ReviewCancers2023
Ten-Year Outcome and Development of Virtual-Assisted Lung Mapping in Thoracic Surgery.
Review in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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
9 citing papers in PubMed, 7 citations in OpenAlex.
- Preoperative and Intraoperative Localization of Small Pulmonary Nodules for Sublobar Resection: Practical Insights into Percutaneous, Bronchoscopic/Robotic, RFID (SuReFInD), and Hybrid-OR CT Workflows.Diseases (Basel, Switzerland) · 2026Review
- Efficacy and safety of virtual-assisted lung mapping using dual staining with indigo carmine and indocyanine green in sublobar lung resection: a single-arm prospective cohort study.Journal of thoracic disease · 2026Article
- Multicenter Prospective Comparative Study of Patient Radiation Doses in Localization Techniques for Small Lung Lesions.Cancers · 2025Article
- Intraoperative patient radiation dose from cone-beam computed tomography in thoracic surgery.Journal of cardiothoracic surgery · 2024Article
- Performing High-Quality Sublobar Resections: Key Differences Between Wedge Resection and Segmentectomy.Cancers · 2024Review
- Augmented fluoroscopy-guided dye localization for small pulmonary nodules in hybrid operating room: intrathoracic stamping versus transbronchial marking.International journal of computer assisted radiology and surgery · 2024Observational
- Current Status and Future Perspectives of Preoperative and Intraoperative Marking in Thoracic Surgery.Cancers · 2024Review
- Advances in the localization of pulmonary nodules: a comprehensive review.Journal of cardiothoracic surgery · 2024Review
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Virtual-assisted lung mapping (VAL-MAP) is a preoperative bronchoscopic multispot dye-marking technique used in sublobar lung resection of barely palpable lung nodules. This review summarizes the history and outcomes of the VAL-MAP procedure. VAL-MAP was developed in 2012, and long-term outcomes of lung resection using VAL-MAP have recently been verified. Problems associated with conventional VAL-MAP include a prerequisite of post-mapping computed tomography (CT), occasional inability to see dye marks during surgery, and infrequent resection failure due to deep resection margins; various techniques have been developed to address these issues. VAL-MAP using electromagnetic navigation bronchoscopy with on-site adjustment can omit post-mapping CT. The use of indocyanine green in VAL-MAP has increased the success rate of marking detection during surgery without causing additional complications. VAL-MAP 2.0-a three-dimensional mapping technique that involves the intrabronchial placement of a microcoil-has increased the accuracy of sublobar resection, particularly for deeply located tumors. Although these promising new techniques have some limitations, they are beneficial for sublobar lung resection.
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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.