論文

査読有り
2013年7月

Multiparametric MR imaging for differentiating between benign and malignant thyroid nodules: Initial experience in 23 patients

Journal of Magnetic Resonance Imaging
  • Miho Sasaki
  • ,
  • Misa Sumi
  • ,
  • Ken-Ichi Kaneko
  • ,
  • Kotaro Ishimaru
  • ,
  • Haruo Takahashi
  • ,
  • Takashi Nakamura

38
1
開始ページ
64
終了ページ
71
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1002/jmri.23948

Purpose To evaluate multiparametric MR imaging with combined use of apparent diffusion coefficients (ADCs) and time-signal intensity curves (TICs) for discriminating malignant thyroid nodules from benign ones. Materials and Methods ADCs and TICs of 7 benign and 16 malignant nodules were retrospectively analyzed on lesion-by-lesion (overall ADCs and TICs) and pixel-by-pixel (ADC and TIC mapping) bases. ADCs were determined using b-values of 500 and 1000 s/mm2. The TICs were classified into 5 patterns on the basis of increment ratio, peak time, and washout ratio. Stepwise approach based on ADC and TIC criteria was used to discriminate between benign and malignant nodules. Results Overall ADC discriminated undifferentiated carcinomas from papillary carcinomas at 91% accuracy (≤1.3 × 10-3 mm2/s) and differentiated lymphomas from the other malignant nodules at 100% accuracy (≤0.65 × 10-3 mm2/s). Most malignant thyroid nodules had large (≥45%) areas of rapid-uptake TIC profile with small (≤15%) areas of flat TIC profile, or had small (&lt
45%) areas of rapid-uptake TIC profile with large (≥25%) areas of extremely low or low ADCs (≤1.2 × 10-3 mm2/s). Stepwise approach discriminated malignant nodules from benign ones at 91% accuracy. Conclusion The multiparametric MR imaging helps discriminating malignant thyroid nodules from benign ones. © 2012 Wiley Periodicals, Inc.

リンク情報
DOI
https://doi.org/10.1002/jmri.23948
PubMed
https://www.ncbi.nlm.nih.gov/pubmed/23188483
URL
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84880125050&origin=inward
ID情報
  • DOI : 10.1002/jmri.23948
  • ISSN : 1053-1807
  • ISSN : 1522-2586
  • PubMed ID : 23188483
  • SCOPUS ID : 84880125050

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