Incomplete Thyroid Ultrasound Reports for Patients With Thyroid Nodules: Implications Regarding Risk Assessment and Management

Karkada, Manolhas; Costa, Andreu F.; Imran, Syed Ali; Hart, Robert D.; Bullock, Martin; Ilie, Gabriela; Rajaraman, Murali

doi:10.2214/ajr.18.20056

Cited by 16 publications

(9 citation statements)

References 23 publications

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“…With regards to clinical application, thyroid ultrasound reports often lack reporting standardization, which contributes to variability in thyroid nodule management 59 . The use of structured reports, however, has led to an improvement in inter‐rater reliability within head and neck ultrasonography 60 .…”

Section: Discussionmentioning

confidence: 99%

Inter‐Rater Reliability of Thyroid Ultrasound Risk Criteria: A Systematic Review and Meta‐Analysis

et al. 2022

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Objective: The most commonly employed diagnostic criteria for identifying thyroid nodules include Thyroid Imaging and Reporting Data System (TI-RADS) and American Thyroid Association (ATA) guidelines. The purpose of this systematic review and meta-analysis is to determine the inter-rater reliability of thyroid ultrasound criteria.Methods: We performed a library search of MEDLINE (Ovid), EMBASE (Ovid), and Web of Science for full-text articles published from January 2005 to June 2022. We included full-text primary research articles that used TI-RADS and/or ATA guidelines to evaluate thyroid nodules in adults. These included studies must have calculated inter-rater reliability using any validated metric. The Quality Appraisal for Reliability Studies (QAREL) was used to assess study quality. We planned for a random-effects meta-analysis, in addition to covariate and publication bias analyses. This study was performed in accordance with Preferred Reporting Items for a Systematic Review and Meta-analysis guidelines and registered prior to conduction (International prospective register of systematic reviews-PROSPERO: CRD42021275072).Results: Of the 951 articles identified via the database search, 35 met eligibility criteria. All studies were observational. The most commonly utilized criteria were ACR Thyroid Imaging and Reporting Data System (TI-RADS) and/or ATA criteria, while the majority of studies employed Κ statistics. For ACR TI-RADS, the pooled Κ was 0.51 (95% confidence interval [CI]: 0.42, 0.57; n = 7) while for ATA, the pooled Κ was 0.52 (95% CI: 0.37, 0.67; n = 3). Due to the small number of studies, covariate or publication bias analyses were not performed.Conclusion: Ultrasound criteria demonstrate moderate inter-rater reliability, but these findings are impacted by poor study quality and a lack of standardization.

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Section: Discussionmentioning

confidence: 99%

Inter‐Rater Reliability of Thyroid Ultrasound Risk Criteria: A Systematic Review and Meta‐Analysis

et al. 2022

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“…Sometimes, patients might seek medical services because of dysphagia, wheezing, hoarseness, palpable lumps or enlarged lymph nodes in the neck. At present, ultrasound examination is regarded as the most common method for thyroid disorders, [ 4 ] and has various advantages such as convenience, low cost, radiation-free, and high diagnostic accuracy. Thyroid nodules are discovered in some patients when undergoing medical examinations.…”

Section: Discussionmentioning

confidence: 99%

Ultrasonographic characteristics of thyroid metastasis from clear cell renal cell carcinoma

Tian¹,

Liu³

et al. 2020

Medicine

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Introduction: Thyroid metastasis from clear cell renal cell carcinoma (ccRCC) is a very rare condition, and its ultrasonographic characteristics have not been summarized in the literature. We herein report a case of thyroid metastasis from ccRCC that occurred 11 years after the surgery and the ultrasonographic characteristics of it are described. Patient concerns: A 57-year-old male patient was admitted to our hospital in September 2018 due to discomfort in the neck. No other abnormalities were found during laboratory examination of thyroid function. The previous medical history of the patient included a right nephrectomy for the treatment of ccRCC in June 2007. Diagnosis: Ultrasound examinations revealed multiple thyroid nodules. After nephrectomy, there was no obvious abnormality in the right renal area. Computed tomography (CT) showed an oval lesion with slightly lower density in the right lobe of the thyroid, and the patient was initially diagnosed with nodular goiter. Interventions: Bilateral partial thyroidectomy under general anesthesia was conducted. Intraoperative frozen pathological examination showed clear cell carcinoma in the right lobe of the thyroid gland. Therefore, total thyroidectomy and lymph node dissection in the central neck area were performed. Outcomes: The patient underwent surgical treatment and recovered successfully. The patient was followed up for 2 years with no further metastasis. Conclusion: Ultrasound examination is a safe and convenient screening method. For patients with a renal malignant tumor, if the ultrasound image of thyroid nodule is found to have the characteristics of malignant tumors, the occurrence of metastasis of renal cancer to the thyroid should be highly suspected. Core needle biopsy (CNB) and histopathological diagnosis should be conducted subsequently for early diagnosis.

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“…As a common endocrine cancer, the incidence of thyroid cancer has increased globally over the last 30 years [1]. Moreover, researches have demonstrated that high-resolution ultrasonography can detect thyroid nodules in 19%-68% of populations chosen at random, while the incidence of malignant nodules, i.e., thyroid cancer, is 7%-15% [2]. Therefore, accurate diagnosis of malignant thyroid nodules has always been the focus of clinical attention.…”

Section: Introductionmentioning

confidence: 99%

A Deep Learning-Based Cascade Automatic Classification System for Malignant Thyroid Nodule Recognition in Ultrasound Image

Zhou

Wang

Zhou

et al. 2022

J. Phys.: Conf. Ser.

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As the most common malignancy in the endocrine system, thyroid cancer is often determined based on ultrasound images by professional radiologists based on ultrasound images. In this study, a cascade automatic classification system (CACS) is proposed to accurately achieve automatic segmentation and classification of thyroid nodules, reducing over-reliance on experienced doctors in the diagnosis. Firstly, the Res-UNet is used to segment the region of interest (ROI) of thyroid nodules in ultrasound images. Then, to overcome the limitations of the small sample size of medical training data as well as category imbalance, the modified Conditional Variational Auto-Encoder (CVAE), learning the probability distribution of the ultrasound images, is trained to produce new medical ultrasound images for ROI data augmentation. Finally, we perform the classification task by a three-branch ensemble network combined with clinical diagnostic features of thyroid nodule such as the aspect ratio, internal and external echoes, and edges. The proposed CACS can identify benign and malignant thyroid nodules with an accuracy of 0.892 and an AUC of 0.887, according to testing on real patient data.

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Incomplete Thyroid Ultrasound Reports for Patients With Thyroid Nodules: Implications Regarding Risk Assessment and Management

Cited by 16 publications

References 23 publications

Inter‐Rater Reliability of Thyroid Ultrasound Risk Criteria: A Systematic Review and Meta‐Analysis

Inter‐Rater Reliability of Thyroid Ultrasound Risk Criteria: A Systematic Review and Meta‐Analysis

Ultrasonographic characteristics of thyroid metastasis from clear cell renal cell carcinoma

A Deep Learning-Based Cascade Automatic Classification System for Malignant Thyroid Nodule Recognition in Ultrasound Image

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