  Diffusion-weighted magnetic resonance imaging (DW-MRI) is used to
characterize brain tissue microstructure employing tissue-specific biophysical
models. A current limitation, however, is that most of the proposed models are
based on the assumption of negligible water exchange between the intra- and
extracellular compartments, which might not be valid in various brain tissues,
including unmyelinated axons, gray matter, and tumors. The purpose of this work
is to quantify the effect of membrane permeability on the estimates of two
popular models neglecting exchange, and compare their performance with a model
including exchange. To this aim, DW-MRI experiments were performed in
controlled environments with Monte-Carlo simulations. The DW-MRI signals were
generated in numerical substrates mimicking biological tissue made of spherical
cells with permeable membranes like cancerous tissue or the brain gray matter.
From these signals, the substrates properties were estimated using SANDI and
VERDICT, the two compartment-based models neglecting exchange, and CEXI, a new
model which includes exchange. Our results show that, in cellular permeable
tissue, the model with exchange outperformed models without exchange in the
estimation of the tissue properties by providing more stable estimates of cell
size, intracellular volume fraction and extracellular diffusion coefficient.
Moreover, the model with exchange estimated accurately the exchange time in the
range of permeability reported for cellular tissue. Finally, the simulations
performed in this work showed that the exchange between the intracellular and
the extracellular space cannot be neglected in permeable tissue with a
conventional PGSE sequence, to obtain accurate estimates. Consequently,
existing compartmentalized models of impermeable tissue cannot be used for
microstructure estimation of cellular permeable tissue.
