Literature DB >> 20018436

Ultrasonic Nakagami imaging: a strategy to visualize the scatterer properties of benign and malignant breast tumors.

Po-Hsiang Tsui1, Chih-Kuang Yeh, Yin-Yin Liao, Chien-Cheng Chang, Wen-Hung Kuo, King-Jen Chang, Chiung-Nien Chen.   

Abstract

Previous studies have demonstrated the usefulness of the Nakagami parameter in characterizing breast tumors by ultrasound. However, physicians or radiologists may need imaging tools in a clinical setting to visually identify the properties of breast tumors. This study proposed the ultrasonic Nakagami image to visualize the scatterer properties of breast tumors and then explored its clinical performance in classifying benign and malignant tumors. Raw data of ultrasonic backscattered signals were collected from 100 patients (50 benign and 50 malignant cases) using a commercial ultrasound scanner with a 7.5 MHz linear array transducer. The backscattered signals were used to form the B-scan and the Nakagami images of breast tumors. For each tumor, the average Nakagami parameter was calculated from the pixel values in the region-of-interest in the Nakagami image. The receiver operating characteristic (ROC) curve was used to evaluate the clinical performance of the Nakagami image. The results showed that the Nakagami image shadings in benign tumors were different from those in malignant cases. The average Nakagami parameters for benign and malignant tumors were 0.69 +/- 0.12 and 0.55 +/- 0.12, respectively. This means that the backscattered signals received from malignant tumors tend to be more pre-Rayleigh distributed than those from benign tumors, corresponding to a more complex scatterer arrangement or composition. The ROC analysis showed that the area under the ROC curve was 0.81 +/- 0.04 and the diagnostic accuracy was 82%, sensitivity was 92% and specificity was 72%. The results showed that the Nakagami image is useful to distinguishing between benign and malignant breast tumors. 2010 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

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Year:  2009        PMID: 20018436     DOI: 10.1016/j.ultrasmedbio.2009.10.006

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


  12 in total

1.  Quantitative Ultrasonic Nakagami Imaging of Neck Fibrosis After Head and Neck Radiation Therapy.

Authors:  Xiaofeng Yang; Emi Yoshida; Richard J Cassidy; Jonathan J Beitler; David S Yu; Walter J Curran; Tian Liu
Journal:  Int J Radiat Oncol Biol Phys       Date:  2015-03-25       Impact factor: 7.038

2.  Ultrasonic Nakagami-parameter characterization of parotid-gland injury following head-and-neck radiotherapy: a feasibility study of late toxicity.

Authors:  Xiaofeng Yang; Srini Tridandapani; Jonathan J Beitler; David S Yu; Ning Wu; Yuefeng Wang; Deborah W Bruner; Walter J Curran; Tian Liu
Journal:  Med Phys       Date:  2014-02       Impact factor: 4.071

3.  Three-dimensional high-frequency backscatter and envelope quantification of cancerous human lymph nodes.

Authors:  Jonathan Mamou; Alain Coron; Michael L Oelze; Emi Saegusa-Beecroft; Masaki Hata; Paul Lee; Junji Machi; Eugene Yanagihara; Pascal Laugier; Ernest J Feleppa
Journal:  Ultrasound Med Biol       Date:  2011-03       Impact factor: 2.998

4.  Noninvasive evaluation of vaginal fibrosis following radiotherapy for gynecologic malignancies: a feasibility study with ultrasound B-mode and Nakagami parameter imaging.

Authors:  Xiaofeng Yang; Peter Rossi; Deborah Watkins Bruner; Srini Tridandapani; Joseph Shelton; Tian Liu
Journal:  Med Phys       Date:  2013-02       Impact factor: 4.071

5.  Quantification of ultrasonic texture intra-heterogeneity via volumetric stochastic modeling for tissue characterization.

Authors:  Omar S Al-Kadi; Daniel Y F Chung; Robert C Carlisle; Constantin C Coussios; J Alison Noble
Journal:  Med Image Anal       Date:  2014-12-27       Impact factor: 8.545

6.  Small-window parametric imaging based on information entropy for ultrasound tissue characterization.

Authors:  Po-Hsiang Tsui; Chin-Kuo Chen; Wen-Hung Kuo; King-Jen Chang; Jui Fang; Hsiang-Yang Ma; Dean Chou
Journal:  Sci Rep       Date:  2017-01-20       Impact factor: 4.379

7.  Breast lesion characterization using Quantitative Ultrasound (QUS) and derivative texture methods.

Authors:  Laurentius O Osapoetra; Lakshmanan Sannachi; Daniel DiCenzo; Karina Quiaoit; Kashuf Fatima; Gregory J Czarnota
Journal:  Transl Oncol       Date:  2020-07-11       Impact factor: 4.243

8.  Breast-lesions characterization using Quantitative Ultrasound features of peritumoral tissue.

Authors:  Ziemowit Klimonda; Piotr Karwat; Katarzyna Dobruch-Sobczak; Hanna Piotrzkowska-Wróblewska; Jerzy Litniewski
Journal:  Sci Rep       Date:  2019-05-28       Impact factor: 4.379

9.  Insights into photoacoustic speckle and applications in tumor characterization.

Authors:  Eno Hysi; Muhannad N Fadhel; Michael J Moore; Jason Zalev; Eric M Strohm; Michael C Kolios
Journal:  Photoacoustics       Date:  2019-04-05

10.  Local scattering ultrasound imaging.

Authors:  Alexander Velichko; Eduardo Lopez Villaverde; Anthony J Croxford
Journal:  Sci Rep       Date:  2021-01-13       Impact factor: 4.379

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