Evidence map›Paper›PMID 31691509›Full record

ArticleCancer medicine2019

The diagnostic value of the ultrasound gray scale ratio for different sizes of thyroid nodules.

Xiaoyu Chen, Ming Gao, Linfei Hu, Jialin Zhu, Sheng Zhang, Xi Wei

Open access · goldAbstract read
In one paragraph

Article in Cancer medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.6field-weighted citation impact, top 15% 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

11 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
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  4. Musculoskeletal Ultrasound Image-Based Radiomics for the Diagnosis of Achilles Tendinopathy in Skiers.Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine · 2023
    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

6 authors at 1 institution in 1 country.

Xiaoyu ChenDepartment of Diagnostic and Therapeutic Ultrasonography, Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin, China.
Ming GaoDepartment of Thyroid and Cervical Tumor, Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center of Cancer, Tianjin, China.
Linfei HuDepartment of Thyroid and Cervical Tumor, Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center of Cancer, Tianjin, China.
Jialin ZhuDepartment of Diagnostic and Therapeutic Ultrasonography, Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin, China.ORCID 0000-0002-3126-2148
Sheng ZhangDepartment of Diagnostic and Therapeutic Ultrasonography, Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin, China.
Xi WeiDepartment of Diagnostic and Therapeutic Ultrasonography, Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin, China.ORCID 0000-0003-4734-3900
Tianjin Medical University Cancer Institute and Hospital · CN

Funding

National Natural Science Foundation of China 81771852
6 · The paper itself

Abstract

At present, hypoechogenicity, as one of the clinically relevant features associated with suspicion of malignant thyroid disease, is affected by the variability of modules and the experience of sonographers, thus leading to unsatisfying results. We propose the ultrasound gray scale ratio (UGSR) to obtain an objective, numerical estimate of the echogenicity degree in different-sized thyroid nodules, and we then evaluate its diagnostic efficacy in differentiating benign and malignant thyroid lesions. In total, 553 ultrasound images of thyroid nodules from one kind of ultrasonographic scanner were analyzed, among which 281 were papillary thyroid carcinomas (PTCs) and 272 were nodular goiters (NGs). The UGSR of the PTCs, NGs, and surrounding normal thyroid tissue was measured by image analysis software. The best cut-off value for distinguishing various sizes of PTCs and NGs was determined by receiver operating characteristic (ROC) curve analysis. As the UGSR increased, the sensitivity of the diagnosing PTCs decreased, and the specificity increased. When the maximum Jordan index was 0.611, the best cut-off value was 0.692, and the corresponding sensitivity and specificity of diagnosing PTCs were 87.9% and 73.2%, respectively. For the analysis of subgroups of different tumor sizes, as the size of thyroid nodules increased from 0.3 to 2 cm, the sensitivity of the diagnosis of PTCs decreased from 97.5% to 58.8%, and the specificity increased from 72.4% to 90.9%. These results strongly suggest that the UGSR is an appropriate objective, numerical method for estimating the echogenicity degree and has various diagnostic efficacies in different-sized thyroid nodules. Thus, the UGSR can be used as an additional ultrasound parameter in the diagnosis of different-sized PTCs and NGs.

Indexed as

Image Processing, Computer-AssistedUltrasonographyDiagnosis, DifferentialHumansReproducibility of ResultsRetrospective StudiesROC CurveThyroid NeoplasmsThyroid NoduleTumor Burdenechogenicitynodular goiterspapillary thyroid carcinomaultrasonic diagnosisultrasound gray scale ratio

Identifiers

PMID31691509
PMCPMC6912051
OpenAlexW2985348987

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LicenceCC BY
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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.