E4525. Muscle Up Your Musculoskeletal MRI: Recognizing and Addressing Common Protocol Pitfalls
  1. Rishabh Gattu; University of Michigan
  2. Joel Morehouse; University of Michigan
  3. Emily Abraham; University of Michigan
  4. Kenneth Buckwalter; University of Michigan
Musculoskeletal (MSK) MRI is challenging because the ROI can vary from a small finger to an entire lower extremity. Technologists comfortable with routine shoulder and knee imaging may be confounded by less common studies. Radiologists can help by collaborating on imaging protocol design and learning to recognize common issues that degrade image quality. This educational exhibit will demonstrate MSK imaging pitfalls with suggested mitigations.

Educational Goals / Teaching Points
After a brief introduction on the importance of specific imaging coils, this presentation will offer solutions to various problems typically encountered during MRI scanning. The viewer will learn different techniques to navigate the usual tradeoff between scan time acceleration and signal-to-noise ratio (SNR) by understanding parallel imaging, compressed sense, simultaneous multislice (SMS), and artificial intelligence (AI)-assisted reconstruction. This exhibit will also offer explanations for techniques to mitigate motion during scanning, including multiple signal averages and radial acquisition of k-space data. Additionally, reducing chemical shift artifact and optimizing short TE turbo or fast spin echo (TSE) images will be discussed. Lastly, we touch upon fat suppression techniques.

Key Anatomic/Physiologic Issues and Imaging Findings/Techniques
In MSK MRI, dedicated coils offer high SNR, but flexible coils are needed for larger patients, leading to lower SNR. Acceleration techniques (i.e., parallel imaging) reduce scan time but compromise SNR and introduce artifacts. Increased parallel imaging factors can cause directional noise, managed by altering phase encoding direction or reducing acceleration. Compressed sense and simultaneous multislice (SMS) are newer techniques. SMS enables concurrent acquisition of multiple slices, although ghosting and halos may occur. AI aids image reconstruction, significantly reducing time with larger matrices, but motion artifacts may be more conspicuous. Acquiring multiple signal averages can reduce motion artifacts, but radial k-space sampling may be more time efficient. Chemical shift artifacts worsen with magnetic field strength and can be mitigated by increasing the receiver bandwidth. Optimizing receiver bandwidth also reduces blurring on short TE turbo/fast spin echo images. Fat suppression methods vary: chemical shift–selective saturation (CHESS) fails for large FOV or air-surrounded regions. Short time to inversion recovery images (STIR) and Dixon techniques are more reliable. Additional methods like spectral presaturation with inversion recovery (SPIR) and spectral attenuated inversion recovery (SPAIR) provide further alternatives.

In the domain of Musculoskeletal MRI, the interaction between scan time, SNR, and variations in anatomy are challenging. Acceleration techniques and AI offer avenues to streamline scan times. Addressing motion-induced degradation, managing chemical shift artifacts, and selecting reliable fat suppression techniques round out the essential strategies highlighted in this exhibit.