A novel computerised quantification of thyroid vascularity in the differentiation of malignant and benign thyroid nodules

被引:0
|
作者
Toomatari, Seyed Babak Moosavi [1 ]
Mohammadi, Afshin [2 ]
Sepehrvand, Nariman [3 ]
Toomatari, Seyed Ehsan Moosavi [4 ]
Ghasemi-Rad, Mohammad [5 ]
Shamspour, Saber Zafar [6 ]
Rezayi, Seyfollah [7 ]
Toubaei, Mohammadreza [1 ]
Sarabi, Zahra Karimi [8 ]
机构
[1] Zanjan Univ Med Sci, Dept Surg, Zanjan, Iran
[2] Urmia Univ Med Sci, Dept Radiol, Orumiyeh, Iran
[3] Univ Alberta, Dept Med, Edmonton, AB, Canada
[4] Tabriz Univ Med Sci, Dept Gen Surg, Tabriz, Iran
[5] Baylor Coll Med, Dept Radiol, Houston, TX 77030 USA
[6] Shiraz Univ Med Sci, Dept Neurosurg, Shiraz, Iran
[7] Urmia Univ Med Sci, Dept Surg, Orumiyeh, Iran
[8] Urmia Univ Med Sci, Dept Anaesthesiol, Orumiyeh, Iran
关键词
ultrasonography; thyroid nodule; colour mapping; malignancy; SONOGRAPHIC FEATURES; PREDICTIVE-VALUE; MANAGEMENT; SYSTEM;
D O I
10.5114/pjr.2019.91208
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Purpose: Only five percent of thyroid nodules are malignant. It is important to find reliable and at the same time non-invasive methods to identify high-risk nodules. The aim of this study was to determine the diagnostic validity of a morphologic feature-oriented approach of ultrasound study for the identification of malignant thyroid nodules. Material and methods: Seventy-one thyroid nodules in 71 consecutive patients were evaluated with both ultrasonography (US) and US-assisted fine needle aspiration biopsy (FNAB). Thyroid grey-scale and power Doppler US were performed, and a Windows-based software was designed to process power Doppler US (PDUS) images that were recorded directly by the US device. We provided a histogram graph of coloured pixels and calculated the Malignancy Index to identify the probability of malignancy for each thyroid nodule. Results: Thirty-six nodules (50.7%) were determined to be malignant in FNAB. Area under the receiver operating curve was 0.91 (95% CI: 0.85-0.98) for PDUS-based malignancy index in differentiating malignant thyroid nodules from benign ones. The best cut-off point for malignancy index was determined to be 0.092, with a sensitivity of 86.1% and specificity of 80% in identifying malignant nodules. Conclusions: This PDUS-driven malignancy index using a contour-finding algorithm approach could accurately and reliably differentiate malignant and benign thyroid nodules. As a pre-FNAB assessment, the malignancy index may be able to reduce the number of patients with nodular thyroid disease undergoing this invasive procedure.
引用
收藏
页码:E517 / E521
页数:5
相关论文
共 50 条
  • [1] Quantitative analysis of vascularity for thyroid nodules on ultrasound using superb microvascular imaging Can nodular vascularity differentiate between malignant and benign thyroid nodules?
    Hong, Min Ji
    Ahn, Hye Shin
    Ha, Su Min
    Park, Hyun Jeong
    Oh, Jiyun
    MEDICINE, 2022, 101 (05) : E28725
  • [2] Differentiation between Benign and Malignant Solid Thyroid Nodules Using an US Classification System
    Lee, Young Hun
    Kim, Dong Wook
    In, Hyun Sin
    Park, Ji Sung
    Kim, Sang Hyo
    Eom, Jae Wook
    Kim, Bomi
    Lee, Eun Joo
    Rho, Myung Ho
    KOREAN JOURNAL OF RADIOLOGY, 2011, 12 (05) : 559 - 567
  • [3] Diagnostic Value of Acoustic Radiation Force Impulse Quantification in the Differentiation of Benign and Malignant Thyroid Nodules
    Pandey, Niraj Nirmal
    Pradhan, Gaurav Shanker
    Manchanda, Alpana
    Garg, Anju
    ULTRASONIC IMAGING, 2017, 39 (05) : 326 - 336
  • [4] Strain Elastography for Differentiation between Benign and Malignant Thyroid Nodules
    Idrees, Asima
    Shahzad, Rafia
    Fatima, Ismat
    Shahid, Abubaker
    JCPSP-JOURNAL OF THE COLLEGE OF PHYSICIANS AND SURGEONS PAKISTAN, 2020, 30 (04): : 369 - 372
  • [5] The Accuracy of Sonography in the Differentiation of Benign and Malignant Thyroid Nodules
    Bacha, Raham
    Manzoor, Iqra
    JOURNAL OF DIAGNOSTIC MEDICAL SONOGRAPHY, 2025,
  • [6] Differentiation of Benign and Malignant Thyroid Nodules with ANFIS by Using Genetic Algorithm and Proposing a Novel CAD-Based Risk Stratification System of Thyroid Nodules
    Ozturk, Ahmet Cankat
    Haznedar, Hilal
    Haznedar, Bulent
    Ilgan, Seyfettin
    Erogul, Osman
    Kalinli, Adem
    DIAGNOSTICS, 2023, 13 (04)
  • [7] The Utility of Ultrasound Elastography and MicroPure Imaging in the Differentiation of Benign and Malignant Thyroid Nodules
    Ciledag, Nazan
    Arda, Kemal
    Aribas, Bilgin Kadri
    Aktas, Elif
    Kose, Serdal Kenan
    AMERICAN JOURNAL OF ROENTGENOLOGY, 2012, 198 (03) : W244 - W249
  • [8] Thyroid Cancer Polygenic Risk Score Improves Classification of Thyroid Nodules as Benign or Malignant
    Pozdeyev, Nikita
    Dighe, Manjiri
    Barrio, Martin
    Raeburn, Christopher
    Smith, Harry
    Fisher, Matthew
    Chavan, Sameer
    Rafaels, Nicholas
    Shortt, Jonathan A.
    Lin, Meng
    Leu, Michael G.
    Clark, Toshimasa
    Marshall, Carrie
    Haugen, Bryan R.
    Subramanian, Devika
    Crooks, Kristy
    Gignoux, Christopher
    Cohen, Trevor
    JOURNAL OF CLINICAL ENDOCRINOLOGY & METABOLISM, 2024, 109 (02) : 402 - 412
  • [9] Ultrasound-based differentiation of malignant and benign thyroid Nodules: An extreme learning machine approach
    Xia, Jianfu
    Chen, Huiling
    Li, Qiang
    Zhou, Minda
    Chen, Limin
    Cai, Zhennao
    Fang, Yang
    Zhou, Hong
    COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2017, 147 : 37 - 49
  • [10] Distinguishing mummified thyroid nodules from malignant thyroid nodules
    Tan, Xiao Qu
    Qian, Lin Xue
    Wang, Yun Hong
    MEDICAL ULTRASONOGRAPHY, 2019, 21 (03) : 251 - 256