Assessment Of Thyroid Nodules Research Articles

Performance of ACR-TIRADS in assessing thyroid nodules does not vary according to patient age.

A few studies have evaluated the performance of the American College of Radiology Thyroid Imaging Reporting And Data System (ACR-TIRADS) in pediatric and elderly patients and found differences between the latter two age groups and middle adulthood. Thus, the present study was undertaken to explore the possible variation of ACR-TIRADS performance across different ages of patients. A retrospective population undergoing thyroidectomy was selected to use histology as the reference standard. Ultrasound images were reviewed, and alignment of ACR-TIRADS with the corresponding histological diagnosis was made afterwards. Results of the age groups were compared. The ACR-TIRADS diagnostic performance was calculated considering the assessment of nodules across risk categories (i.e., from TR1 to TR5), rate of unnecessary FNAC (UN-FNAC), and rate of necessary but non-performed FNAC (NNP-FNAC). Overall, 114 patients with a total of 220 nodules (46 carcinomas) were included. The rate of UN-FNAC was 66.3%, being 93.1% in TR3, 82.1% in TR4, and 31.4% in TR5. There were 15 NNP-FNACs. No significant difference was observed between age groups in terms of sample size, nodule, cancer, and FNAC. The nodule assessment according to ACR-TIRADS categories did not vary across ages. Sensitivity and specificity recorded in three age tertiles were not significantly different. The present study shows that the performance of ACR-TIRADS is not significantly influenced by patient age.

Evaluation of Thyroid Nodule by US Including Elastography versus MRI T2W and Diffusion Sequences

Abstract Background The thyroid gland frequently develops thyroid nodules. Effective treatment of malignant thyroid nodules depends on an early and accurate diagnosis. Benign and malignant thyroid nodules are typically distinguished using conventional thyroid ultrasonography (US). In order to explore changes in tissue stiffness, strain elastography (SE) uses an external force and a deformation response detector. A promising method for distinguishing between benign and malignant thyroid nodules is ultrasound elastography. Malignant versus benign thyroid nodules might be distinguished using MRI apparent diffusion coefficient (ADC) values. This study compares MRI T2W and diffusion sequences with ultrasound, which includes elastography, to assess thyroid nodules. Methods This cross-sectional research was carried out at Ain-Shams University's radiodiagnosis department. It included 23 female or male patients with suspicious thyroid nodule by clinical examination, or ultrasonography including some cases elastography if present for further work up with MR diffusion subjected to DWI and ADC value and results were compared with histopathology if present or follow up of the patients. The duration of the study was 24 months. Results Diffusion had an accuracy of 91.3%, while the ADC value and elastography had a greater diagnostic accuracy with an area under the curve of 95.7% in discriminating between benign and malignant cases. Conclusions When describing thyroid nodules, ADC value provided better diagnostic performance than US TIRADS rating. Over and above ACR-TIRADS classification, useful information is added by ultrasound elastography and strain ratio analysis of thyroid nodules. It is advised as an auxiliary tool. However, the distinction of cancerous and benign thyroid nodules might potentially be done with greater precision using diffusion weighted MRI.

Texture Analysis of Thyroid Nodules Using Computed Tomography: Is it a Viable Method for Objective Assessment of Thyroid Nodules?

Texture Analysis of Thyroid Nodules Using Computed Tomography: Is it a Viable Method for Objective Assessment of Thyroid Nodules?

Diagnostic performance of artificial intelligence in interpreting thyroid nodules on ultrasound images: a multicenter retrospective study.

Thyroid nodules are commonly identified through ultrasound imaging, which plays a crucial role in the early detection of malignancy. The diagnostic accuracy, however, is significantly influenced by the expertise of radiologists, the quality of equipment, and image acquisition techniques. This variability underscores the critical need for computational tools that support diagnosis. This retrospective study evaluates an artificial intelligence (AI)-driven system for thyroid nodule assessment, integrating clinical practices from multiple prominent Thai medical centers. We included patients who underwent thyroid ultrasonography complemented by ultrasound-guided fine needle aspiration (FNA) between January 2015 and March 2021. Participants formed a consecutive series, enhancing the study's validity. A comparative analysis was conducted between the AI model's diagnostic performance and that of both an experienced radiologist and a third-year radiology resident, using a dataset of 600 ultrasound images from three distinguished Thai medical institutions, each verified with cytological findings. The AI system demonstrated superior diagnostic performance, with an overall sensitivity of 80% [95% confidence interval (CI): 59.3-93.2%] and specificity of 71.4% (95% CI: 53.7-85.4%). At Siriraj Hospital, the AI achieved a sensitivity of 90.0% (95% CI: 55.5-99.8%), specificity of 100.0% (95% CI: 69.2-100%), positive prediction value (PPV) of 100.0%, negative prediction value (NPV) of 90.9%, and an overall accuracy of 95.0%, indicating the benefits of AI's extensive training across diverse datasets. The experienced radiologist's sensitivity was 40.0% (95% CI: 21.1-61.3%), while the specificity was 80.0% (95% CIs: 63.6-91.6%), respectively, showing that the AI significantly outperformed the radiologist in terms of sensitivity (P=0.043) while maintaining comparable specificity. The inter-observer variability analysis indicated a moderate agreement (K=0.53) between the radiologist and the resident, contrasting with fair agreement (K=0.37/0.33) when each was compared with the AI system. Notably, 95% CIs for these diagnostic indexes highlight the AI system's consistent performance across different settings. The findings advocate for the integration of AI into clinical settings to enhance the diagnostic accuracy of radiologists in assessing thyroid nodules. The AI system, designed as a supportive tool rather than a replacement, promises to revolutionize thyroid nodule diagnosis and management by providing a high level of diagnostic precision.

Assessment of thyroid nodules using elastography and scintigraphy :review of literature

Assessment of thyroid nodules using elastography and scintigraphy :review of literature

Head-to-head comparison of American, European, and Asian TIRADSs in thyroid nodule assessment: systematic review and meta-analysis.

Ultrasound-based risk stratification systems (Thyroid Imaging Reporting and Data Systems (TIRADSs)) of thyroid nodules (TNs) have been implemented in clinical practice worldwide based on their high performance. However, it remains unexplored whether different TIRADSs perform uniformly across a range of TNs in routine practice. This issue is highly relevant today, given the ongoing international effort to establish a unified TIRADS (i.e. I-TIRADS), supported by the leading societies specializing in TNs. The study aimed to conduct a direct comparison among ACR-, EU-, and K-TIRADS in the distribution of TNs: (1) across the TIRADS categories, and (2) based on their estimated cancer risk. A search was conducted on PubMed and Embase until June 2023. Original studies that sequentially assessed TNs using TIRADSs, regardless of FNAC indication, were selected. General study characteristics and data on the distribution of TNs across TIRADSs were extracted. Seven studies, reporting a total of 41,332 TNs, were included in the analysis. The prevalence of ACR-TIRADS 1-2 was significantly higher than that of EU-TIRADS 2 and K-TIRADS 2, with no significant difference observed among intermediate- and high-risk categories of TIRADSs. According to malignancy risk estimation, K-TIRADS often classified TNs as having more severe risk, ACR-TIRADS as having moderate risk, and EU-TIRADS classified TNs as having lower risk. ACR-, EU-, and K-TIRADS assess TNs similarly across their categories, with slight differences in low-risk classifications. Despite this, focusing on cancer risk estimation, the three TIRADSs assess TNs differently. These findings should be considered as a prerequisite for developing the I-TIRADS.

Detecting thyrotropin receptor mRNA from peripheral blood of patients with differentiated thyroid cancer rules out non-aggressive cases.

Early diagnosis of thyroid cancer is hampered by the inability of fine-needle aspiration biopsy (FNAB) to accurately classify ∼30% of cases while preoperative cancer staging detects lymph nodal involvement in only half of cases. Liquid biopsy may present an accurate, non-invasive alternative for preoperative thyroid nodule assessment. Thyrotropin receptor (TSHR) mRNA, a surrogate marker for circulating cancer cells (CTC), may be an option for early detection of malignancy from peripheral blood, but requires methodological improvements. We aimed to investigate if TSHR mRNA can be detected in low sample volumes by employing an ultrasensitive method - droplet digital PCR (ddPCR). Less than 5mL of blood was collected from 47 patients with thyroid nodules (25 benign and 22 malignant). RNA was isolated from the fraction of mononuclear cells where CTCs segregate. Samples were analysed for the presence of TSHR mRNA by ddPCR. Thyrotropin receptor mRNA was detectable in 4mL sample volumes, with the test having good specificity (80%) but modest diagnostic accuracy (68.1%). Combining TSHR mRNA with ultrasound features and FNAB diagnosis, the test reaches high rule-out performances (sensitivity = 90% and NPV = 88.2%). Strikingly, TSHR mRNA correctly classified all samples with thyroid capsule invasion, lymph node metastasis and extrathyroidal extension. If aggressiveness is defined using these parameters, TSHR mRNA test reaches 100% sensitivity and 100% NPV for detecting high-risk cases. Employing ddPCR for TSHR mRNA improves its measurement by enabling detection in sample volumes common for laboratory testing. The test displays high prognostic performance, showing potential in preoperative risk assessment.

Clinico Pathological Study of Solitary Thyroid Nodule - A Prospective Study of 50 Cases.

Background: A common Presentation of thyroid disorder is solitary nodule. A discrete swelling in an impalpable gland is termed as solitary nodule of thyroid. The majority of solitary thyroid nodule are benign. The incidence of malignancy is more common in female with mean age 35 years. Timely intervention in nodular lesion of thyroid can significantly reduce morbidity and mortality.Objectives: The objective of this study was to evaluate the clinicopathological aspects of solitary thyroid nodule.Materials and Methods: This study was conducted in the department of otolaryngology and general surgery of Shaheed Monsur Ali Medical College and Hospital in 50 patients with Solitary Thyroid Nodule from July 2016 to July 2019. All the patients those who were diagnosed solitary thyroid nodule underwent thyroid surgery after through clinical evaluation, USG and FNAC. The histopathological reports were evaluated and correlated with clinical diagnosis and discussed.Results: Out of 50 patients’ majority were female only 8 were male patients. Peak incidence observed in the age group 30 to 40 years. Most of the patients presented with a swelling in front of neck 100% followed by pain 8%, dysphagia 4% and change of voice 4%. Swelling is located in the right lobe 70% followed by left lobe 26%. On FNAC examination they were presented with colloid nodular goitre 66%, follicular neoplasm 14%, thyroiditis 8%, papillary carcinoma 4% & cystic lesions 8%. But final histopathological report showed highest 30 (60%) cases was nodular goiter then follicular adenoma 10 (20%) and 6 (12%) were malignant.Conclusion: From this study we considered that STN is present most commonly in female. Most of them are benign, but remarkable proportion 12% of solitary thyroid nodule were malignant, so careful assessment of thyroid nodule is important for early diagnosis and treatment. KYAMC Journal Volume: 14, No: 03, October 2023: 161-164.

A multitask approach for automated detection and segmentation of thyroid nodules in ultrasound images

An increase in the incidence and diagnosis of thyroid nodules and thyroid cancer underscores the need for a better approach to nodule detection and risk stratification in ultrasound (US) images that can reduce healthcare costs, patient discomfort, and unnecessary invasive procedures. However, variability in ultrasound technique and interpretation makes the diagnostic process partially subjective. Therefore, an automated approach that detects and segments nodules could improve performance on downstream tasks, such as risk stratification. Ultrasound studies were acquired from 280 patients at UCLA Health, totaling 9888 images, and annotated by collaborating radiologists. Current deep learning architectures for segmentation are typically semi-automated because they are evaluated solely on images known to have nodules and do not assess ability to identify suspicious images. However, the proposed multitask approach both detects suspicious images and segments potential nodules; this allows for a clinically translatable model that aptly parallels the workflow for thyroid nodule assessment. The multitask approach is centered on an anomaly detection (AD) module that can be integrated with any UNet architecture variant to improve image-level nodule detection. Of the evaluated multitask models, a UNet with a ImageNet pretrained encoder and AD achieved the highest F1 score of 0.839 and image-wide Dice similarity coefficient of 0.808 on the hold-out test set. Furthermore, models were evaluated on two external validations datasets to demonstrate generalizability and robustness to data variability. Ultimately, the proposed architecture is an automated multitask method that expands on previous methods by successfully both detecting and segmenting nodules in ultrasound.

Classifying thyroid nodules with the American College of Radiology Thyroid Imaging Reporting and Data System: A simple and cost-effective approach for assessing malignancy risk

ABSTRACT Background: Thyroid nodules are common, with up to 68% of adults having them. Ultrasonography is commonly used to examine them, but cannot determine if they are benign or malignant. High-res ultrasonography can detect disease before diagnosis but confirmation requires an invasive procedure, fine-needle aspiration cytology (FNAC), which has risks. Thyroid Imaging Reporting and Data System (TI-RADS) classifies nodules based on ultrasound findings, providing objectivity and guidance. Aim: The aim of this study is to evaluate the ultrasound characteristics of thyroid nodules & categorize them using the ACR-TIRADS category based on suspicious ultrasound findings, assess the malignancy risk and co-relate with the pathological(FNAC) findings. Materials and Methods: A study involving 50 participants was conducted in the department of radiodiagnosis at our institute to assess thyroid nodules using ultrasound. The patients underwent ultrasound examination and FNAC, and the results were analysed using Microsoft Excel 2016. Results: Out of the 50 cases, 88% had single nodules and 72% were classified as TI-RADS 3, 20% as TI-RADS 4 and 8% as TI-RADS 5. The FNAC results revealed benign and malignant nodules. All patients with TI-RADS 3 criteria were benign, 80% of those with TI-RADS 4 criteria were benign and all patients with TI-RADS 5 criteria were malignant. Conclusion: The study concludes that the American College of Radiology (ACR) TI-RADS scoring system is an effective and practical way to categorise thyroid nodules using ultrasound. It provides a level of certainty about the likelihood of malignancy and helps healthcare providers make informed decisions about which nodules require biopsy, monitoring or no further action based on their ultrasound characteristics. This system reduces the need for unnecessary biopsies and surgeries, making it a cost-effective solution.

Learnability of Thyroid Nodule Assessment on Ultrasonography: Using a Big Data Set.

The aims of the work described here were to evaluate the learnability of thyroid nodule assessment on ultrasonography (US) using a big data set of US images and to evaluate the diagnostic utilities of artificial intelligence computer-aided diagnosis (AI-CAD) used by readers with varying experience to differentiate benign and malignant thyroid nodules. Six college freshmen independently studied the "learning set" composed of images of 13,560 thyroid nodules, and their diagnostic performance was evaluated after their daily learning sessions using the "test set" composed of images of 282 thyroid nodules. The diagnostic performance of two residents and an experienced radiologist was evaluated using the same "test set." After an initial diagnosis, all readers once again evaluated the "test set" with the assistance of AI-CAD. Diagnostic performance of almost all students increased after the learning program. Although the mean areas under the receiver operating characteristic curves (AUROCs) of residents and the experienced radiologist were significantly higher than those of students, the AUROCs of five of the six students did not differ significantly compared with that of the one resident. With the assistance of AI-CAD, sensitivity significantly increased in three students, specificity in one student, accuracy in four students and AUROC in four students. Diagnostic performance of the two residents and the experienced radiologist was better with the assistance of AI-CAD. A self-learning method using a big data set of US images has potential as an ancillary tool alongside traditional training methods. With the assistance of AI-CAD, the diagnostic performance of readers with varying experience in thyroid imaging could be further improved.

Pathology and new insights in thyroid neoplasms in the 2022 WHO classification

Purpose of review The assessment of thyroid nodules is a common clinical problem, linked to the high incidence of thyroid nodules in the population and the low incidence of aggressive thyroid carcinoma. The screening is therefore one of the strengths of our patient care. Recently, the 2023 Bethesda System for Reporting Thyroid Cytopathology (TBSRTC) and 2022 WHO classification of thyroid neoplasms have been released based on the definition of new entities and the growing impact of molecular testing. The aim of this review is to analyze how these upgrades can help us in the daily routine practice diagnosis of thyroid cancer. Recent findings Our review is focused on the most frequent thyroid tumors derived from thyroid follicular cell. Fine needle aspiration (FNA) is the gold standard for the screening of thyroid nodules with very high levels of sensitivity and specificity. These sensitivity and specificity are improved by molecular testing, which refines the risk of malignancy. The 2023 TBSRTC integrates molecular data and the upgrades integrated in the 2022 WHO classification such as the ‘low-risk neoplasms’ and the ‘high-grade follicular-cells derived carcinoma’. The morphological examination remains crucial since the capsular and/or vascular invasion are key features of malignancy in the follicular thyroid neoplasms. Low-risk neoplasms represent a clinical challenge since no specific guidelines are available. Challenges remain regarding oncocytic thyroid lesions, which are not associated with specific diagnostic molecular biomarkers. Molecular testing can help not only in deciphering the prognosis but also in the targeted therapeutic strategy. Summary While molecular testing has succeeded to substantially improve the pre and postoperative diagnosis and risk stratification of thyroid tumors, the morphological examination is still central in the daily routine diagnosis of thyroid pathology. Future is the integrated diagnosis of clinical, morphological, molecular and epigenetic features with the help of artificial intelligence algorithms.

Impact of Region-of-Interest Size on the Diagnostic Performance of Shear Wave Elastography in Differentiating Thyroid Nodules.

This study investigated the impact of different region-of-interest (ROI) sizes (Max, 1 mm, and 2 mm) on shear wave elastography (SWE) in differentiating between malignant and benign thyroid nodules. The study cohort comprised 129 thyroid nodules (50 malignant, 79 benign) and 78 normal subjects. Diagnostic efficacy was assessed through pairwise comparisons of area under the curve (AUC) values in receiver operating characteristic analysis by using DeLong's test. Our results indicated significant differences in all SWE elasticity metrics between the groups, with malignant nodules exhibiting higher values than benign nodules (p < 0.05). Smaller ROIs (1 and 2 mm) were found to outperform the max ROI in terms of diagnostic accuracy, particularly for the Emax and Emin elasticity metrics. Emax(1mm) had the highest diagnostic accuracy, with an AUC of 0.883, sensitivity of 74.0%, and specificity of 86.1%. This study underscores the significant influence of ROI size selection on the diagnostic performance of SWE, offering valuable insights for future research and clinical applications in thyroid nodule assessment.

Preoperative Thyroid-Stimulating Hormone Levels and Risk of Thyroid Cancer in Post-thyroidectomy Patients for Thyroid Nodules: A Study From a Tertiary Hospital in Western Saudi Arabia.

Background Although serum thyroid-stimulating hormone (TSH) is one of the basic investigations to assess thyroid nodules, its role in thyroid oncogenesis remains unclear. Previous literature has conflicting findings regarding TSH levels and the prediction of malignancy. This study aims to investigate the association between TSH levels and the risk of malignancy and advanced staging in patients who underwent thyroidectomy for nodular thyroid disease. Additionally, it aims to assess if higher TSH correlates with malignancy in Bethesda staging III, IV, and V. Methodology This retrospective cohort study was conducted among participants who underwent near-total/total thyroidectomy or hemithyroidectomy at King Abdulaziz Medical City between 2016 and 2021. Results A total of 378 cases were included, and 50.3% of the cases had malignant nodules in the surgical histopathology findings. The median TSH levels were higher in malignant nodules compared to benign ones (1.64 mIU/L versus 1.49 mIU/L; p < 0.001). Additionally, higher TSH levels were not associated with advanced staging or malignancy in patients with Bethesda stage III-V. Conclusions Higher TSH levels are associated with an increased risk of malignancy in patients with nodular thyroid disease. Using TSH levels as an adjunctive tool for identifying high-risk patients with thyroid nodules would aid in management planning.

Retracted: Application Value of a Deep Convolutional Neural Network Model for Cytological Assessment of Thyroid Nodules.

[This retracts the article DOI: 10.1155/2021/6076135.].

Automatic ultrasound diagnosis of thyroid nodules: a combination of deep learning and KWAK TI-RADS

Objective. There has been a considerable amount of computer-aided diagnosis (CAD) methods highlighted in the field of ultrasonic examination (USE) of thyroid nodules. However, few researches focused on the automatic risk classification, which was the basis for determining whether fine needle aspiration (FNA) was needed. The aim of this work was to implement automatic risk level assessment of thyroid nodules. Approach. Firstly, 1862 cases of thyroid nodules with the results of USE and FNA were collected as the dataset. Then, an improved U-Net++ model was utilized for segmenting thyroid nodules in ultrasound images automatically. Finally, the segmentation result was imported into a multi-task convolutional neural network (MT-CNN), the design of which was based on the clinical guideline called KWAK TI-RADS. Apart from the category of benign and malignant, the MT-CNN also exported the classification result of four malignant features, solid component (SC), hypoechogenicity or marked hypoechogenicity (HMH), microlobulated or irregular margin (MIM), microcalcification (MC), which were used for counting the risk level in KWAK TI-RADS. Main results. The performance of the improved U-Net++ was evaluated on our test set, including 302 cases. The Dice coefficient and intersection over union reached 0.899, 0.816, respectively. The classification accuracy rates of SC, HMH, MIM, MC, were 94.5%, 92.8%, 86.1%, 88.9%, while the false positive (FP) rate was 6.0%, 5.6%, 10.6%, 12.9% respectively. As for the category of benign and malignant, the precision and recall rates were 93.7% and 94.4%. Significance. The proposed CAD method showed favourable performance in the diagnosis of thyroid nodules. Compared with other methods, it could provide reports closer to clinical practice for doctors.

Thyroid Ultrasound Elastography: A Promising Undeniably Diagnostic Tool for Predicting the Risk of Malignancy

Thyroid disease is of common occurrence, especially in iodine deficient areas. Thyroid nodules are common findings in the general population. It is important to distinguish the subset of thyroid nodules that are malignant, as morbidity and mortality from thyroid cancer increases with disease stage. B-mode ultrasound features are initially used to select thyroid nodules for FNA. Although FNA is considered the gold standard for diagnosis, it is yet imperfect as up to 1530% of samples are considered non-diagnostic or indeterminate. Thyroid ultrasound elastography(USE) is a noninvasive method of assessing thyroid nodules that provides complementary information to B-mode ultrasound and FNA. The combined use of thyroid USE with B-mode ultrasound may improve the ability to discriminate benign from malignant thyroid nodules and reduce the number of needed FNAs. Thyroid USE may also aid with the difficult problem of distinguishing between malignant and benign follicular neoplasm.The elastic properties of tissue have always been of interest in clinical practice. In the past, the identification of structures that were stiffer on physical palpation would raise the suspicion. With the development and advancement of medicine, there proved to be a true correlation in the prediction of malignancy of lesion: malignant disease tends to stiffen the affected tissue, either by increased cell proliferation or fibrosis. Palpation is the oldest method for the detection of thyroid nodules, which if informed by the knowledge that malignant thyroid lesions tend to be much harder than benign ones. Palpation is dependent on the size, location and skill of the physician. Nodules are very small or located in deep regions; there detection by palpation is difficult or even impossible. Although malignant lesion differs in terms of elasticity, it may not have echogenic properties, preventing its detection by conventional ultrasound. Imaging that indicates the stiffness or deformation related to their structural formation.&#x0D; Bangabandhu Sheikh Mujib Med. Coll. J. 2022;1(2):96-98

FRI522 Impact Of TIRADS Score On Thyroid Nodule Biopsy

Abstract Disclosure: U.B. Adeniran: None. A. Olabumuyi: None. O. Adeniran: None. G. Bahtiyar: None. G. Rodriguez: None. Introduction: Thyroid nodules are prevalent, however many thyroid nodules biopsied are benign. In 2017, the Thyroid Imaging Reporting and Data systems Committee of the American college of Radiology (TI-RADS) presented the use of TI-RADS score to risk stratify nodules to TR1 to TR5 with recommendations on biopsy vs follow up. The aim of our study was to ascertain any changes in thyroid biopsy rate before and after the use of ACR TI-RADS in thyroid ultrasound scans in a community hospital in Brooklyn, NY. Methods: We conducted a retrospective single center observational cohort study on patients referred for thyroid nodule assessment between March 2019 - March 2020 &amp; March 2021 - March 2022. Inclusion criteria- all patients with thyroid ultrasound scans without TI-RADS scoring from March 2019- March 2020, all patients with TI-RADS scoring from March 2021-March 2022. Duplicate referrals, patients lost to follow up, incomplete records were excluded. Primary endpoint was to ascertain any differences in thyroid biopsy recommendation rate before and after the use of TI-RADS score in ultrasounds. Chi square test was used to determine the association between TI-RADS use in ultrasound scans and thyroid biopsy recommendation rate. Thyroid nodules were categorized based on the Bethesda System for Reporting Thyroid Cytopathology (BSRTC). Results: A total of 91 patients met the inclusion/exclusion criteria, 13 men and 78 women (M:F- 1:6). Thyroid nodules of 53 patients on ultrasound were reported using TI-RADS score and 38 patients without using the TI-RADS score. TI-RADS group and non TI-RADS group were similar in age, gender, race, and ethnicity. The use of the TI-RADS reporting system was associated with a statistically significant reduction in recommendation for biopsy. Only 26.4% of the patients who had TI-RADS were recommended for biopsy compared to 47.4% of the patients who did not have TI-RADS (P-Value 0.039).A total of 32 patients were recommended for biopsy, however biopsy was done in 26 patients. Majority of the nodules biopsied were benign (BSRTC II), 10 of 14 patients (71.5%) were benign (BSRTC II) in Non TI-RADS group, and 8 of 12 (66.7%) were benign (BSRTC II) in TI-RADS group. Conclusion: TI-RADS score significantly reduced the biopsy recommendations. Its implementation thus results in saving the Healthcare commission a significant cost of unnecessary biopsy in the region of $1,999 per biopsy. With the implementation of TIRADS, the proportion of malignant biopsies was expected to rise. However, there was no significant difference in this group. This may be because the total number of biopsies analyzed was small. It could also be that some of the nodules the TIRADS score did not recommend for biopsy may have been malignant. Further studying of a larger cohort is thus warranted. Presentation: Friday, June 16, 2023

Correlation of the ultrasound thyroid imaging reporting and data system with cytology findings among patients in Uganda

BackgroundUltrasonography is a noninvasive modality for the initial assessment of thyroid nodules. The American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) has demonstrated good performance in differentiating malignant thyroid nodules. However, the combination of ACR TI-RADS categories and cytology has not been studied extensively, in Uganda. The study aims to correlate ACR TI-RADS with cytology among patients referred for US-guided fine-needle aspiration at Mulago National Referral Hospital.MethodsThis was a hospital-based cross-sectional study that recruited 132 patients with thyroid nodules. Spearman’s correlation was used to establish a relationship between TI-RADS and cytology findings. The diagnostic accuracy of TI-RADS was assessed using sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios.ResultsOf 132 study participants, 90% (n = 117) were females, and the mean age was 41 ± 13 years. One hundred sixty-one thyroid nodules were analyzed. More than half of the thyroid nodules (54.7%, n = 87) were solid or almost solid, 96.9% (n = 154) were shaped wider than tall, 57.2% (n = 91) had smooth margins, 83.7% (n = 133) were hyperechoic or isoechoic, and 88.7% (n = 141) had no echogenic foci. TI-RADS 3 was the most common at 42.9% (n = 69). The proportions of malignancy for TI-RADS 4 and TI-RADS 5 were 73.3% and 85.7%, respectively. The correlation between ACR TI-RADS and the Bethesda system of thyroid classification scores was r = 0.577. The sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios of ACR TI-RADS were 90.9%, 98.5%, 90%, 99.3%, 62.3, and 0.1, respectively.ConclusionWe found that ACR TI-RADS classification is an appropriate and noninvasive method for assessing thyroid nodules in routine practice. It can safely reduce the number of unnecessary fine-needle aspiration in a significant proportion of benign thyroid lesions. Thyroid nodules classified as TI-RADS 3 should be followed routinely. ACR TI-RADS should be standardized as the screening tool in resource-limited areas.

Evaluation of FNAC Thyroid Smears Using Bethesda System For Reporting Thyroid Cytopathology Nomenclature With Clinicopathological Correlation

Background: The study aimed to interpret thyroid cytology by the Bethesda System for reporting thyroid cytology (TBSRTC) and to analyze the distribution of lesions under various diagnostic categories and subcategories.&#x0D; Methodology: This study was conducted as an observational study at tertiary care centre on patients with thyroid lesions. After history taking and detailed local, general and systemic examination, thyroid function tests were conducted. Apart from this, ultrasonography of lesion was done. Patients were subjected to FNAC and after fixation smears were stained with Papanicolaou stain.&#x0D; Results: About 53% thyroid lesions were hemorrhagic, followed by 17% blood mixed colloid and 4% colorless serous fluid. Sample adequacy was noted in 93.5% cases in our study. According to Bethesda system of classification, majority of lesions were benign (81.5%) whereas 6.5% lesions were unsatisfactory. Only 6% lesions were categorsied as malignant.&#x0D; Conclusion: FNAC is widely accepted as the most accurate, sensitive, specific, and cost- effective diagnostic procedure in the preoperative assessment of thyroid nodules. It is the first line of investigation and can differentiate benign nodules from malignant nodules of the thyroid in 95% cases. Applying a standard reporting system for thyroid cytology may enhance the communication between pathologists and clinicians, assists them to find out the rate of malignancy in each cytological group, and facilitating a more reliable approach for patient management.