Fast quantitative MRI: Spiral Acquisition Matching-Based Algorithm (SAMBA) for Robust T₁ and T₂ Mapping

Area of Science:

• Biomedical Imaging
• Magnetic Resonance Imaging (MRI)
• Quantitative MRI (qMRI)

Background:

• Conventional MRI is qualitative and subjective.
• Quantitative MRI (qMRI) offers objective assessment in preclinical research.
• Low-field (≤3.0T) preclinical qMRI is crucial for evaluating contrast agents at human field strengths but faces challenges like long scan times and motion artifacts.

Purpose of the Study:

• To develop a rapid qMRI method for preclinical 3.0T MRI scanners.
• To enable faster and quantitative evaluation of MRI contrast agents.
• To overcome limitations of existing low-field qMRI techniques.

Main Methods:

• Introduction of a novel rapid qMRI method combining Spiral Acquisition with a Matching-Based Algorithm (SAMBA).
• Comparison of SAMBA with gold-standard Spin Echo MRI methods using Least Squares Fitting (SELSF).
• In vitro phantom studies were conducted to validate the method.

Main Results:

• SAMBA demonstrated significantly shorter scan times compared to conventional methods.
• The method maintained measurement accuracy and repeatability.
• No compromise in data quality was observed despite the accelerated acquisition.

Conclusions:

• The developed SAMBA method provides a rapid and accurate approach for quantitative MRI on preclinical scanners.
• This technique is effective for evaluating MRI contrast agents.
• Results support future in vivo applications of SAMBA for advanced chemical probe studies.