Detecting peritoneal dissemination of ovarian cancer in mice by DWIBS

Hye Jeong Lee, Jeffrey J. Luci, Mohammed N. Tantawy, Haakil Lee, Ki Taek Nam, Todd E. Peterson, Ronald R. Price

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)


Diffusion-weighted whole-body imaging with background body signal suppression (DWIBS) is a relatively new diffusion-based pulse sequence that produces positron emission tomography (PET) with 2-[fluorine-18]-fluoro-2-deoxy-D-glucose (18F-FDG)-like images. We tested the feasibility of DWIBS in detecting peritoneal ovarian cancer in a syngeneic mouse model. Female C57BL/6 mice were injected intraperitoneally with ID8 murine ovarian carcinoma cells. After 11 weeks, the abdomen was imaged by DWIBS. A respiratory gating diffusion-weighted spin-echo echo-planar imaging in abdomen was used (imaging parameters of field of view of 47×47 mm2, matrix size of 64×64 zero-filled to 256×256 and b-value of 1500 s/mm2). We also performed FDG microPET as the reference standard. For comparison of the correlating surface areas of tumor foci on both DWIBS and FDG microPET imaging, two-dimensional region-of-interest (ROI) analysis was performed, and correlation between the two modalities was determined. Mice were also subjected to macroscopic examination for tumor location and pathology after imaging. DWIBS in all mice depicted the tumors as abnormal high signal intensity. The results show that the ROI analysis of correlating lesions reveals relatively high correlation (r2=0.7296) and significant difference (P=021) between DWIBS and FDG microPET. These results demonstrate that DWIBS has the potential for detecting peritoneal dissemination of ovarian cancer. Nonetheless, due to low ratios of image signal-to-noise and motion artifacts, DWIBS can be limited for lesions near the liver.

Original languageEnglish
Pages (from-to)227-234
Number of pages8
JournalMagnetic Resonance Imaging
Issue number2
Publication statusPublished - 2013 Feb

Bibliographical note

Funding Information:
We appreciate excellent support from the Vanderbilt University Institute of Imaging Science. We thank Dr. Dineo Khabele for discussing the ovarian cancer mouse model. We also thank Jarrod True and Jordan Fritz at the CSAI for their assistance with microPET and microCT scan, and Jeff Clanton and Jarrod Driskill for 18 F-FDG production. This work was supported by NIH grants NIH R25 CA092043 and NIH P30 CA68485 .

All Science Journal Classification (ASJC) codes

  • Biophysics
  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging


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