Reproducibility of APT-weighted CEST-MRI at 3T in healthy brain and tumor across sessions and scanners

The Proton Resonance Enhancement for CEST imaging and Shift Exchange (PRECISE) family of RF pulse shapes for Chemical Exchange Saturation Transfer MRI

Purpose

To optimize a 100 msec pulse for producing CEST MRI contrast and evaluate in mice.

Methods

A gradient ascent algorithm was employed to generate a family of 100 point, 100 msec pulses for use in CEST pulse trains ('PRECISE'). Gradient ascent optimizations were performed for exchange rates (k ca ) = 500 s -1 , 1,500 s -1 , 2,500 s -1 , 3,500 s -1 and 4,500 s -1 and offsets (Δω) = 9.6, 7.8, 4.2 and 2.0 ppm. 7 PRECISE pulse shapes were tested on an 11.7 T scanner using a phantom containing three representative CEST agents with peak saturation B 1 = 4 μT. The pulse producing the most contrast in phantoms was then evaluated for CEST MRI pH mapping of the kidneys in healthy mice after iopamidol administration.

Results

The most promising pulse in terms of contrast performance across all three phantoms was the 9.6 ppm, 2500 s -1 optimized pulse with ∼2.7 x improvement over Gaussian and ∼1.3x's over Fermi pulses. This pulse also displayed a large improvement in contrast over the Gaussian pulse after administration of iopamidol in live mice.

Conclusion

A new 100 msec pulse was developed based on gradient ascent optimizations which produced better contrast compared to standard Gaussian and Fermi pulses in phantoms. This shape also showed a substantial improvement for CEST MRI pH mapping in live mice over the Gaussian shape and appears promising for a wide range of CEST applications.

Diagnostic and Therapeutic Issues in Glioma Using Imaging Data: The Challenge of Numerical Twinning

Glial tumors represent the leading etiology of primary brain tumors. Their particularities lie in (i) their location in a highly functional organ that is difficult to access surgically, including for biopsy, and (ii) their rapid, anisotropic mode of extension, notably via the fiber bundles of the white matter, which further limits the possibilities of resection. The use of mathematical tools enables the development of numerical models representative of the oncotype, genotype, evolution, and therapeutic response of lesions. The significant development of digital technologies linked to high-resolution NMR exploration, coupled with the possibilities offered by AI, means that we can envisage the creation of digital twins of tumors and their host organs, thus reducing the use of physical sampling.