Evidence map›Paper›PMID 34093429›Full record

ArticleFrontiers in endocrinology2021

A Preliminary Study of Quantitative Ultrasound for Cancer-Risk Assessment of Thyroid Nodules.

Poorani N Goundan, Jonathan Mamou, Daniel Rohrbach, Jason Smith, Harshal Patel, Kirk D Wallace, Ernest J Feleppa, Stephanie L Lee

Open access · goldAbstract read
In one paragraph

Article in Frontiers in endocrinology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.8field-weighted citation impact, top 9% 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

7 citing papers in PubMed, 20 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

8 authors at 5 institutions in 1 country.

Poorani N GoundanSection of Endocrinology, Diabetes and Nutrition, Boston Medical Center, Boston University School of Medicine, Boston, MA, United States.
Jonathan MamouLizzi Center for Biomedical Engineering, Riverside Research, New York, NY, United States.
Daniel RohrbachVerasonics, Inc., Kirkland, WA, United States.
Jason SmithDepartment of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY, United States.
Harshal PatelSection of Endocrinology, Diabetes and Nutrition, Boston Medical Center, Boston University School of Medicine, Boston, MA, United States.
Kirk D WallaceGeneral Electric Research, Niskayuna, NY, United States.
Ernest J FeleppaLizzi Center for Biomedical Engineering, Riverside Research, New York, NY, United States.
Stephanie L LeeSection of Endocrinology, Diabetes and Nutrition, Boston Medical Center, Boston University School of Medicine, Boston, MA, United States.
Boston University · USRiverside Research Institute · USBoston Medical Center · USGeneral Electric (United States) · USRensselaer Polytechnic Institute · US

Funding

Characterization of Thyroid Nodules by Quantitative UltrasoundR21CA212744 · NCI · BOSTON MEDICAL CENTER · PI LEE, STEPHANIE L. · 2017 to 2018
$465k
NCI NIH HHS R21 CA212744
6 · The paper itself

Abstract

Background: Gray-scale, B-mode ultrasound (US) imaging is part of the standard clinical procedure for evaluating thyroid nodules (TNs). It is limited by its instrument- and operator-dependence and inter-observer variability. In addition, the accepted high-risk B-mode US TN features are more specific for detecting classic papillary thyroid cancer rather than the follicular variant of papillary thyroid cancer or follicular thyroid cancer. Quantitative ultrasound (QUS) is a technique that can non-invasively assess properties of tissue microarchitecture by exploiting information contained in raw ultrasonic radiofrequency (RF) echo signals that is discarded in conventional B-mode imaging. QUS provides quantitative parameter-value estimates that are a function of the properties of US scatterers and microarchitecture of the tissue. The purpose of this preliminary study was to assess the performance of QUS parameters in evaluating benign and malignant thyroid nodules. Methods: Patients from the Thyroid Health Center at the Boston Medical Center were recruited to participate. B-mode and RF data were acquired and analyzed in 225 TNs (24 malignant and 201 benign) from 208 patients. These data were acquired either before (167 nodules) or after (58 nodules) subjects underwent fine-needle biopsy (FNB). The performance of a combination of QUS parameters (CQP) was assessed and compared with the performance of B-mode risk-stratification systems. Results: CQP produced an ROC AUC value of 0.857 ± 0.033 compared to a value of 0.887 ± 0.033 (p=0.327) for the American College of Radiology Thyroid Imaging, Reporting and Data System (ACR TI-RADS) and 0.880 ± 0.041 (p=0.367) for the American Thyroid Association (ATA) risk-stratification system. Furthermore, using a CQP threshold of 0.263 would further reduce the number of unnecessary FNBs in 44% of TNs without missing any malignant TNs. When CQP used in combination with ACR TI-RADS, a potential additional reduction of 49 to 66% in unnecessary FNBs was demonstrated. Conclusion: This preliminary study suggests that QUS may provide a method to classify TNs when used by itself or when combined with a conventional gray-scale US risk-stratification system and can potentially reduce the need to biopsy TNs.

Indexed as

Adenocarcinoma, FollicularAdultAgedFemaleHumansMaleMiddle AgedRetrospective StudiesRisk AssessmentThyroid Cancer, PapillaryThyroid GlandThyroid NeoplasmsThyroid NoduleUltrasonographyquantitative ultrasoundthyroid biopsythyroid cancerthyroid neoplasmthyroid nodule

Identifiers

PMID34093429
PMCPMC8170470
OpenAlexW3162615486

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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.