Dataset Information

Automated Steerable Path Planning for Deep Brain Stimulation Safeguarding Fiber Tracts and Deep Gray Matter Nuclei.

ABSTRACT: Deep Brain Stimulation (DBS) is a neurosurgical procedure consisting in the stereotactic implantation of stimulation electrodes to specific brain targets, such as deep gray matter nuclei. Current solutions to place the electrodes rely on rectilinear stereotactic trajectories (RTs) manually defined by surgeons, based on pre-operative images. An automatic path planner that accurately targets subthalamic nuclei (STN) and safeguards critical surrounding structures is still lacking. Also, robotically-driven curvilinear trajectories (CTs) computed on the basis of state-of-the-art neuroimaging would decrease DBS invasiveness, circumventing patient-specific obstacles. This work presents a new algorithm able to estimate a pool of DBS curvilinear trajectories for reaching a given deep target in the brain, in the context of the EU's Horizon EDEN2020 project. The prospect of automatically computing trajectory plans relying on sophisticated newly engineered steerable devices represents a breakthrough in the field of microsurgical robotics. By tailoring the paths according to single-patient anatomical constraints, as defined by advanced preoperative neuroimaging including diffusion MR tractography, this planner ensures a higher level of safety than the standard rectilinear approach. Ten healthy controls underwent Magnetic Resonance Imaging (MRI) on 3T scanner, including 3DT1-weighted sequences, 3Dhigh-resolution time-of-flight MR angiography (TOF-MRA) and high angular resolution diffusion MR sequences. A probabilistic q-ball residual-bootstrap MR tractography algorithm was used to reconstruct motor fibers, while the other deep gray matter nuclei surrounding STN and vessels were segmented on T1 and TOF-MRA images, respectively. These structures were labeled as obstacles. The reliability of the automated planner was evaluated; CTs were compared to RTs in terms of efficacy and safety. Targeting the anterior STN, CTs performed significantly better in maximizing the minimal distance from critical structures, by finding a tuned balance between all obstacles. Moreover, CTs resulted superior in reaching the center of mass (COM) of STN, as well as in optimizing the entry angle in STN and in the skull surface.

SUBMITTER: Segato A

PROVIDER: S-EPMC7806057 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Automated Steerable Path Planning for Deep Brain Stimulation Safeguarding Fiber Tracts and Deep Gray Matter Nuclei.

Segato Alice A Pieri Valentina V Favaro Alberto A Riva Marco M Falini Andrea A De Momi Elena E Castellano Antonella A

Frontiers in robotics and AI 20190806

Deep Brain Stimulation (DBS) is a neurosurgical procedure consisting in the stereotactic implantation of stimulation electrodes to specific brain targets, such as deep gray matter nuclei. Current solutions to place the electrodes rely on rectilinear stereotactic trajectories (RTs) manually defined by surgeons, based on pre-operative images. An automatic path planner that accurately targets subthalamic nuclei (STN) and safeguards critical surrounding structures is still lacking. Also, robotically ...[more]

PMID: 33501085

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Project description:Quantification of tissue magnetic susceptibility using MRI offers a non-invasive measure of important tissue components in the brain, such as iron and myelin, potentially providing valuable information about normal and pathological conditions during aging. Despite many advances made in recent years on imaging techniques of quantitative susceptibility mapping (QSM), accurate and robust automated segmentation tools for QSM images that can help generate universal and sharable susceptibility measures in a biologically meaningful set of structures are still not widely available. In the present study, we developed an automated process to segment brain nuclei and quantify tissue susceptibility in these regions based on a susceptibility multi-atlas library, consisting of 10 atlases with T1-weighted images, gradient echo (GRE) magnitude images and QSM images of brains with different anatomic patterns. For each atlas in this library, 10 regions of interest in iron-rich deep gray matter structures that are better defined by QSM contrast were manually labeled, including caudate, putamen, globus pallidus internal/external, thalamus, pulvinar, subthalamic nucleus, substantia nigra, red nucleus and dentate nucleus in both left and right hemispheres. We then tested different pipelines using different combinations of contrast channels to bring the set of labels from the multi-atlases to each target brain and compared them with the gold standard manual delineation. The results showed that the segmentation accuracy using dual contrasts QSM/T1 pipeline outperformed other dual-contrast or single-contrast pipelines. The dice values of 0.77 ± 0.09 using the QSM/T1 multi-atlas pipeline rivaled with the segmentation reliability obtained from multiple evaluators with dice values of 0.79 ± 0.07 and gave comparable or superior performance in segmenting subcortical nuclei in comparison with standard FSL FIRST or recent multi-atlas package of volBrain. The segmentation performance of the QSM/T1 multi-atlas was further tested on QSM images acquired using different acquisition protocols and platforms and showed good reliability and reproducibility with average dice of 0.79 ± 0.08 to manual labels and 0.89 ± 0.04 in an inter-protocol manner. The extracted quantitative magnetic susceptibility values in the deep gray matter nuclei also correlated well between different protocols with inter-protocol correlation constants all larger than 0.97. Such reliability and performance was ultimately validated in an external dataset acquired at another study site with consistent susceptibility measures obtained using the QSM/T1 multi-atlas approach in comparison to those using manual delineation. In summary, we designed a susceptibility multi-atlas tool for automated and reliable segmentation of QSM images and for quantification of magnetic susceptibilities. It is publicly available through our cloud-based platform (www.mricloud.org). Further improvement on the performance of this multi-atlas tool is expected by increasing the number of atlases in the future.

Project description:BackgroundNeuropathological studies have revealed copper and iron accumulation in the deep gray matter (DGM) nuclei of patients with Wilson's disease (WD). However, the association between metal accumulation and neurodegeneration in WD has not been well studied in vivo. The study was aimed to investigate whether metal accumulation in the DGM was associated with the structural and functional changes of DGM in neurological WD patients.MethodsSeventeen neurological WD patients and 20 healthy controls were recruited for the study. Mean bulk susceptibility values and volumes of DGM were obtained from quantitative susceptibility mapping (QSM). Regions of interest including the head of the caudate nucleus, globus pallidus, putamen, thalamus, substantia nigra, red nucleus, and dentate nucleus were manually segmented. The susceptibility values and volumes of DGM in different groups were compared using a linear regression model. Correlations between susceptibility values and volumes of DGM and Unified Wilson's Disease Rating Scale (UWDRS) neurological subscores were investigated.ResultsThe susceptibility values of all examined DGM in WD patients were higher than those in healthy controls (P < 0.05). Volume reductions were observed in the head of the caudate nucleus, globus pallidus, putamen, thalamus, and substantia nigra of WD patients (P < 0.001). Susceptibility values were negatively correlated with the volumes of the head of the caudate nucleus (r p = -0.657, P = 0.037), putamen (r p = -0.667, P = 0.037), and thalamus (r p = -0.613, P = 0.046) in WD patients. UWDRS neurological subscores were positively correlated with the susceptibility values of all examined DGM. The susceptibility values of putamen, head of the caudate nucleus, and dentate nucleus could well predict UWDRS neurological subscores.ConclusionOur study provided in vivo evidence that paramagnetic metal accumulation in the DGM was associated with DGM atrophy and neurological impairment. The susceptibility of DGM could be used as a biomarker to assess the severity of neurodegeneration in WD.

Project description:BackgroundHistopathological studies in Wilson's disease (WD) have revealed increased copper and iron concentrations in the deep gray matter nuclei. However, the commonly used mean bulk susceptibility only reflects the regional metal concentration rather than the total metal content, and regional atrophy may affect the assessment of mean bulk susceptibility. Our study aimed to quantitatively assess the changes of metal concentration and total metal content in deep gray matter nuclei by quantitative susceptibility mapping to distinguish patients with neurological and hepatic WD from healthy controls.MethodsQuantitative susceptibility maps were obtained from 20 patients with neurological WD, 10 patients with hepatic WD, and 25 healthy controls on a 3T magnetic resonance imaging system. Mean bulk susceptibility, volumes, and total susceptibility of deep gray matter nuclei in different groups were compared using a linear regression model. The area under the curve (AUC) was calculated by receiver characteristic curve to analyze the diagnostic capability of mean bulk susceptibility and total susceptibility.ResultsMean bulk susceptibility and total susceptibility of multiple deep gray matter nuclei in patients with WD were higher than those in healthy controls. Compared with patients with hepatic WD, patients with neurological WD had higher mean bulk susceptibility but similar total susceptibility in the head of the caudate nuclei, globus pallidus, and putamen. Mean bulk susceptibility of putamen demonstrated the best diagnostic capability for patients with neurological WD, the AUC was 1, and the sensitivity and specificity were all equal to 1. Total susceptibility of pontine tegmentum was most significant for the diagnosis of patients with hepatic WD, the AUC was 0.848, and the sensitivity and specificity were 0.7 and 0.96, respectively.ConclusionBrain atrophy may affect the assessment of mean bulk susceptibility in the deep gray matter nuclei of patients with WD, and total susceptibility should be an additional metric for total metal content assessment. Mean bulk susceptibility and total susceptibility of deep gray matter nuclei may be helpful for the early diagnosis of WD.

Dataset Information

Automated Steerable Path Planning for Deep Brain Stimulation Safeguarding Fiber Tracts and Deep Gray Matter Nuclei.

Publications

Automated Steerable Path Planning for Deep Brain Stimulation Safeguarding Fiber Tracts and Deep Gray Matter Nuclei.

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