Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 1,101

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Thyroid Imaging Reporting and Data System for US Features of Nodules: A Step in Establishing Better Stratification of Cancer Risk

Open access
Kwak, Jin Young, Han, Kyung Hwa, Yoon, Jung Hyun, Moon, Hee Jung, Son, Eun Ju, Park, So Hee, Jung, Hyun Kyung, Choi, Ji Soo, Kim, Bo Mi, Kim, Eun-Kyung·2011·Radiology

Abstract

PURPOSE: To develop a practical thyroid imaging reporting and data system (TIRADS) with which to categorize thyroid nodules and stratify their malignant risk. MATERIALS AND METHODS: The institutional review board approved this retrospective study, and the requirement to obtain informed consent for the review of images and records was waived. From May to December 2008, ultrasonographically (US)-guided fine-needle aspiration biopsy (FNAB) was performed in 3674 focal thyroid nodules in 3414 consecutive patients. The study included the 1658 thyroid nodules (≥1 cm in maximum diameter at US) in 1638 patients (1373 women, 265 men) for which pathologic diagnosis or follow-up findings were available. Univariate and multivariate analyses with generalized estimating equations were performed to investigate the relationship between suspicious US features and thyroid cancer. A score for each significant factor was assigned and multiplied by the β coefficient obtained for each significant factor from multivariate logistic regression analysis. Scores for each significant factor were then added, resulting in an equation that fitted the probability of malignancy in thyroid nodules. The authors evaluated the fitted probability by using a regression equation; the risk of malignancy was determined according to the number of suspicious US features. RESULTS: The following US features showed a significant association with malignancy: solid component, hypoechogenicity, marked hypoechogenicity, microlobulated or irregular margins, microcalcifications, and taller-than-wide shape. As the number of suspicious US features increased, the fitted probability and risk of malignancy also increased. Positive predictive values according to the number of suspicious US features were significantly different (P < .001). CONCLUSION: Risk stratification of thyroid malignancy by using the number of suspicious US features allows for a practical and convenient TIRADS.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1148/radiol.11110206

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 1 references

Cited by

See all 1,101

Metadata

Authors
Kwak, J. Y., Han, K. H., Yoon, J. H., Moon, H. J., Son, E. J., Park, S. H., Jung, H. K., Choi, J. S., Kim, B. M., & Kim, E.-K.
Venue
Radiology
Published
2011-09
Volume
260
Issue
3
Pages
892-899
ISSN
  • 0033-8419 (ISSN-L)
  • 1527-1315
OpenAlex
W2131867827
Cited by
1,101
References
1
FWCI
16.95
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Thyroid Imaging Reporting and Data System for US Features of Nodules: A Step in Establishing Better Stratification of Cancer Risk. https://app.cochat.ai/papers/10.1148/radiol.11110206
The paper
Kwak, J. Y., Han, K. H., Yoon, J. H., Moon, H. J., Son, E. J., Park, S. H., Jung, H. K., Choi, J. S., Kim, B. M., & Kim, E.-K. (2011). Thyroid Imaging Reporting and Data System for US Features of Nodules: A Step in Establishing Better Stratification of Cancer Risk. Radiology. https://doi.org/10.1148/radiol.11110206

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.