Evidence map›Paper›PMID 32642262›Full record

ReviewJournal of thoracic disease2020

How to identify intersegmental planes in performing sublobar anatomical resections.

Giulia Nex, Marcella Schiavone, Angela De Palma, Rosatea Quercia, Debora Brascia, Giulia De Iaco, Francesca Signore, Teodora Panza, Giuseppe Marulli

Registry-linked trialAbstract readReview
In one paragraph

Review in Journal of thoracic disease, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05545085 (Thoracoscopic Laser Speckle Contrast Imaging for the Demarcation of Lung Segments), which is not on this map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

NCT05545085 unknown statusnot on this mapstarted 2022, after this paper: background citation

Thoracoscopic Laser Speckle Contrast Imaging for the Demarcation of Lung Segments

Typeobservational_patient_registrySponsorFrisius Medisch CentrumRan2022 to 2023Enrolled10ConditionsPulmonary CancerArmsLaser Speckle Contrast Imaging using the PerfusiX-Imaging Device
3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Giulia NexThoracic Surgery Unit, Department of Emergency and Organ Transplantation (DETO), University Hospital of Bari, Bari, Italy.
Marcella SchiavoneThoracic Surgery Unit, Department of Emergency and Organ Transplantation (DETO), University Hospital of Bari, Bari, Italy.
Angela De PalmaThoracic Surgery Unit, Department of Emergency and Organ Transplantation (DETO), University Hospital of Bari, Bari, Italy.
Rosatea QuerciaThoracic Surgery Unit, Department of Emergency and Organ Transplantation (DETO), University Hospital of Bari, Bari, Italy.
Debora BrasciaThoracic Surgery Unit, Department of Emergency and Organ Transplantation (DETO), University Hospital of Bari, Bari, Italy.
Giulia De IacoThoracic Surgery Unit, Department of Emergency and Organ Transplantation (DETO), University Hospital of Bari, Bari, Italy.
Francesca SignoreThoracic Surgery Unit, Department of Emergency and Organ Transplantation (DETO), University Hospital of Bari, Bari, Italy.
Teodora PanzaThoracic Surgery Unit, Department of Emergency and Organ Transplantation (DETO), University Hospital of Bari, Bari, Italy.
Giuseppe MarulliThoracic Surgery Unit, Department of Emergency and Organ Transplantation (DETO), University Hospital of Bari, Bari, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pulmonary segmentectomy is a common surgical procedure in thoracic surgery nowadays. Though this technique helps preventing postoperative pulmonary function loss, potential challenges are the management of air leaks and the difficulty of palpating ground-glass components during surgery, as well as how to deal with the intersegmental planes. Several techniques have been proposed for the identification and treatment of the intersegmental planes during sublobar anatomical resections: this review focuses on preoperative planning and workup and intraoperative strategies. Three-dimensional computed tomography bronchography and angiography (3D-CTBA), virtual-assisted mapping (VAL-MAP) using bronchoscopy multi-spot dye marking and three-dimensional computed tomography (3D-CT) are preoperative tools that may facilitate the planning of operation. Inflation-deflation techniques, infrared-fluorescence-enhanced method combined with bronchial and intravenous injection of indocyanine green (ICG) and near-infrared fluorescence (NIF) mapping with ICG have been described as intraoperative strategies to identify the intersegmental plane. The treatment and section of the intersegmental planes is mainly accomplished by stapler and electrocautery or energy devices. The use of staplers reduces postoperative air leaks, bleeding risks and operative time but seems to reduce preserved lung volume, compromising adjacent lung expansion; in addition, higher costs and sometimes non-adequate oncological margins, being a non-anatomical technique have been described. The electrocautery and energy devices allow for a more anatomical and precise dissection maintaining safe oncological margins, with a better lung expansion and so an increased postoperative lung function. Time consuming procedure and frequent requirement of aero-haemostatic tools to treat air and blood leaks are the main drawbacks. In conclusion, there are several methods to identify and treat the intersegmental planes but there are no significant differences between the different tools, therefore the use of one technique rather than another depends overall on surgeon's preference and the location of the segment.

Indexed as

identification and treatmentintersegmental planeslung cancerPulmonary segmentectomy

Identifiers

PMID32642262
PMCPMC7330755

What OpenQuestion holds

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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.