Fast, interleaved, Look-Locker-based T1 mapping with a variable averaging approach: Towards temperature mapping at low magnetic field.

Proton resonance frequency shift (PRFS) is currently the gold standard method for magnetic resonance thermometry. However, the linearity between the temperature-dependent phase accumulation and the static magnetic field B0 confines its use to rather high-field scanners. Applications such as thermal therapies could naturally benefit from lower field MRI settings through leveraging increased accessibility, a lower physical and economical footprint, and further consideration of the technical challenges associated with the integration of heating systems into conventional clinical scanners. T 1 -based thermometry has been proposed as an alternative to the gold standard; however, because of longer acquisition times, it has found clinical use solely with adipose tissue where PRFS fails. At low field, the enhanced T 1 dispersion, combined with reduced relaxation times, make T 1 mapping an appealing candidate. Here, an interleaved Look-Locker-based T 1 mapping sequence was proposed for temperature quantification at 0.1 T. A variable averaging scheme was introduced, to maximize the signal-to-noise ratio throughout T 1 recovery. In calibrated samples, an average T 1 accuracy of 85% ± 4% was achieved in 10 min, compared with the 77% ± 7% obtained using a standard averaging scheme. Temperature maps between 29.0 and 41.7°C were eventually reconstructed, with a precision of 3.0 ± 1.1°C and an accuracy of 1.5 ± 1.0°C. Accounting for longer thermal treatments and less strict temperature constraints, applications such as MR-guided mild hyperthermia treatments at low field could be envisioned.

Impact of axisymmetric deformation on MR elastography of a nonlinear tissue-mimicking material and implications in peri-tumour stiffness quantification.

Solid tumour growth is often associated with the accumulation of mechanical stresses acting on the surrounding host tissue. Due to tissue nonlinearity, the shear modulus of the peri-tumoural region inherits a signature from the tumour expansion which depends on multiple factors, including the soft tissue constitutive behaviour and its stress/strain state. Shear waves used in MR-elastography (MRE) sense the apparent change in shear modulus along their propagation direction, thereby probing the anisotropic stiffness field around the tumour. We developed an analytical framework for a heterogeneous shear modulus distribution using a thick-shelled sphere approximation of the tumour and soft tissue ensemble. A hyperelastic material (plastisol) was identified to validate the proposed theory in a phantom setting. A balloon-catheter connected to a pressure sensor was used to replicate the stress generated from tumour pressure and growth while MRE data were acquired. The shear modulus anisotropy retrieved from the reconstructed elastography data confirmed the analytically predicted patterns at various levels of inflation. An alternative measure, combining the generated deformation and the local wave direction and independent of the reconstruction strategy, was also proposed to correlate the analytical findings with the stretch probed by the waves. Overall, this work demonstrates that MRE in combination with non-linear mechanics, is able to identify the apparent shear modulus variation arising from the strain generated by a growth within tissue, such as an idealised model of tumour. Investigation in real tissue represents the next step to further investigate the implications of endogenous forces in tissue characterisation through MRE.

Towards noninvasive estimation of tumour pressure by utilising MR elastography and nonlinear biomechanical models: a simulation and phantom study.

The solid and fluid pressures of tumours are often elevated relative to surrounding tissue. This increased pressure is known to correlate with decreased treatment efficacy and potentially with tumour aggressiveness and therefore, accurate noninvasive estimates of tumour pressure would be of great value. We present a proof-of-concept method to infer the total tumour pressure, that is the sum of the fluid and solid parts, by examining stiffness in the peritumoural tissue with MR elastography and utilising nonlinear biomechanical models. The pressure from the tumour deforms the surrounding tissue leading to changes in stiffness. Understanding and accounting for these biases in stiffness has the potential to enable estimation of total tumour pressure. Simulations are used to validate the method with varying pressure levels, tumour shape, tumour size, and noise levels. Results show excellent matching in low noise cases and still correlate well with higher noise. Percent error remains near or below 10% for higher pressures in all noise level cases. Reconstructed pressures were also calculated from experiments with a catheter balloon embedded in a plastisol phantom at multiple inflation levels. Here the reconstructed pressures generally match the increases in pressure measured during the experiments. Percent errors between average reconstructed and measured pressures at four inflation states are 17.9%, 52%, 23.2%, and 0.9%. Future work will apply this method to in vivo data, potentially providing an important biomarker for cancer diagnosis and treatment.