Evidence map›Paper›PMID 34603989›Full record

ArticleQuantitative imaging in medicine and surgery2021

Improved detection of solitary pulmonary nodules on radiographs compared with deep bone suppression imaging.

Jiefang Wu, Weiguo Chen, Fengxia Zeng, Le Ma, Weimin Xu, Wei Yang, Genggeng Qin

Open access · diamondAbstract read
In one paragraph

Article in Quantitative imaging in medicine and surgery, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 41% 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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 2 citations in OpenAlex.

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4 · The record

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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

7 authors at 2 institutions in 1 country.

Jiefang WuDepartment of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Weiguo ChenDepartment of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Fengxia ZengDepartment of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Le MaDepartment of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Weimin XuDepartment of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Wei YangSchool of Biomedical Engineering, Southern Medical University, Guangzhou, China.
Genggeng QinDepartment of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Southern Medical University · CNNanfang Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe present study aimed to investigate whether deep bone suppression imaging (BSI) could increase the diagnostic performance for solitary pulmonary nodule detection compared with digital tomosynthesis (DTS), dual-energy subtraction (DES) radiography, and conventional chest radiography (CCR).

methodsA total of 256 patients (123 with a solitary pulmonary nodule, 133 with normal findings) were included in the study. The confidence score of 6 observers determined the presence or absence of pulmonary nodules in each patient. These were first analyzed using a CCR image, then with CCR plus deep BSI, then with CCR plus DES radiography, and finally with DTS images. Receiver-operating characteristic curves were used to evaluate the performance of the 6 observers in the detection of pulmonary nodules.

resultsFor the 6 observers, the average area under the curve improved significantly from 0.717 with CCR to 0.848 with CCR plus deep BSI (P<0.01), 0.834 with CCR plus DES radiography (P<0.01), and 0.939 with DTS (P<0.01). Comparisons between CCR and CCR plus deep BSI found that the sensitivities of the assessments by the 3 residents increased from 53.2% to 69.5% (P=0.014) for nodules located in the upper lung field, from 30.6% to 44.6% (P=0.015) for nodules that were partially/completely obscured by the bone, and from 33.2% to 45.8% (P=0.006) for nodules <10 mm.

conclusionsThe deep BSI technique can significantly increase the sensitivity of radiology residents for solitary pulmonary nodules compared with CCR. Increased detection was seen mainly for smaller nodules, nodules with partial/complete obscuration, and nodules located in the upper lung field.

Indexed as

Bone suppressiondigital tomosynthesisdual-energy subtractionsolitary pulmonary nodules

Identifiers

PMID34603989
PMCPMC8408784
OpenAlexW3173661851

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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.