Optimization of MP2RAGE T1 mapping with radial view-ordering for deep brain stimulation targeting at 7 T MRI

Real-Time Optimal Synthetic Inversion Recovery Image Selection (RT-OSIRIS) for Deep Brain Stimulation Targeting

Deep brain stimulation (DBS) is a method of electrical neuromodulation used to treat a variety of neuropsychiatric conditions including essential tremor, Parkinson's disease, epilepsy, and obsessive-compulsive disorder. The procedure requires precise placement of electrodes such that the electrical contacts lie within or in close proximity to specific target nuclei and tracts located deep within the brain. DBS electrode trajectory planning has become increasingly dependent on direct targeting with the need for precise visualization of targets. MRI is the primary tool for direct visualization, and this has led to the development of numerous sequences to aid in visualization of different targets. Synthetic inversion recovery images, specified by an inversion time parameter, can be generated from T1 relaxation maps, and this represents a promising method for modifying the contrast of deep brain structures to accentuate target areas using a single acquisition. However, there is currently no accessible method for dynamically adjusting the inversion time parameter and observing the effects in real-time in order to choose the optimal value. In this work, we examine three different approaches to implementing an application for real-time optimal synthetic inversion recovery image selection and evaluate them based on their ability to display continually-updated synthetic inversion recovery images as the user modifies the inversion time parameter. These methods include continuously computing the inversion recovery equation at each voxel in the image volume, limiting the computation only to the voxels of the orthogonal slices currently displayed on screen, or using a series of lookup tables with precomputed solutions to the inversion recovery equation. We find the latter implementation provides for the quickest display updates both when modifying the inversion time and when scrolling through the image. We introduce a publicly available cross-platform application built around this conclusion. We also briefly discuss other details of the implementations and considerations for extensions to other use cases.

Pushing MP2RAGE boundaries: Ultimate time-efficient parameterization combined with exhaustive T1 synthetic contrasts

PURPOSE

MP2RAGE parameter optimization is redefined to allow more time-efficient MR acquisitions, whereas the T1 -based synthetic imaging framework is used to obtain on-demand T1 -weighted contrasts. Our aim was to validate this concept on healthy volunteers and patients with multiple sclerosis, using plug-and-play parallel-transmission brain imaging at 7 T.

METHODS

A "time-efficient" MP2RAGE sequence was designed with optimized parameters including TI and TR set as small as possible. Extended phase graph formalism was used to set flip-angle values to maximize the gray-to-white-matter contrast-to-noise ratio (CNR). Several synthetic contrasts (UNI, EDGE, FGATIR, FLAWSMIN , FLAWSHCO ) were generated online based on the acquired T1 maps. Experimental validation was performed on 4 healthy volunteers at various spatial resolutions. Clinical applicability was evaluated on 6 patients with multiple sclerosis, scanned with both time-efficient and conventional MP2RAGE parameterizations.

RESULTS

The proposed time-efficient MP2RAGE protocols reduced acquisition time by 40%, 30%, and 19% for brain imaging at (1 mm)3 , (0.80 mm)3 and (0.65 mm)3 , respectively, when compared with conventional parameterizations. They also provided all synthetic contrasts and comparable contrast-to-noise ratio on UNI images. The flexibility in parameter selection allowed us to obtain a whole-brain (0.45 mm)3 acquisition in 19 min 56 s. On patients with multiple sclerosis, a (0.67 mm)3 time-efficient acquisition enhanced cortical lesion visualization compared with a conventional (0.80 mm)3 protocol, while decreasing the scan time by 15%.

CONCLUSION

The proposed optimization, associated with T1 -based synthetic contrasts, enabled substantial decrease of the acquisition time or higher spatial resolution scans for a given time budget, while generating all typical brain contrasts derived from MP2RAGE.

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

BACKGROUND

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.

OBJECTIVES

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.

METHOD

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.

RESULTS

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.

CONCLUSIONS

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.