Comparison of Four Ultrasonography-Based Risk Stratification Systems in Thyroid Nodules with Nondiagnostic/Unsatisfactory Cytology: A Real-World Study.
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SUBMITTER: Lee YB
PROVIDER: S-EPMC8073392 | biostudies-literature |
REPOSITORIES: biostudies-literature
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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.
| S-EPMC6813575 | biostudies-literature
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.
| S-EPMC8314784 | biostudies-literature
Project description:Background: Thyroid ultrasound (US), fine needle aspiration biopsy (FNAB), and molecular testing have been widely used to stratify the risk of malignancy in thyroid nodules. The goal of this study was to investigate a novel diagnostic approach for cytologically indeterminate thyroid nodules (ITN) based upon a combination of US features and genetic alterations. Methods: We performed a pilot cohort study of patients with ITN (Bethesda III/IV), who underwent surgical treatment. Based on standardized sonographic patterns established by the American Thyroid Association (ATA), each ITN received an US score (XUS), ranging between 0 and 0.9 according to its risk of thyroid cancer (TC). DNA and RNA were extracted from pathologic material, available for all patients, and subjected to Oncomine™ Comprehensive Assay v2 (OCAv2) next-generation sequencing. Each genetic alteration was annotated based on its strength of association with TC and its sum served as the genomic classifier score (XGC). The total risk score (TRS) was the sum of XUS and XGC. ROC curves were generated to assess the diagnostic accuracy of XUS, XGC, and TRS. Results: The study cohort consisted of 50 patients (39 females and 11 males), aged 47.5 ± 14.8 years. Three patients were excluded due to molecular testing failure. Among the remaining 47 patients, 28 (59.6%) were diagnosed with TC. BRAFV600E was the most common mutation in papillary TC, PAX8-PPARG fusion was present in NIFTP, pathogenic variants of SLX4, ATM, and NRAS were found in Hürthle cell TC and RET mutations in medullary TC. The diagnostic accuracy of XGC and TRS was significantly higher compared with XUS (88 vs. 62.5%, p < 0.001; 85.2 vs. 62.5%, p < 0.001, respectively). However, this increased accuracy was due to significantly better sensitivity (80.7 vs. 34.6%, p < 0.001; 84.6 vs. 34.6%, p < 0.001, respectively) without improved specificity (94.7 vs. 90%, p = 0.55; 85.7 vs. 90%, p = 0.63, respectively). Conclusion: Molecular testing might not be necessary in ITN with high-risk US pattern (XUS = 0.9), as specificity of TC diagnosis based on Xus alone is sufficient and not improved with molecular testing. OCAv2 is useful in guiding the management of ITN with low-to-intermediate risk US features (XUS < 0.9), as it increases the accuracy of TC diagnosis.
| S-EPMC7040241 | biostudies-literature
Project description:BACKGROUND: Following fine needle aspiration, 15-30% of thyroid nodules are not clearly benign or malignant. These cytologically indeterminate nodules are often referred for diagnostic surgery, though most prove benign. A novel diagnostic test measuring the expression of 167 genes has shown promise in improving pre-operative risk assessment. We evaluated this test in a prospective, multicenter study. METHODS: Over 19 months, we performed a prospective study at 49 clinical sites enrolling 3,789 patients and collecting 4,812 samples from thyroid nodules >1cm requiring evaluation. We obtained 577 cytologically indeterminate aspirates with corresponding histopathology of excised lesions on 413. Central blinded histopathologic review served as the reference (“gold”) standard. After applying inclusion criteria, gene expression classifier results were obtained for 265 indeterminate nodules used in this analysis, and performance was calculated. RESULTS: 85 of 265 indeterminate nodules were malignant. The gene expression classifier correctly identified 78 of 85 as ‘suspicious’ (92% sensitivity, [84%-97%] 95% CI). Specificity was 52%, [44%-59%]. The negative predictive value was 95%, 94%, and 85%, respectively, for aspirates with AUS/FLUS, FN/SFN, or ‘suspicious’ cytology. Analysis of 7 false negative cases revealed 6 with a paucity of thyroid follicular cells, suggesting that insufficient sampling of the nodule had occurred. CONCLUSIONS: Though individualized clinical care is recommended, these data support consideration of a conservative approach for most patients with indeterminate FNA cytology and benign gene expression classifier results.
2012-06-25 | GSE34289 | GEO
Project description:Background:It is important to distinguish benign thyroid nodules from malignant thyroid nodules. Hence, this study aimed to determine the characteristics of patients with thyroid cancer using thyroid ultrasonography. Methods:We retrospectively examined the ultrasonographic findings of 327 patients with 457 thyroid nodules (age: 59.9 ± 14.3 years; sex, n (%): female 242 (74.0%)) at a single center from 2014 to 2016. Ultrasonography was used to determine the nodule size, shape, border, internal echogenicity, presence of coarse calcifications and microcalcifications within the nodule, internal blood flow and whether the nodule was solid or contained cystic structures. Thyroid fine needle aspiration cytology (FNAC) was performed in all patients. The ultrasonographic findings were compared between patients with benign nodules and those with papillary thyroid carcinoma (PTC). Furthermore, in the analysis of anti-thyroglobulin (Tg) antibody-negative patients with single nodules, values of serum Tg/nodule volume were calculated and compared between patients with benign nodules and those with PTC. Results:There were 298 (65.2%) benign nodules, 33 (7.2%) PTCs and 126 (27.6%) others (104 follicular neoplasms, 19 masses of undetermined significance and three other malignant tumors). The nodules diagnosed as PTC had significantly lower internal echogenicity (P < 0.01), more microcalcifications (P < 0.01) and comprised more nodules rich in blood flow (P < 0.05) than benign nodules. Solid nodules were found significantly more in the PTC group (P < 0.01). The serum Tg/nodule volume ratio was significantly higher in the PTC group (P < 0.05). Conclusions:Findings suggestive of PTC were found from images obtained using thyroid ultrasonography. In the diagnosis of PTC, the frequency of FNAC examinations should be reduced as this method is costly and invasive.
| S-EPMC7430871 | biostudies-literature
Project description:According to the 2015 American Thyroid Association (ATA), referred risk stratification and thyroid nodules with intermediate- and low-suspicion patterns are difficult to diagnose. The objective of this study is to evaluate the diagnostic performance of contrast-enhanced ultrasonography (CEUS) and elastosonography (ES) for the differentiation of these thyroid nodules. From November 2011 to June 2016, a total of 163 thyroid nodules with intermediate- and low-suspicion patterns in 150 consecutive patients at our hospital were studied before surgery. With surgical pathology as the standard, the diagnostic value of CEUS and ES was analyzed. There were 29 (17.8%) malignant lesions and 134 (82.2%) benign lesions. The enhancement patterns of CEUS, the echogenicity, and the elastography were significantly different between malignant and benign lesions (P < 0.05). Heterogenous enhancement was more common in malignant nodules, and the sensitivity, specificity, positive predictive value, negative predictive value, and odds ratio were 51.7, 88.1, 48.4, 89.4, and 10.1%, respectively. The diagnostic accuracy of CEUS was better than the conventional ultrasound [area under the curve (AUC), 0.729 vs. 0.616, P = 0.021]. The enhancement patterns of CEUS were helpful in the differential diagnosis of thyroid nodules with intermediate and low suspicion.
| S-EPMC7056834 | biostudies-literature
Project description:Background:The Korea Thyroid Association published the revised guidelines for thyroid nodules in 2016. However, whether fine-needle aspiration is accurately performed based on indications and whether the results of this procedure are appropriately addressed according to clinical guidelines, particularly in subcentimeter nodules, are unclear. Methods:We retrospectively analyzed the fine-needle aspiration data of 331 thyroid nodules of patients who were referred to a tertiary hospital clinic for fine-needle aspiration. Each nodule was categorized according to ultrasonography findings based on the recommendations of the Korea Thyroid Association for fine-needle aspiration. Only nodules with a final pathological diagnosis of benign or malignant made using the Bethesda system were included. Results:Up to 32% of thyroid nodules that were not indicated for fine-needle aspiration were aspirated. Regarding subcentimeter nodules, only 28 of 123 (22.8%) aspirated nodules were indicated for fine-needle aspiration. Of the 49 malignant subcentimeter nodules, 33 (67.3%) underwent immediate surgery. Meanwhile, 14 (28.6%) nodules were lost to follow-up, and two (4.1%) were under active surveillance. Eighteen (36.7%) malignant subcentimeter nodules were not indicated for fine-needle aspiration but underwent surgical resection instead of active surveillance. Conclusion:Despite the recommendations in the revised guidelines, several thyroid nodules that do not meet the indications for FNA are aspirated in real-world practice. To reduce overtreatment, a widespread knowledge of the correct indications for fine-needle aspiration is important in clinical practice, particularly for subcentimeter nodules.
| S-EPMC7468373 | biostudies-literature
Project description:BACKGROUND: Following fine needle aspiration, 15-30% of thyroid nodules are not clearly benign or malignant. These cytologically indeterminate nodules are often referred for diagnostic surgery, though most prove benign. A novel diagnostic test measuring the expression of 167 genes has shown promise in improving pre-operative risk assessment. We evaluated this test in a prospective, multicenter study. METHODS: Over 19 months, we performed a prospective study at 49 clinical sites enrolling 3,789 patients and collecting 4,812 samples from thyroid nodules >1cm requiring evaluation. We obtained 577 cytologically indeterminate aspirates with corresponding histopathology of excised lesions on 413. Central blinded histopathologic review served as the reference (“gold”) standard. After applying inclusion criteria, gene expression classifier results were obtained for 265 indeterminate nodules used in this analysis, and performance was calculated. RESULTS: 85 of 265 indeterminate nodules were malignant. The gene expression classifier correctly identified 78 of 85 as ‘suspicious’ (92% sensitivity, [84%-97%] 95% CI). Specificity was 52%, [44%-59%]. The negative predictive value was 95%, 94%, and 85%, respectively, for aspirates with AUS/FLUS, FN/SFN, or ‘suspicious’ cytology. Analysis of 7 false negative cases revealed 6 with a paucity of thyroid follicular cells, suggesting that insufficient sampling of the nodule had occurred. CONCLUSIONS: Though individualized clinical care is recommended, these data support consideration of a conservative approach for most patients with indeterminate FNA cytology and benign gene expression classifier results. 265 cytologically indetermine samples, 47 cytologically benign and 55 cytologically malignant samples
2012-06-24 | E-GEOD-34289 | biostudies-arrayexpress
Project description:Introduction: To compare the efficacy of four different ultrasound-based risk-stratification systems in assessing the malignancy risk of thyroid nodules in the Chinese population. Methods: We retrospectively reviewed the digital ultrasound images of 1,568 patients (1,612 thyroid nodules) who underwent surgery in our hospital between January 2012 and December 2017. All thyroid nodules were pathologically identified as malignant or benign. We evaluated the following ultrasound characteristics: size, location, composition, echogenicity, shape, margins, calcification or echogenic foci, and extrathyroidal extension. Each nodule was categorized using four risk-stratification systems: the American Thyroid Association (ATA) classification, the Thyroid Imaging, Reporting, and Data System (TIRADS) of the American College of Radiology (ACR-TIRADS), the European Thyroid Association TIRADS (EU-TIRADS), and the TIRADS developed by Kwak et al. (Kwak-TIRADS). The diagnostic performance of each risk-stratification system relative to the pathological results was analyzed. We used receiver operating characteristic curves to identify cutoff values that yielded optimal sensitivity (SEN), specificity (SPE), positive predictive value (PPV), negative predictive value (NPV), and accuracy (ACC). Results: Of the 1,612 nodules, 839 (52.0%) were benign, and 773 (48.0%) were malignant. The AUCs of the ACR-TIRADS, EU-TIRADS, Kwak-TIRADS, and ATA classification were 0.879, 0.872, 0.896, and 0.869, respectively. The Kwak-TIRADS had the best SEN, NPV, ACC, and AUC, while the ACR-TIRADS had the best SPE and PPV. Conclusion: All four risk-stratification systems had good diagnostic performances (AUCs > 86%). Considering its high SEN, NPV, ACC, and AUC, we believe that the Kwak-TIRADS may be the more effective risk-stratification system in the Chinese population.
| S-EPMC6527759 | biostudies-literature
Project description:BackgroundComputer-aided diagnosis (CAD) systems are being applied to the ultrasonographic diagnosis of malignant thyroid nodules, but it remains controversial whether the systems add any accuracy for radiologists.ObjectiveTo determine the accuracy of CAD systems in diagnosing malignant thyroid nodules.MethodsPubMed, EMBASE, and the Cochrane Library were searched for studies on the diagnostic performance of CAD systems. The diagnostic performance was assessed by pooled sensitivity and specificity, and their accuracy was compared with that of radiologists. The present systematic review was registered in PROSPERO (CRD42019134460).ResultsNineteen studies with 4,781 thyroid nodules were included. Both the classic machine learning- and the deep learning-based CAD system had good performance in diagnosing malignant thyroid nodules (classic machine learning: sensitivity 0.86 [95% CI 0.79-0.92], specificity 0.85 [95% CI 0.77-0.91], diagnostic odds ratio (DOR) 37.41 [95% CI 24.91-56.20]; deep learning: sensitivity 0.89 [95% CI 0.81-0.93], specificity 0.84 [95% CI 0.75-0.90], DOR 40.87 [95% CI 18.13-92.13]). The diagnostic performance of the deep learning-based CAD system was comparable to that of the radiologists (sensitivity 0.87 [95% CI 0.78-0.93] vs. 0.87 [95% CI 0.85-0.89], specificity 0.85 [95% CI 0.76-0.91] vs. 0.87 [95% CI 0.81-0.91], DOR 40.12 [95% CI 15.58-103.33] vs. DOR 44.88 [95% CI 30.71-65.57]).ConclusionsThe CAD systems demonstrated good performance in diagnosing malignant thyroid nodules. However, experienced radiologists may still have an advantage over CAD systems during real-time diagnosis.
| S-EPMC7445671 | biostudies-literature