Literature DB >> 21546154

Computerized detection and quantification of microcalcifications in thyroid nodules.

Kuen-Yuan Chen1, Chiung-Nien Chen, Ming-Hsun Wu, Ming-Chih Ho, Hao-Chih Tai, Wen-Chang Huang, Yuan-Chang Chung, Argon Chen, King-Jen Chang.   

Abstract

To improve the ultrasonographic detection rates of thyroid cancers with microcalcifications, we propose to enhance the sensitivity of sonographic calcifications detection and to avoid interobserver variation by a computerized quantification method in a prospective setting. A total of 227 participants with 258 nodules were evaluated. Among them, two nodules were excluded for suspicious aspiration cytology results without pathologic proof. Among the remaining 256 nodules, the diagnosis of 181 nodules was verified by surgical pathology and the diagnosis of 75 was based on fine needle aspiration (FNA) biopsy results. There were 173 benign thyroid nodules and 83 malignant thyroid nodules, which included 74 papillary carcinomas. Patient clinical data were collected and the presence of calcifications on conventional gray-scale ultrasound images was retrospectively reviewed by a thyroid specialist. Quantification of cystic components and calcifications was automatically performed by a proprietary program (AmCAD-UT) implemented with methods proposed in this article. The calcification index (CI) was calculated after the cystic component was excluded. The CI between benign and malignant nodules diagnosed by combined FNA biopsy and surgical pathology results (total number, 256) showed a significant difference (p < 0.0001, AUC = 0.746). Furthermore, we excluded patients without surgical pathology results for further validation and the CI between benign and malignant nodules confirmed by pathology results (total number, 181) showed a significant difference (p < 0.0001, AUC = 0.763). To learn whether our computer program increased our diagnostic capabilities, we analyzed human investigators and their abilities to detect and evaluate. In this study, calcifications were noted in 48.19% (40 of 83) of malignant thyroid nodules and in 10.98% (19 of 173) of benign nodules. This new computer-aided diagnosis method to evaluate the sonographic calcifications of thyroid nodules is a more sensitive and more objective method. It can provide better sensitivity than conventional methods in the diagnosis of thyroid malignancies containing microcalcifications.
Copyright © 2011 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Entities:  

Mesh:

Year:  2011        PMID: 21546154     DOI: 10.1016/j.ultrasmedbio.2011.03.002

Source DB:  PubMed          Journal:  Ultrasound Med Biol        ISSN: 0301-5629            Impact factor:   2.998


  6 in total

1.  Software-Based Analysis of the Taller-Than-Wide Feature of High-Risk Thyroid Nodules.

Authors:  Ming-Hsun Wu; Kuen-Yuan Chen; Argon Chen; Chiung-Nien Chen
Journal:  Ann Surg Oncol       Date:  2021-01-03       Impact factor: 5.344

2.  Risk Stratification in Patients With Follicular Neoplasm on Cytology: Use of Quantitative Characteristics and Sonographic Patterns.

Authors:  Ming-Hsun Wu; Kuen-Yuan Chen; Min-Shu Hsieh; Argon Chen; Chiung-Nien Chen
Journal:  Front Endocrinol (Lausanne)       Date:  2021-04-30       Impact factor: 5.555

3.  Quantitative analysis of echogenicity for patients with thyroid nodules.

Authors:  Ming-Hsun Wu; Chiung-Nien Chen; Kuen-Yuan Chen; Ming-Chih Ho; Hao-Chih Tai; Yu-Hsin Wang; Argon Chen; King-Jen Chang
Journal:  Sci Rep       Date:  2016-10-20       Impact factor: 4.379

Review 4.  Artificial Intelligence for Personalized Medicine in Thyroid Cancer: Current Status and Future Perspectives.

Authors:  Ling-Rui Li; Bo Du; Han-Qing Liu; Chuang Chen
Journal:  Front Oncol       Date:  2021-02-09       Impact factor: 6.244

5.  Assessing Detection Accuracy of Computerized Sonographic Features and Computer-Assisted Reading Performance in Differentiating Thyroid Cancers.

Authors:  Hao-Chih Tai; Kuen-Yuan Chen; Ming-Hsun Wu; King-Jen Chang; Chiung-Nien Chen; Argon Chen
Journal:  Biomedicines       Date:  2022-06-26

6.  The Diagnostic Efficiency of Ultrasound Computer-Aided Diagnosis in Differentiating Thyroid Nodules: A Systematic Review and Narrative Synthesis.

Authors:  Nonhlanhla Chambara; Michael Ying
Journal:  Cancers (Basel)       Date:  2019-11-08       Impact factor: 6.639

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.