Diagnostic Accuracy of the Bethesda System for Reporting Thyroid Cytopathology (TBSRTC): An Institution Experience

Rai, Karima; Park, Joseph; Gokhale, Shamika; Irshaidat, Fatima; Singh, Gurdeep

doi:10.1155/2023/9615294

Cited by 4 publications

(2 citation statements)

References 21 publications

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“…Higher performance was evident in TBSRTC due to its detailed criterion mentioned per category with subcategorization of AUS by features of cytological and architectural atypia. Similarly, suspicious for papillary thyroid carcinoma listed out different patterns, namely sparsely cellular specimen pattern, incomplete nuclear changes pattern and patchy nuclear changes pattern each with their own set of definitions [16]. These standardized criteria ensure high PPV and also minimize AUS case numbers considerably.…”

Section: Discussionmentioning

confidence: 99%

Unveiling Variations: A Comprehensive Comparison of Five Globally Used Thyroid Cytology Reporting Systems With Histopathological Correlation

Ramamoorthy,

Boddapati,

Venkata Renuka

et al. 2024

Cureus

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Introduction Accurate cytological assessment is pivotal for managing thyroid lesions and various global reporting systems are in use, such as the globally acclaimed The Bethesda System for Reporting Thyroid Cytopathology (TBSRTC), alongside other reporting systems namely, the Japanese Reporting System for Thyroid Aspiration Cytology (JRSTAC), Italian Consensus for the Classification and Reporting of Thyroid Cytology (ICCRTC), the UK Royal College of Pathologists System for Reporting Thyroid Cytopathology (UK RCPath), the Royal College of Pathologists of Australasia and Australian Society of Cytology Classification System (RCPA/ASC). Notably, variations exist among these systems which are influenced by country-specific statistics. Given the lack of large-scale data in India and the difference in prevalence of diagnostic entities compared to the western population, this study aimed to identify reporting systems suitable for the Indian population focusing on distinguishing neoplastic from non-neoplastic lesions. Materials and methods A cross-sectional analysis of 40 thyroid cytology cases with histopathological correlation was conducted. Pathologists independently assessed cytology slides using JRSTAC, ICCRTC, RCPA/ASC, UK RCPath and TBSRTC. Five performance indicators, sensitivity, specificity, positive predictive value (PPV) of neoplastic conditions, negative predictive value (NPV) of non-neoplastic conditions, diagnostic accuracy and two quality indicators, percentage of Atypia of undetermined significance (AUS) and AUS/Malignant ratio were analyzed and compared. Results Among 40 cases, 22 cases were neoplastic (16 papillary thyroid carcinoma, six follicular adenoma) and 18 non-neoplastic (14 multinodular goiter, four lymphocytic thyroiditis). Specific patterns emerged in cases labeled “Non-diagnostic”, prompted questions about categorizing inadequately cellular cases as “benign” in light of the presence of specific findings. All reporting systems showed 100% specificity in detecting non-neoplastic and neoplastic conditions in Category 1 and Category 6 respectively. Performance and quality indicators varied among reporting systems with TBSRTC (PPV of neoplastic cases 85.71%, NPV of non-neoplastic cases 70.58%, specificity 85.7%, sensitivity 70.58%, diagnostic accuracy 60%, AUS percentage 22.5% and AUS/Malignant ratio 3%) and RCPA/ASC (PPV of neoplastic cases 76.47%, NPV of non-neoplastic cases 70.58%, specificity 75%, sensitivity 72.2%, diagnostic accuracy 62.5%, AUS percentage 15% and AUS/Malignant ratio 3%) showing better results. Conclusion Among the five thyroid cytology reporting systems studied, TBSRTC and RCPA/ASC showed better overall performance results and quality indicators were close to benchmark. Better performance by TBSRTC 2023 could be due to the detailed criterion mentioned per category with subcategorization of AUS and suspicious for malignancy by features of cytological and architectural atypia. Similarly, RCPA/A...

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Section: Discussionmentioning

confidence: 99%

Unveiling Variations: A Comprehensive Comparison of Five Globally Used Thyroid Cytology Reporting Systems With Histopathological Correlation

Ramamoorthy,

Boddapati,

Venkata Renuka

et al. 2024

Cureus

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“…Bethesda category IV lesions account for 7-9% of nodules diagnosed through FNA and carry a malignancy rate in a wide range of 10-40% ( 28 ). The prevalence of diagnosis for Bethesda category IV has been found to differ in multiple cohorts, from as low as 1.5% to as high as 21.6% ( 29 , 30 ), while a meta-analysis showed a wide range of 1.2 to 25.3% (mean 10.1%) with a risk of malignancy of 26.1% ( 31 ). The third edition of the Bethesda System was published in September 2023, with updates regarding the names of each diagnostic categories as well as their risk of malignancy ( 32 ).…”

Section: Introductionmentioning

confidence: 99%

Impact of ultrasound elastography in evaluating Bethesda category IV thyroid nodules with histopathological correlation

Latia,

Borlea,

Mihuta

et al. 2024

Front. Endocrinol.

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IntroductionFine needle aspiration (FNA) is the gold standard method recommended in the diagnosis of thyroid nodules. Bethesda IV cytology results are identified in 7-9% of nodules investigated through FNA, with reported malignancy rate in a wide range of 10-40%. The recommended treatment is either surgical or risk additional molecular testing before surgery. However, a large number of nodules belonging to this category (60-80%) are observed to be benign after surgical excision, which can put the patient at risk of unnecessary surgical morbidity. This study aimed to assess the diagnostic performance of conventional ultrasound, the ACR TI-RADS score and elastography in cases of Bethesda IV cytology on FNA.MethodsWe evaluated ninety-seven consecutive cases with Bethesda category IV results on FNA by using conventional B-mode ultrasound, qualitative strain or shear-wave elastography (Hitachi Preirus Machine, Hitachi Inc., Japan and Aixplorer Mach 30 Supersonic Imagine, Aix-en-Provence, France) and all nodules were classified according to the ACR TI-RADS system. Conventional ultrasound was used to categorize the nodules as potentially malignant based on the following features: hypoechogenicity, inhomogeneity, a taller than wide shape, irregular margins, presence of microcalcifications, an interrupted thyroid capsule and suspicious cervical lymph nodes. Elastography classified nodules with increased stiffness as suspicious for malignancy.ResultsWe considered pathology results as the gold standard diagnosis, finding that 32 out of 97 nodules were carcinomas (33%) and 65 out of 97 were benign nodules (67%). The benign group included twenty cases of non-invasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP). Finally, we compared ultrasound data with pathology results, which showed that nineteen out of the 32 malignant nodules presented with increased stiffness on elastography (p=0.0002). On conventional ultrasound, we found that microcalcifications (p=0.007), hypoechogenicity and irregular margins (p=0.006) are features which can distinguish between benign and malignant nodules with statistical significance.DiscussionIntegrating elastography as a parameter of the ACR TI-RADS score in the evaluation of Bethesda category IV nodules showed a sensitivity of 90.62% in detecting thyroid cancer cases (p=0.006). We can conclude that elastographic stiffness as an addition to high risk features observed on conventional ultrasound improves the detection of malignant nodules in cases with Bethesda IV cytology.

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Deep learning-based cell segmentation for rapid optical cytopathology of thyroid cancer

Jermain,

Oswald,

Langdun

et al. 2024

Sci Rep

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Fluorescence polarization (Fpol) imaging of methylene blue (MB) is a promising quantitative approach to thyroid cancer detection. Clinical translation of MB Fpol technology requires reduction of the data analysis time that can be achieved via deep learning-based automated cell segmentation with a 2D U-Net convolutional neural network. The model was trained and tested using images of pathologically diverse human thyroid cells and evaluated by comparing the number of cells selected, segmented areas, and Fpol values obtained using automated (AU) and manual (MA) data processing methods. Overall, the model segmented 15.8% more cells than the human operator. Differences in AU and MA segmented cell areas varied between − 55.2 and + 31.0%, whereas differences in Fpol values varied from − 20.7 and + 10.7%. No statistically significant differences between AU and MA derived Fpol data were observed. The largest differences in Fpol values correlated with greatest discrepancies in AU versus MA segmented cell areas. Time required for auto-processing was reduced to 10 s versus one hour required for MA data processing. Implementation of the automated cell analysis makes quantitative fluorescence polarization-based diagnosis clinically feasible.

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Diagnostic Accuracy of the Bethesda System for Reporting Thyroid Cytopathology (TBSRTC): An Institution Experience

Cited by 4 publications

References 21 publications

Unveiling Variations: A Comprehensive Comparison of Five Globally Used Thyroid Cytology Reporting Systems With Histopathological Correlation

Unveiling Variations: A Comprehensive Comparison of Five Globally Used Thyroid Cytology Reporting Systems With Histopathological Correlation

Impact of ultrasound elastography in evaluating Bethesda category IV thyroid nodules with histopathological correlation

Deep learning-based cell segmentation for rapid optical cytopathology of thyroid cancer

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