In vivo imaging of cancer cell size and cellularity using temporal diffusion spectroscopy.

Jiang X, Li H, Xie J, McKinley ET, Zhao P, Gore JC, Xu J
Magn Reson Med. 2017 78 (1): 156-164

PMID: 27495144 · PMCID: PMC5293685 · DOI:10.1002/mrm.26356

PURPOSE - A temporal diffusion MRI spectroscopy based approach has been developed to quantify cancer cell size and density in vivo.

METHODS - A novel imaging microstructural parameters using limited spectrally edited diffusion (IMPULSED) method selects a specific limited diffusion spectral window for an accurate quantification of cell sizes ranging from 10 to 20 μm in common solid tumors. In practice, it is achieved by a combination of a single long diffusion time pulsed gradient spin echo (PGSE) and three low-frequency oscillating gradient spin echo (OGSE) acquisitions. To validate our approach, hematoxylin and eosin staining and immunostaining of cell membranes, in concert with whole slide imaging, were used to visualize nuclei and cell boundaries, and hence, enabled accurate estimates of cell size and cellularity.

RESULTS - Based on a two compartment model (incorporating intra- and extracellular spaces), accurate estimates of cell sizes were obtained in vivo for three types of human colon cancers. The IMPULSED-derived apparent cellularities showed a stronger correlation (r = 0.81; P < 0.0001) with histology-derived cellularities than conventional ADCs (r = -0.69; P < 0.03).

CONCLUSION - The IMPULSED approach samples a specific region of temporal diffusion spectra with enhanced sensitivity to length scales of 10-20 μm, and enables measurements of cell sizes and cellularities in solid tumors in vivo. Magn Reson Med 78:156-164, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

© 2016 International Society for Magnetic Resonance in Medicine.

MeSH Terms (13)

Animals Cell Line, Tumor Cell Size Diffusion Tensor Imaging Female Humans Image Interpretation, Computer-Assisted Intravital Microscopy Magnetic Resonance Spectroscopy Mice, Nude Neoplasms, Experimental Reproducibility of Results Sensitivity and Specificity

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