The subthalamic nucleus at 7.0 Tesla: evaluation of sequence and orientation for deep-brain stimulation

Substantia Nigra Volume Dissociates Bradykinesia and Rigidity from Tremor in Parkinson's Disease: A 7 Tesla Imaging Study

Background:

In postmortem analysis of late stage Parkinson’s disease (PD) neuronal loss in the substantial nigra (SN) correlates with the antemortem severity of bradykinesia and rigidity, but not tremor.

Objective:

To investigate the relationship between midbrain nuclei volume as an in vivo biomarker for surviving neurons in mild-to-moderate patients using 7.0 Tesla MRI.

Methods:

We performed ultra-high resolution quantitative susceptibility mapping (QSM) on the midbrain in 32 PD participants with less than 10 years duration and 8 healthy controls. Following blinded manual segmentation, the individual volumes of the SN, subthalamic nucleus, and red nucleus were measured. We then determined the associations between the midbrain nuclei and clinical metrics (age, disease duration, MDS-UPDRS motor score, and subscores for bradykinesia/rigidity, tremor, and postural instability/gait difficulty).

Results:

We found that smaller SN correlated with longer disease duration (r = –0.49, p = 0.004), more severe MDS-UPDRS motor score (r = –0.42, p = 0.016), and more severe bradykinesia-rigidity subscore (r = –0.47, p = 0.007), but not tremor or postural instability/gait difficulty subscores. In a hemi-body analysis, bradykinesia-rigidity severity only correlated with SN contralateral to the less-affected hemi-body, and not contralateral to the more-affected hemi-body, possibly reflecting the greatest change in dopamine neuron loss early in disease. Multivariate generalized estimating equation model confirmed that bradykinesia-rigidity severity, age, and disease duration, but not tremor severity, predicted SN volume.

Conclusions:

In mild-to-moderate PD, SN volume relates to motor manifestations in a motor domain-specific and laterality-dependent manner. Non-invasive in vivo 7.0 Tesla QSM may serve as a biomarker in longitudinal studies of SN atrophy and in studies of people at risk for developing PD.

Cortical and subcortical contributions to interference resolution and inhibition - An fMRI ALE meta-analysis

Interacting with our environment requires the selection of appropriate responses and the inhibition of others. Such effortful inhibition is achieved by a number of interference resolution and global inhibition processes. This meta-analysis including 57 studies and 73 contrasts revisits the overlap and differences in brain areas supporting interference resolution and global inhibition in cortical and subcortical brain areas. Activation likelihood estimation was used to discern the brain regions subserving each type of cognitive control. Individual contrast analysis revealed a common activation of the bilateral insula and supplementary motor areas. Subtraction analyses demonstrated the voxel-wise differences in recruitment in a number of areas including the precuneus in the interference tasks and the frontal pole and dorsal striatum in the inhibition tasks. Our results display a surprising lack of subcortical involvement within these types of cognitive control, a finding that is likely to reflect a systematic gap in the field of functional neuroimaging.

Quantity and quality: Normative open-access neuroimaging databases

The focus of this article is to compare twenty normative and open-access neuroimaging databases based on quantitative measures of image quality, namely, signal-to-noise (SNR) and contrast-to-noise ratios (CNR). We further the analysis through discussing to what extent these databases can be used for the visualization of deeper regions of the brain, such as the subcortex, as well as provide an overview of the types of inferences that can be drawn. A quantitative comparison of contrasts including T1-weighted (T1w) and T2-weighted (T2w) images are summarized, providing evidence for the benefit of ultra-high field MRI. Our analysis suggests a decline in SNR in the caudate nuclei with increasing age, in T1w, T2w, qT1 and qT2* contrasts, potentially indicative of complex structural age-dependent changes. A similar decline was found in the corpus callosum of the T1w, qT1 and qT2* contrasts, though this relationship is not as extensive as within the caudate nuclei. These declines were accompanied by a declining CNR over age in all image contrasts. A positive correlation was found between scan time and the estimated SNR as well as a negative correlation between scan time and spatial resolution. Image quality as well as the number and types of contrasts acquired by these databases are important factors to take into account when selecting structural data for reuse. This article highlights the opportunities and pitfalls associated with sampling existing databases, and provides a quantitative backing for their usage.

Improved depiction of subthalamic nucleus and globus pallidus internus with optimized high-resolution quantitative susceptibility mapping at 7 T

The subthalamic nucleus (STN) and globus pallidus internus (GPi) are commonly used targets in deep-brain stimulation (DBS) surgery for the treatment of movement disorders. The success of DBS critically depends on the spatial precision of stimulation. By taking advantage of good contrast between iron-rich deep-brain nuclei and surrounding tissues, quantitative susceptibility mapping (QSM) has shown promise in differentiating the STN and GPi from the adjacent substantia nigra and globus pallidus externus, respectively. Nonlinear morphology-enabled dipole inversion (NMEDI) is a widely used QSM algorithm, but the image quality of reconstructed susceptibility maps relies on the regularization parameter selection. To date, few studies have systematically optimized the regularization parameter at the ultra-high field of 7 T. In this study, we optimized the regularization parameter in NMEDI to improve the depiction of STN and GPi at different spatial resolutions at both 3 T and 7 T. The optimized QSM images were further compared with other susceptibility-based images, including T2*-weighted (T2*w), R2*, susceptibility-weighted, and phase images. QSM showed better depiction of deep-brain nuclei with clearer boundaries compared with the other methods, and 7 T QSM at 0.35 × 0.35 × 1.0 mm³ demonstrated superior performance to the others. Our findings suggest that optimized high-resolution QSM at 7 T allows for improved delineation of deep-brain nuclei with clear and sharp borders between nuclei, which may become a promising tool for DBS nucleus preoperative localization.

Deep Cerebellar Nuclei Segmentation via Semi-Supervised Deep Context-Aware Learning from 7T Diffusion MRI

Deep cerebellar nuclei are a key structure of the cerebellum that are involved in processing motor and sensory information. It is thus a crucial step to accurately segment deep cerebellar nuclei for the understanding of the cerebellum system and its utility in deep brain stimulation treatment. However, it is challenging to clearly visualize such small nuclei under standard clinical magnetic resonance imaging (MRI) protocols and therefore precise segmentation is not feasible. Recent advances in 7 Tesla (T) MRI technology and great potential of deep neural networks facilitate automatic patient-specific segmentation. In this paper, we propose a novel deep learning framework (referred to as DCN-Net) for fast, accurate, and robust patient-specific segmentation of deep cerebellar dentate and interposed nuclei on 7T diffusion MRI. DCN-Net effectively encodes contextual information on the patch images without consecutive pooling operations and adding complexity via proposed dilated dense blocks. During the end-to-end training, label probabilities of dentate and interposed nuclei are independently learned with a hybrid loss, handling highly imbalanced data. Finally, we utilize self-training strategies to cope with the problem of limited labeled data. To this end, auxiliary dentate and interposed nuclei labels are created on unlabeled data by using DCN-Net trained on manual labels. We validate the proposed framework using 7T B0 MRIs from 60 subjects. Experimental results demonstrate that DCN-Net provides better segmentation than atlas-based deep cerebellar nuclei segmentation tools and other state-of-the-art deep neural networks in terms of accuracy and consistency. We further prove the effectiveness of the proposed components within DCN-Net in dentate and interposed nuclei segmentation.

Automatic localization of the subthalamic nucleus on patient-specific clinical MRI by incorporating 7 T MRI and machine learning: Application in deep brain stimulation

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) has shown clinical potential for relieving the motor symptoms of advanced Parkinson's disease. While accurate localization of the STN is critical for consistent across-patients effective DBS, clear visualization of the STN under standard clinical MR protocols is still challenging. Therefore, intraoperative microelectrode recordings (MER) are incorporated to accurately localize the STN. However, MER require significant neurosurgical expertise and lengthen the surgery time. Recent advances in 7 T MR technology facilitate the ability to clearly visualize the STN. The vast majority of centers, however, still do not have 7 T MRI systems, and fewer have the ability to collect and analyze the data. This work introduces an automatic STN localization framework based on standard clinical MRIs without additional cost in the current DBS planning protocol. Our approach benefits from a large database of 7 T MRI and its clinical MRI pairs. We first model in the 7 T database, using efficient machine learning algorithms, the spatial and geometric dependency between the STN and its adjacent structures (predictors). Given a standard clinical MRI, our method automatically computes the predictors and uses the learned information to predict the patient-specific STN. We validate our proposed method on clinical T2 W MRI of 80 subjects, comparing with experts-segmented STNs from the corresponding 7 T MRI pairs. The experimental results show that our framework provides more accurate and robust patient-specific STN localization than using state-of-the-art atlases. We also demonstrate the clinical feasibility of the proposed technique assessing the post-operative electrode active contact locations.

Individualized tractography-based parcellation of the globus pallidus pars interna using 7T MRI in movement disorder patients prior to DBS surgery

The success of deep brain stimulation (DBS) surgeries for the treatment of movement disorders relies on the accurate placement of an electrode within the motor portion of subcortical brain targets. However, the high number of electrodes requiring relocation indicates that today's methods do not ensure sufficient accuracy for all patients. Here, with the goal of aiding DBS targeting, we use 7 Tesla (T) MRI data to identify the functional territories and parcellate the globus pallidus pars interna (GPi) into motor, associative and limbic regions in individual subjects. 7 T MRI scans were performed in seventeen patients (prior to DBS surgery) and one healthy control. Tractography-based parcellation of each patient's GPi was performed. The cortex was divided into four masks representing motor, limbic, associative and "other" regions. Given that no direct connections between the GPi and the cortex have been shown to exist, the parcellation was carried out in two steps: 1) The thalamus was parcellated based on the cortical targets, 2) The GPi was parcellated using the thalamus parcels derived from step 1. Reproducibility, via repeated scans of a healthy subject, and validity of the findings, using different anatomical pathways for parcellation, were assessed. Lastly, post-operative imaging data was used to validate and determine the clinical relevance of the parcellation. The organization of the functional territories of the GPi observed in our individual patient population agrees with that previously reported in the literature: the motor territory was located posterolaterally, followed anteriorly by the associative region, and further antero-ventrally by the limbic territory. While this organizational pattern was observed across patients, there was considerable variability among patients. The organization of the functional territories of the GPi was remarkably reproducible in intra-subject scans. Furthermore, the organizational pattern was observed consistently by performing the parcellation of the GPi via the thalamus and via a different pathway, going through the striatum. Finally, the active therapeutic contact of the DBS electrode, identified with a combination of post-operative imaging and post-surgery DBS programming, overlapped with the high-probability "motor" region of the GPi as defined by imaging-based methods. The consistency, validity, and clinical relevance of our findings have the potential for improving DBS targeting, by increasing patient-specific knowledge of subregions of the GPi to be targeted or avoided, at the stage of surgical planning, and later, at the stage when stimulation is adjusted.

Visualizing the Human Subcortex Using Ultra-high Field Magnetic Resonance Imaging

With the recent increased availability of ultra-high field (UHF) magnetic resonance imaging (MRI), substantial progress has been made in visualizing the human brain, which can now be done in extraordinary detail. This review provides an extensive overview of the use of UHF MRI in visualizing the human subcortex for both healthy and patient populations. The high inter-subject variability in size and location of subcortical structures limits the usability of atlases in the midbrain. Fortunately, the combined results of this review indicate that a large number of subcortical areas can be visualized in individual space using UHF MRI. Current limitations and potential solutions of UHF MRI for visualizing the subcortex are also discussed.

Quantification of local geometric distortion in structural magnetic resonance images: Application to ultra-high fields

Ultra-high field magnetic resonance imaging (MRI) provides superior visualization of brain structures compared to lower fields, but images may be prone to severe geometric inhomogeneity. We propose to quantify local geometric distortion at ultra-high fields in in vivo datasets of human subjects scanned at both ultra-high field and lower fields. By using the displacement field derived from nonlinear image registration between images of the same subject, focal areas of spatial uncertainty are quantified. Through group and subject-specific analysis, we were able to identify regions systematically affected by geometric distortion at air-tissue interfaces prone to magnetic susceptibility, where the gradient coil non-linearity occurs in the occipital and suboccipital regions, as well as with distance from image isocenter. The derived displacement maps, quantified in millimeters, can be used to prospectively evaluate subject-specific local spatial uncertainty that should be taken into account in neuroimaging studies, and also for clinical applications like stereotactic neurosurgery where accuracy is critical. Validation with manual fiducial displacement demonstrated excellent correlation and agreement. Our results point to the need for site-specific calibration of geometric inhomogeneity. Our methodology provides a framework to permit prospective evaluation of the effect of MRI sequences, distortion correction techniques, and scanner hardware/software upgrades on geometric distortion.

Subthalamic nucleus volumes are highly consistent but decrease age-dependently-a combined magnetic resonance imaging and stereology approach in humans

The subthalamic nucleus (STN) is a main target structure of deep brain stimulation (DBS) in idiopathic Parkinson's disease. Nevertheless, there is an ongoing discussion regarding human STN volumes and neuron count, which could potentially have an impact on STN-DBS. Moreover, a suspected functional subdivision forms the basis of the tripartite hypothesis, which has not yet been morphologically substantiated. In this study, it was aimed to investigate the human STN by means of combined magnetic resonance imaging (MRI) and stereology. STN volumes were obtained from 14 individuals (ranging from 65 to 96 years, 25 hemispheres) in 3 T MRI and in luxol-stained histology slices. Neuron number and cell densities were investigated stereologically over the entire STN and in pre-defined subregions in anti-human neuronal protein HuC/D-stained slices. STN volumes measured with MRI were smaller than in stereology but appeared to be highly consistent, measuring on average 99 ± 6 mm³ (MRI) and 132 ± 20 mm³ (stereology). The neuron count was 431,088 ± 72,172. Both STN volumes and cell count decreased age-dependently. Neuron density was different for the dorsal, medial and ventral subregion with significantly higher values ventrally than dorsally. Small variations in STN volumes in both MRI and stereology contradict previous findings of large variations in STN size. Age-dependent decreases in STN volumes and neuron numbers might influence the efficacy of STN-DBS in a geriatric population. Though the study is limited in sample size, site-dependent differences for the STN subregions form a morphological basis for the tripartite theory. Hum Brain Mapp 38:909-922, 2017. © 2016 Wiley Periodicals, Inc.

Post-operative imaging in deep brain stimulation: A controversial issue

In deep brain stimulation (DBS), post-operative imaging has been used on the one hand to assess complications, such as haemorrhage; and on the other hand, to detect misplaced contacts. The post-operative determination of the accurate location of the final electrode plays a critical role in evaluating the precise area of effective stimulation and for predicting the potential clinical outcome; however, safety remains a priority in postoperative DBS imaging. A plethora of diverse post-operative imaging methods have been applied at different centres. There is neither a consensus on the most efficient post-operative imaging methodology, nor is there any standardisation for the automatic or manual analysis of the images within the different imaging modalities. In this article, we give an overview of currently applied post-operative imaging modalities and discuss the current challenges in post-operative imaging in DBS.

Magnetic resonance imaging of the subthalamic nucleus for deep brain stimulation

The subthalamic nucleus (STN) is one of the most important stereotactic targets in neurosurgery, and its accurate imaging is crucial. With improving MRI sequences there is impetus for direct targeting of the STN. High-quality, distortion-free images are paramount. Image reconstruction techniques appear to show the greatest promise in balancing the issue of geometrical distortion and STN edge detection. Existing spin echo- and susceptibility-based MRI sequences are compared with new image reconstruction methods. Quantitative susceptibility mapping is the most promising technique for stereotactic imaging of the STN.

Semiautomatic segmentation of brain subcortical structures from high-field MRI

Volumetric segmentation of subcortical structures, such as the basal ganglia and thalamus, is necessary for noninvasive diagnosis and neurosurgery planning. This is a challenging problem due in part to limited boundary information between structures, similar intensity profiles across the different structures, and low contrast data. This paper presents a semiautomatic segmentation system exploiting the superior image quality of ultrahigh field (7 T) MRI. The proposed approach utilizes the complementary edge information in the multiple structural MRI modalities. It combines optimally selected two modalities from susceptibility-weighted, T2-weighted, and diffusion MRI, and introduces a tailored new edge indicator function. In addition to this, we employ prior shape and configuration knowledge of the subcortical structures in order to guide the evolution of geometric active surfaces. Neighboring structures are segmented iteratively, constraining oversegmentation at their borders with a nonoverlapping penalty. Several experiments with data acquired on a 7 T MRI scanner demonstrate the feasibility and power of the approach for the segmentation of basal ganglia components critical for neurosurgery applications such as deep brain stimulation surgery.

Ultra-high field magnetic resonance imaging of the basal ganglia and related structures

Deep brain stimulation is a treatment for Parkinson's disease and other related disorders, involving the surgical placement of electrodes in the deeply situated basal ganglia or thalamic structures. Good clinical outcome requires accurate targeting. However, due to limited visibility of the target structures on routine clinical MR images, direct targeting of structures can be challenging. Non-clinical MR scanners with ultra-high magnetic field (7T or higher) have the potential to improve the quality of these images. This technology report provides an overview of the current possibilities of visualizing deep brain stimulation targets and their related structures with the aid of ultra-high field MRI. Reviewed studies showed improved resolution, contrast- and signal-to-noise ratios at ultra-high field. Sequences sensitive to magnetic susceptibility such as T2^* and susceptibility weighted imaging and their maps in general showed the best visualization of target structures, including a separation between the subthalamic nucleus and the substantia nigra, the lamina pallidi medialis and lamina pallidi incompleta within the globus pallidus and substructures of the thalamus, including the ventral intermediate nucleus (Vim). This shows that the visibility, identification, and even subdivision of the small deep brain stimulation targets benefit from increased field strength. Although ultra-high field MR imaging is associated with increased risk of geometrical distortions, it has been shown that these distortions can be avoided or corrected to the extent where the effects are limited. The availability of ultra-high field MR scanners for humans seems to provide opportunities for a more accurate targeting for deep brain stimulation in patients with Parkinson's disease and related disorders.

Comparison of magnetic resonance imaging sequences for depicting the subthalamic nucleus for deep brain stimulation

Electrodes are surgically implanted into the subthalamic nucleus (STN) of Parkinson’s disease patients to provide deep brain stimulation. For ensuring correct positioning, the anatomic location of the STN must be determined preoperatively. Magnetic resonance imaging has been used for pinpointing the location of the STN. To identify the optimal imaging sequence for identifying the STN, we compared images produced with T₂ star-weighted angiography (SWAN), gradient echo T₂*-weighted imaging, and fast spin echo T₂-weighted imaging in 6 healthy volunteers. Our comparison involved measurement of the contrast-to-noise ratio (CNR) for the STN and substantia nigra and a radiologist’s interpretations of the images. Of the sequences examined, the CNR and qualitative scores were significantly higher on SWAN images than on other images (p < 0.01) for STN visualization. Kappa value (0.74) on SWAN images was the highest in three sequences for visualizing the STN. SWAN is the sequence best suited for identifying the STN at the present time.

Volumetric analysis of the subthalamic and red nuclei based on magnetic resonance imaging in patients with Parkinson's disease

Parkinson's disease (PD) is associated with degeneration of the dopaminergic neurons in the substantia nigra. The subthalamic nucleus (STN) plays a pivotal role in the pathogenesis. However, there is not much known about the morphological changes in the STN. The red nucleus (RN) has many connections with the motor coordinating pathways although it is not primarily involved in the pathogenesis. In this study we aimed to compare the volumes of the STN and RN measured by magnetic resonance imaging in PD patients and controls to investigate how these structures are affected at the morphological level. Twenty patients with PD and twenty age/sex matched controls were enrolled in this study. Severity score was determined by Hoehn & Yahr staging: 6 at stage II and 14 at stage III in med-off state. Imaging was performed by a 1.5 Tesla (T) MR scanner. Measurements of total brain and normalized STN and RN volumes were performed by manual planimetry using Image J software. No statistically significant differences were observed between two groups based on age or gender and disease stage and nuclei volumes. The total estimated brain volumes were not different between PD patients and controls. However, normalized volumes of the STN and RN were 14% and 16% larger, respectively, in PD patients compared to the controls (p < 0.05). Our findings suggest that the volumes of the STN and RN are increased in patients with PD. These changes possibly reflect the altered metabolic activity of these regions demonstrated by neurophysiological studies.