The presence of multinucleated giant cells: Noninvasive follicular thyroid neoplasm with papillary-like nuclear features vs the follicular variant of papillary thyroid carcinoma

Detailed fine needle aspiration cytopathology findings of noninvasive follicular thyroid neoplasm with papillary-like nuclear features with nuclear grading correlated to that of biopsy and Bethesda category and systematic review

BACKGROUND

Noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP) poses diagnostic challenge in fine needle aspiration cytopathology (FNAC). We aimed first to document our FNAC Bethesda categories (BCs) for all of our NIFTPs and compare our findings with those in the literature with series containing at least 14 cases each.

METHODS

Cases with final histopathological diagnoses of NIFTP and their preoperative FNAC were retrieved from 2006 to 2022 and our cytopathological BCs were documented. Then the slides were re-reviewed in a blinded manner for detailed classification and the results of both the BCs and blinded reclassification were compared with series in the literature for both BCs and detailed cytopathological review of the cases.

RESULTS

Thyroid FNACs of 43 out of 86 patients with final NIFTP diagnoses were obtained. Females composed 72.1% (F/M: 31/12); mean age and mean tumor diameter was 47.6 (19-72 years) and 23.4 mm (7-60 mm), respectively. Totally 81.4% (35/43) were classified in the "indeterminate" diagnostic categories; namely 44.2% (19/43) were reported as atypia of undetermined significance (AUS; BC III), 20.9% (9/43) were follicular neoplasm (FN; BC IV), and 16.3% (7/43) were suspicious for malignancy (SM; BC V). No patient was diagnosed as positive for malignancy (BC VI), preoperatively. Detailed cytomorphologic reevaluation revealed heterogeneous cytopathologic findings and nuclear grade (especially nuclear enlargement, membrane irregularity and elongation) significantly increased with respect to BCs. Systematic review confirmed extremely heterogeneous cytomorphologic nature of NIFTP.

CONCLUSIONS

NIFTPs were categorized most frequently as AUS, followed by FN and SM on FNAC. Our re-review were not able to specify features solely unique to NIFTP alone but may distinguish these cases from classic papillary thyroid carcinoma.

Noninvasive Follicular Thyroid Neoplasm with Papillary-like Nuclear Features (NIFTP): Tumour Entity with a Short History. A Review on Challenges in Our Microscopes, Molecular and Ultrasonographic Profile

Since Noninvasive Follicular Thyroid Neoplasm with Papillary-like Nuclear Features (NIFTP) was introduced as a new thyroid tumour entity, many studies, and meta-analyses on diagnosing NIFTP have been published. NIFTP-revised histopathological criteria emerged in 2018. NIFTP is defined as a histological entity and its diagnosis requires a careful histological examination. Its molecular profile is similar to follicular-like tumours. Ultrasound features are unable to differentiate NIFTP. NIFTP is not a cytological diagnosis, but it influences the risk of malignancy in several categories of The Bethesda System for Reporting Thyroid Cytopathology terminology.

Non-Invasive Follicular Thyroid Neoplasm with Papillary-Like Nuclear Features Is Not a Cytological Diagnosis, but It Influences Cytological Diagnosis Outcomes: A Systematic Review and Meta-Analysis

BACKGROUND

A low-risk thyroid tumour, non-invasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP) was introduced in 2016. NIFTP criteria require a thorough histological examination to rule out capsular and lymphovascular invasion, which denies the possibility of preoperative cytological diagnosis. Nevertheless, since the adoption of the new entity, the cytology of NIFTP has been a subject of interest.

OBJECTIVES

The present systematic review and meta-analysis investigate the cytological diagnosis of NIFTP.

METHOD

An online PubMed literature search was conducted between March 1, 2020, and June 30, 2020, for all original articles considering the cytology of histologically proven NIFTP. The studies including data on fine needle aspiration specimens classified by The Bethesda System for Reporting Thyroid Cytology (TBSRTC) categories, risk of malignancy (ROMs) in the TBSRTC categories, and cytomorphological features of NIFTP were included in the meta-analysis. Non-English studies and case reports were excluded. The data were tabulated and statistical analysis was performed with Open Meta-Analyst program.

RESULTS

Fifty-eight studies with a total of 2,553 NIFTP cases were included in the study. The pooled prevalence of NIFTP cases was calculated among 25,892 surgically resected cases from 20 studies and the results show that NIFTP consisted 4.4% (95% confidence interval [CI]: 3.5-5.4%) of all cases. Most of the NIFTP cases (79.0%) belonged to the intermediate categories of TBSRTC. The pooled distribution of NIFTP cases in each TBSRTC category was 1.3% (95% CI: 0.8-1.7%) in non-diagnostic (ND), 8.9% (95% CI: 6.9-10.8%) in benign, 29.2% (95% CI: 25.0-33.4%) in atypia of undetermined significance or follicular lesion of undetermined significance (AUS/FLUS), 24.2% (95% CI: 19.6-28.9%) in follicular neoplasm (FN), 19.5% (95% CI: 16.1-22.9%) in suspicious for malignancy (SM), and 6.9% (95% CI: 5.2-8.7%) in malignant. Compared to pre-NIFTP era, the pooled risk differences of ROM were reduced by 2.4% in ND, 2.7% in benign, 8.2% in AUS/FLUS, 8.2% in FN, 7.3% in SM, and 1.1% in the malignant category. The cytomorphological features of NIFTP were similar to follicular variant of papillary thyroid carcinoma (FVPTC) but lesser to papillary thyroid carcinoma (PTC).

CONCLUSIONS

Based on our results, NIFTP remains a histological diagnosis. Although cytomorphological features cannot be used in differentiating NIFTP from FVPTC, they may guide in separating NIFTP from PTC. Features such as papillae, microfollicles, giant cells, psammoma bodies, and the amount of papillary-like nuclear features should be taken into account when suspicious of NIFTP. NIFTP should not have papillae or psammoma bodies, and giant cells were rarely observed.

Artificial Intelligence for Personalized Medicine in Thyroid Cancer: Current Status and Future Perspectives

Thyroid cancers (TC) have increasingly been detected following advances in diagnostic methods. Risk stratification guided by refined information becomes a crucial step toward the goal of personalized medicine. The diagnosis of TC mainly relies on imaging analysis, but visual examination may not reveal much information and not enable comprehensive analysis. Artificial intelligence (AI) is a technology used to extract and quantify key image information by simulating complex human functions. This latent, precise information contributes to stratify TC on the distinct risk and drives tailored management to transit from the surface (population-based) to a point (individual-based). In this review, we started with several challenges regarding personalized care in TC, for example, inconsistent rating ability of ultrasound physicians, uncertainty in cytopathological diagnosis, difficulty in discriminating follicular neoplasms, and inaccurate prognostication. We then analyzed and summarized the advances of AI to extract and analyze morphological, textural, and molecular features to reveal the ground truth of TC. Consequently, their combination with AI technology will make individual medical strategies possible.

Molecular Correlates and Nuclear Features of Encapsulated Follicular-Patterned Thyroid Neoplasms

BACKGROUND

Assessing nuclear features is diagnostically challenging in the aspect of thyroid pathology. The aim of this study was to determine whether pathologists could distinguish BRAF-like and RAS-like nuclear features morphologically and identify morphological features to differentiate thyroid tumors with RAS-like mutations from encapsulated papillary thyroid carcinoma (PTC) with predominant follicular growth and BRAFV600E mutation.

METHODS

Representative whole slide images of 16 encapsulated thyroid tumors with predominant follicular growth were reviewed by 12 thyroid pathologists using a web browser-based image viewer. Total nuclear score was calculated from semi-quantitatively scored eight nuclear features. The molecular profile of RAS and BRAF genes was determined by Sanger sequencing.

RESULTS

Total nuclear score ranging 0 to 24 could differentiate BRAF-like tumors from RAS-like tumors with a cut-off value of score 14. The interobserver agreement was the highest for the assessment of nuclear pseudoinclusions (NPIs) but the lowest for nuclear elongation and sickle-shaped nuclei. NPIs were found in tumors with BRAFV600E mutation, but not in tumors with RAS-like mutations. Total nuclear scores were significantly higher for tumors with BRAFV600E than for those with RAS-like mutations (P<0.001).

CONCLUSION

Our results suggest that NPIs and high nuclear scores have diagnostic utility as rule-in markers for differentiating PTC with BRAFV600E mutation from benign or borderline follicular tumors with RAS-like mutations. Relaxation of rigid criteria for nuclear features resulted in an overdiagnosis of PTC. Immunostaining or molecular testing for BRAFV600E mutation is a useful adjunct for cases with high nuclear scores to identify true PTC.

The pursuit of understanding multinucleated giant cells in indeterminate and malignant thyroid cytology samples

BACKGROUND

Multinucleated giant cell (MGC) present in a variety of non-neoplastic and neoplastic lesions of the thyroid on cytology samples. We aimed to investigate whether certain MGC features that can help us in routine cytopathology practice.

METHOD

One hundred and thirty seven cases thyroid fine-needle aspiration material, which was diagnosed as indeterminate or malignant according to the Bethesda categorization, were reviewed. All cytomorphological features of the MGCs were documented. These features correlated with Bethesda categories and the final diagnosis of the subsequent surgical specimen.

RESULTS

The presence of the MGCs was identified in 42% of the samples (58 cases-total 236 MGCs). Eighty eight of them (37%) had dense cytoplasm, 148 of them had foamy cytoplasm. The mean number of dense and foamy MGC per case was higher in the malignant category (3.2 for dense MGC and 6 for foamy MGC per case). All dense MGCs were found to be in patients with papillary thyroid carcinoma (PTC). Remarkably, follicular patterned lesions had less often dense MGC compared to papillary patterned lesions (16.6% and 46.8% respectively). We detected a nuclear irregularity in 49 dense MGC (55%), groove-like features in 24 dense MGC (27.2%), and presence of some material/cell in 8 dense MGC (9%).

CONCLUSION

The presence of dense MGC is an important finding for guiding accurate Bethesda categorization, especially in indeterminate and malignant categories. Besides, the presence of some material or cell in MGCs cytoplasm can be an important indicator for the prognosis of the PTC cases.