Publication

Enhancing 7T MRI for deep brain stimulation with deep-learning based image reconstruction and dynamic parallel transmission

2026

Abstract

Objective Precise targeting of subcortical structures is crucial for deep brain stimulation (DBS). Although 7T MRI provides superior resolution and contrast, its clinical adoption remains limited by B1+ transmit inhomogeneity, prolonged scan times, and motion sensitivity. This study applied deep learning (DL)–based image reconstruction and dynamic parallel transmission (pTx) to optimize DBS protocols and improve image quality. Methods Thirteen patients scanned using a conventional 7T DBS protocol were compared to 13 imaged after implementing DL reconstruction and dynamic pTx. Two readers scored image quality, motion artifact, and target conspicuity on 5-point Likert scales. Ordinal logistic regression was used to calculate odds ratios (OR) for improvements with the enhanced protocol, adjusted for multiple comparisons. Results Enhanced MP2RAGE reduced voxel volume by 65.8% and scan time by 32.9%, with improved image quality (OR = 4.4;p = 0.003), target conspicuity (OR = 3.4;p = 0.011), and reduced motion artifacts (OR = 3.8;p = 0.006). Fast gray matter acquisition T1 inversion recovery (FGATIR) scan time decreased by 45.2% with improved target delineation of both globus pallidus interna (OR = 22.9;p < 0.001) and dentato-rubro-thalamic tract (OR = 8.8;p < 0.001). T2-weighted sampling perfection with application-optimized contrasts using different flip angle evolutions (SPACE) improved subthalamic nucleus (STN) delineation (OR = 25.3;p < 0.001). Susceptibility-weighted imaging (SWI) improved image quality (OR = 17.4;p < 0.001), STN delineation (OR = 16.9;p < 0.001), and reduced scan time by 42.6%. Enhanced 3D spoiled gradient recall echo improved image quality (OR = 17.4;p < 0.001) and vessel visualization (OR = 26.1;p < 0.001) with reduced motion artifact (OR = 8.8;p < 0.001). Scan time decreased from 4:33 to 1:35, reducing protocol duration from 42:16 to 26:40 (36.9%). Conclusions DL reconstruction and dynamic pTx improved image quality, target definition, and motion robustness while shortening 7T DBS protocol time.

Official source

https://infoscience.epfl.ch/entities/publication/d2a3d5e2-7f95-47fa-b146-f1432e23a349

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2026

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/d2a3d5e2-7f95-47fa-b146-f1432e23a349

About this result

Related concepts (32)

Deep brain stimulation

Deep brain stimulation (DBS) is a neurosurgical procedure involving the placement of a medical device called a neurostimulator, which sends electrical impulses, through implanted electrodes, to specific targets in the brain (the brain nucleus) for the treatment of movement disorders, including Parkinson's disease, essential tremor, dystonia, and other conditions such as obsessive-compulsive disorder (OCD) and epilepsy. While its underlying principles and mechanisms are not fully understood, DBS directly changes brain activity in a controlled manner.

CT scan

A computed tomography scan (usually abbreviated to CT scan; formerly called computed axial tomography scan or CAT scan) is a medical imaging technique used to obtain detailed internal images of the body. The personnel that perform CT scans are called radiographers or radiology technologists. CT scanners use a rotating X-ray tube and a row of detectors placed in a gantry to measure X-ray attenuations by different tissues inside the body.

Compression artifact

A compression artifact (or artefact) is a noticeable distortion of media (including , audio, and video) caused by the application of lossy compression. Lossy data compression involves discarding some of the media's data so that it becomes small enough to be stored within the desired or transmitted (streamed) within the available bandwidth (known as the data rate or bit rate). If the compressor cannot store enough data in the compressed version, the result is a loss of quality, or introduction of artifacts.

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Enhancing 7T MRI for deep brain stimulation with deep-learning based image reconstruction and dynamic parallel transmission

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