Synthetic Inversion Image Generation using MP2RAGE T1 Mapping for Surgical Targeting in Deep Brain Stimulation and...

Advances in MRI technology have increased interest in direct targeting for deep brain stimulation (DBS). Various imaging sequences have been shown to provide increased contrast of numerous common DBS targets, such as T1-weighted, Fast Gray Matter Acquisition T1 Inversion Recovery (FGATIR), gray matter nulled, and Edge-Enhancing Gradient Echo (EDGE); however, the continual increase in the number of necessary sequences has led to an increase in imaging time, which is undesirable. Additionally, carefully timed inversion pulses can often lead to less-than-ideal contrast in some subjects, particularly in ultra-high field MRI, where B1+ field inhomogeneity can lead to substantial contrast variation.

This study proposes using 3D MP2RAGE-based T1 maps to retrospectively synthesize images of any desired inversion time, including T1-weighted, FGATIR, and EDGE contrasts, to visualize specific DBS targets at both 3T and 7T.

First, a systematic sequence optimization framework was applied to optimize MP2RAGE T1 mapping sequence parameters for the purpose of DBS planning. Next, we show that synthetic inversion-time images can be generated through a mathematical transformation of the T1 maps. The sequence was then applied to patients undergoing preoperative planning for DBS at 3T and 7T to generate synthetic contrasts used in surgical planning.

We show that synthetic image contrasts can be generated across a full range of inversion times at 3T and 7T, including commonly used sequences for DBS targeting, such as T1-weighted, FGATIR, and EDGE. Acquisition through a single sequence shortens scan time compared to acquiring the sequences independently without affecting image quality or contrast.

The generation of synthetic images for DBS targeting allows faster acquisition of many key sequences, as well as the ability to optimize contrast properties post-acquisition to account for the variable B1+ effects present in ultra-high field MRI. The proposed approach has the potential to reduce imaging time and improve the accuracy of DBS targeting at 1.5T, 3T, and 7T.