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Advanced Ultrasound Application - Impact on Presurgical Risk Stratification of the Thyroid Nodules.

ABSTRACT: Aim:Current major guidelines recommend risk stratification of the thyroid nodules, after each diagnostic evaluation, in order to focus attention on potentially risky nodules. The main aim of our study was to evaluate the performance of combined advanced ultrasound techniques in this process, compared with conventional stratification models, in order to reduce unnecessary fine-needle biopsies, respectively, surgery. Material and Methods:We evaluated 261 cases (261 nodules) using conventional ultrasound (2B), real-time Doppler evaluation (4D) respectively, real-time elastography, using a linear multifrequency probe and a linear volumetric probe (Hitachi Prerius Machine, Hitachi Inc, Japan). All the nodules were classified using a risk stratification model comprising seven conventional US characteristics, two 4 D characteristics and a color map RTE aspect. The results were compared with the pathology results, considered the golden standard diagnosis. Results:The prevalence of malignant nodules was 21.83% (57 cases). Conventional risk classification generated: 106 low-risk cases, 113 intermediate-risk and 42 high-risk cases. Our proposed risk classification changes the conventional risk classification with a risk upgrade in 27 cases and with a risk downgrade in 69 cases. The diagnostic quality of the combined risk stratification model was better, considering a low-risk category predictive for benignancy and a high category predictive for malignancy: Sensitivity: 80.88% versus 49.01%, respectively, Specificity: 91.22% versus 54.38. The diagnostic power differences were observed regardless of the nodule size. Conclusion:Advanced ultrasound techniques did add diagnostic value in the presurgical risk assessment of the thyroid nodules.

SUBMITTER: Stoian D

PROVIDER: S-EPMC6996024 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Advanced Ultrasound Application - Impact on Presurgical Risk Stratification of the Thyroid Nodules.

Stoian Dana D Ivan Viviana V Sporea Ioan I Florian Varcus V Mozos Ioana I Navolan Dan D Nemescu Dragos D

Therapeutics and clinical risk management 20200121

<h4>Aim</h4>Current major guidelines recommend risk stratification of the thyroid nodules, after each diagnostic evaluation, in order to focus attention on potentially risky nodules. The main aim of our study was to evaluate the performance of combined advanced ultrasound techniques in this process, compared with conventional stratification models, in order to reduce unnecessary fine-needle biopsies, respectively, surgery.<h4>Material and methods</h4>We evaluated 261 cases (261 nodules) using co ...[more]

PMID: 32099374

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Project description:ObjectivesTo investigate the ability of the currently used ultrasound-based malignancy risk stratification systems for thyroid neoplasms (ATA, AACE/ACE/AME, K-TIRADS, EU-TIRADS, ACR-TIRADS and C-TIRADS) in distinguishing follicular thyroid carcinoma (FTC) from follicular thyroid adenoma (FTA). Additionally, we evaluated the ability of these systems in correctly determining the indication for biopsy.MethodsThree hundred twenty-nine follicular neoplasms with definitive postoperative histopathology were included. The nodules were categorized according to each of six stratification systems, based on ultrasound findings. We dichotomized nodules into the positive predictive group of FTC (high and intermediate risk) and negative group of FTC based on the classification results. Missed biopsy was defined as neoplasms that were diagnosed as FTCs but for which biopsy was not indicated based on lesion classification. Unnecessary biopsy was defined as neoplasms that were diagnosed as FTAs but for whom biopsy was considered indicated based on classification. The diagnostic performance and missed and unnecessary biopsy rates were evaluated for each stratification system.ResultsThe area under the curve of each system for distinguishing follicular neoplasms was < 0.700 (range, 0.511-0.611). The missed biopsy rates were 9.0-22.4%. The missed biopsy rates for lesions ≤ 4 cm and lesions sized 2-4 cm were 16.2-35.1% and 0-20.0%, respectively. Unnecessary biopsy rates were 65.3-93.1%. In ≤ 4 cm group, the unnecessary biopsy rates were 62.2-89.7%.ConclusionThe malignancy risk stratification systems can select appropriate nodules for biopsy in follicular neoplasms, while they have limitations in distinguishing follicular neoplasms and reducing unnecessary biopsy. Specific stratification systems and recommendations should be established for follicular neoplasms.Key points• Current ultrasound-based malignancy risk stratification systems of thyroid nodules had low efficiency in the characterization of follicular neoplasms. • The adopted stratification systems showed acceptable performance for selecting FTC for biopsy but unsatisfactory performance for reducing unnecessary biopsy.

Project description:Importance:Thyroid nodules are common incidental findings. Ultrasonography and molecular testing can be used to assess risk of malignant neoplasm. Objective:To examine whether a model developed through automated machine learning can stratify thyroid nodules as high or low genetic risk by ultrasonography imaging alone compared with stratification by molecular testing for high- and low-risk mutations. Design, Setting, and Participants:This diagnostic study was conducted at a single tertiary care urban academic institution and included patients (n?=?121) who underwent ultrasonography and molecular testing for thyroid nodules from January 1, 2017, through August 1, 2018. Nodules were classified as high risk or low risk on the basis of results of an institutional molecular testing panel for thyroid risk genes. All thyroid nodules that underwent genetic sequencing for cytological results with Bethesda System categories III and IV were reviewed. Patients without diagnostic ultrasonographic images within 6 months of fine-needle aspiration or who received definitive treatment at an outside medical center were excluded. Main Outcomes and Measures:Thyroid nodules were categorized by the model as high risk or low risk using ultrasonographic images. Results were compared using genetic testing. Results:Among the 134 lesions identified in 121 patients (mean [SD] age, 55.7 [14.2] years; 102 women [84.3%]), 683 diagnostic ultrasonographic images were selected. Of the 683 images, 556 (81.4%) were used for training the model, 74 (10.8%) for validation, and 53 (7.8%) for testing. Most nodules had no mutation (75 [56.0%]), whereas 43 nodules (32.1%) had a high-risk mutation and 16 (11.9%) had an unknown or a low-risk mutation (?2?=?39.060; P?<?.001). In total, 228 images (33.4%) were of nodules classified as genetically high risk (n?=?43), and 455 (66.6%) were of low-risk nodules (n?=?91). The model performed with a sensitivity of 45% (95% CI,?23.1%-68.5%), a specificity of 97% (95% CI,?84.2%-99.9%), a positive predictive value of 90% (95% CI,?55.2%-98.5%), a negative predictive value of 74.4% (95% CI,?66.1%-81.3%), and an overall accuracy of 77.4% (95% CI,?63.8%-97.7%). Conclusions and Relevance:The study found that the model developed through automated machine learning could produce high specificity for identifying nodules with high-risk mutations on molecular testing. This finding shows promise for the diagnostic applications of machine learning interpretation of sonographic imaging of indeterminate thyroid nodules.

Project description:IntroductionThyroid ultrasound (US) is crucial for clinical decision in the management of thyroid nodules. In this cross-sectional study, we aimed to test if the evaluation of thyroid nodules' vascularization could improve the risk stratification ability of the American College of Radiology (ACR) TI-RADS classification system.MethodsA total of 873 thyroid nodules undergoing fine-needle aspiration were classified according to ACR TI-RADS US classification. Three types of vascularization were identified: type 0, no vascular signals; type 1, peripheral vascular signals; type 2, peripheral and intralesional vascular signals. Cytology specimens were evaluated conforming to the Italian Reporting System for Thyroid Cytology, and TIR3b, TIR4, and TIR5 were defined as high risk for malignancy. Odds ratios (ORs) with 95% confidence intervals (CI) and the areas under the receiver operating characteristic curves (ROC-AUC) for high-risk cytology categories were calculated.ResultsThe 3 vascular patterns were differently distributed within the cytology categories: 52.4% of TIR1c, 15.9% of TIR2, 5.9% of TIR3a, 6.7% of TIR3b, 12.5% of TIR4, and 28.9% of TIR5 nodules had no vascular signals (p < 0.001). Nodule vascularity alone was not associated with a higher risk of malignant cytology (OR [95% CI] 0.75 [0.43-1.32], p = 0.32), without differences between peripheral (OR [95% CI] 0.65 [0.35-1.20]) and intranodular (OR [95% CI] 0.88 [0.48-1.62]) vascularization (p = 0.22). The ROC-AUC (95% CI) for the diagnosis of malignant cytology was similar when considering TI-RADS classification alone (0.736 [0.684-0.786]) and when considering TI-RADS classification plus the presence/absence of vascular signals (0.736 [0.683-0.789], p value for differences between the ROC-AUCs: 0.91). Among TR1, TR2, and TR3 TI-RADS classes, no nodules without vascular signals showed a malignant cytology, allowing the identification of nodules with benign cytology with 100% specificity within these US classes.ConclusionsColor Doppler study of thyroid nodules does not improve the risk stratification ability of the ACR TI-RADS US classification system.

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Advanced Ultrasound Application - Impact on Presurgical Risk Stratification of the Thyroid Nodules.

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Advanced Ultrasound Application - Impact on Presurgical Risk Stratification of the Thyroid Nodules.

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