Evidence map›Paper›PMID 37195266›Full record

ArticleJournal of applied clinical medical physics2023

Preoperative assessment of pleural adhesions in patients with lung cancer based on quantitative motion analysis with dynamic chest radiography: A retrospective study.

Rie Tanaka, Isao Matsumoto, Tetsuya Takayama, Noriyuki Ohkura, Dai Inoue

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Article in Journal of applied clinical medical physics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.6field-weighted citation impact, top 16% 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

8 citing papers in PubMed, 6 citations in OpenAlex.

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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

5 authors at 2 institutions in 1 country.

Rie TanakaCollege of Medical, Pharmaceutical & Health Sciences, Kanazawa University, Kanazawa, Japan.
Isao MatsumotoDepartment of Thoracic Surgery, Kanazawa University, Kanazawa, Japan.
Tetsuya TakayamaDepartment of Thoracic Surgery, Kanazawa University, Kanazawa, Japan.
Noriyuki OhkuraDepartment of Respiratory Medicine, Kanazawa University Hospital, Kanazawa, Japan.
Dai InoueDepartment of Radiology, Kanazawa University Hospital, Kanazawa, Japan.
Kanazawa University · JPKanazawa University Hospital · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposePreoperative assessment of pleural adhesion is crucial for appropriate surgical planning. This study aimed to quantitatively evaluate the usefulness of motion analysis using dynamic chest radiography (DCR) for assessing pleural adhesions.

methodsSequential chest radiographs of 146 lung cancer patients with or without pleural adhesions (n = 25/121) were obtained using a DCR system during respiration (registration number: 1729). The local motion vector was measured, and the percentage of poor motion area to the maximum expiration lung area (%lung area with poor motion) was calculated. Subsequently, percentage values ≥49.0% were considered to indicate pleural adhesions. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated to assess the prediction performance. The percentage of lung area with poor motion was compared between patients with and without pleural adhesions (p < 0.05).

resultsDCR-based motion analysis correctly predicted pleural adhesions in 21 out of 25 patients, with 47 false-positive results (sensitivity, 84.0%; specificity, 61.2%; PPV, 30.9%; NPV, 94.9%). The lung with pleural adhesions showed a significantly greater %lung area with poor motion than the opposite lung in the same patient, similar to the cancerous lung in patients without pleural adhesions.

conclusionOn DCR-based motion analysis, pleural adhesions could be indicated by an increase in the percentage of lung area with poor motion. Although the proposed method cannot identify the exact location of pleural adhesions, information regarding the presence or absence of pleural adhesions provided by DCR would help surgeons prepare for challenging surgeries and obtain informed consent from patients.

Indexed as

Lung NeoplasmsPleural DiseasesHumansRadiographyRetrospective StudiesSensitivity and Specificitydigital radiographylung cancermotion analysispleural adhesions

Identifiers

PMID37195266
PMCPMC10338755
OpenAlexW4376871106

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Registered trials

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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.