Programmed death-ligand 1 expression by digital image analysis advances thyroid cancer diagnosis among encapsulated follicular lesions

Morphometric Analysis of Lateral Cervical Lymph Node Metastasis in Papillary Thyroid Carcinoma Using Digital Pathology

Digital pathology uses digitized images for cancer research. We aimed to assess morphometric parameters using digital pathology for predicting recurrence in patients with papillary thyroid carcinoma (PTC) and lateral cervical lymph node (LN) metastasis. We analyzed 316 PTC patients and assessed the longest diameter and largest area of metastatic focus in LNs using a whole slide imaging scanner. In digital pathology assessment, the longest diameters and largest areas of metastatic foci in LNs were positively correlated with traditional optically measured diameters (R = 0.928 and R2 = 0.727, p < 0.001 and p < 0.001, respectively). The optimal cutoff diameter was 8.0 mm in both traditional microscopic (p = 0.009) and digital pathology (p = 0.016) evaluations, with significant differences in progression-free survival (PFS) observed at this cutoff (p = 0.006 and p = 0.002, respectively). The predictive area's cutoff was 35.6 mm2 (p = 0.005), which significantly affected PFS (p = 0.015). Using an 8.0-mm cutoff in traditional microscopic evaluation and a 35.6-mm2 cutoff in digital pathology showed comparable predictive results using the proportion of variation explained (PVE) methods (2.6% vs. 2.4%). Excluding cases with predominant cystic changes in LNs, the largest metastatic areas by digital pathology had the highest PVE at 3.9%. Furthermore, high volume of LN metastasis (p = 0.001), extranodal extension (p = 0.047), and high ratio of metastatic LNs (p = 0.006) were associated with poor prognosis. Both traditional microscopic and digital pathology evaluations effectively measured the longest diameter of metastatic foci in LNs. Moreover, digital pathology offers limited advantages in predicting PFS of patients with lateral cervical LN metastasis of PTC, especially those without predominant cystic changes in LNs.

Trends in Diagnosis of Noninvasive Follicular Thyroid Neoplasm With Papillarylike Nuclear Features and Total Thyroidectomies for Patients With Papillary Thyroid Neoplasms

Importance

Increasing detection of early-stage papillary thyroid neoplasms without improvements in mortality has prompted development of strategies to prevent or mitigate overtreatment.

Objective

To determine adoption rates of 2 recent strategies developed to limit overtreatment of low-risk thyroid cancers: (1) a new classification, noninvasive follicular thyroid neoplasm with papillarylike nuclear features (NIFTP), and (2) hemithyroidectomy for selected papillary thyroid carcinomas (PTCs) up to 4 cm in size.

Design, Setting, and Participants

This is a cross-sectional analysis of 3368 pathology records of 2 cohorts of patients from 18 hospitals in 6 countries during 2 time periods (2015 and 2019). Participating hospitals were included from the US (n = 12), Canada (n = 2), Denmark (n = 1), South Korea (n = 1), South Africa (n = 1), and India (n = 1). The records of the first 100 patients per institution for each year who underwent thyroid-directed surgery (hemithyroidectomy, total thyroidectomy, or completion thyroidectomy) were reviewed.

Main Outcomes and Measures

Frequency of diagnosis of NIFTP, PTCs, and thyroidectomies during the study period.

Results

Of the 790 papillary thyroid neoplasms captured in the 2019 cohort, 38 (4.8%) were diagnosed as NIFTP. Diagnosis of NIFTP was observed in the US, South Africa, and India. There was minimal difference in the total proportion of PTCs in the 2015 cohort compared with the 2019 cohort (778 [47.1%] vs 752 [44.5%]; difference, 2.6% [95% CI, -16.9% to 22.1%]). The proportion of PTCs eligible for hemithyroidectomy but treated with total thyroidectomy in the 2 cohorts demonstrated a decreasing trend from 2015 to 2019 (341 of 453 [75.3%] vs 253 of 434 [58.3%]; difference, 17.0% [95% CI, -1.2% to 35.2%]).

Conclusions and Relevance

Results of this cohort study showed that the 2 mitigation strategies for preventing overtreatment of early-stage thyroid cancer have had mixed success. The diagnosis of NIFTP has only been applied to a small proportion of thyroid neoplasms compared with expected rates. However, more patients eligible for hemithyroidectomy received it in 2019 compared with 2015, showing some success with this deescalation strategy.

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.

Impact of image analysis and artificial intelligence in thyroid pathology, with particular reference to cytological aspects

OBJECTIVE

Thyroid pathology has great potential for automated/artificial intelligence algorithm application as the incidence of thyroid nodules is increasing and the indeterminate interpretation rate of fine-needle aspiration remains relatively high. The aim of the study is to review the published literature on automated image analysis and artificial intelligence applications to thyroid pathology with whole-slide imaging.

METHODS

Systematic search was carried out in electronic databases. Studies dealing with thyroid pathology and use of automated algorithms applied to whole-slide imaging were included. Quality of studies was assessed with a modified QUADAS-2 tool.

RESULTS

Of 919 retrieved articles, 19 were included. The main themes addressed were the comparison of automated assessment of immunohistochemical staining with manual pathologist's assessment, quantification of differences in cellular and nuclear parameters among tumour entities, and discrimination between benign and malignant nodules. Correlation coefficients with manual assessment were higher than 0.76 and diagnostic performance of automated models was comparable with an expert pathologist diagnosis. Computational difficulties were related to the large size of whole-slide images.

CONCLUSIONS

Overall, the results are promising and it is likely that, with the resolution of technical issues, the application of automated algorithms in thyroid pathology will increase and be adopted following suitable validation studies.

PD-1 Ligand Expression in Epithelial Thyroid Cancers: Potential Clinical Implications

The new immunotherapy targeting the programmed cell death 1 (PD-1) receptor and its cognate ligand PD-L1 has renewed hopes of eradicating the most difficult human cancers to treat. Among these, there are the poorly differentiated and anaplastic thyroid cancers, unresponsive to all the therapies currently in use. In the present review we will summarize information regarding the expression of PD-L1 in the different thyroid cancer histotypes, its correlation with clinicopathological features, and its potential prognostic value. Then, we will evaluate the available data indicating the PD-1/PD-L1 axis as a promising target for thyroid cancer therapy.