Literature DB >> 23791356

Quantitative analysis of dynamic power Doppler sonograms for patients with thyroid nodules.

Ming-Hsun Wu1, Chiung-Nien Chen, Kuen-Yuan Chen, Ming-Chih Ho, Hao-Chih Tai, Yuan-Chang Chung, Chan-Peng Lo, Argon Chen, King-Jen Chang.   

Abstract

To clarify and determine whether power Doppler sonograms are useful for the detection of malignant thyroid nodules, a computerized quantification method was used to evaluate the vascular density of a thyroid nodule in a prospective setting. Sonographic power Doppler images were collected in consecutive frames (45 frames of images), and a proprietary program (AmCAD-UV) was implemented using methods proposed in this article automatically calculated a quantified power Doppler vascular index (PDVI). The minimum PDVI value (PDVImin) was suggested as a measure of the vascular density of the nodule. The vascular densities of the peripheral and central areas of the nodule, referred to as central PDVImin and Ring PDVImin, respectively, were also evaluated. For 238 tumors (79 malignant and 159 benign) from 208 patients, all of the proposed indices of benign lesions were significantly higher than those of the malignant lesions. The area under the receiver operating characteristic curve (AUC) reaches 71% with the PDVImin. When the vascular patterns were further classified into intra-nodular and peripheral vascularity types, no vascularity type was observed significantly more frequently in malignant nodules than in benign nodules. These proposed computerized vascular indices provide a quantification method to objectively evaluate thyroid nodules and have potential as predictors of thyroid malignancy. The conventional vascular characterizations of malign nodules, that is, more vessels are observed in malignant nodules than in benign nodules, are shown to be unreliable in our study. Instead, a higher value of the quantified power Doppler vascular density was observed in benign nodules.
Copyright © 2013 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Computer-aided detection; Power Doppler; Thyroid cancer; Vascular index; Vascularity

Mesh:

Year:  2013        PMID: 23791356     DOI: 10.1016/j.ultrasmedbio.2013.03.009

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


  11 in total

1.  Is vascular flow a predictor of malignant thyroid nodules? A meta-analysis.

Authors:  Helmi Khadra; Mohamed Bakeer; Adam Hauch; Tian Hu; Emad Kandil
Journal:  Gland Surg       Date:  2016-12

2.  Superb microvascular imaging compared with contrast-enhanced ultrasound to assess microvessels in thyroid nodules.

Authors:  Zhao Yongfeng; Zhou Ping; Peng Hong; Liu Wengang; Zhang Yan
Journal:  J Med Ultrason (2001)       Date:  2020-03-03       Impact factor: 1.314

3.  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

4.  Vascular flow on doppler sonography may not be a valid characteristic to distinguish colloid nodules from papillary thyroid carcinoma even when accounting for nodular size.

Authors:  J Matthew Debnam; Thinh Vu; Jia Sun; Wei Wei; Savitri Krishnamurthy; Mark E Zafereo; Steven P Weitzman; Naveen Garg; Salmaan Ahmed
Journal:  Gland Surg       Date:  2019-10

5.  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

6.  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

7.  Computer-aided assessment of regional vascularity of thyroid nodules for prediction of malignancy.

Authors:  Faisal N Baig; Jurgen T J van Lunenburg; Shirley Y W Liu; Shea-Ping Yip; Helen K W Law; Michael Ying
Journal:  Sci Rep       Date:  2017-10-30       Impact factor: 4.379

8.  Analysis of vascularization in thyroid gland nodes with superb microvascular imaging (SMI) and CD34 expression histology: a pilot study.

Authors:  Thomas Studeny; Wolfgang Kratzer; Julian Schmidberger; Tilmann Graeter; Thomas F E Barth; Andreas Hillenbrand
Journal:  BMC Med Imaging       Date:  2021-10-30       Impact factor: 1.930

9.  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

10.  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

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