Image-guided EBUS bronchoscopy system for lung-cancer staging

Zang, Xiaonan; Cheirsilp, Ronnarit; Byrnes, Patrick; Kuhlengel, T.; Abendroth, Catherine; Allen, Thomas Wesley; Mahraj, Rickhesvar; Toth, Jennifer; Bascom, Rebecca; Higgins, William E.

doi:10.1016/j.imu.2021.100665

Cited by 6 publications

(9 citation statements)

References 43 publications

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“…The registration method has been integrated into a complete image-guided EBUS bronchoscopy system, as described more fully in [ 26 ]. Figure 9 illustrates a retrospective example of system guidance for a 68-year-old female lung cancer patient presenting a station 4R lymph node.…”

Section: Resultsmentioning

confidence: 99%

“…We first overview the protocol employed by our image-guided EBUS bronchoscopy system [ 26 ]. Section 2.2 then discusses the method for registering the virtual EBUS to live EBUS probe views.…”

Section: Methodsmentioning

confidence: 99%

“…As discussed in Section 2.2 , this second step critically hinges on our proposed CT-EBUS registration method, which synchronizes the positions of the virtual and real EBUS probes. Section 3 later highlights the complete system during image-guided bronchoscopy, while Zang et al gives more system detail [ 26 ].…”

Section: Methodsmentioning

confidence: 99%

“…Our proposed registration method draws upon the concept of a CT-based virtual EBUS, as introduced by Zang et al [ 25 , 26 ]. The virtual EBUS, which mimics the FOV of the convex-probe EBUS, acts as a complementary analog to the virtual bronchoscope used for image-guided navigation.…”

Section: Introductionmentioning

confidence: 99%

“…During live EBUS localization, our proposed method uses an optimization process, which combines both NMI and region shape information, to register CT-based virtual EBUS views to the live views generated by the real EBUS probe. We also integrated the method into an image-guided EBUS bronchoscopy system that features a multimodal virtual EBUS bronchoscope, which integrates both the standard virtual videobronchoscope and the virtual EBUS [ 26 ]. Thus, intuitive image guidance is now attainable for both videobronchoscopic navigation and EBUS localization.…”

Section: Introductionmentioning

confidence: 99%

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Multimodal Registration for Image-Guided EBUS Bronchoscopy

et al. 2022

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The state-of-the-art procedure for examining the lymph nodes in a lung cancer patient involves using an endobronchial ultrasound (EBUS) bronchoscope. The EBUS bronchoscope integrates two modalities into one device: (1) videobronchoscopy, which gives video images of the airway walls; and (2) convex-probe EBUS, which gives 2D fan-shaped views of extraluminal structures situated outside the airways. During the procedure, the physician first employs videobronchoscopy to navigate the device through the airways. Next, upon reaching a given node’s approximate vicinity, the physician probes the airway walls using EBUS to localize the node. Due to the fact that lymph nodes lie beyond the airways, EBUS is essential for confirming a node’s location. Unfortunately, it is well-documented that EBUS is difficult to use. In addition, while new image-guided bronchoscopy systems provide effective guidance for videobronchoscopic navigation, they offer no assistance for guiding EBUS localization. We propose a method for registering a patient’s chest CT scan to live surgical EBUS views, thereby facilitating accurate image-guided EBUS bronchoscopy. The method entails an optimization process that registers CT-based virtual EBUS views to live EBUS probe views. Results using lung cancer patient data show that the method correctly registered 28/28 (100%) lymph nodes scanned by EBUS, with a mean registration time of 3.4 s. In addition, the mean position and direction errors of registered sites were 2.2 mm and 11.8∘, respectively. In addition, sensitivity studies show the method’s robustness to parameter variations. Lastly, we demonstrate the method’s use in an image-guided system designed for guiding both phases of EBUS bronchoscopy.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Multimodal Registration for Image-Guided EBUS Bronchoscopy

et al. 2022

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Navigated ultrasound bronchoscopy with integrated positron emission tomography - A human feasibility study

Kildahl-Andersen,

Hofstad,

Solberg

et al. 2024

Preprint

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Background and objectivePatients suspected to have lung cancer, undergo endobronchial ultrasound bronchoscopy (EBUS) for the purpose of diagnosis and staging. For presumptive curable patients, the EBUS bronchoscopy is planned based on images and data from computed tomography (CT) images and positron emission tomography (PET). Our study aimed to evaluate the feasibility of a multimodal electromagnetic navigation platform for EBUS bronchoscopy, integrating ultrasound and segmented CT, and PET scan imaging data.MethodsThe proof-of-concept study included patients with suspected lung cancer and pathological mediastinal/hilar lymph nodes identified on both CT and PET scans. Images obtained from these two modalities were segmented to delineate target lymph nodes and then incorporated into the CustusX navigation platform. The EBUS bronchoscope was equipped with a sensor, calibrated, and affixed to a 3D printed click-on device positioned at the bronchoscope’s tip. Navigation accuracy was measured postoperatively using ultrasound recordings.ResultsThe study enrolled three patients, all presenting with suspected mediastinal lymph node metastasis (N1-3). All PET-positive lymph nodes were displayed in the navigation platform during the EBUS procedures. In total, five distinct lymph nodes were sampled, yielding malignant cells from three nodes and lymphocytes from the remaining two. The median accuracy of the navigation system was 7.7 mm.ConclusionOur study introduces a feasible multimodal electromagnetic navigation platform that combines intraoperative ultrasound with preoperative segmented CT and PET imaging data for EBUS lymph node staging examinations. This innovative approach holds promise for enhancing the accuracy and effectiveness of EBUS procedures.

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