ArticleJournal of thoracic disease2026
Utilizing 3D Slicer for pulmonary bronchovascular anatomy reconstruction: a practical workflow and case examples.
Article in Journal of thoracic disease, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Three-Dimensional Bronchovascular Modelling in Sublobar Pulmonary Resection: A Tool for Personalised Thoracic Surgery.Journal of personalized medicine · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Current surgical planning relies on conventional two-dimensional (2D) imaging, but this is limited by its inability to fully represent three-dimensional (3D) anatomical relationships. This limitation is particularly evident in thoracic surgery, where accurate visualization of the pulmonary bronchovascular anatomy is essential for planning lung resections in a surgical field that has high anatomical variations and dynamic deformation during surgery. Although 3D reconstruction techniques have been explored to address these limitations, their adoption into routine clinical practice has been constrained by reliance on expensive proprietary software and a lack of detailed, efficient, reproducible workflows. Here, we describe a novel, practical imaging-based approach for generating patient-specific 3D reconstructions of pulmonary anatomy from computed tomography (CT) data using 3D Slicer, an open-source platform for imaging segmentation and 3D modelling. A reproducible step-by-step workflow is presented, detailing segmentation of pulmonary arteries, veins, bronchi, tumour localization, and resection margin assessment, together with common pitfalls, troubleshooting strategies, and factors influencing accuracy and efficiency. The workflow is designed to be intuitive and time-feasible, with model generation achievable within routine pre-operative planning timeframes. The process is demonstrated through two representative cases in which 3D reconstruction altered surgical planning by clarifying ambiguous anatomy, enabling precise pulmonary tumour localization and accurate resection. With the use of 3D reconstruction technology, anatomical understanding and operative precision can be enhanced, supporting more informed surgical decision-making and potentially improving patient outcomes.
Indexed as
Identifiers
What OpenQuestion holds
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.