ArticleERJ open research2024
The incremental contribution of mobile cone-beam computed tomography to the tool-lesion relationship during shape-sensing robotic-assisted bronchoscopy.
Article in ERJ open research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
13 citing papers in PubMed.
- Trial
- Article
- Shape-Sensing Robotic Bronchoscopy with Integrated Mobile Cone-Beam CT Guidance for Intraoperative Localization of Lung Tumors Using Indocyanine Green.Diagnostics (Basel, Switzerland) · 2026Article
- Comparing the effectiveness and safety of robotic-assisted bronchoscopy and computed tomography-guided transthoracic biopsy for evaluating pulmonary lung nodules: results from the DYSTRICT study.ERJ open research · 2026Article
- Best practices in shape-sensing robotic bronchoscopy with mobile cone beam computed tomography guidance: how I do it.Journal of thoracic disease · 2026Review
- The Additional Accuracy Gained by Cone Beam CT in Shape-Sensing Robotic Bronchoscopy.CHEST pulmonary · 2025Article
- VirtualJournal of thoracic disease · 2025Article
- Robotic-assisted bronchoscopy for histopathologic subtyping of primary lung adenocarcinoma.Lung cancer (Amsterdam, Netherlands) · 2025Article
- Chinese expert consensus on shape-sensing robotic-assisted bronchoscopy (ssRAB) in the management of peripheral pulmonary lesions.Translational lung cancer research · 2025Review
- Review
- Bedside to bench and back again-translational research in interventional pulmonology.Current opinion in pulmonary medicine · 2025Review
- Improving Shape-Sensing Robotic-Assisted Bronchoscopy Outcomes with Mobile Cone-Beam Computed Tomography Guidance.Diagnostics (Basel, Switzerland) · 2024Article
- Robot-assisted vascular surgery: literature review, clinical applications, and future perspectives.Journal of robotic surgery · 2024Review
Corrections and comments
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Authors and funding
15 authors.
Funding
Abstract
Introduction: This study aims to answer the question of whether adding mobile cone-beam computed tomography (mCBCT) imaging to shape-sensing robotic-assisted bronchoscopy (ssRAB) translates into a quantifiable improvement in the tool-lesion relationship. Methods: Data from 102 peripheral lung lesions with ≥2 sequential mCBCT orbital spins and from 436 lesions with 0-1 spins were prospectively captured and retrospectively analysed. The primary outcome was the tool-lesion relationship status across the first and the last mCBCT spins. Secondary outcomes included 1) the change in distance between the tip of the sampling tool and the centre of the lesion between the first and the last spins and 2) the per-lesion diagnostic yield. Results: Compared to lesions requiring 0-1 spins, lesions requiring ≥2 spins were smaller and had unfavourable bronchus sign and intra-operative sonographic view. On the first spin, 54 lesions (53%) were designated as non-tool-in-lesion (non-TIL) while 48 lesions (47%) were designated as TIL. Of the 54 initially non-TIL cases, 49 (90%) were converted to TIL status by the last spin. Overall, on the last spin, 96 out of 102 lesions (94%) were defined as TIL and six out of 102 lesions (6%) were defined as non-TIL (p<0.0001). The mean distance between the tool and the centre of the lesion decreased from 10.4 to 6.6 mm between the first and last spins (p<0.0001). The overall diagnostic yield was 77%. Conclusion: Targeting traditionally challenging lung lesions, intra-operative volumetric imaging allowed for the conversion of 90% of non-TIL status to TIL. Guidance with mCBCT resulted in a significant decrease in the distance between the tip of the needle to lesion centre.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.