scholarly journals The Presence of Hypoechoic Micronodules in Patients with Hashimoto′s Thyroiditis Increases the Risk of an Alarming Cytological Outcome

2021 ◽  
Vol 10 (4) ◽  
pp. 638
Author(s):  
Dorota Słowińska-Klencka ◽  
Martyna Wojtaszek-Nowicka ◽  
Mariusz Klencki ◽  
Kamila Wysocka-Konieczna ◽  
Bożena Popowicz
Keyword(s):  
Surgical Treatment ◽  
Connective Tissue ◽  
Fine Needle Aspiration ◽  
Fine Needle Aspiration Biopsy ◽  
Needle Aspiration ◽  
Aspiration Biopsy ◽  
Fine Needle ◽  
Bethesda System ◽  
Thyroid Cytopathology ◽  
Thyroid Parenchyma

The aim of the study was to identify a possible relation between various ultrasonographic (US) appearances of Hashimoto′s thyroiditis (HT) and the risk of obtaining an alarming cytology of coexisting nodules. The study included 557 patients with HT, who had been referred for fine needle aspiration biopsy (FNA). We divided US patterns of HT (UP-HT) into eight groups: (a) Hypoechoic (compared to submandibular glands), homogeneous/fine echotexture; (b) hypoechoic, heterogeneous/coarse echotexture; (c) marked hypoechoic (darker than strap muscles), heterogeneous/coarse echotexture; (d) heterogeneous echotexture with hyperechoic, fibrous septa; (e) multiple, discrete marked hypoechoic areas (sized as 1 to 6 mm); (f) normoechoic pseudo-nodular areas; (g) echostructure similar to connective tissue; (h) thyroid parenchyma with no signs of HT. Indications for a surgical treatment resulting from the FNA outcome (categories IV–VI of Bethesda System for Reporting Thyroid Cytopathology) were identified only in patients with variants b, c, and e of UP-HT, but merely the “multiple, discrete marked hypoechoic areas” variant significantly increased the odds of obtaining such cytology (OR:5.7). The presence of the “normoechoic pseudo-nodular areas” variant significantly increased the odds for the benign cytology (OR:1.7). There are significant differences in the frequency of obtaining an alarming cytology in relation to the UP-HT variant.

Factors Predicting Thyroid Malignancy in Fine Needle Aspiration Biopsy Specimens Classified as Atypia of Uncertain Significance/Follicular Lesion of Uncertain Significance

2018 ◽  
Vol 84 (7) ◽  
pp. 1207-1213 ◽  
Author(s):  
Ciara Brown ◽  
William Mangano ◽  
Stephanie Thompson ◽  
Bryan Richmond
Keyword(s):  
Fine Needle Aspiration ◽  
Fine Needle Aspiration Biopsy ◽  
Needle Aspiration ◽  
Aspiration Biopsy ◽  
Fine Needle ◽  
Nuclear Atypia ◽  
Uncertain Significance ◽  
Bethesda System ◽  
Needle Aspiration Biopsy ◽  
Thyroid Cytopathology

The atypia of uncertain significance/follicular lesion of uncertain significance (AUS/FLUS) category of the Bethesda system for reporting thyroid cytopathology for fine needle aspiration biopsy (FNAB) has a predicted incidence of malignancy from 5 to 15 per cent. The literature has reported that suspicious ultrasound (SUS) characteristics can assist in predicting malignancy in thyroid biopsies. Some research suggests further subdivision of AUS/FLUS into nuclear atypia predominant or follicular predominant. We hypothesized that the rate of malignancy would be higher in AUS/FLUS biopsies with SUS characteristics and in the AUS/FLUS subset classified as nuclear atypia predominant. We performed a four-year retrospective analysis of patients who underwent FNAB classified as AUS/FLUS and who subsequently underwent thyroidectomy from October 2008–October 2012. A total of 3839 thyroid FNAB were performed over the four-year period, of which 342 received AUS/FLUS classification. Of these, we identified 119 patients who underwent thyroidectomy, of which 27 (23%) malignancies were identified. Reported cytology (nuclear atypia vs follicular predominant) did not differ between patients with and without carcinomas (P = 0.33). Suspicious ultrasound appearance failed to be significantly associated with an underlying carcinoma (P = 0.14); although, nearly 70 per cent of malignancies displayed SUS compared with 50 per cent within the benign group. Ultrasound seems to have no additional value in predicting malignancy in the AUS/FLUS categorization. Further subcategorization did not aid in risk stratification of this indeterminate category. This may suggest an expanded role for ancillary technologies such as molecular markers in this challenging Bethesda system for reporting thyroid cytopathology class. Further study of these findings is warranted.

scholarly journals Second opinion in thyroid fine-needle aspiration biopsy by the Bethesda system

2012 ◽  
Vol 59 (3) ◽  
pp. 205-212 ◽  
Author(s):  
Jae Hyun Park ◽  
Hyun Ki Kim ◽  
Sang-Wook Kang ◽  
Jong Ju Jeong ◽  
Kee-Hyun Nam ◽  
...  
Keyword(s):  
Fine Needle Aspiration ◽  
Fine Needle Aspiration Biopsy ◽  
Needle Aspiration ◽  
Aspiration Biopsy ◽  
Second Opinion ◽  
Fine Needle ◽  
Thyroid Fine Needle Aspiration ◽  
Bethesda System ◽  
Needle Aspiration Biopsy ◽  
The Bethesda System

scholarly journals Artificial Intelligence in Thyroid Fine Needle Aspiration Biopsies

2020 ◽  
Vol 65 (4) ◽  
pp. 324-329
Author(s):  
Brie Kezlarian ◽  
Oscar Lin
Keyword(s):  
Artificial Intelligence ◽  
Fine Needle Aspiration ◽  
Fine Needle Aspiration Biopsy ◽  
Needle Aspiration ◽  
Aspiration Biopsy ◽  
Key Words And Phrases ◽  
Fine Needle ◽  
Thyroid Fine Needle Aspiration ◽  
Needle Aspiration Biopsy ◽  
Thyroid Cytopathology

<b><i>Background:</i></b> From cell phones to aerospace, artificial intelligence (AI) has wide-reaching influence in the modern age. In this review, we discuss the application of AI solutions to an equally ubiquitous problem in cytopathology – thyroid fine needle aspiration biopsy (FNAB). Thyroid nodules are common in the general population, and FNAB is the sampling modality of choice. The resulting prevalence in the practicing pathologist’s daily workload makes thyroid FNAB an appealing target for the application of AI solutions. <b><i>Summary:</i></b> This review summarizes all available literature on the application of AI to thyroid cytopathology. We follow the evolution from morphometric analysis to convolutional neural networks. We explore the application of AI technology to different questions in thyroid cytopathology, including distinguishing papillary carcinoma from benign, distinguishing follicular adenoma from carcinoma and identifying non-invasive follicular thyroid neoplasm with papillary-like nuclear features by key words and phrases. <b><i>Key Messages:</i></b> The current literature shows promise towards the application of AI technology to thyroid fine needle aspiration biopsy. Much work is needed to define how this powerful technology will be of best use to the future of cytopathology practice.

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