Low field MR imaging for patients with orthopedic implants

• Applicants: Dr. Rafael Heiß; Professor Dr. Florian Knoll; Professor Armin Nagel, Ph.D.
• Subject Area: Medical Physics, Biomedical Technology ; Radiology
• Term: since 2025
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 556079651

Over the past two decades, the prevalence of total implant surgery has grown enormously as the aging population expands and seeks to preserve mobility. This growing volume has important implications on the demand for high-quality implant imaging, particularly with MRI, which offers superior soft tissue contrast compared to other modalities. Since the advent of implant MRI, the modality has been plagued by metal artifacts related to field inhomogeneity such as distortion, signal void, and signal pileup. Significant advances have been made over the past decade in minimizing these artifacts with the development of dedicated pulse sequences like SEMAC (Slice Encoding for Metal Artifact Correction). However, there remains an important clinical need for this growing population of patients to properly evaluate for periprosthetic complications and thereby impact patient management and outcomes. We endeavor to solve this problem with a low field (0.55T), high performance MRI system, by harnessing the advantage of reduced metal artifacts at lower field strengths. However, this advantage of the lower field strength comes at the cost of several drawbacks. The main drawback is reduced SNR. Second, the scan-times for a metal artifact reduction sequence at our low field system are currently on the order of 15 minutes for a single sequence, which is prohibitively long for routine clinical use. Third, due to the reduced difference in the precession frequencies of spins from water and fat tissues at lower field strengths, the clinically essential fat suppression becomes challenging. The central goal our proposal is to address these three issues with a novel data acquisition and image reconstruction approach. We will use sparse sampling in the 4-dimensional SEMAC k-space domain to bring the scan duration to a clinically feasible time of 4 minutes and use machine learning for image reconstruction to remove aliasing artifacts and suppress noise enhancement. To address the issue of fat-suppression, we will use subject-specific spectral-spatial (SPSP) fat-suppression pulses. Together with the reduced metal artifacts due to the lower field strength, our goal is to reach unprecedented MR image quality near orthopedic implants.

• DFG Programme: Research Grants