facilitating real-time updating of target locations for catheter adjustments during the procedure.


Evidence and diagnostic yield in CBCT-guided procedures

Studies have repeatedly highlighted the value of CBCT in enhancing the diagnostic yield of PPLs and especially in small (<20 mm) lesions with normally, as previously mentioned, with a normally lower diagnostic yield in comparison with larger lesions. A meta-analysis by Kops et al. indicated that newer techniques, such as CBCT, robotic bronchoscopy, and tomosynthesis guided electromagnetic navigation (EMN), show a higher diagnostic yield compared to older technologies, such as virtual bronchoscopy and EMN (3). However, Nadig et al. showed no significant difference in the diagnostic yield of the different technologies (2) (Table 1). In current clinical practice, it appears that the target nodules median size is decreasing, which may be influenced by the growing use of newer techniques and concurrent adjustment of inclusion criteria.

Table 1

Overview of the DY of navigation techniques, using the intermediate definition (3) and strict definition (2)

Navigation technique Summary DY (%) [number of studies (arms)/nodules] Subgroup analysis DY (%) at follow-up, nodule <20 mm (number of studies/nodules)
Kops et al. (3) Nadig et al. (2) Kops et al. (3)
EMN 70.3 (46/5,669) 74 (24/1,952) 82.1 (3/482)
Virtual bronchoscopy 69.4 (39/3,628) 72.4 (4/293) 66.7 (11/1,386)
Virtual bronchoscopy + rEBUS NA 76.4 (13/1,048)
RAB 76.5 (6/558) 77.6 (6/483) 81.8 (1/159)
CBCT 78.2 (5/371) NA 74.9 (6/439)
CBCT multimodality 77.4 (10/456) NA

CBCT, cone beam computed tomography; DY, diagnostic yield; EMN, electromagnetic navigation; NA, not applicable; RAB, robotic assisted bronchoscopy; rEBUS, radial endobronchial ultrasound.

Various other studies showed that incorporating CBCT into bronchoscopy procedures significantly increases diagnostic yield (Table 2).

Table 2

Overview of studies on the diagnostic yield of navigation bronchoscopy procedure with and without CBCT and the use of AF

Author Year Procedure Without CBCT With CBCT
Casal et al. (10) 2018 Ultrathin bronchoscopy 50% 70%
Verhoeven et al. (11) 2021 EMN 52.2% 87.5%
Pritchett et al. (12) 2018 EMN NA 83.7%
Kheir et al. (13) 2021 EMN 51.6% 74.2%
Yu et al. (14) 2021 rEBUS 52.8% 75.5%
Lin et al. (15) 2021 rEBUS 86.8% 96.5%

AF, augmented fluoroscopy; CBCT, cone beam computed tomography; EMN, electromagnetic navigation; NA, not applicable; rEBUS, radial endobronchial ultrasound.

As indicated by the results demonstrated in Table 2, several studies have demonstrated that using CBCT leads to a higher diagnostic yield. The capability of CBCT to provide precise 3D information about tool location relative to lesions is valuable, especially for smaller lesions (<20 mm) and when pre- or intraprocedural imaging indicates a required transparenchymal pathway due to the absence of an endobronchial route. Intra-procedural 3D detailed imaging allows for full correction of CT-to-body-divergence. It gives the opportunity to confirm tool in nodule or to make subtle catheter repositions to obtain a better position to gain samples of the lesion. Furthermore, beyond the procedure, it may give more assurance to the operator and multi-disciplinary team discussions, such as additional confidence when tool in lesion has been confirmed but no malignancy can be found in final pathology outcome.


RAB platforms can be used with CBCT to improve the diagnosis of PPLs. RAB systems use a highly maneuverable robotic catheter with an articulating tip and endoscopic vision, which together is supposed to offer greater control and stability as well as visibility during navigation and biopsy compared to currently available alternatives. This enhanced control, when coupled with real-time CBCT guidance, allows pulmonologists to navigate the robotic catheter through complex bronchial pathways to reach the target lesion while minimizing trauma to the surrounding lung tissues. Especially the combination with CBCT allows sampling of lesions that are beyond peripheral airways and reachable only trans-parenchymal.

There are three main RAB systems currently commercially available (Figure 4). The Ion Endoluminal System by Intuitive uses shape-sensing technology and Monarch from Johnson & Johnson is based on EMN. Both can be adjusted based upon CBCT information. Finally, the Galaxy from Noah uses EMN with integration of C-arm tomosynthesis instead of CBCT. Figure 5 displays an example room setup of CBCT in combination with RAB.

Figure 4 Examples of RAB systems. RAB, robotic assisted bronchoscopy.
Figure 5 Room setup example of CBCT + RAB for ceiling mounted CBCT or mobile CBCT and a photo of a room setup of CBCT + RAB (ION Endoluminal System, Intuitive) for floor mounted CBCT (Siemens Artis Pheno - Forcheim, Germany). CBCT, cone beam computed tomography; RAB, robotic assisted bronchoscopy; rEBUS, radial endobronchial ultrasound.

Recent and ongoing studies about combining RAB with CBCT showed improved diagnostic performance compared to RAB alone. The (preliminary) results of these studies are summarized in Table 3. Pyarali et al. (2024) recently synthesized the available published literature in a meta-analysis of 23 studies, including 1,409 patients and 1,541 nodules (28). The addition of RAB to CBCT-guided procedures resulted in shorter procedure durations (65 vs. 110 minutes, P<0.025) and reduced radiation exposure (median dose area product 5,114 vs. 8,755 µGy·m2, P<0.0001) (24) compared to CBCT guidance alone, without compromising diagnostic yield (pooled 81.9%, 12 studies included) or increasing complications (pooled incidence pneumothoraces 0.60%, major bleeding <0.01%) (28). The key factors contributing to improved efficiency of the combined approach are likely the robotic platform’s stability, maneuverability, and additional mental support owing to the integration of multiple inputs. RAB provides visual cues to help determine the catheter’s position to critical structures like the pleura and the 3D imaging spin provides more spatial information about the catheter, airway and nodule. This allows the physician to fine-tune the catheter’s position using the RAB system and gives the possibility to confirm that the tool is in the lesion. However, using the robotic platform for navigation is still subject to CT-to-body divergence. Using mobile 3D imaging combined with shape-sensing RAB (ssRAB) gives the possibility to overcome CT-to-body divergence. This is also concluded by Reisenauer et al. (2022) and Bashour et al. (2024) (19,25).

Table 3

Overview of studies on CBCT supported robotic assisted bronchoscopy

Author Year Patients, n Nodules, n Mean size, mm Prevalence cancer (%) RAB system Fixed/mobile/tomo DY (%)/accuracy DY definition
Benn (16) 2021 52 59 21.9 64 ssRAB (I) Fixed 86 InterMed
Styrvoky (17) 2022 200 209 (solid only) 22.6 64 ssRAB Fixed 91.4 InterMed
Abia-Trujillo (18) 2024 105 117 (66% solid) 12.3 ssRAB Mobile 83.8 InterMed
Reisenauer (19) 2022 30 30 17.5 ssRAB Mobile 93.3 InterMed
Chambers (20) 2023 75 79 20 ssRAB Mobile (O) 77 InterMed
Cumbo-Nacheli (21) 2022 20 20 22 EMN (M) NR 75 InterMed
Saghaie (22) 2024 18 19 (90% solid) 20 78 EMN-TilT (G) Tomo 89.5 Strict
Bruinen (prelim) (23) 2024 95 133 11.8 ssRAB Fixed 85 Strict
Shaller (24) 2024 100 100 16 EMN (M) Fixed 90 InterMed
Bashour (25) 2024 67 67 17 78 ssRAB Mobile 86.6 Strict
Kalchiem-Dekel (26) 2024 196 256 21.5 ssRAB Mobile 79.7 Strict
Abdelghani (27) 2024 111 (78% solid) 12 64 ssRAB Fixed 89.2 Strict

CBCT, cone beam computed tomography; DY, diagnostic yield; EMN, electromagnetic navigation; NR, not reported; RAB, robotic assisted bronchoscopy; rEBUS, radial endobronchial ultrasound; ssRAB, shape-sensing robotic assisted bronchoscopy.


Optimizing ventilation is vital to prevent atelectasis, potentially obscuring the targeted lesion and introducing intra-procedural CT-to-body divergence. This is especially relevant for obese patients and those with lesions in the posterior lung lobes. There are two key ventilation strategies recommended. Firstly, the lung nodule ventilation protocol. This strategy aims to maintain lung inflation during CBCT acquisition (29). Secondly, the ventilation strategy for prevention of atelectasis, this approach underscores the significance of tailored ventilation protocols to minimize atelectasis (30).

Learning curve—the use of RAB with CBCT to diagnose and treat pulmonary nodules may become more common in the future. Because of its ease of use it could potentially have a shorter learning curve in comparison with CBCT navigation bronchoscopy. Xie et al. (2022) showed that for navigation and total procedure time as well as diagnostic yield competency in inexperienced navigation bronchoscopy endoscopists with the Ion endoluminal system, was obtained after approximately 18 to 20 cases (31). Recently, Bott et al. (2024) show a threshold of 25 cases (32). A study on CBCT found, after a medium of 105 procedures, an acceptable diagnostic failure rate, with a high variability ranging from 40 to more than 300 cases (33). Future transbronchial treatments will likely involve both robotic control and 3D imaging (34,35).


Scattering objects

To enhance image quality during CBCT scans, it’s crucial to minimize objects within the radiation field. Even if these objects aren’t directly visible in the resulting images, they can scatter photons and negatively impact image quality. This is particularly important because CBCT utilizes a cone-shaped beam, making it susceptible to scattering artifacts.


Radiation safety

Training and awareness

As Wijma et al. show and summarize, radiation safety in navigation bronchoscopy varies significantly throughout studies and could potentially be related to awareness and training (36). Verhoeven et al. corroborate these findings, showing that they could reduce radiation exposure while increasing the amount of fluoroscopy time and CBCT’s made (37). It is therefore important that measures are taken to limit exposure, create continuous awareness as well as to train future physicians in adequately and effectively using radiation according to the as low as reasonably achievable (ALARA) principle.

Dose examples

As Wijma et al. summarize and exemplify, navigation bronchoscopy procedures guided by X-ray imaging reported dose area products varied between 9.78 and 77.78 Gy·cm2 in CBCT-guided diagnostic navigation bronchoscopies, with no significant difference observed between fixed and mobile CBCT systems (36). The median effective dose across various studies was 5.5 mSv, which is comparable to a diagnostic chest CT scan. Combined, it can be concluded that CBCT-based navigation bronchoscopy is a safe procedure in terms of radiation exposure.


Discussion

CBCT based navigation bronchoscopy is a very sensitive, safe and accurate approach to diagnose small (less than 20 mm) peripheral pulmonary nodules. Using this technology without any robotic assistance, a diagnostic yield of approximately 80% can be achieved. Several studies that have utilized CBCT in combination with RAB report yields of 85% or higher might be obtained (16-19,23,25-27). In this review a comprehensive overview of the application of CBCT in navigation bronchoscopy is given. A primary limitation is the inclusion of studies with preliminary results in the review and relatively small sample sizes. Additionally, the studies on RAB combined with CBCT predominantly included one of the RAB systems (ssRAB), as reports on other platforms are less widely available.

Currently, there are several CBCT imaging techniques available, each with advantages and limitations. Fixed systems are stable and offer high image quality and AF. Mobile CBCT systems are ideal for flexibility and mobility and are less expensive. Until very recently, the biggest limitation of mobile systems was the lack of AF. Whereas the first system supporting AF has now become available, it is to be expected that more mobile CBCT systems will follow. Future directions and implications of CBCT for interventional pulmonology are of particular interest for local therapies. All treatments need very precise imaging that CBCT may offer. It has a potential for guiding therapeutic interventions, such as tumor ablation, stent placement and bronchoscopic lung volume reduction procedures. Its ability for precise 3D imaging could enhance the accuracy and safety of these interventions, potentially expanding the scope of what is achievable in interventional pulmonology and improving patient outcomes. The differentiation between the need for a fixed or mobile CBCT system may potentially depend on the center’s goal of local therapy and the future imaging quality of these systems. Whereas in a diagnostic arena it is agreeable that tool in lesion confirmation suffice, therapy might require the highest quality of imaging as currently provided by fixed systems to introduce and validate novel techniques. Consequently, depending on the specific requirements, a decision can be made to opt for either a mobile or a fixed CBCT system.

There is a need for continued research to fully understand the long-term benefits, cost-effectiveness of combining technologies and optimal applications of CBCT-guided navigation bronchoscopy. Continuous technological advancements, particularly in the development of mobile CBCT systems with enhanced capabilities and more sophisticated RAB platforms, give the potential for further refining the precision, safety, and (cost-)effectiveness of a broad range of interventional pulmonology procedures.


Conclusions

With the upcoming global implementation of screening, the need for lung cancer to be diagnosed more frequently and earlier mostly with PPLs, will increase. These PPL often present a diagnostic challenge. CBCT is a revolutionary technology in interventional pulmonology, and combined with RAB might further improve diagnostic outcomes. It is a useful tool for diagnosing and treating pulmonary diseases, such as PPL, due to its capacity to provide detailed 3D imaging and compensate for CT-to-body-divergence, which previous navigation guidance technologies were unable to. By providing enhanced visualization of complex anatomy, CBCT allows more accurate navigation to the target site.

The combination of CBCT with the new technology of RAB is promising for PPLs, allowing pulmonologists to navigate complex airways with greater control and stability. Due to the active steerable tip, precise repositioning is made possible under CBCT guidance.

Although further research is needed to fully explore its potential and address ongoing challenges, CBCT will probably become the standard of care for a wide range of diagnostic and therapeutic procedures in interventional pulmonology. More research needs to be done on combining CBCT with technologies such as RAB; its learning curve, cost-effectiveness as well as performance.


Acknowledgments

None.


Footnote

Provenance and Peer Review: This article was commissioned by the Guest Editor (Fayez Kheir) for the series “Advances in Interventional Pulmonary” published in Journal of Thoracic Disease. The article has undergone external peer review.

Peer Review File: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-24-1828/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-24-1828/coif). The special series “Advances in Interventional Pulmonary” was commissioned by the editorial office without any funding or sponsorship. R.L.J.V. received discloses institutional and departmental research contracts with Pentax medical, AstraZeneca, Johnson & Johnson, Philips, Intuitive, Innovative Health Initiative (EU fund), KWF (national cancer fund), as well as consulting fees from Intuitive, Johnson & Johnson, NLC paid to the institution, travel support from Intuitive and Johnson & Johnson, equipment gifts from Philips Medical, and a current board membership at the Dutch society for Technical Physicians (NVvTG, unpaid). E.H.F.M.v.d.H. received discloses institutional research grants from Pentax medical, AstraZeneca, Johnson & Johnson, Philips, Intuitive, Innovative Health Initiative (EU fund), KWF (national cancer fund), as well as consulting fees from Intuitive, Johnson & Johnson and NLC paid to the institution, travel support from Intuitive and Johnson & Johnson; speaker fees paid to institution by Janssen-Cilag, Pentax, Philips, Astra Zeneca, Intuitive, Siemens and Ethicon; equipment gifts from Philips Medical and equipment loans from Pentax Medical and Intuitive, and a current executive board membership at the European Association for Bronchology and Interventional Pulmonology (unpaid). The authors have no other conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work, ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All procedures performed in this study were 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 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/.


References

  1. Baaklini WA, Reinoso MA, Gorin AB, et al. Diagnostic yield of fiberoptic bronchoscopy in evaluating solitary pulmonary nodules. Chest 2000;117:1049-54. [Crossref] [PubMed]
  2. Nadig TR, Thomas N, Nietert PJ, et al. Guided Bronchoscopy for the Evaluation of Pulmonary Lesions: An Updated Meta-analysis. Chest 2023;163:1589-98. [Crossref] [PubMed]
  3. Kops SEP, Heus P, Korevaar DA, et al. Diagnostic yield and safety of navigation bronchoscopy: A systematic review and meta-analysis. Lung Cancer 2023;180:107196. [Crossref] [PubMed]
  4. Tsuboi E, Ikeda S, Tajima M, et al. Transbronchial biopsy smear for diagnosis of peripheral pulmonary carcinomas. Cancer 1967;20:687-98. [Crossref] [PubMed]
  5. Abdelghani R, Omballi M, Abia-Trujillo D, et al. Imaging modalities during navigational bronchoscopy. Expert Rev Respir Med 2024;18:175-88. [Crossref] [PubMed]
  6. Pritchett MA, Bhadra K, Calcutt M, et al. Virtual or reality: divergence between preprocedural computed tomography scans and lung anatomy during guided bronchoscopy. J Thorac Dis 2020;12:1595-611. [Crossref] [PubMed]
  7. Dunn BK, Blaj M, Stahl J, et al. Evaluation of Electromagnetic Navigational Bronchoscopy Using Tomosynthesis-Assisted Visualization, Intraprocedural Positional Correction and Continuous Guidance for Evaluation of Peripheral Pulmonary Nodules. J Bronchology Interv Pulmonol 2023;30:16-23. [Crossref] [PubMed]
  8. Aboudara M, Roller L, Rickman O, et al. Improved diagnostic yield for lung nodules with digital tomosynthesis-corrected navigational bronchoscopy: Initial experience with a novel adjunct. Respirology 2020;25:206-13. [Crossref] [PubMed]
  9. Beyaz F, Verhoeven RLJ, Hoogerwerf N, et al. Cone Beam Computed Tomography-Guided Navigation Bronchoscopy with Augmented Fluoroscopy for the Diagnosis of Peripheral Pulmonary Nodules: A Step-by-Step Guide. Respiration 2025;104:216-28. [Crossref] [PubMed]
  10. Casal RF, Sarkiss M, Jones AK, et al. Cone beam computed tomography-guided thin/ultrathin bronchoscopy for diagnosis of peripheral lung nodules: a prospective pilot study. J Thorac Dis 2018;10:6950-9. [Crossref] [PubMed]
  11. Verhoeven RLJ, Fütterer JJ, Hoefsloot W, et al. Cone-Beam CT Image Guidance With and Without Electromagnetic Navigation Bronchoscopy for Biopsy of Peripheral Pulmonary Lesions. J Bronchology Interv Pulmonol 2021;28:60-9. [Crossref] [PubMed]
  12. Pritchett MA, Schampaert S, de Groot JAH, et al. Cone-Beam CT With Augmented Fluoroscopy Combined With Electromagnetic Navigation Bronchoscopy for Biopsy of Pulmonary Nodules. J Bronchology Interv Pulmonol 2018;25:274-82. [Crossref] [PubMed]
  13. Kheir F, Thakore SR, Uribe Becerra JP, et al. Cone-Beam Computed Tomography-Guided Electromagnetic Navigation for Peripheral Lung Nodules. Respiration 2021;100:44-51. [Crossref] [PubMed]
  14. Yu KL, Yang SM, Ko HJ, et al. Efficacy and Safety of Cone-Beam Computed Tomography-Derived Augmented Fluoroscopy Combined with Endobronchial Ultrasound in Peripheral Pulmonary Lesions. Respiration 2021;100:538-46. [Crossref] [PubMed]
  15. Lin CK, Fan HJ, Yao ZH, et al. Cone-Beam Computed Tomography-Derived Augmented Fluoroscopy Improves the Diagnostic Yield of Endobronchial Ultrasound-Guided Transbronchial Biopsy for Peripheral Pulmonary Lesions. Diagnostics (Basel) 2021;12:41. [Crossref] [PubMed]
  16. Benn BS, Romero AO, Lum M, et al. Robotic-Assisted Navigation Bronchoscopy as a Paradigm Shift in Peripheral Lung Access. Lung 2021;199:177-86. [Crossref] [PubMed]
  17. Styrvoky K, Schwalk A, Pham D, et al. Shape-Sensing Robotic-Assisted Bronchoscopy with Concurrent use of Radial Endobronchial Ultrasound and Cone Beam Computed Tomography in the Evaluation of Pulmonary Lesions. Lung 2022;200:755-61. [Crossref] [PubMed]
  18. Abia-Trujillo D, Folch EE, Yu Lee-Mateus A, et al. Mobile cone-beam computed tomography complementing shape-sensing robotic-assisted bronchoscopy in the small pulmonary nodule sampling: A multicentre experience. Respirology 2024;29:324-32. [Crossref] [PubMed]
  19. Reisenauer J, Duke JD, Kern R, et al. Combining Shape-Sensing Robotic Bronchoscopy With Mobile Three-Dimensional Imaging to Verify Tool-in-Lesion and Overcome Divergence: A Pilot Study. Mayo Clin Proc Innov Qual Outcomes 2022;6:177-85. [Crossref] [PubMed]
  20. Chambers J, Knox D, Leclair T. O-arm CT for Confirmation of Successful Navigation During Robotic Assisted Bronchoscopy. J Bronchology Interv Pulmonol 2023;30:155-62. [Crossref] [PubMed]
  21. Cumbo-Nacheli G, Velagapudi RK, Enter M, et al. Robotic-assisted Bronchoscopy and Cone-beam CT: A Retrospective Series. J Bronchology Interv Pulmonol 2022;29:303-6. [Crossref] [PubMed]
  22. Saghaie T, Williamson JP, Phillips M, et al. First-in-human use of a new robotic electromagnetic navigation bronchoscopic platform with integrated Tool-in-Lesion Tomosynthesis (TiLT) technology for peripheral pulmonary lesions: The FRONTIER study. Respirology 2024;29:969-75. [Crossref] [PubMed]
  23. Bruinen A, van der Heijden E, Verhoeven R. Diagnostic yield of ssRAB combined with CBCT imaging in comparison with CBCT-based navigation bronchoscopy using a passive catheter-based approach: preliminary results. Eur Respir J 2024;64:OA4681.
  24. Shaller BD, Duong DK, Swenson KE, et al. Added Value of a Robotic-assisted Bronchoscopy Platform in Cone Beam Computed Tomography-guided Bronchoscopy for the Diagnosis of Pulmonary Parenchymal Lesions. J Bronchology Interv Pulmonol 2024;31:e0971. [Crossref] [PubMed]
  25. Bashour SI, Khan A, Song J, et al. Improving Shape-Sensing Robotic-Assisted Bronchoscopy Outcomes with Mobile Cone-Beam Computed Tomography Guidance. Diagnostics (Basel) 2024;14:1955. [Crossref] [PubMed]
  26. Kalchiem-Dekel O, Bergemann R, Ma X, et al. Determinants of radiation exposure during mobile cone-beam CT-guided robotic-assisted bronchoscopy. Respirology 2024;29:803-14. [Crossref] [PubMed]
  27. Abdelghani R, Espinoza D, Uribe JP, et al. Cone-beam computed tomography-guided shape-sensing robotic bronchoscopy vs. electromagnetic navigation bronchoscopy for pulmonary nodules. J Thorac Dis 2024;16:5529-38. [Crossref] [PubMed]
  28. Pyarali FF, Hakami-Majd N, Sabbahi W, et al. Robotic-assisted Navigation Bronchoscopy: A Meta-Analysis of Diagnostic Yield and Complications. J Bronchology Interv Pulmonol 2024;31:70-81. [Crossref] [PubMed]
  29. Bhadra K, Setser RM, Condra W, et al. Lung Navigation Ventilation Protocol to Optimize Biopsy of Peripheral Lung Lesions. J Bronchology Interv Pulmonol 2022;29:7-17. [Crossref] [PubMed]
  30. Salahuddin M, Sarkiss M, Sagar AS, et al. Ventilatory Strategy to Prevent Atelectasis During Bronchoscopy Under General Anesthesia: A Multicenter Randomized Controlled Trial (Ventilatory Strategy to Prevent Atelectasis -VESPA- Trial). Chest 2022;162:1393-401. [Crossref] [PubMed]
  31. Xie F, Zhang Q, Liu S, et al. Learning curve of a robotic-assisted bronchoscopy system in sampling peripheral pulmonary nodules. Chin Med J (Engl) 2022;135:2753-5. [Crossref] [PubMed]
  32. Bott MJ, Toumbacaris N, Tan KS, et al. Characterizing a learning curve for robotic-assisted bronchoscopy: Analysis of skills acquisition in a high-volume academic center. J Thorac Cardiovasc Surg 2025;169:269-278.e6. [Crossref] [PubMed]
  33. Ahn SY, Park CM, Yoon SH, et al. Learning Curve of C-Arm Cone-beam Computed Tomography Virtual Navigation-Guided Percutaneous Transthoracic Needle Biopsy. Korean J Radiol 2019;20:844-53. [Crossref] [PubMed]
  34. van der Heijden EHFM, Verhoeven RLJ. Robotic Assisted Bronchoscopy: The Ultimate Solution for Peripheral Pulmonary Nodules? Respiration 2022;101:437-40. [Crossref] [PubMed]
  35. Fielding D, van der Heijden EHFM. Cone-beam CT imaging for robotic navigation bronchoscopy. Respirology 2024;29:274-6. [Crossref] [PubMed]
  36. Wijma IN, Casal RF, Cheng GZ, et al. Radiation Principles, Protection, and Reporting for Interventional Pulmonology: A World Association of Bronchology and Interventional Pulmonology White Paper. Respiration 2024;103:707-22. [Crossref] [PubMed]
  37. Verhoeven RLJ, van der Sterren W, Kong W, et al. Cone-beam CT and Augmented Fluoroscopy-guided Navigation Bronchoscopy: Radiation Exposure and Diagnostic Accuracy Learning Curves. J Bronchology Interv Pulmonol 2021;28:262-71. [Crossref] [PubMed]
Cite this article as: Bruinen ARC, Verhoeven RLJ, van der Heijden EHFM. Cone beam computed tomography for navigational bronchoscopy. J Thorac Dis 2025;17(8):6254-6264. doi: 10.21037/jtd-24-1828

Download Citation