Evidence map›Paper›PMID 37860943›Full record

ArticleThoracic cancer2023

Three-dimensional lung reconstructions for the localization of lung nodules to be resected during surgery.

Giovanni Natale, Beatrice Leonardi, Gaetana Messina, Grazia Bergameo, Vincenzo Di Filippo, Giulia Chisari, Gabriele Raciti, Sofia Paola Lombardo, Rosa Mirra, Francesca Capasso and 3 more

Abstract read
In one paragraph

Article in Thoracic cancer, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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.

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

6 citing papers in PubMed.

  1. Article
  2. Intraoperative Contrast-Enhanced Ultrasound Versus Traditional Intraoperative Ultrasound for Detecting Lung Nodules During Robotic-assisted Thoracic Surgery.European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery · 2026
    Article
  3. Article
  4. Article
  5. 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

13 authors.

Giovanni NataleThoracic Surgery Unit, Department of Translation Medicine, Università della Campania "LuigiVanvitelli", Naples, Italy.ORCID 0000-0002-1940-0288
Beatrice LeonardiThoracic Surgery Unit, Department of Translation Medicine, Università della Campania "LuigiVanvitelli", Naples, Italy.
Gaetana MessinaThoracic Surgery Unit, Department of Translation Medicine, Università della Campania "LuigiVanvitelli", Naples, Italy.ORCID 0000-0001-5129-7201
Grazia BergameoThoracic Surgery Unit, Department of Translation Medicine, Università della Campania "LuigiVanvitelli", Naples, Italy.
Vincenzo Di FilippoThoracic Surgery Unit, Department of Translation Medicine, Università della Campania "LuigiVanvitelli", Naples, Italy.
Giulia ChisariGenomics and Experimental Oncology Unit, IOM Ricerca, Viagrande, Italy.
Gabriele RacitiGenomics and Experimental Oncology Unit, IOM Ricerca, Viagrande, Italy.
Sofia Paola LombardoGenomics and Experimental Oncology Unit, IOM Ricerca, Viagrande, Italy.
Rosa MirraThoracic Surgery Unit, Department of Translation Medicine, Università della Campania "LuigiVanvitelli", Naples, Italy.
Francesca CapassoThoracic Surgery Unit, Department of Translation Medicine, Università della Campania "LuigiVanvitelli", Naples, Italy.
Francesco LeoneThoracic Surgery Unit, Department of Translation Medicine, Università della Campania "LuigiVanvitelli", Naples, Italy.
Davide Gerardo PicaThoracic Surgery Unit, Department of Translation Medicine, Università della Campania "LuigiVanvitelli", Naples, Italy.
Alfonso FiorelliThoracic Surgery Unit, Department of Translation Medicine, Università della Campania "LuigiVanvitelli", Naples, Italy.ORCID 0000-0002-0628-613X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe localization of lung nodules is challenging during thoracoscopy. In this study, we evaluated the use of three-dimensional (3D) lung reconstruction for use in the operating room to guide the identification of lung nodules during thoracoscopy.

methodsThis was a single-center retrospective study. All consecutive patients undergoing thoracoscopic resection of lung nodules were included in the study. Patients were retrospectively divided into two groups based upon whether the thoracoscopic resection was performed with the assistance (3D group) or not (standard group) of 3D lung reconstruction. The operative time (minutes) to detect lung nodules was statistically compared between the two study groups in relation to the characteristics of lung nodules as size, localization, and distance from the visceral pleura.

resultsOur study population consisted of 170 patients: 85 in the 3D group and 85 in the standard group. No intergroup difference differences were found regarding the characteristics and histological diagnosis of lesions. The standard group compared to the 3D group was associated with a significantly longer operative time for the detection of lesions <10 mm (13.87 ± 2.59 vs. 5.52 ± 1.01, p < 0.001), lesions between 10 and 20 mm (5.05 ± 0.84 vs. 3.89 ± 0.92; p = 0.03), lesions localized in complex segments (7.49 ± 4.25 vs. 5.11 ± 0.97; p < 0.001), and deep lesions (9.58 ± 4.82 vs. 5.4 ± 1.01, p < 0.001).

conclusionsOur 3D lung reconstruction model for use in the operating room may be an additional tool for thoracic surgeons to guide the detection of small and deep nodules during thoracoscopy. It is a noninvasive and cost saving procedure and may be widely used.

Indexed as

Lung NeoplasmsSolitary Pulmonary NoduleHumansLungRetrospective StudiesThoracic Surgery, Video-AssistedThoracoscopyTomography, X-Ray Computed3D lung reconstructiondigital 3D modelslung nodule localization

Identifiers

PMID37860943
PMCPMC10693940

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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.