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Wang F, Zhao D, Xu WY, Liu Y, Sun H, Lu S, Ji Y, Jiang J, Chen Y, He Q, Gong C, Liu R, Su Z, Dong Y, Yan Z, Liu L. Blood leukocytes as a non-invasive diagnostic tool for thyroid nodules: a prospective cohort study. BMC Med 2024; 22:147. [PMID: 38561764 PMCID: PMC10986011 DOI: 10.1186/s12916-024-03368-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Accepted: 03/22/2024] [Indexed: 04/04/2024] Open
Abstract
BACKGROUND Thyroid nodule (TN) patients in China are subject to overdiagnosis and overtreatment. The implementation of existing technologies such as thyroid ultrasonography has indeed contributed to the improved diagnostic accuracy of TNs. However, a significant issue persists, where many patients undergo unnecessary biopsies, and patients with malignant thyroid nodules (MTNs) are advised to undergo surgery therapy. METHODS This study included a total of 293 patients diagnosed with TNs. Differential methylation haplotype blocks (MHBs) in blood leukocytes between MTNs and benign thyroid nodules (BTNs) were detected using reduced representation bisulfite sequencing (RRBS). Subsequently, an artificial intelligence blood leukocyte DNA methylation (BLDM) model was designed to optimize the management and treatment of patients with TNs for more effective outcomes. RESULTS The DNA methylation profiles of peripheral blood leukocytes exhibited distinctions between MTNs and BTNs. The BLDM model we developed for diagnosing TNs achieved an area under the curve (AUC) of 0.858 in the validation cohort and 0.863 in the independent test cohort. Its specificity reached 90.91% and 88.68% in the validation and independent test cohorts, respectively, outperforming the specificity of ultrasonography (43.64% in the validation cohort and 47.17% in the independent test cohort), albeit with a slightly lower sensitivity (83.33% in the validation cohort and 82.86% in the independent test cohort) compared to ultrasonography (97.62% in the validation cohort and 100.00% in the independent test cohort). The BLDM model could correctly identify 89.83% patients whose nodules were suspected malignant by ultrasonography but finally histological benign. In micronodules, the model displayed higher specificity (93.33% in the validation cohort and 92.00% in the independent test cohort) and accuracy (88.24% in the validation cohort and 87.50% in the independent test cohort) for diagnosing TNs. This performance surpassed the specificity and accuracy observed with ultrasonography. A TN diagnostic and treatment framework that prioritizes patients is provided, with fine-needle aspiration (FNA) biopsy performed only on patients with indications of MTNs in both BLDM and ultrasonography results, thus avoiding unnecessary biopsies. CONCLUSIONS This is the first study to demonstrate the potential of non-invasive blood leukocytes in diagnosing TNs, thereby making TN diagnosis and treatment more efficient in China.
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Affiliation(s)
- Feihang Wang
- Department of Interventional Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- National Clinical Research Center for Interventional Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- Shanghai Institute of Medical Imaging, Shanghai, 200032, China
| | - Danyang Zhao
- Department of Interventional Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- National Clinical Research Center for Interventional Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- Shanghai Institute of Medical Imaging, Shanghai, 200032, China
| | - Wang-Yang Xu
- Singlera Genomics (Shanghai) Ltd., Shanghai, 201203, China
| | - Yiying Liu
- Singlera Genomics (Shanghai) Ltd., Shanghai, 201203, China
| | - Huiyi Sun
- Department of Interventional Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- National Clinical Research Center for Interventional Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- Shanghai Institute of Medical Imaging, Shanghai, 200032, China
| | - Shanshan Lu
- Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Yuan Ji
- Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Jingjing Jiang
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Yi Chen
- Department of Interventional Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- National Clinical Research Center for Interventional Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- Shanghai Institute of Medical Imaging, Shanghai, 200032, China
| | - Qiye He
- Singlera Genomics (Shanghai) Ltd., Shanghai, 201203, China
| | | | - Rui Liu
- Singlera Genomics (Shanghai) Ltd., Shanghai, 201203, China
| | - Zhixi Su
- Singlera Genomics (Shanghai) Ltd., Shanghai, 201203, China.
| | - Yi Dong
- Department of Ultrasound, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, China.
| | - Zhiping Yan
- Department of Interventional Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
- National Clinical Research Center for Interventional Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
- Shanghai Institute of Medical Imaging, Shanghai, 200032, China.
| | - Lingxiao Liu
- Department of Interventional Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
- National Clinical Research Center for Interventional Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
- Shanghai Institute of Medical Imaging, Shanghai, 200032, China.
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Yang L, Li C, Chen Z, He S, Wang Z, Liu J. Diagnostic efficiency among Eu-/C-/ACR-TIRADS and S-Detect for thyroid nodules: a systematic review and network meta-analysis. Front Endocrinol (Lausanne) 2023; 14:1227339. [PMID: 37720531 PMCID: PMC10501732 DOI: 10.3389/fendo.2023.1227339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 08/16/2023] [Indexed: 09/19/2023] Open
Abstract
Background The performance in evaluating thyroid nodules on ultrasound varies across different risk stratification systems, leading to inconsistency and uncertainty regarding diagnostic sensitivity, specificity, and accuracy. Objective Comparing diagnostic performance of detecting thyroid cancer among distinct ultrasound risk stratification systems proposed in the last five years. Evidence acquisition Systematic search was conducted on PubMed, EMBASE, and Web of Science databases to find relevant research up to December 8, 2022, whose study contents contained elucidation of diagnostic performance of any one of the above ultrasound risk stratification systems (European Thyroid Imaging Reporting and Data System[Eu-TIRADS]; American College of Radiology TIRADS [ACR TIRADS]; Chinese version of TIRADS [C-TIRADS]; Computer-aided diagnosis system based on deep learning [S-Detect]). Based on golden diagnostic standard in histopathology and cytology, single meta-analysis was performed to obtain the optimal cut-off value for each system, and then network meta-analysis was conducted on the best risk stratification category in each system. Evidence synthesis This network meta-analysis included 88 studies with a total of 59,304 nodules. The most accurate risk category thresholds were TR5 for Eu-TIRADS, TR5 for ACR TIRADS, TR4b and above for C-TIRADS, and possible malignancy for S-Detect. At the best thresholds, sensitivity of these systems ranged from 68% to 82% and specificity ranged from 71% to 81%. It identified the highest sensitivity for C-TIRADS TR4b and the highest specificity for ACR TIRADS TR5. However, sensitivity for ACR TIRADS TR5 was the lowest. The diagnostic odds ratio (DOR) and area under curve (AUC) were ranked first in C-TIRADS. Conclusion Among four ultrasound risk stratification options, this systemic review preliminarily proved that C-TIRADS possessed favorable diagnostic performance for thyroid nodules. Systematic review registration https://www.crd.york.ac.uk/prospero, CRD42022382818.
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Affiliation(s)
- Longtao Yang
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Cong Li
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Zhe Chen
- Department of Thoracic Surgery, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Shaqi He
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Zhiyuan Wang
- Department of Ultrasound, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, Hunan, China
| | - Jun Liu
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
- Clinical Research Center for Medical Imaging in Hunan Province, Changsha, China
- Department of Radiology Quality Control Center in Hunan Province, Changsha, China
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