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Updated: Aug 5, 2026
A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
Published on: April 21, 2023
Grading medullary thyroid carcinoma on fine needle aspiration biopsy specimens: a comparative study between manual
Annie Elizabeth Abraham1, Mega Lahori1, Esma Ersoy1
1Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, New York.
Introduction:
The International Medullary Thyroid Carcinoma Grading System stratifies medullary thyroid carcinoma (MTC) using Ki-67 proliferation index, mitotic index, and tumor necrosis. However, the ability to predict MTC grade using fine needle aspiration (FNA) specimens is unclear. Artificial intelligence (AI)-based quantification tools are increasingly being adopted. We therefore evaluated the concordance of MTC grading on cytology using manual counting and an AI-based digital quantification platform.
Materials And Methods:
Eighteen MTC cases with paired FNA and surgical resections (2013-2022) were retrospectively identified. MTC grading was assessed on FNAs and resections according to the International Medullary Thyroid Carcinoma Grading System criteria. Manual cytologic Ki-67 proliferation index (MCPI) and manual surgical proliferation index (MSPI) were compared. Digital cytologic Ki-67 proliferation index (DCPI) was generated using DeepLIIF. Concordance between Ki-67 proliferation indices and overall MTC grade was evaluated using Cohen's kappa.
Results:
Substantial agreement was observed between MCPI and MSPI (94% concordance; kappa = 0.77). Overall grade concordance between cytology and surgical specimens was 83% (kappa = 0.49), with discrepancies largely due to necrosis identified only in resections. Agreement between MCPI and DCPI was fair (61%; kappa = 0.22), with digital analysis frequently overestimating Ki-67 proliferation index. Concordance between DCPI and MSPI was 67% (kappa = 0.33), and overall grade agreement between digital cytology assessment and surgery was slight (56%; kappa = 0.11).
Conclusions:
Grading of MTC on cytology demonstrates substantial concordance for Ki-67 assessment but only modest agreement for overall grade, primarily because necrosis is often only focally present. The limited performance of the AI-based digital quantification platform emphasizes the need for specimen-specific development and validation prior to clinical implementation.
