Thyroid Imaging Reporting And Data System Level Research Articles

Combining radiomics with thyroid imaging reporting and data system to predict lateral cervical lymph node metastases in medullary thyroid cancer.

Medullary Thyroid Carcinoma (MTC) is a rare type of thyroid cancer. Accurate prediction of lateral cervical lymph node metastases (LCLNM) in MTC patients can help guide surgical decisions and ensure that patients receive the most appropriate and effective surgery. To our knowledge, no studies have been published that use radiomics analysis to forecast LCLNM in MTC patients. The purpose of this study is to develop a radiomics combined with thyroid imaging reporting and data system (TI-RADS) model that can use preoperative thyroid ultrasound images to noninvasively predict the LCLNM status of MTC. We retrospectively included 218 MTC patients who were confirmed from postoperative pathology as LCLNM negative (n=111) and positive (n=107). Ultrasound features were selected using the Student's t-test, while radiomics features are first extracted from preoperative thyroid ultrasound images, and then a two-step feature selection approach was used to select features. These features are then used to establish three regularized logistic regression models, namely the TI-RADS model (TM), the radiomics model (RM), and the radiomics-TI-RADS model (RTM), in 5-fold cross-validation to determine the likelihood of the LCLNM. The Delong's test and decision curve analysis (DCA) were used to evaluate and compare the performance of the models. The ultrasound features of margin and TI-RADS level, and a total of 12 selected radiomics features, were significantly different between the LCLNM negative and positive groups (p<0.05). The TM, RM, and RTM yielded an averaged AUC of 0.68±0.05, 0.78±0.06, and 0.82±0.05 in the 5-fold cross-validation dataset, respectively. RM and RTM are statistically better than TM (p<0.05 and p<0.001) according to Delong test. DCA demonstrates that RTM brings more benefit than TM and RM. We have developed a joint radiomics-based model for noninvasive prediction of the LCLNM in MTC patients solely using preoperative thyroid ultrasound imaging. It has the potential to be used as a complementary tool to help guide treatment decisions for this rare form of thyroid cancer.

A practical trial to use Thyroid Imaging Reporting and Data System (TI-RADS) in differentiation between benign and malignant thyroid nodules

BackgroundThyroid nodules have been reported up to 68% in adults using ultrasound examination. The American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) is founded on the evaluation of ultrasound (US) features in five categories: composition, echogenicity, shape, margin, and echogenic foci; the nodule’s total points determine its risk level, which ranges from TI-RADS1 (TR1) (benign) to TI-RADS5 (TR5) (highly suspicious). In conjunction with the nodule’s maximum diameter, the TR level determines whether to recommend a fine-needle aspiration (FNA) biopsy, a follow-up US examination, or no further action; our aim in this study was to apply ACR TI-RADS as a method for discrimination between benign and malignant nodules.MethodsWe applied ACR TI-RADS template for 40 thyroid nodules, the total points given to thyroid nodules ranged from 0 to 14 points, then we compared our results with scintigraphy, fine-needle aspiration cytology (FNAC), and histopathological reports after surgery.ResultsOf 40 thyroid nodules, 31 nodules (77.5%) were benign and 9 nodules (22.5%) were malignant; there was a statistically high significant trend of increasing risk of malignancy as the final TI-RADS level increased from TR1 to TR5 (P value < 0.001).ConclusionThe ACR TI-RADS scoring system is a simple easy method to be applied in daily ultrasound practice; it has an excellent diagnostic accuracy for the diagnosis of malignant thyroid nodules in the present study, as the aggregate risk of malignancy increased as the TI-RADS level increases from TR1 to TR5.

A Direct Comparison of the Ata and Ti-Rads Ultrasound Scoring Systems

Objective: This study compares the American Thyroid Association (ATA) classification system with the 2017 American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) for predicting cancer risk in thyroid nodules. Methods: This is a retrospective review of ultrasound imaging of all adult patients with thyroid nodules >5 mm who underwent thyroidectomy at a tertiary care hospital in 2016. We assessed the ability of either system to predict malignancy based on surgical histopathology. Sensitivity, specificity, negative predictive values (NPV) and positive predictive values (PPV), and area-under-the-curve (AUC) were calculated and compared using McNemar's, Fisher exact, or DeLong's tests. Results: Three hundred and twenty-three nodules from 213 adults were included. Median patient age was 55 years; 75.6% were female. 27.2% nodules were malignant. Both ATA and ACR TI-RADS provide effective diagnostic performance, a sensitivity of 77.3% versus 78.4%, respectively, a specificity of 76.6% versus 73.2%, respectively, a PPV of 55.3% versus 52.3%, respectively, and a NPV of 90% for both. The level of agreement between the two classification systems was almost perfect (weighted Kappa statistic = 0.93, AUC 0.77 ATA versus 0.76 TI-RADS [P = .18]). However, of the 40 (TI-RADS level 3) TR3 nodules (<2.5 cm), 10% were malignant, and of the 31 (TI-RADS level 4) TR4 nodules (<1.5 cm), 38% were malignant. Conclusion: The ATA and TI-RADS classification systems appear to have similar diagnostic value for predicting thyroid cancer. However, subanalysis of TR3 and TR4 nodules with consideration of size criteria showed that there is a higher risk of missing a malignancy if the ACR TI-RADS recommendation is followed. These results should be validated in a different patient cohort with a lower incidence of cancer. Abbreviations: ACR = American College of Radiology; ATA = American Thyroid Association; FNA = Fine Needle Aspiration; κ = weighted Kappa statistic; NPV = negative predictive values; PPV = positive predictive values; TI-RADS = Thyroid Imaging Reporting and Data System; TR1 = TI-RADS level 1; TR2 = TI-RADS level 2; TR3 = TI-RADS level 3; TR4 = TI-RADS level 4; TR5 = TI-RADS level 5.

Thyroid Imaging Reporting and Data System(TI-RADS): Interobserver variability and positive predictive value for assessment of thyroid nodules

Objective To retrospectively evaluate interobserver variability between radiologists by using lexicon of the Thyroid Imaging Reporting and Data System (TI-RADS) to classify lesions on ultrasonography and retrospectively determine the positive predictive value (PPV) of each TI-RADS level. Methods Five radiologists retrospectively reviewed 188 consecutive thyroid nodules with known pathologic diagnosis of 172 patients from June, 2016 to November, 2016. Each observer described each lesion with TI-RADS terminology and final TI-RADS level were assigned by adding the points from all categories. Cohen κ statistic was used to assessed the interobserver variability for each ultrasonographic(US) descriptors and final TI-RADS level. PPV for all TI-RADS levels were determined for all readers combined. Results For each US descriptor, composition, echogenicity, shape, margin, echogenic foci, their κ were 0.743 (0.713-0.772), 0.418 (0.319-0.517), 0.468 (0.389-0.547), 0.397 (0.291-0.503) and 0.566 (0.514-0.617) respectively (data in parentheses are 95% confidential intervals). The κ for TI-RADS level was 0.782 (0.749-0.81). PPV for TI-RADS level 1 to 5 were 0(0/8), 0(0/23), 14.3%(4/28), 29.7%(11/37) and 85.7%(78/91). Conclusions Interobserver agreement with the TI-RADS terminology is substantial for composition, moderate for echogenicity, shape and echogenic foci, fair for margin.Interobserver agreement is substantial for TI-RADS level. Consequently different understanding in US images has little influence in patient management, justifying the use of ACR-TIRADS in clinical practice. Key words: Ultrasonography; Thyroid nodule; Observer variation; Positive predictive value