Evidence map›Paper›PMID 33563295›Full record

ArticleWorld journal of surgical oncology2021

Dynamic perfusion digital radiography for predicting pulmonary function after lung cancer resection.

Jun Hanaoka, Makoto Yoden, Kazuki Hayashi, Takuya Shiratori, Keigo Okamoto, Ryosuke Kaku, Yo Kawaguchi, Yasuhiko Ohshio, Akinaga Sonoda

Open access · goldAbstract read
In one paragraph

Article in World journal of surgical oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
2.3field-weighted citation impact, top 12% 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

16 citing papers in PubMed, 23 citations in OpenAlex.

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  14. CMaf-Inducing Protein Promotes LUAD Proliferation and Metastasis by Activating the MAPK/ERK Pathway.Evidence-based complementary and alternative medicine : eCAM · 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

9 authors at 1 institution in 1 country.

Jun HanaokaDivision of General Thoracic Surgery, Department of Surgery, Shiga University of Medical Science, Shiga, Japan. hanaoka@belle.shiga-med.ac.jp.
Makoto YodenDivision of General Thoracic Surgery, Department of Surgery, Shiga University of Medical Science, Shiga, Japan.
Kazuki HayashiDivision of General Thoracic Surgery, Department of Surgery, Shiga University of Medical Science, Shiga, Japan.
Takuya ShiratoriDivision of General Thoracic Surgery, Department of Surgery, Shiga University of Medical Science, Shiga, Japan.
Keigo OkamotoDivision of General Thoracic Surgery, Department of Surgery, Shiga University of Medical Science, Shiga, Japan.
Ryosuke KakuDivision of General Thoracic Surgery, Department of Surgery, Shiga University of Medical Science, Shiga, Japan.
Yo KawaguchiDivision of General Thoracic Surgery, Department of Surgery, Shiga University of Medical Science, Shiga, Japan.
Yasuhiko OhshioDivision of General Thoracic Surgery, Department of Surgery, Shiga University of Medical Science, Shiga, Japan.
Akinaga SonodaDepartment of Radiology, Shiga University of Medical Science, Shiga, Japan.
Shiga University of Medical Science · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAccurate prediction of postoperative pulmonary function is important for ensuring the safety of patients undergoing radical resection for lung cancer. Dynamic perfusion digital radiography is an excellent and easy imaging method for detecting blood flow in the lung compared with the less-convenient conventional lung perfusion scintigraphy. As such, the present study aimed to confirm whether dynamic perfusion digital radiography can be evaluated in comparison with pulmonary perfusion scintigraphy in predicting early postoperative pulmonary function and complications.

methodsDynamic perfusion digital radiography and spirometry were performed before and 1 and 3 months after radical resection for lung cancer. Correlation coefficients between blood flow ratios calculated using dynamic perfusion digital radiography and pulmonary perfusion scintigraphy were then confirmed in the same cases. In all patients who underwent dynamic perfusion digital radiography, the correlation predicted values calculated from the blood flow ratio, and measured values were examined. Furthermore, ppo%FEV1 or ppo%DLco values, which indicated the risk for perioperative complications, were examined.

resultsA total of 52 participants who satisfied the inclusion criteria were analyzed. Blood flow ratios measured using pulmonary perfusion scintigraphy and dynamic perfusion digital radiography showed excellent correlation and acceptable predictive accuracy. Correlation coefficients between predicted FEV1 values obtained from dynamic perfusion digital radiography or pulmonary perfusion scintigraphy and actual measured values were similar. All patients who underwent dynamic perfusion digital radiography showed excellent correlation between predicted values and those measured using spirometry. A significant difference in ppo%DLco was observed for respiratory complications but not cardiovascular complications.

conclusionsOur study demonstrated that dynamic perfusion digital radiography can be a suitable alternative to pulmonary perfusion scintigraphy given its ability for predicting postoperative values and the risk for postoperative respiratory complications. Furthermore, it seemed to be an excellent modality because of its advantages, such as simplicity, low cost, and ease in obtaining in-depth respiratory functional information.

trial registrationRegistered at UMIN on October 25, 2017. https://upload.umin.ac.jp/cgi-open-bin/ctr/ctr_his_list.cgi?recptno=R000033957 Registration number: UMIN000029716.

Indexed as

Lung NeoplasmsRadiographic Image EnhancementHumansLungPerfusionPneumonectomyPrognosisDynamic chest radiographyDynamic perfusion digital radiographyPrediction of postoperative respiratory functionPulmonary perfusionPulmonary perfusion scintigraphy

Identifiers

PMID33563295
PMCPMC7874664
OpenAlexW3123223625

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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.