Evidence map›Paper›PMID 35004248›Full record

ArticleTranslational lung cancer research2021

Augmented reality-assisted localization of solitary pulmonary nodules for precise sublobar lung resection: a preliminary study using an animal model.

Mingzheng Peng, Lingming Yu, Yang Zhou, Yunhai Yang, Qingquan Luo, Xinghua Cheng

Open access · diamondAbstract read
In one paragraph

Article in Translational lung cancer research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
1.0field-weighted citation impact, top 22% of its field
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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.

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  9. State of the Art in Lung Nodule Localization.Journal of clinical medicine · 2022
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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

6 authors at 2 institutions in 1 country.

Mingzheng PengShanghai Lung Tumor Clinical Medical Center, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
Lingming YuDepartment of Radiology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
Yang ZhouDepartment of Equipment, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
Yunhai YangShanghai Lung Tumor Clinical Medical Center, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
Qingquan LuoShanghai Lung Tumor Clinical Medical Center, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
Xinghua ChengShanghai Lung Tumor Clinical Medical Center, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
Shanghai Chest Hospital · CNShanghai Jiao Tong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAccurate localization of early lung cancer, manifested as solitary pulmonary nodules (SPNs) on computed tomography (CT), is critical in sublobar lung resection. The AR-assisted localization of SPNs was evaluated using a pig animal model.

methodsA Microsoft HoloLens AR system was used. First, a plastic thoracic model was used for the pilot study. Three female 12 months 45 kg Danish Landrace Pigs were then used for the animal study. Thirty natural pulmonary structures, such as lymphonodus and bifurcated bronchioles or bronchial vessels, were chosen as simulated SPNs. The average angle between the actual puncturing needle and the expected path, the average distance between the puncture point and the plan point, and the difference between the actual puncturing depth and expected depth were recorded, and the accuracy rate was calculated.

resultsThe point selected in the plastic thoracic model could be hit accurately with the assistance from the AR system in the pilot study. Moreover, the average angle between the actual puncturing needle and the expected path was 14.52°±6.04°. Meanwhile, the average distance between the puncture point and the expected point was 8.74±5.07 mm, and the difference between the actual and expected depths was 9.42±7.95 mm. Puncturing within a 1 cm

conclusionsThe HoloLens AR-assisted localization of SPNs may become a promising technique to improve the surgical treatment of early-stage lung cancer. Here, we evaluated its feasibility in an animal model. Nevertheless, its safety and effectiveness require further investigation in clinical trials.

Indexed as

animal modelaugmented realitylocalizationSolitary pulmonary nodules (SPNs)sublobar lung resection

Identifiers

PMID35004248
PMCPMC8674605
OpenAlexW3212563418

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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.