Diffusion-weighted MR imaging for differentiating acute benign from pathologic compression fractures: A reinvestigation of the usefulness of diffusion-weighted imaging

Yun Hsuan Tzeng, Tein Yow Chang, Guo Shu Huang, Gong Yau Lan, Wu Yu Hou, Hung Ju Shen

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The aim of this study was to reinvestigate the usefulness of diffusion-weighted MR imaging for differentiating acute benign from neoplastic vertebral compression fractures. Thirty-three patients with 42 lesions of acute vertebral compression fractures on conventional MR imaging were examined with diffusion-weighted MR imaging using a steady-state free precession (SSFP) sequence. In 42 lesions, 24 lesions were benign osteoporotic compression fractures; the remaining 18 lesions were pathologic fractures due to metastatic tumor infiltration. All lesions were confirmed by surgical histopathology, clinical or MRI follow-up. The signal characteristics of all lesions were investigated and scored by two independent radiologists blinded to clinical information. On diffusion-weighted imaging, all lesions with acute benign fractures showed hypo- or isointense relative to normal vertebral body reflecting edema in the vertebral marrow. Most lesions with pathologic fractures showed hyperintense relative to normal vertebral body reflecting tumor infiltration in the vertebral marrow. Statistical analysis was performed using Student's t test, showing that there were significant difference in signal-intensity scores on diffusion-weighted imaging in these two groups (P < 0.01). Our results confirmed that diffusion-weighted MR imaging could be a useful and practicable tool on daily works in differentiating acute benign from pathologic compression fractures.

Original languageEnglish
Pages (from-to)109-115
Number of pages7
JournalChinese Journal of Radiology
Issue number3
Publication statusPublished - Jun 1 2004
Externally publishedYes



  • Diffusion study
  • Fractures, MR
  • Magnetic resonance (MR)
  • Spine

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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