Literature DB >> 27131839

Diagnostic Accuracy of Computer-Aided Assessment of Intranodal Vascularity in Distinguishing Different Causes of Cervical Lymphadenopathy.

Michael Ying1, Sammy C H Cheng1, Anil T Ahuja2.   

Abstract

Ultrasound is useful in assessing cervical lymphadenopathy. Advancement of computer science technology allows accurate and reliable assessment of medical images. The aim of the study described here was to evaluate the diagnostic accuracy of computer-aided assessment of the intranodal vascularity index (VI) in differentiating the various common causes of cervical lymphadenopathy. Power Doppler sonograms of 347 patients (155 with metastasis, 23 with lymphoma, 44 with tuberculous lymphadenitis, 125 reactive) with palpable cervical lymph nodes were reviewed. Ultrasound images of cervical nodes were evaluated, and the intranodal VI was quantified using a customized computer program. The diagnostic accuracy of using the intranodal VI to distinguish different disease groups was evaluated and compared. Metastatic and lymphomatous lymph nodes tend to be more vascular than tuberculous and reactive lymph nodes. The intranodal VI had the highest diagnostic accuracy in distinguishing metastatic and tuberculous nodes with a sensitivity of 80%, specificity of 73%, positive predictive value of 91%, negative predictive value of 51% and overall accuracy of 68% when a cutoff VI of 22% was used. Computer-aided assessment provides an objective and quantitative way to evaluate intranodal vascularity. The intranodal VI is a useful parameter in distinguishing certain causes of cervical lymphadenopathy and is particularly useful in differentiating metastatic and tuberculous lymph nodes. However, it has limited value in distinguishing lymphomatous nodes from metastatic and reactive nodes.
Copyright © 2016 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Blood vessels; Computer assisted; Image processing; Lymph nodes; Power Doppler; Ultrasonography; Vascularity index

Mesh:

Year:  2016        PMID: 27131839     DOI: 10.1016/j.ultrasmedbio.2016.03.014

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


  6 in total

1.  Efficacy of logistic regression model based on multiparametric ultrasound in assessment of cervical lymphadenopathy - a retrospective study.

Authors:  Dongyan Cai; Size Wu
Journal:  Dentomaxillofac Radiol       Date:  2021-10-05       Impact factor: 2.419

2.  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

3.  Diagnostic Value of AngioPLUS Microvascular Imaging in Thyroid Nodule Diagnosis Using Quantitative and Qualitative Vascularity Grading.

Authors:  Nonhlanhla Chambara; Shirley Yuk Wah Liu; Xina Lo; Michael Ying
Journal:  Biomedicines       Date:  2022-06-29

4.  Deep learning radiomics of dual-modality ultrasound images for hierarchical diagnosis of unexplained cervical lymphadenopathy.

Authors:  Yangyang Zhu; Zheling Meng; Xiao Fan; Yin Duan; Yingying Jia; Tiantian Dong; Yanfang Wang; Juan Song; Jie Tian; Kun Wang; Fang Nie
Journal:  BMC Med       Date:  2022-08-26       Impact factor: 11.150

5.  Quantification of intranodal vascularity by computer pixel-counting method enhances the accuracy of ultrasound in distinguishing metastatic and tuberculous cervical lymph nodes.

Authors:  Sammy C H Cheng; Anil T Ahuja; Michael Ying
Journal:  Quant Imaging Med Surg       Date:  2019-11

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

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