Evidence map›Paper›PMID 38872150›Full record

ArticleCancer imaging : the official publication of the International Cancer Imaging Society2024

Thyroid imaging reporting and data system with MRI morphological features for thyroid nodules: diagnostic performance and unnecessary biopsy rate.

Tingting Zheng, Yuan Zhang, Hao Wang, Lang Tang, Xiaoli Xie, Qingyin Fu, Pu-Yeh Wu, Bin Song

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Article in Cancer imaging : the official publication of the International Cancer Imaging Society, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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5citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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5 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Tingting Zheng *Department of Radiology, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, Shanghai, 201199, China.
Yuan Zhang *Department of Radiology, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, Shanghai, 201199, China.
Hao WangDepartment of Radiology, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, Shanghai, 201199, China.
Lang TangDepartment of Ultrasound, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, Shanghai, 201199, China.
Xiaoli XieDepartment of Pathology, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, Shanghai, 201199, China.
Qingyin FuDepartment of Ultrasound, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, Shanghai, 201199, China.
Pu-Yeh WuGE Healthcare, MR Research China, Beijing, China.
Bin SongDepartment of Radiology, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, Shanghai, 201199, China. songbin@fudan.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo assess MRI-based morphological features in improving the American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS) for categorizing thyroid nodules.

methodsA retrospective analysis was performed on 728 thyroid nodules (453 benign and 275 malignant) that postoperative pathology confirmed. Univariate and multivariate logistic regression analyses were used to find independent predictors of MRI morphological features in benign and malignant thyroid nodules. The improved method involved increasing the ACR-TIRADS level by one when there are independent predictors of MRI-based morphological features, whether individually or in combination, and conversely decreasing it by one. The study compared the performance of conventional ACR-TIRADS and different improved versions.

resultsAmong the various MRI morphological features analyzed, restricted diffusion and reversed halo sign were determined to be significant independent risk factors for malignant thyroid nodules (OR = 45.1, 95% CI = 23.2-87.5, P < 0.001; OR = 38.0, 95% CI = 20.4-70.7, P < 0.001) and were subsequently included in the final assessment of performance. The areas under the receiver operating characteristic curves (AUCs) for both the conventional and four improved ACR-TIRADSs were 0.887 (95% CI: 0.861-0.909), 0.945 (95% CI: 0.926-0.961), 0.947 (95% CI: 0.928-0.962), 0.945 (95% CI: 0.926-0.961) and 0.951 (95% CI: 0.932-0.965), respectively. The unnecessary biopsy rates for the conventional and four improved ACR-TIRADSs were 62.8%, 30.0%, 27.1%, 26.8% and 29.1%, respectively, while the malignant missed diagnosis rates were 1.1%, 2.8%, 3.7%, 5.4% and 1.2%.

conclusionsMRI morphological features with ACR-TIRADS has improved diagnostic performance and reduce unnecessary biopsy rate while maintaining a low malignant missed diagnosis rate.

Indexed as

Magnetic Resonance ImagingThyroid NoduleAdolescentAdultAgedBiopsyFemaleHumansMaleMiddle AgedRetrospective StudiesROC CurveThyroid GlandUnnecessary ProceduresYoung AdultAmerican College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS)Diagnostic performanceMagnetic resonance imaging (MRI)Risk stratificationThyroid nodule

Identifiers

PMID38872150
PMCPMC11177423

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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.