Metastases in mediastinal and hilar lymph nodes in patients with non-small cell lung cancer: Quantitative assessment with diffusion-weighted magnetic resonance imaging and apparent diffusion coefficient

Jun Nakayama, Kazuo Miyasaka, Tokuhiko Omatsu, Yuuya Onodera, Satoshi Terae, Yoshihiro Matsuno, Yasushi Cho, Yasuhiro Hida, Kichizo Kaga, Hiroki Shirato

Research output: Contribution to journalArticlepeer-review

68 Citations (Scopus)

Abstract

Objective: To evaluate diffusion-weighted magnetic resonance (DW-MR) imaging for detection of metastases in lymph nodes by using quantitative analysis. Methods: Seventy patients with non-small cell lung cancer were examined with DW and short inversion time inversion recovery (STIR) turbo-spin-echo MR imaging. Apparent diffusion coefficient of each lung cancer and lymph node was calculated from DW-MR images. Difference of the apparent diffusion coefficient in a lung cancer and a lymph node was calculated (D1). From STIR turbo-spin-echo MR images, ratios of signal intensity in a lymph node to that in a 0.9% saline phantom was calculated (lymph node-saline ratio [LSR1]). For quantitative analysis, the threshold value for a positive test was determined on a per node basis and tested for ability to enable a correct diagnosis on a per patient basis. Results of quantitative analyses of DW- and STIR-MR images were compared on a per patient basis with McNemar testing. Results: Mean D1 in the lymph node group with metastases was lower than that in the group without metastases (P < 0.001). When an D1 of 0.24 × 10 mm/s was used as the positive test threshold, sensitivity, specificity, and accuracy were 69.2%, 100%, and 94.0%, respectively, on a per patient basis. There was no significant difference (P > 0.05) between quantitative analyses of DW-MR images and STIR-MR images. Conclusions: Quantitative analysis of DW-MR images enables differentiation of lymph nodes with metastasis from those without.

Original languageEnglish
Pages (from-to)1-8
Number of pages8
JournalJournal of Computer Assisted Tomography
Volume34
Issue number1
DOIs
Publication statusPublished - 01-2010
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging

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