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A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

Published on: April 21, 2023

Avoidable biopsies? Validating artificial intelligence-based decision support software in indeterminate thyroid

Christopher J Carnabatu¹, David T Fetzer², Alexander Tessnow³

¹Division of Endocrine Surgery, UT Southwestern Medical Center, Dallas, TX. Electronic address: https://twitter.com/CarnabatuMD.

|October 13, 2024

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This summary is machine-generated.

This study validated an artificial intelligence (AI) system for thyroid nodule risk stratification. The AI improved malignancy classification accuracy, potentially reducing unnecessary biopsies for indeterminate thyroid nodules.

Area of Science:

Medical imaging
Artificial intelligence in medicine
Oncology

Background:

Artificial intelligence (AI) systems are increasingly approved for thyroid nodule risk stratification using sonographic data.
Validating AI tools like Koios DS is crucial for improving diagnostic accuracy.

Purpose of the Study:

To validate the Koios DS artificial intelligence (AI) system for enhanced risk stratification of indeterminate thyroid nodules.
To assess the AI's impact on malignancy classification and biopsy decisions.

Main Methods:

Retrospective analysis of 28 indeterminate thyroid nodules with molecular testing and surgical pathology.
Evaluation of nodules using Koios DS, comparing AI-derived and radiologist-derived Thyroid Imaging Reporting and Data System (TI-RADS) levels.

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Assessment of malignancy classification performance and biopsy threshold adjustments using the AI-adapter.

Main Results:

The AI system showed fair agreement (Cohen's κ=0.25) with radiologist-derived TI-RADS levels.
The AI-adapter improved malignancy classification, increasing positive predictive value (PPV) from 33.3% to 54.5% while minimally impacting negative predictive value (NPV).
Utilizing the AI-adapter could have deferred 14 biopsies, with 13 of those being benign.

Conclusions:

Koios DS demonstrated consistent agreement with radiologist assessments for indeterminate thyroid nodules.
The AI-adapter enhances malignancy risk stratification, improving PPV with minimal reduction in NPV.
AI-assisted risk stratification may improve patient counseling and reduce unnecessary biopsies for indeterminate thyroid nodules.