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Artificial intelligence defines protein-based classification of thyroid nodules.


ABSTRACT: Determination of malignancy in thyroid nodules remains a major diagnostic challenge. Here we report the feasibility and clinical utility of developing an AI-defined protein-based biomarker panel for diagnostic classification of thyroid nodules: based initially on formalin-fixed paraffin-embedded (FFPE), and further refined for fine-needle aspiration (FNA) tissue specimens of minute amounts which pose technical challenges for other methods. We first developed a neural network model of 19 protein biomarkers based on the proteomes of 1724 FFPE thyroid tissue samples from a retrospective cohort. This classifier achieved over 91% accuracy in the discovery set for classifying malignant thyroid nodules. The classifier was externally validated by blinded analyses in a retrospective cohort of 288 nodules (89% accuracy; FFPE) and a prospective cohort of 294 FNA biopsies (85% accuracy) from twelve independent clinical centers. This study shows that integrating high-throughput proteomics and AI technology in multi-center retrospective and prospective clinical cohorts facilitates precise disease diagnosis which is otherwise difficult to achieve by other methods.

SUBMITTER: Sun Y 

PROVIDER: S-EPMC9448820 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

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Artificial intelligence defines protein-based classification of thyroid nodules.

Sun Yaoting Y   Selvarajan Sathiyamoorthy S   Zang Zelin Z   Liu Wei W   Zhu Yi Y   Zhang Hao H   Chen Wanyuan W   Chen Hao H   Li Lu L   Cai Xue X   Gao Huanhuan H   Wu Zhicheng Z   Zhao Yongfu Y   Chen Lirong L   Teng Xiaodong X   Mantoo Sangeeta S   Lim Tony Kiat-Hon TK   Hariraman Bhuvaneswari B   Yeow Serene S   Alkaff Syed Muhammad Fahmy SMF   Lee Sze Sing SS   Ruan Guan G   Zhang Qiushi Q   Zhu Tiansheng T   Hu Yifan Y   Dong Zhen Z   Ge Weigang W   Xiao Qi Q   Wang Weibin W   Wang Guangzhi G   Xiao Junhong J   He Yi Y   Wang Zhihong Z   Sun Wei W   Qin Yuan Y   Zhu Jiang J   Zheng Xu X   Wang Linyan L   Zheng Xi X   Xu Kailun K   Shao Yingkuan Y   Zheng Shu S   Liu Kexin K   Aebersold Ruedi R   Guan Haixia H   Wu Xiaohong X   Luo Dingcun D   Tian Wen W   Li Stan Ziqing SZ   Kon Oi Lian OL   Iyer Narayanan Gopalakrishna NG   Guo Tiannan T  

Cell discovery 20220906 1


Determination of malignancy in thyroid nodules remains a major diagnostic challenge. Here we report the feasibility and clinical utility of developing an AI-defined protein-based biomarker panel for diagnostic classification of thyroid nodules: based initially on formalin-fixed paraffin-embedded (FFPE), and further refined for fine-needle aspiration (FNA) tissue specimens of minute amounts which pose technical challenges for other methods. We first developed a neural network model of 19 protein  ...[more]

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