Evidence map›Paper›PMID 42267007›Full record

ArticleAnnals of thoracic surgery short reports2026

Dual Techniques for Identifying Intersegmental Planes Using Indocyanine Green and Virtual-Assisted Lung Mapping in Robotic Segmentectomy.

Shinsuke Uchida, Yukio Watanabe, Mariko Fukui, Hisashi Tomita, Aritoshi Hattori, Takeshi Matsunaga, Kota Imashimizu, Kazuya Takamochi, Kenji Suzuki

Abstract read
In one paragraph

Article in Annals of thoracic surgery short reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

9 authors.

Shinsuke UchidaDepartment of General Thoracic Surgery, Juntendo University School of Medicine, Tokyo, Japan.
Yukio WatanabeDepartment of General Thoracic Surgery, Juntendo University School of Medicine, Tokyo, Japan.
Mariko FukuiDepartment of General Thoracic Surgery, Juntendo University School of Medicine, Tokyo, Japan.
Hisashi TomitaDepartment of General Thoracic Surgery, Juntendo University School of Medicine, Tokyo, Japan.
Aritoshi HattoriDepartment of General Thoracic Surgery, Juntendo University School of Medicine, Tokyo, Japan.
Takeshi MatsunagaDepartment of General Thoracic Surgery, Juntendo University School of Medicine, Tokyo, Japan.
Kota ImashimizuDepartment of General Thoracic Surgery, Juntendo University School of Medicine, Tokyo, Japan.
Kazuya TakamochiDepartment of General Thoracic Surgery, Juntendo University School of Medicine, Tokyo, Japan.
Kenji SuzukiDepartment of General Thoracic Surgery, Juntendo University School of Medicine, Tokyo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Useful methods for identifying the intersegmental plane during robot-assisted thoracoscopic surgery (RATS) remain unclear. This study aimed to investigate techniques for identifying the intersegmental plane during robotic segmentectomy. Methods: Patients who underwent robotic segmentectomy between January 2017 and January 2023 were enrolled. We retrospectively evaluated methods for identifying the intersegmental plane by using selective segmental inflation-deflation RATS and intravenous indocyanine green (ICG) with or without virtual-assisted lung mapping (VAL-MAP) RATS. Patients' characteristics and perioperative outcomes were compared among the groups. Results: Among the 497 patients who underwent robotic lung resection, this study enrolled 112 patients (23%) who underwent robotic segmentectomy. Fifty-three patients (47%) underwent selective segmental inflation-deflation RATS, and 59 patients (53%) received ICG injection with or without VAL-MAP RATS. Clinical factors, surgical findings, and postoperative complications were similar among all groups. Complex segmentectomy was performed more frequently in the ICG with or without VAL-MAP RATS group than in the selective segmental inflation-deflation RATS group (35 patients vs 12 patients). Dual techniques involving ICG injection and VAL-MAP marking robotic complex segmentectomy were performed for tumors located close to the intersegmental plane in 4 patients. In these patients, the distance to the surgical margin was greater than the tumor diameter. No complications were caused by ICG injection or VAL-MAP markings. Conclusions: Dual techniques for identifying intersegmental planes using ICG and preoperative VAL-MAP markings are safe and useful for robotic lung segmentectomy.

Identifiers

PMID42267007
PMCPMC13245351

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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.