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

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, H&E 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.

Time-Dependent Diffusion MRI in Cancer: Tissue Modeling and Applications

“…The IMPULSED (imaging microstructural parameters using limited spectrally edited diffusion) model combines multiple low-frequency OGSE measurements (f OGSE < 150 Hz) and a single PGSE acquisition in the long time regime (Figure 4A) to quantify the characteristic size of restriction and ICS fraction [14,46]. This approach was shown successful in estimating cancer cell size in vitro in the range (5-10) µm using only a small subset of measurements on murine (MEL) and human leukemia cells (K562) [14].…”

“…This approach was shown successful in estimating cancer cell size in vitro in the range (5-10) µm using only a small subset of measurements on murine (MEL) and human leukemia cells (K562) [14]. In vivo, the correlation between histology and IMPULSEDbased cellularities were found superior than between histology and conventional PGSE measurements, in three different colorectal cancer xenograft tumor models (DiFi, HCT116, and SW620) [46]. This model assumes that the ECS diffusion varies linearly with frequency f OGSE in the range 50-150 Hz.…”

“…After preliminary work on model selection, . Synthetic data for different cell lines (SW620, GL261, and LS174T) were generated using the best fits for the diffusion signals respectively reported in Reynaud et al [15], Panagiotaki et al [16], Jiang et al [46]. The range of frequencies and diffusion times probed with IMPULSED (red), POMACE (blue) and VERDICT (green) can be appreciated in (A,B).…”

“…Similarly, synthetic diffusion data was generated using the IMPULSED framework [46] in order to mimic TDD in colorectal tumors (see Table 1). Multiple instances of gaussian noise (typical in vivo SNR = 120, n = 2,500) were added to the signal before fitting.…”

“…Distributions of intracellular volume fractions and cell radius estimates on noisy data (synthetic GL261 glioma signal, SNR = 120, n = 2,500) using (A) OGSE measurements in the range (65-225) Hz, or (B) a combination of PGSE ( 6/9/16/31 ms) and OGSE data as in POMACE [15]. Fit estimates distribution when characterizing tumor microstructure in vivo inside DiFi (C) and HCT116 (D) colorectal tumors with IMPULSED [46]. The ground truth is indicated by a black square.…”