Evidence map›Paper›PMID 29208984›Full record

ArticleScientific reports2017

A nonlinear approach to identify pathological change of thyroid nodules based on statistical analysis of ultrasound RF signals.

Huan Xu, Chunrui Liu, Ping Yang, Juan Tu, Bin Yang, Dong Zhang

Abstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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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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

2 citing papers in PubMed.

  1. 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.

Huan XuKey Laboratory of Modern Acoustics (MOE), Department of Physics, Collaborative Innovation Center of Advanced Microstructure, Nanjing University, Nanjing, 210093, China.
Chunrui LiuDepartment of Ultrasound, Jinling Hospital, Medical School of Nanjing University, Nanjing, 210016, China.
Ping YangNational Institute of Metrology, Beijing, 100029, China.
Juan TuKey Laboratory of Modern Acoustics (MOE), Department of Physics, Collaborative Innovation Center of Advanced Microstructure, Nanjing University, Nanjing, 210093, China. juantu@nju.edu.cn.
Bin YangDepartment of Ultrasound, Jinling Hospital, Medical School of Nanjing University, Nanjing, 210016, China. yangbin12yx@163.com.
Dong ZhangKey Laboratory of Modern Acoustics (MOE), Department of Physics, Collaborative Innovation Center of Advanced Microstructure, Nanjing University, Nanjing, 210093, China. dzhang@nju.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In order to reassure the majority of patients with benign nodules from unnecessary needle biopsy, there is an increasing clinical requirement to identify benign and malignant thyroid nodules during ultrasound diagnosis. A nonlinear approach based on statistical analysis of ultrasound radio-frequency (RF) signals was developed for differential diagnosing the thyroid nodules to improve the diagnostic accuracy. Data from 44 patients with solitary thyroid nodules were collected, following with the ultrasound-guided fine needle aspiration (FNA) as the ground truth. The relative P-value (rP-value) was estimated to quantify the pathophysiologic changes by comparing the region of interest (ROI) with the no pathological change part in the thyroid gland using only one frame of raw RF data. The malignant nodules were distinguished from benign ones with high accuracy and high credibility (sensitivity = 100%, specificity = 80%). Suspicious nodules (rP-value < 0.5) could be picked out for FNA with no additional instruments. This method shows promising in differentiating malignant from benign thyroid nodules, subsequently avoiding unnecessary biopsies.

Indexed as

Biopsy, Fine-NeedleHumansImage Processing, Computer-AssistedNonlinear DynamicsSensitivity and SpecificityThyroid NoduleUltrasonography

Identifiers

PMID29208984
PMCPMC5717253

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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.