Integrating Digital Ki-67 Labeling Index and K-TIRADS for Malignancy Risk Stratification in Thyroid Core Needle...

Area of Science:

• Endocrinology
• Oncology
• Pathology

Background:

• Preoperative risk stratification of indeterminate thyroid nodules, especially follicular neoplasms (category IV), is challenging.
• Molecular testing aids decision-making but faces cost and availability limitations.
• Accurate prediction of malignancy in thyroid nodules is crucial for appropriate patient management.

Purpose of the Study:

• To evaluate the utility of digitally quantified Ki-67 labeling index in predicting thyroid nodule malignancy.
• To assess if combining Ki-67 index with Korean Thyroid Imaging Reporting and Data System (K-TIRADS) improves malignancy prediction.
• To determine the diagnostic performance of Ki-67 in core needle biopsy (CNB) specimens.

Main Methods:

• Retrospective analysis of 130 thyroid nodules from ultrasound-guided CNB.
• Digital quantification of Ki-67 labeling index in immunohistochemically stained CNB sections.
• Classification of ultrasound features using K-TIRADS and statistical analysis including ROC curves and logistic regression.

Main Results:

• The Ki-67 labeling index demonstrated excellent malignancy prediction (AUC=0.924) with an optimal cutoff of 1.73% (88.7% sensitivity, 83.1% specificity).
• In category IV nodules, both K-TIRADS and Ki-67 index were independent predictors of malignancy.
• A Ki-67 index of 5% predicted a 98.1% probability of malignancy in the Ki-67-only model.

Conclusions:

• Digital Ki-67 quantification is a practical tool for malignancy risk stratification in thyroid CNB specimens.
• Integrating Ki-67 with K-TIRADS enhances risk assessment, particularly for challenging category IV nodules.
• Further external validation is recommended to confirm the findings and clinical utility.