Optimizing knee MRI near orthopedic hardware using a 3D-printed anatomical phantom.

Area of Science:

• Medical Imaging
• Biomedical Engineering
• Orthopedic Surgery

Background:

• Metallic orthopedic implants in patients undergoing MRI can cause significant artifacts, degrading image quality and potentially hindering diagnosis.
• Optimizing MRI sequences is crucial for overcoming artifact challenges posed by metallic hardware.
• Current methods for MRI sequence optimization are often empirical and lack standardization.

Purpose of the Study:

• To evaluate a dedicated, anatomically realistic knee phantom with orthopedic implants for optimizing clinical MRI sequences.
• To assess if phantom-optimized sequences improve image quality compared to routine MRI protocols in the presence of metallic implants.

Main Methods:

• Development of a 3D-printed knee phantom with titanium and stainless-steel implants.
• Iterative optimization of T1-weighted (T1w) and Short Tau Inversion Recovery (STIR) MRI sequences using the phantom on a 1.5 T system.
• Comparison of phantom-optimized sequences with vendor-default and routine clinical protocols.
• Validation of optimized sequences in asymptomatic volunteers with metallic knee implants.
• Independent assessment of image quality by four blinded readers using a 5-point Likert scale.

Main Results:

• Phantom-optimized sequences demonstrated significantly higher image quality scores compared to routine protocols (p < 0.001 for all criteria).
• Improvements were observed in spatial resolution (+0.70 points), artifact reduction (+0.65 points), and overall image quality (+0.78 points).
• These gains were achieved for both T1w and STIR sequences without increasing acquisition times.

Conclusions:

• Phantom-guided optimization offers a reproducible, patient-independent method for tuning MRI protocols in the presence of orthopedic hardware.
• Anatomically realistic phantoms are valuable tools for developing, testing, and standardizing MRI sequences under controlled, clinically relevant conditions.
• This methodology holds promise for improving MRI diagnostic accuracy in patients with metallic implants.