Real-Time Semi-Automated and Automated Voxel Placement for Repeated Acquisition Magnetic Resonance Spectroscopy

Magnetic resonance spectroscopy (MRS) is heavily dependent on the investigative team to prescribe, or demarcate, the desired tissue volume-of-interest. Manual prescription, the current standard in the field, requires expertise in neuroanatomy to ensure spatial consistency within and across subjects. Spatial precision of MRS voxel placement thus presents challenges for cross-sectional studies, and even more so for repeated-measure and multi-acquisition designs. Furthermore, voxel prescriptions based-solely on anatomical landmarks may not be ideal in regions with substantial functional and cytoarchitectural variability or to examine individualized/targeted interventions. Here we propose and validate robust and real-time methods to automate MRS voxel placement using functionally defined coordinates within the left dorsolateral prefrontal cortex in clinical cohorts of chronic pain and depression. We hypothesized that increased automation would produce more consistent voxel placement across repeated acquisitions particularly in reference to standard manual prescription. Data were collected and analyzed using two independent prospective transcranial magnetic stimulation studies: 1) a single-day multi-session sandwich design and 2) a longitudinal design. Participants with fibromyalgia syndrome (N=50) and major depressive disorder (N=35) underwent MRI as part of ongoing clinical studies. MEGA-PRESS and Optimized-PRESS MRS acquisitions were acquired at 3-tesla. Evaluation of the reproducibility of spatial location and tissue segmentation was assessed for: 1) manual, 2) semi-automated, and 3) automated voxel prescription approaches. Variability of grey and white matter voxel tissue composition was reduced using automated placement protocols as confirmed by common MRS software processing pipelines (Gannet; SPM-based segmentation) and via Freesurfer-based segmentation. Spatially, post-to pre-voxel center-of-gravity distance was reduced and voxel overlap increased significantly across datasets using automated compared to manual procedures. These results demonstrate the within subject reliability and reproducibility of a method for reducing variability introduced by spatial inconsistencies during MRS acquisitions. The proposed method is a meaningful advance toward improved consistency of MRS data in neuroscience and can be leveraged for multi-session and longitudinal studies that target precisely defined regions-of-interest via a coordinate-based approach.