A method for T₁ and T₂ relaxation times validation and harmonization as a support to MRI mapping

Area of Science:

• Medical Imaging
• Quantitative MRI
• Magnetic Resonance Spectroscopy

Background:

• Quantitative magnetic resonance imaging (MRI) T1 and T2 mapping are crucial for consistent clinical diagnosis and research.
• Variability in MRI protocols across different scanners and institutions hinders data harmonization and inter-center validation.
• Establishing reliable in-scanner reference standards is essential for accurate T1 and T2 map validation.

Purpose of the Study:

• To present a proof-of-concept for a novel method to validate and harmonize MRI T1 and T2 mapping data.
• To establish a standardized approach for intra- and inter-center data comparison using in-scan ground-truth references.
• To assess the performance of different MRI sequences using a standardized validation method.

Main Methods:

• Utilized manganese chloride (MnCl2) aqueous solutions with precisely measured T1 and T2 relaxation times via an NMR laboratory relaxometer.
• Renormalized MnCl2 relaxation times to scanner temperature, establishing in-scan ground-truth reference values.
• Applied the method across diverse clinical MRI scanners and sequences, including standard, turbo, IR, SE, IR-TSE, MOLLI, and T2-prep TrueFISP.

Main Results:

• Demonstrated good agreement for standard and turbo sequences (5% for IR, SE, IR-TSE; 10% for TSE).
• Observed under-estimation for MOLLI and over-estimation for T2-prep TrueFISP, consistent with existing literature.
• Confirmed the linearity of relaxation rates with concentration, as predicted by the Solomon-Bloembergen-Morgan theory, for most sequences.

Conclusions:

• The MnCl2 sample method provides a robust approach for intra- and inter-center validation and harmonization of MRI T1 and T2 maps.
• This technique facilitates reliable quantitative MRI data acquisition across different clinical settings and scanner protocols.
• Preliminary in vivo results suggest the method's applicability in real-world imaging scenarios.