PTC-MAS: A Deep Learning-Based Preoperative Automatic Assessment of Lymph Node Metastasis in Primary Thyroid Cancer

作者全名："Fu, Ruqian; Yang, Hao; Zeng, Dezhi; Yang, Shuhan; Luo, Peng; Yang, Zhijie; Teng, Hua; Ren, Jianli"

作者地址："[Fu, Ruqian; Yang, Hao; Zeng, Dezhi; Luo, Peng; Teng, Hua; Ren, Jianli] Chongqing Med Univ, Dept Ultrasound, Affiliated Hosp 2, Chongqing 400010, Peoples R China; [Fu, Ruqian; Yang, Hao; Zeng, Dezhi; Yang, Shuhan; Ren, Jianli] Chongqing Med Univ, Med Data Sci Acad, Chongqing 400010, Peoples R China; [Yang, Zhijie] Chongqing Med Univ, Breast & Thyroid Surg, Affiliated Hosp 2, Chongqing 400010, Peoples R China"

通信作者："Ren, JL (通讯作者)，Chongqing Med Univ, Dept Ultrasound, Affiliated Hosp 2, Chongqing 400010, Peoples R China.; Ren, JL (通讯作者)，Chongqing Med Univ, Med Data Sci Acad, Chongqing 400010, Peoples R China."

来源：DIAGNOSTICS

ESI学科分类：CLINICAL MEDICINE

WOS号：WOS:000996996900001

JCR分区：Q1

影响因子：3

年份：2023

卷号：13

期号：10

开始页：　

结束页：　

文献类型：Article

关键词：transfer learning; lymph node metastasis; thyroid cancer; deep learning; ultrasonography; diagnosis

摘要："Background: Identifying cervical lymph node metastasis (LNM) in primary thyroid cancer preoperatively using ultrasound is challenging. Therefore, a non-invasive method is needed to assess LNM accurately. Purpose: To address this need, we developed the Primary Thyroid Cancer Lymph Node Metastasis Assessment System (PTC-MAS), a transfer learning-based and B-mode ultrasound images-based automatic assessment system for assessing LNM in primary thyroid cancer. Methods: The system has two parts: YOLO Thyroid Nodule Recognition System (YOLOS) for obtaining regions of interest (ROIs) of nodules, and LMM assessment system for building the LNM assessment system using transfer learning and majority voting with extracted ROIs as input. We retained the relative size features of nodules to improve the system's performance. Results: We evaluated three transfer learning-based neural networks (DenseNet, ResNet, and GoogLeNet) and majority voting, which had the area under the curves (AUCs) of 0.802, 0.837, 0.823, and 0.858, respectively. Method III preserved relative size features and achieved higher AUCs than Method II, which fixed nodule size. YOLOS achieved high precision and sensitivity on a test set, indicating its potential for ROIs extraction. Conclusions: Our proposed PTC-MAS system effectively assesses primary thyroid cancer LNM based on preserving nodule relative size features. It has potential for guiding treatment modalities and avoiding inaccurate ultrasound results due to tracheal interference."

基金机构：Chongqing Medical University [YJSZHYX202207]; Chongqing Science and Health Joint Medical Research Project-Young and Middle-aged High-level Talent Project [2020GDRC011]

基金资助正文：This research was funded by 2022 Intelligent Medicine Graduate Student Innovation Program of Chongqing Medical University (grant number: YJSZHYX202207) and by Chongqing Science and Health Joint Medical Research Project-Young and Middle-aged High-level Talent Project (grant number: 2020GDRC011).