Magnetic resonance imaging for lung cancer

Hisanobu Koyama, Yoshiharu Ohno, Shinichiro Seki, Mizuho Nishio, Takeshi Yoshikawa, Sumiaki Matsumoto, Kazuro Sugimura

Research output: Contribution to journalArticlepeer-review

67 Citations (Scopus)


Since the publication of the Radiologic Diagnostic Oncology Group Report in 1991, the clinical application of pulmonary magnetic resonance imaging (MRI) in patients with lung cancer has been limited. In contrast, MRI for lung cancer has undergone continuous development, and several promising techniques have been introduced to overcome the previously suggested limitations. In addition, comparative studies involving multidetector-row computed tomography and positron emission tomography or positron emission tomography/computed tomography with 2-deoxy-2-[F]fluoro-D-glucose have shown useful new clinical applications for MRI in lung cancer. Moreover, MRI can provide not only morphologic information based on various parameters such as T1 and T2 relaxation times, tissue diffusion, perfusion, etc. but also functional information; it also has a significant role in nuclear medicine studies. In this review article, we describe recent advances made in MRI with respect to lung cancer, focusing on (1) detection of solid pulmonary nodules; (2) characterization of solid pulmonary nodules; (3) TNM staging assessment using chest and whole-body MRI examinations; (4) prediction of postsurgical lung function; and (5) prediction of tumor treatment response. We believe that further basic studies, as well as studies on clinical applications of new MRI techniques, are important for improving the management of lung cancer patients.

Original languageEnglish
Pages (from-to)138-150
Number of pages13
JournalJournal of Thoracic Imaging
Issue number3
Publication statusPublished - 05-2013
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging
  • Pulmonary and Respiratory Medicine


Dive into the research topics of 'Magnetic resonance imaging for lung cancer'. Together they form a unique fingerprint.

Cite this