In vivo imaging of cancer cell size and cellularity using temporal diffusion spectroscopy.
Magn Reson Med
; 78(1): 156-164, 2017 07.
Article
em En
| MEDLINE
| ID: mdl-27495144
ABSTRACT
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 78156-164, 2017. © 2016 International Society for Magnetic Resonance in Medicine.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Interpretação de Imagem Assistida por Computador
/
Espectroscopia de Ressonância Magnética
/
Tamanho Celular
/
Imagem de Tensor de Difusão
/
Microscopia Intravital
/
Neoplasias Experimentais
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
Limite:
Animals
/
Female
/
Humans
Idioma:
En
Ano de publicação:
2017
Tipo de documento:
Article