Academic Radiology
Volume 15, Issue 7 , Pages 853-858 , July 2008

Computer-Aided Diagnosis for the Differentiation of Malignant from Benign Thyroid Nodules on Ultrasonography

  • Kyoung Ja Lim, MD

      Affiliations

    • Department of Radiology, College of Medicine, Hallym University, Kangdong Sacred Heart Hospital, Kil-1 dong, Kangdong-gu, Seoul 134-701, Korea
    • Department of Radiology, Kangwon National University College of Medicine, Kangwon-do, Korea
    • Department of Radiology, College of Medicine, University of Ulsan, Asan Medical Center, Seoul, Korea.
    • ,
  • Chul Soon Choi, MD

      Affiliations

    • Department of Radiology, College of Medicine, Hallym University, Kangdong Sacred Heart Hospital, Kil-1 dong, Kangdong-gu, Seoul 134-701, Korea
    • Corresponding Author InformationAddress correspondence to: C.S.C.
    • ,
  • Dae Young Yoon, MD

      Affiliations

    • Department of Radiology, College of Medicine, Hallym University, Kangdong Sacred Heart Hospital, Kil-1 dong, Kangdong-gu, Seoul 134-701, Korea
    • ,
  • Suk Ki Chang, MD

      Affiliations

    • Department of Radiology, College of Medicine, Hallym University, Kangdong Sacred Heart Hospital, Kil-1 dong, Kangdong-gu, Seoul 134-701, Korea
    • ,
  • Kwang Ki Kim, PhD

      Affiliations

    • Department of Biomedical Engineering Branch, Division of Basic and Applied Science, National Cancer Center, Geongi-do, Korea
    • ,
  • Heon Han, MD

      Affiliations

    • Department of Radiology, Kangwon National University College of Medicine, Kangwon-do, Korea
    • ,
  • Sam Soo Kim, MD

      Affiliations

    • Department of Radiology, Kangwon National University College of Medicine, Kangwon-do, Korea
    • ,
  • Jiwon Lee, MD

      Affiliations

    • Department of Radiology, Kangwon National University College of Medicine, Kangwon-do, Korea
    • ,
  • Yong Hwan Jeon, MD

      Affiliations

    • Department of Radiology, Kangwon National University College of Medicine, Kangwon-do, Korea

Received 3 August 2007 ,Accepted 25 December 2008.

Refernces 

  1. Kim EK, Park CS, Chung WY, et al. Incidentally found thyroid nodules in women with no previous thyroid disease: Its significance. In: J Korean Radiol Soc. 2002;449–453
  2. Marqusee E, Benson CB, Frates MC, et al. Usefulness of ultrasonography in the management of nodular thyroid disease. Ann Intern Med. 2000;133:696–700
  3. Mazzaferri EL. Management of a solitary thyroid nodule. N Engl J Med. 1993;328:553–559
  4. Hegedus L. Thyroid ultrasound. Endocrinol Metab Clin North Am. 2001;30:339–360
  5. Pacini F, Schlumberger M, Dralle H, et al. European consensus for the management of patients with differentiated thyroid carcinoma of the follicular epithelium. Eur J Endocrinol. 2006;154:787–803
  6. Frates MC, Benson CB, Doubilet PM, et al. Can color Doppler sonography aid in the prediction of malignancy of thyroid nodules?. J Ultrasound Med. 2003;22:127–131quiz 132–124
  7. Kim EK, Park CS, Chung WY, et al. New sonographic criteria for recommending fine-needle aspiration biopsy of nonpalpable solid nodules of the thyroid. AJR Am J Roentgenol. 2002;178:687–691
  8. Papini E, Guglielmi R, Bianchini A, et al. Risk of malignancy in nonpalpable thyroid nodules: Predictive value of ultrasound and color-Doppler features. J Clin Endocrinol Metab. 2002;87:1941–1946
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  16. Warren Burhenne LJ, Wood SA, D'Orsi CJ, et al. Potential contribution of computer-aided detection to the sensitivity of screening mammography. Radiology. 2000;215:554–562
  17. Metz CE. ROC methodology in radiologic imaging. Invest Radiol. 1986;21:720–733
  18. Frates MC, Benson CB, Charboneau JW, et al. Management of thyroid nodules detected at US: Society of Radiologists in Ultrasound consensus conference statement. Radiology. 2005;237:794–800
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  21. Fukushima A, Ashizawa K, Yamaguchi T, et al. Application of an artificial neural network to high-resolution CT: Usefulness in differential diagnosis of diffuse lung disease. AJR Am J Roentgenol. 2004;183:297–305
  22. Nakamura K, Yoshida H, Engelmann R, et al. Computerized analysis of the likelihood of malignancy in solitary pulmonary nodules with use of artificial neural networks. Radiology. 2000;214:823–830
  23. Matsuki Y, Nakamura K, Watanabe H, et al. Usefulness of an artificial neural network for differentiating benign from malignant pulmonary nodules on high-resolution CT: Evaluation with receiver operating characteristic analysis. AJR Am J Roentgenol. 2002;178:657–663

1 Dr. Lim's current address is Department of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 388-1 Pungnap-2 dong, Songpa-gu, Seoul 138-736, Korea.

PII: S1076-6332(08)00041-X

doi: 10.1016/j.acra.2007.12.022

Academic Radiology
Volume 15, Issue 7 , Pages 853-858 , July 2008

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