Correlation of diffusion-weighted imaging data with apoptotic and proliferation indexes in CT26 colorectal tumor homografts in balb/c mouse

J Magn Reson Imaging. 2011 May;33(5):1171-6. doi: 10.1002/jmri.22558.

Abstract

Purpose: To investigate whether the percentage of apparent diffusion coefficient (ADC) changes could be used as an imaging marker related to tumor cell apoptotic and Ki-67 proliferation index of tumors.

Materials and methods: Mice bearing CT26 colorectal carcinoma tumors were scanned before radiotherapy, then divided into radiotherapy (n = 24) and control groups (n = 24). Diffusion-weighted imaging (DWI) and anatomic T2WI were performed on six randomly chosen mice in total from two groups at different timepoints after radiotherapy (4, 8, 12 hours, 1, 2, 3, 5, 7 days). After imaging, six animals were sacrificed at each timepoint and histological analyses were undertaken. ADC maps were calculated on a pixel-by-pixel basis using built-in software (Functool, GE). Regions of interest were manually circumscribed for all high-signal areas on lesions observed during DWI. The percentage of ADC changes were calculated at predefined timepoints and compared with the apoptotic and proliferation index from the histological analyses by using the Pearson correlation test.

Results: A significant positive correlation was found between the percentage of ADC changes of the viable tissue and apoptotic index. A significant negative correlation was found between the percentage of ADC changes of the viable tissue and Ki-67 proliferation index.

Conclusion: Our results suggest that the percentage of ADC changes can be used as a measurement of cell apoptotic and proliferation index in colorectal carcinoma.

MeSH terms

  • Animals
  • Apoptosis
  • Biomarkers / metabolism
  • Cell Line, Tumor
  • Cell Proliferation
  • Diffusion Magnetic Resonance Imaging / methods*
  • Female
  • Humans
  • Ki-67 Antigen / biosynthesis
  • Magnetic Resonance Imaging / methods
  • Mice
  • Mice, Inbred BALB C
  • Radiotherapy / methods
  • Software
  • Time Factors

Substances

  • Biomarkers
  • Ki-67 Antigen