Thyroid Imaging Reporting And Data System Research Articles

The 2017 ACR TI-RADS: pictorial essay.

High-resolution ultrasound is the imaging method of choice for the evaluation of thyroid nodules. The method has recently come to be used widely and often, which has increased the rate of thyroid nodule detection. In 2017, the American College of Radiology (ACR) established a risk-stratification system designated the Thyroid Imaging Reporting and Data System (TI-RADS) to be a practical guide for widespread use, with a single lexicon and standardization of ultrasound reports of thyroid nodules. The objective of this study was to present a practical approach, using examples to illustrate the criteria evaluated by the 2017 ACR TI-RADS, in order to help minimize uncertainties regarding its application by sonographers.

Do ACR TI-RADS scores demonstrate unique thyroid molecular profiles?

PurposeThe present study aimed to examine the molecular profiles of cytologically indeterminate thyroid nodules stratified by American College of Radiology Thyroid Imaging Reporting and Data System (TI-RADS) categories and to determine whether certain ultrasonographic features display particular molecular alterations.MethodsA retrospective review was conducted of cases from January 1, 2016 to April 1, 2018. Cases with in-house ultrasonography, fine-needle aspiration Bethesda System for Reporting Thyroid Cytopathology (TBSRTC) diagnoses, molecular testing, and surgery were included. All cases were diagnosed as TBSRTC indeterminate categories. The ultrasound studies were retrospectively reviewed and assigned TI-RADS scores (TR1-TR5) by board-certified radiologists. The final diagnoses were determined based on the surgical resection pathology. Binary logistic regression analysis was used to study whether demographic characteristics, TI-RADS levels, and TBSRTC diagnoses were associated with ThyroSeq molecular results.ResultsEighty-one cases met the inclusion criteria. RAS mutations were the most common alteration across all TI-RADS categories (TR2 2/2; TR3 10/19, TR4 13/44, and TR5 8/16), and did not stratify with any particular TI-RADS category. Only TR4 and TR5 categories displayed more aggressive mutations such as BRAFV600E; and TERT. ThyroSeq results were positively correlated with thyroid malignancy when non-invasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP) was categorized in the malignant category (odds ratio [OR], 6.859; P<0.01), but not when NIFTP was removed from the malignancy category. Echogenicity scores were found to be negatively correlated with ThyroSeq results in thyroid nodules (OR, 0.162; P<0.01).ConclusionHigher-risk molecular alterations tended to stratify with the higher TI-RADS categories.

Ultrasonic Characterization of Primary Squamous Cell Carcinoma of the Thyroid.

To identify the ultrasonographic characteristics of primary squamous cell carcinoma of the thyroid (PSCCT), and to assess the value of the 2015 American Thyroid Association (ATA) guideline and 2017 American College of Radiology (ACR) Thyroid Imaging, Reporting and Data System (TI-RADS) in the evaluation of this disease. Eight patients with 9 PSCCTs over a 20-year study period were enrolled. Ultrasonic characteristics including nodule echogenicity, composition, shape, margin, calcification, size, vascularity, and cervical lymphadenopathy were reviewed. All nodules were then evaluated by 2017 ACR TI-RADS and 2015 ATA guidelines. The average size of PSCCTs was 3.87 ± 1.41 cm. All PSCCTs were hypoechoic or very hypoechoic, solid nodules with intranodular vascularity. The average resistive index (RI) was 0.84 ± 0.18. Near half of PSCCTs (44.4%) demonstrated extrathyroidal extension. Taller-than-wide signs and cervical lymphadenopathy were observed in 33.3% of PSCCTs, and microcalcification was observed in 11.1% of them. All PSCCTs were classified as high suspicion patterns by 2015 ATA and recommended for fine-needle aspiration (FNA). Six PSCCTs (66.7%) were classified as grade 5 by 2017 ACR TI-RADS, while the remaining were grade 4. 88.9% of PSCCTs were recommended for FNA based on 2017 ACR TI-RADS. PSCCT has certain ultrasonic features, including relatively large, hypoechoic, or very hypoechoic solid nodules with intranodular vascularity and extrathyroidal extension. Both 2015 ATA and 2017 ACR TI-RADS could identify PSCCT as suspicious for malignancy.

A Comparison of Different Thyroid Imaging Reporting and Data Systems to Reduce Unnecessary FNAs and Missed Malignancies

Objective: The Thyroid Imaging Reporting and Data System (TIRADS) has been proposed to reduce the number of unnecessary fine needle aspirations (FNA) from thyroid nodules. Materials and Methods: An individual radiologist provided sonographic examinations and FNA on a collection of 188 thyroid nodules. The recommendations based on the TIRADS system, for each nodule, was determined and evaluated against the cytology results. Results: The American College of Radiology (ACR), artificial intelligence (AI), European (EU), and Korean (K) scoring systems reduced FNAs by 53%, 56%, 48%, and 28%, respectively. Among those lesions without a recommendation for immediate FNA, The ACR would have missed four malignant nodules, the AI would have missed four malignant nodules, and K TIRADS would have missed three malignant nodules but with a recommended follow-up imaging. The ACR would have missed three malignant nodules, the AI would have missed four malignant nodules, and EU TIRADS would have missed four malignant nodules, without a recommended follow-up examination. The highest and lowest kappa interrelated agreements were between ACR and AI (0.902) and AI and K (0.448). Conclusion: The ACR and AI TIRADS could substantially decrease the number of FNAs but rely on follow-up imaging. The EU TIRADS reduced the number of FNAs, the least however this system had less dependence on follow-up imaging. The K TIRADS was the most conservative method and the least dependent on follow-up diagnostics.

Comparison of Thyroid Risk Categorization Systems and Fine-Needle Aspiration Recommendations in a Multi-Institutional Thyroid Ultrasound Registry.

The aim of this study was to compare how often fine-needle aspiration (FNA) would be recommended for nodules in unselected, low-risk adult patients referred for sonographic evaluation of thyroid nodules by ACR Thyroid Imaging Reporting and Data System (TI-RADS), the American Thyroid Association guidelines (ATA), Korean Thyroid Imaging Reporting and Data System (K-TIRADS), European Thyroid Imaging Reporting and Data System (EU-TIRADS), and Artificial Intelligence Thyroid Imaging Reporting and Data System (AI-TIRADS). Seven practices prospectively submitted thyroid ultrasound reports on adult patients to the ACR Thyroid Imaging Research Registry between October 2018 and March 2020. Data were collected about the sonographic features of each nodule using a structured reporting template with fields for the five ACR TI-RADS ultrasound categories plus maximum nodule size. The nodules were also retrospectively categorized according to criteria from ACR TI-RADS, the ATA, K-TIRADS, EU-TIRADS, and AI-TIRADS to compare FNA recommendation rates. For 27,933 nodules in 12,208 patients, ACR TI-RADS recommended FNA for 8,128 nodules (29.1%, 95% confidence interval [CI] 0.286-0.296). The ATA guidelines, EU-TIRADS, K-TIRADS, and AI-TIRADS would have recommended FNA for 16,385 (58.7%, 95% CI 0.581-0.592), 10,854 (38.9%, 95% CI 0.383-0.394), 15,917 (57.0%, 95% CI 0.564-0.576), and 7,342 (26.3%, 95% CI 0.258-0.268) nodules, respectively. Recommendation for FNA on TR3 and TR4 nodules was lowest for ACR TI-RADS at 18% and 30%, respectively. ACR TI-RADS categorized more nodules as TR2, which does not require FNA. At the high suspicion level, the FNA rate was similar for all guidelines at 68.7% to 75.5%. ACR TI-RADS recommends 25% to 50% fewer biopsies compared with ATA, EU-TIRADS, and K-TIRADS because of differences in size thresholds and criteria for risk levels.

Prediction of central compartment nodal metastases in papillary thyroid cancer using TI-RADS score, blood flow, and multifocality.

The relationship between the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) and the risk of lymph node metastases in papillary thyroid cancer (PTC) could improve the detection rate of lymph node metastases in thyroid cancer and provide a scientific basis for clinical diagnosis. To evaluate the risk of lymph node metastases of PTC associated with the score from ACR TI-RADS adjusted for other correlative factors. A total of 560 patients with pathologically confirmed PTC were included in the study and classified into a metastases group and a non-metastases group. Clinical and pathological manifestations of the patients were collected. The median TI-RADS score was 13 (p25-p75 = 11-14) among the patients with lymph node metastases, higher than those without metastases 9 (8-10) (P < 0.001). Multiple logistic regression indicated that TI-RADS score (odds ratio [OR] = 2.204), male sex (OR = 2.376), multifocality (OR = 4.170), and rich blood flow (OR = 3.656) were risk factors for lymph node metastases in patients with thyroid carcinoma. Some related factors such as TI-RADS score, age(<45years old), male, multifocality and rich blood flow were related to lymph node metastases in the central area of the neck which could provide therapeutic strategy for further treatment. it is not just the TI-RADS score but also multifocality, blood flow, and sex that influence the prediction of the risk of PTC central lymph node metastases.

The impact of the use of the ACR-TIRADS as a screening tool for thyroid nodules in a cancer center.

The Thyroid Imaging Reporting and Data System (TIRADS) was created to assess risk of thyroid nodules through ultrasound. Plenty classifications methods for thyroid nodules have already been created, but none of them have yet achieved global utilization. This study analyzed the performance of the American College of Radiology (ACR) TIRADS, its reproducibility and the impact of its utilization as a screening method in a large Cancer Center cohort. Thyroid nodules which underwent fine-needle aspiration (FNA) in a 1-year period were selected, with their ultrasound images retrospectively classified according to the ACR TI-RADS. Cytological evaluation of the nodules and final histology (whenever available) was used to assess risk of neoplasm (RON) and risk of malignancy (ROM) associated to each ACR-TIRADS category. Further analyses were also carried out according to recommendation or not of FNA by the ACR-TIRADS and nodule size. Inter-observer agreement for the system was also assessed. A total of 1112 thyroid nodules were included. RON for each category according to final cytological diagnosis was 0% for TR1 and TR2, 2.1% for TR3; 15.6% for TR4 and 68.9% for TR5. No significant difference was observed between the RON of the categories for cases above or below 1.0 cm. Nodules that met the criteria for FNA had 3 times greater chance of a positive outcome. Substantial agreement (kappa 0.77) was seen between two different observers. ACR TI-RADS scoring system has demonstrated to be an accurate method to stratify thyroid nodules in a Cancer Center, with a high reproducibility.

Effect of the size of benign thyroid degenerative nodules on ACR TI-RADS categories.

Our study aimed to identify ultrasound characteristics of benign thyroid degenerative nodules and reveal the correlation between their sizes and 2017 ACR Thyroid Imaging Reporting and Data System (TI-RADS) categories. A total of 174 thyroid degenerative nodules were divided into three groups: 0.5-1cm group (70 nodules), 1-2cm group (27 nodules), and > 2cm group (77 nodules). The ultrasound appearance of each nodule was evaluated, and the ACR TI-RADS scores and levels of the nodules were also calculated and compared among the three groups. The ultrasound appearance of degenerative nodules of different sizes is diversified, and the 0.5-1cm group tended to have more malignant features and higher TI-RADS scores and categories. The scatterplot of Spearman correlation showed a significant negative correlation between the nodule sizes and TI-RADS categories. The 2017 ACR TI-RADS, which recommends fine-needle aspiration according to the nodule size and category, is still useful in managing these nodules, and following the clinical recommendations of ACR TI-RADS is necessary.

Diagnostic accuracy of TI-RADS classification in differentiating benign and malignant thyroid nodules-a study from Southern Punjab, Pakistan

&lt;p&gt;&lt;strong&gt;Background and Objective:&lt;/strong&gt; Thyroid imaging reporting and data system (TI-RADS) is developed to determine the risk of malignancy in patients with thyroid nodules. The aim of this study was to determine the diagnostic accuracy of TI-RADS classification for diagnosing malignant thyroid nodules taking Fine needle aspiration cytology (FNAC) as a gold standard in the local population.&lt;/p&gt;&#x0D; &lt;p&gt;&lt;strong&gt;Methods:&lt;/strong&gt; In this cross-sectional validation study, 201 patients presenting with thyroid nodules at the Department of Radiology, Bakhtawar Amin Hospital Multan, Pakistan from July 2020 to December 2020 were included. In all patients, thyroid nodules were evaluated on grey scale (B-mode) modality. TI-RADS score was calculated for each patient. Patients with TI-RADS score 4 and 5 were labelled as having malignant nodules. After that FNAC samples were taken and sent for histopathologic evaluation of thyroid nodules. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of TI-RADS taking FNAC as a gold standard were determined.&lt;/p&gt;&#x0D; &lt;p&gt;&lt;strong&gt;Results:&lt;/strong&gt; The mean age of the patients was 47.8 &amp;plusmn; 4.5 years; there were 129 (67.2%) women and 72 (35.82%) men. There were 42 patients who tested true positive and 36 patients tested false positive and 12 patients were false negative and 111 patients true negative. The TIRADS sensitivity was 77.8%, specificity was 75.5%, PPV was 53.8%, and NPV 90.2%. the diagnostic accuracy was 76.1%.&lt;/p&gt;&#x0D; &lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;Differentiating benign thyroid nodules from malignant using the TI-RADS score has a high diagnostic accuracy. Our study results support the TIRADS as a first-line imaging evaluation for diagnosis of thyroid malignancy.&lt;/p&gt;

Machine Learning Assisted Doppler Features for Enhancing Thyroid Cancer Diagnosis: A Multi-Cohort Study.

This pilot study aims at exploiting machine learning techniques to extract color Doppler ultrasound (CDUS) features and to build an artificial neural network (ANN) model based on these CDUS features for improving the diagnostic performance of thyroid cancer classification. A total of 674 patients with 712 thyroid nodules (TNs) (512 from internal dataset and 200 from external dataset) were randomly selected in this retrospective study. We used ANN to build a model (TDUS-Net) for classifying malignant and benign TNs using both the automatically extracted quantitative CDUS features (whole ratio, intranodular ratio, peripheral ratio, and number of vessels) and gray-scale ultrasound (US) features defined by the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS). Then, we compared the diagnostic performance of the model, the performance of another ANN model based on the gray-scale US features alone (TUS-Net), and that of radiologists. The TDUS-Net (0.898, 95% CI: 0.868-0.922) achieved a higher area under the curve (AUC) than that of TUS-Net (0.881, 95% CI: 0.850-0.908) in the internal tests. Compared with radiologists, TDUS-Net (AUC: 0.925, 95% CI: 0.880-0.958) performed better than radiologists (AUC: 0.810, 95% CI: 0.749-0.862) in the external tests. Applying a machine learning model by combining both gray-scale US features and CDUS features can achieve comparable or even higher performance than radiologists in classifying TNs.

Construction and Validation of a Predictive Nomogram Based on Ultrasound for Lymph Node Metastasis of Papillary Thyroid Carcinoma in the Cervical Central Region.

To establish and validate a nomogram for predicting lymph node metastasis (LNM) of papillary thyroid carcinoma (PTC) in the cervical central region. This retrospective study included 287 PTC patients with 309 nodules treated from December 2018 to May 2020 at our hospital. The cohort was divided randomly into a training set and a testing set according to a 7:3 ratio. The training set contained 216 nodules, and the testing set contained 93 nodules. The nomogram was developed using the training set, and the data of the testing set were used to validate the performance of nomogram. The predictive accuracy and discriminative ability of the nomogram were determined by concordance index (C-index) and calibration curve. The study showed multifocality, thyroid lesion size, and American College of Radiology Thyroid Imaging, Reporting and Data System (TI-RADS) score were significantly independently associated with LNM in the cervical central region. In the testing set, the calibration curve showed that the nomogram had good discrimination with a C-index of 0.775 (95% confidence interval, 0.680-0.869) and adequate calibration ( P = 0.808). By decision curve analysis and clinical impact curve analysis, the nomogram was shown to have a satisfactory net benefit between thresholds of 0.40 and 0.75. The nomogram can be used for predicting LNM of PTC in the cervical central region and may provide valuable guidance for planning the surgical treatment of PTC patients.

Diagnostic value of 2017 ACR Thyroid Imaging Reporting and Data System (TI-RADS) combined with fine needle aspiration biopsy in thyroid nodules

To evaluate diagnostic value of Thyroid Imaging Reporting and Data System published by American College of Radiology (ACR TI-RADS) in 2017, ultrasound-guided fine-needle aspiration (US-FNA), and the combination of both methods in differentiation between benign and malignant thyroid nodules. The data of US-FNA and ACR TI-RADS are collected from 159 patients underwent thyroid surgery in our hospital, which include a total of 178 thyroid nodules. A Bethesda System for Reporting Thyroid Cytopathology category of ≥IV and an ACR TI-RADS category ≥4 are regarded as diagnosis standards for malignancy in US-FNA and ACR TI-RADS, respectively. The pathological results after surgery are considered as the gold standard. The sensitivity, specificity, accuracy, positive predictive value and negative predictive value of the ACR TI-RADS, US-FNA and the combination of both methods for the differential diagnosis of thyroid nodules are calculated, respectively. The sensitivity, specificity and accuracy of ACR TI-RADS are 85.4%, 37.5%and 72.5%, respectively. The sensitivity, specificity and accuracy of US-FNA are 70.0%, 100%and 78.1%, respectively. After combining these two methods, the sensitivity, specificity and accuracy increase to 99.23%, 37.50%and 82.58%, respectively. The sensitivity of ACR TI-RADS is higher than that of US-FAN, and the sensitivity of combining these two methods is also higher than that of using ACR TI-RADS and US-FNA alone. The established ACR TI-RADS can help in selecting the target during nodule puncture, while the combination of ACR TI-RADS and US-FAN can further improve diagnostic ability for detecting malignant thyroid nodules.

Use of Diagnostic Criteria from ACR and EU-TIRADS Systems to Improve the Performance of Cytology in Thyroid Nodule Triage.

Simple SummaryFrom a prospective series of 480 thyroid nodules, we compared the performances of the American College of Radiology (ACR) and the European Thyroid Association (EU) scoring systems in triaging thyroid nodules for fine-needle aspiration (FNA). FNA was recommended on 46.5% and 51.9% of the nodules using the ACR and EU-TIRADS scores, respectively. The ACR system demonstrated a higher specificity as compared to the EU-TIRADS (59.0% vs. 52.4%, p = 0.0012) in predicting ≥TIR3A/III (SIAPEC/Bethesda) nodules. Moreover, specific radiological features (i.e., echogenic foci and margins), combined with the cytological classes improved the specificity (97.5% vs. 91%, p < 0.0001) and positive predictive value (77.5% vs. 50.7%, p < 0.0001) of the cytology alone, maintaining an excellent sensitivity and negative predictive value.Objective: The American College of Radiology (ACR) and the European Thyroid Association (EU) have proposed two scoring systems for thyroid nodule classification. Here, we compared the ability of the two systems in triaging thyroid nodules for fine-needle aspiration (FNA) and tested the putative role of an approach that combines ultrasound features and cytology for the detection of malignant nodules. Design and Methods: The scores obtained with the ACR and EU Thyroid Imaging Reporting and Data Systems (TIRADS) from a prospective series of 480 thyroid nodules acquired from 435 subjects were compared to assess their performances in FNA triaging on the final cytological diagnosis. The US features that showed the highest contribution in discriminating benign nodules from malignancies were combined with cytology to improve its diagnostic performance. Results: FNA was recommended on 46.5% and 51.9% of the nodules using the ACR and EU-TIRADS scores, respectively. The ACR system demonstrated a higher specificity as compared to the EU-TIRADS (59.0% vs. 52.4%, p = 0.0012) in predicting ≥ TIR3A/III (SIAPEC/Bethesda) nodules. Moreover, specific radiological features (i.e., echogenic foci and margins), combined with the cytological classes improved the specificity (97.5% vs. 91%, p < 0.0001) and positive predictive values (77.5% vs. 50.7%, p < 0.0001) compared to cytology alone, especially in the setting of indeterminate nodules (TIR3A/III and TIR3B/IV), maintaining an excellent sensitivity and negative predictive value. Conclusions: The ACR-TIRADS system showed a higher specificity compared to the EU-TIRADS in triaging thyroid nodules. The use of specific radiological features improved the diagnostic ability of cytology.

Exploring the Performance of Ultrasound Risk Stratification Systems in Thyroid Nodules of Pediatric Patients.

Simple SummaryAlthough pediatric thyroid nodules are uncommon, they need high clinical expertise and alert since they carry a greater risk of malignancy compared with those presenting in adults. Since there are no specific ultrasound (US)-based risk stratification systems (RSSs) for pediatric thyroid nodules, the application of adult-based RSSs in the pediatric population could represent a step forward in the care of children and adolescents with thyroid nodules. We compared the diagnostic performance of the main US-based RSSs *i.e., the American College of Radiology (ACR), European (EU), Korean (K) Thyroid Imaging Reporting and Data Systems (TI-RADSs) and ATA US RSS criteria) for detecting malignant thyroid lesions in pediatric patients. For ACR TI-RADS and EU-TIRADS, we found a sensitivity of 41.7%, and, for K-TIRADS and ATA US RSS, we found a sensitivity of 50%. The four US-based RSSs (i.e., ACR-TIRADS, EU-TIRADS, K-TIRADS, and ATA US RSS) have suboptimal performance in managing pediatric patients with thyroid nodules, with one-half of cancers without indication for FNA according to their recommendations. All thyroidologists, as well as the panelists of next TIRADSs, should be aware of these findings.Neck ultrasound (nUS) is the cornerstone of clinical management of thyroid nodules in pediatric patients, as well as adults. The current study was carried out to explore and compare the diagnostic performance of the main US-based risk stratification systems (RSSs) (i.e., the American College of Radiology (ACR), European (EU), Korean (K) TI-RADSs and ATA US RSS criteria) for detecting malignant thyroid lesions in pediatric patients. We conducted a retrospective analysis of consecutive children and adolescents who received a diagnosis of thyroid nodule. We included subjects with age <19 years having thyroid nodules with benign cytology/histology or final histological diagnosis. We excluded subjects with (a) a previous malignancy, (b) a history of radiation exposure, (c) cancer genetic susceptibility syndromes, (d) lymph nodes suspicious for metastases of thyroid cancer at nUS, (e) a family history of thyroid cancer, or (f) cytologically indeterminate nodules without histology and nodules with inadequate cytology. We included 41 nodules in 36 patients with median age 15 years (11–17 years). Of the 41 thyroid nodules, 29 (70.7%) were benign and 12 (29.3%) were malignant. For both ACR TI-RADS and EU-TIRADS, we found a sensitivity of 41.7%. Instead, for both K-TIRADS and ATA US RSS, we found a sensitivity of 50%. The missed malignancy rate for ACR-TIRADS and EU-TIRADS was 58.3%, while that for K-TIRADS and ATA US RSS was 50%. The unnecessary FNA prevalence for ACR TI-RADS and EU-TIRADS was 58.3%, while that for K-TIRADS and ATA US RSS was 76%. Our findings suggest that the four US-based RSSs (i.e., ACR-TIRADS, EU-TIRADS, K-TIRADS, and ATA US RSS) have suboptimal performance in managing pediatric patients with thyroid nodules, with one-half of cancers without indication for FNA according to their recommendations.

Use of an Easily Applicable Thyroid Imaging-Reporting and Data System (TI-RADS): Our Kwak TI-RADS Experience

Background: Early detection of malignant thyroid nodules is possible using ultrasonography (US)-guided fine needle aspiration biopsy (US-FNAB), which is a minimally invasive and easily applicable method. There are several guidelines based on the US findings, including the Thyroid Imaging-Reporting and Data System (TI-RADS), to identify patients requiring FNAB or patients with nodules suspicious of malignancy. Objectives: To emphasize the importance of the easily applicable Kwak TI-RADS classification system. Patients and Methods: In this cross-sectional study, the radiological and pathological findings of 641 consecutive patients, who underwent US-FNAB in our center, were retrospectively evaluated. The relationship between the cytological/histopathological results and the US findings was investigated using univariate and multivariate analyses. The results were also compared with the data in the literature. Results: In the univariate analysis, US features, including the presence of a solid component, hypoechogenicity, microlobulation or irregular margins, microcalcifications, and a taller-than-wide shape, were significantly associated with malignancy (P &lt; 0.05). However, in the multivariate analysis, only hypoechogenicity and a taller-than-wide shape significantly contributed to the diagnosis of malignancy (P &lt; 0.05). The malignancy rates of TI-RADS 3, 4a, and 4b lesions were lower in the present study compared to the literature. Conclusions: The US features, including the presence of a solid component, microcalcifications, hypoechogenicity, microlobulation or irregular margins, and a taller-than-wide shape, must be evaluated during US examinations. Besides, the widespread use of Kwak TI-RADS classification system, similar to the Breast Imaging-Reporting and Data System (BI-RADS), should be encouraged to provide a common tool for clinicians and prevent unnecessary surgical procedures.

Exploring the Value of Radiomics Features Based on B-Mode and Contrast-Enhanced Ultrasound in Discriminating the Nature of Thyroid Nodules.

BackgroundWith the improvement of ultrasound imaging resolution and the application of various new technologies, the detection rate of thyroid nodules has increased greatly in recent years. However, there are still challenges in accurately diagnosing the nature of thyroid nodules. This study aimed to evaluate the clinical application value of the radiomics features extracted from B-mode ultrasound (B-US) images combined with contrast-enhanced ultrasound (CEUS) images in the differentiation of benign and malignant thyroid nodules by comparing the diagnostic performance of four logistic models.MethodsWe retrospectively collected and ultimately included B-US images and CEUS images of 123 nodules from 123 patients, and then extracted the corresponding radiomics features from these images respectively. Meanwhile, a senior radiologist combined the thyroid imaging reporting and data system (TI-RADS) and the enhancement pattern of the ultrasonography to make a graded diagnosis of the malignancy of these nodules. Next, based on these radiomics features and grades, logistic regression was used to help build the models (B-US radiomics model, CEUS radiomics model, B-US+CEUS radiomics model, and TI-RADS+CEUS model). Finally, the study assessed the diagnostic performance of these radiomics features with a comparison of the area under the curve (AUC) of the receiver operating characteristic curve of four logistic models for predicting the benignity or malignancy of thyroid nodules.ResultsThe AUC in the differential diagnosis of the nature of thyroid nodules was 0.791 for the B-US radiomics model, 0.766 for the CEUS radiomics model, 0.861 for the B-US+CEUS radiomics model, and 0.785 for the TI-RADS+CEUS model. Compared to the TI-RADS+CEUS model, there was no statistical significance observed in AUC between the B-US radiomics model, CEUS radiomics model, B-US+CEUS radiomics model, and TI-RADS+CEUS model (P>0.05). However, a significant difference was observed between the single B-US radiomics model or CEUS radiomics model and B-US+CEUS radiomics model (P<0.05).ConclusionIn our study, the B-US radiomics model, CEUS radiomics model, and B-US+CEUS radiomics model demonstrated similar performance with the TI-RADS+CEUS model of senior radiologists in diagnosing the benignity or malignancy of thyroid nodules, while the B-US+CEUS radiomics model showed better diagnostic performance than single B-US radiomics model or CEUS radiomics model. It was proved that B-US radiomics features and CEUS radiomics features are of high clinical value as the combination of the two had better diagnostic performance.

Risk stratification of indeterminate thyroid nodules using ultrasound and machine learning algorithms.

Indeterminate thyroid nodules (Bethesda III) are challenging to characterize without diagnostic surgery. Auxiliary strategies including molecular analysis, machine learning models, and ultrasound grading with Thyroid Imaging, Reporting and Data System (TI-RADS) can help to triage accordingly, but further refinement is needed to prevent unnecessary surgeries and increase positive predictive values. Retrospective review of 88 patients with Bethesda III nodules who had diagnostic surgery with final pathological diagnosis. Each nodule was retrospectively scored through TI-RADS. Two deep learning models were tested, one previously developed and trained on another data set, mainly containing determinate cases and then validated on our data set while the other one trained and tested on our data set (indeterminate cases). The mean TI-RADS score was 3 for benign and 4 for malignant nodules (p = .0022). Radiological high risk (TI-RADS 4,5) and low risk (TI-RADS 2,3) categories were established. The PPV for the high radiological risk category in those with >10 mm nodules was 85% (CI: 70%-93%). The NPV for low radiological risk in patients >60 years (mean age was 100% (CI: 83%-100%). The area under the curve (AUC) value of our novel classifier was 0.75 (CI: 0.62-0.84) and differed significantly from the chance-level (p < .00001). Novel radiomic and radiologic strategies can be employed to assist with preoperative diagnosis of indeterminate thyroid nodules.

Nomogram Combining Radiomics With the American College of Radiology Thyroid Imaging Reporting and Data System Can Improve Predictive Performance for Malignant Thyroid Nodules.

PurposeTo develop and validate a nomogram combining radiomics of B-mode ultrasound (BMUS) images and the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) for predicting malignant thyroid nodules and improving the performance of the guideline.MethodA total of 451 thyroid nodules referred for surgery and proven pathologically at an academic referral center from January 2019 to September 2020 were retrospectively collected and randomly assigned to training and validation cohorts (7:3 ratio). A nomogram was developed through combining the BMUS radiomics score (Rad-Score) with ACR TI-RADS score (ACR-Score) in the training cohort; the performance of the nomogram was assessed with respect to discrimination, calibration, and clinical application in the validation and entire cohorts.ResultsThe ACR-Rad nomogram showed good calibration and yielded an AUC of 0.877 (95% CI 0.836–0.919) in the training cohort and 0.864 (95% CI 0.799–0.931) in the validation cohort, which were significantly better than the ACR-Score model (p < 0.001 and 0.031, respectively). The significantly improved AUC, net reclassification index (NRI), and integrated discriminatory improvement (IDI) of the nomogram were found for both senior and junior radiologists (all p < 0.001). Decision curve analysis indicated that the nomogram was clinically useful. When cutoff values for 50% predicted malignancy risk (ACR-Rad_50%) were applied, the nomogram showed increased specificity, accuracy and positive predictive value (PPV), and decreased unnecessary fine-needle aspiration (FNA) rates in comparison to ACR TI-RADS.ConclusionThe ACR-Rad nomogram has favorable value in predicting malignant thyroid nodules and improving performance of the ACR TI-RADS for senior and junior radiologists.

Value of Thyroid Imaging Reporting and Data System in Initial Bethesda Category III Thyroid Nodules

Background. To evaluate the role of Thyroid Imaging Reporting and Data System (TI-RADS) in predicting malignancy for cytological Bethesda system III nodules. Method. The study included 188 thyroid nodules with first Bethesda system III cytology on surgery or repeat FNA. Patients' clinicopathologic parameters and ultrasonographic (US) nodule characteristics were evaluated according to benignity and malignancy. Using the TI-RADS classification system, thyroid nodules were categorized. Results. The size of malignant nodules was significantly lower than that of benign nodules ( P &lt; 0.001). Thyroid nodules associated with concomitant thyroid carcinoma had a significantly increased risk of malignancy ( P &lt; 0.001). Univariate analysis indicated that there were significant differences in the images of benign and malignant nodules in terms of solid composition, hypoechogenicity or marked hypoechogenicity, a taller-than-wide or irregular shape, ill-defined margins, and microcalcifications presence ( P &lt; 0.05). TI-RADS categories 4c (OR = 8.3, 95% CI 3.8–18.1; P = 0.043) and 5 (OR = 9.4; 95% CI 1.2–74.2; P = 0.026) were predictive for malignancy. Conclusions. The TI-RADS US evaluation may assist the physician in deciding whether to proceed with follow-up, repeating FNA, or surgical intervention.

A Computer-Aided Diagnosis System and Thyroid Imaging Reporting and Data System for Dual Validation of Ultrasound-Guided Fine-Needle Aspiration of Indeterminate Thyroid Nodules.

PurposeThe fully automatic AI-Sonic computer-aided design (CAD) system was employed for the detection and diagnosis of benign and malignant thyroid nodules. The aim of this study was to investigate the efficiency of the AI-Sonic CAD system with the use of a deep learning algorithm to improve the diagnostic accuracy of ultrasound-guided fine-needle aspiration (FNA).MethodsA total of 138 thyroid nodules were collected from 124 patients and diagnosed by an expert, a novice, and the Thyroid Imaging Reporting and Data System (TI-RADS). Diagnostic efficiency and feasibility were compared among the expert, novice, and CAD system. The application of the CAD system to enhance the diagnostic efficiency of novices was assessed. Moreover, with the experience of the expert as the gold standard, the values of features detected by the CAD system were also analyzed. The efficiency of FNA was compared among the expert, novice, and CAD system to determine whether the CAD system is helpful for the management of FNA.ResultIn total, 56 malignant and 82 benign thyroid nodules were collected from the 124 patients (mean age, 46.4 ± 12.1 years; range, 12–70 years). The diagnostic area under the curve of the CAD system, expert, and novice were 0.919, 0.891, and 0.877, respectively (p < 0.05). In regard to feature detection, there was no significant differences in the margin and composition between the benign and malignant nodules (p > 0.05), while echogenicity and the existence of echogenic foci were of great significance (p < 0.05). For the recommendation of FNA, the results showed that the CAD system had better performance than the expert and novice (p < 0.05).ConclusionsPrecise diagnosis and recommendation of FNA are continuing hot topics for thyroid nodules. The CAD system based on deep learning had better accuracy and feasibility for the diagnosis of thyroid nodules, and was useful to avoid unnecessary FNA. The CAD system is potentially an effective auxiliary approach for diagnosis and asymptomatic screening, especially in developing areas.