Correction: Statistical segmentation model for accurate electrode positioning in Parkinson's deep brain stimulation based on clinical low-resolution image data and electrophysiology.

[This corrects the article DOI: 10.1371/journal.pone.0298320.].

Statistical segmentation model for accurate electrode positioning in Parkinson's deep brain stimulation based on clinical low-resolution image data and electrophysiology.

BACKGROUND: Deep Brain Stimulation (DBS), applying chronic electrical stimulation of subcortical structures, is a clinical intervention applied in major neurologic disorders. In order to achieve a good clinical effect, accurate electrode placement is necessary. The primary localisation is typically based on presurgical MRI imaging, often followed by intra-operative electrophysiology recording to increase the accuracy and to compensate for brain shift, especially in cases where the surgical target is small, and there is low contrast: e.g., in Parkinson's disease (PD) and in its common target, the subthalamic nucleus (STN). METHODS: We propose a novel, fully automatic method for intra-operative surgical navigation. First, the surgical target is segmented in presurgical MRI images using a statistical shape-intensity model. Next, automated alignment with intra-operatively recorded microelectrode recordings is performed using a probabilistic model of STN electrophysiology. We apply the method to a dataset of 120 PD patients with clinical T2 1.5T images, of which 48 also had available microelectrode recordings (MER). RESULTS: The proposed segmentation method achieved STN segmentation accuracy around dice = 0.60 compared to manual segmentation. This is comparable to the state-of-the-art on low-resolution clinical MRI data. When combined with electrophysiology-based alignment, we achieved an accuracy of 0.85 for correctly including recording sites of STN-labelled MERs in the final STN volume. CONCLUSION: The proposed method combines image-based segmentation of the subthalamic nucleus with microelectrode recordings to estimate their mutual location during the surgery in a fully automated process. Apart from its potential use in clinical targeting, the method can be used to map electrophysiological properties to specific parts of the basal ganglia structures and their vicinity.

Semi-Automated MicroCT Analysis of Bone Anatomy and Mineralization in Mouse Models.

The skeletal system mirrors several processes in the vertebrate body that impact developmental malfunctions, hormonal disbalance, malfunction of calcium metabolism and turn over, and inflammation processes such as arthrosis. X-ray micro computed tomography is a useful tool for 3D in situ evaluation of the skeletal system in a time-related manner, but results depend highly on resolution. Here, we provide the methodological background for a graduated evaluation from whole-body analysis of skeletal morphology and mineralization to high-resolution analysis of femoral and vertebral microstructure. We combine an expert-based evaluation with a machine-learning-based computational approach, including pre-setup analytical task lists. © 2024 Wiley Periodicals LLC. Basic Protocol 1: In vivo microCT scanning and skeletal analysis in mice Basic Protocol 2: Ex vivo high-resolution microCT scanning and microstructural analysis of the femur and L4 vertebra.

Influence of Substrate Moisture State and Roughness on Interface Microstructure and Bond Strength: Slant Shear vs. Pull-Off Testing.

There are conflicting views in the literature concerning the optimum moisture state for an existing substrate prior to the application of a repair material. Both saturated-surface-dry (SSD) and dry substrates have been found to be preferable in a variety of studies. One confounding factor is that some studies evaluate bonding of the repair material to the substrate via pull-off (direct tension) testing, while others have employed some form of shear specimens as their preferred testing configuration. Available evidence suggests that dry substrate specimens usually perform equivalently or better in shear testing, while SSD ones generally exhibit higher bond strengths when a pull-off test is performed, although exceptions to these trends have been observed. This paper applies a variety of microstructural characterization tools to investigate the interfacial microstructure that develops when a fresh repair material is applied to either a dry or SSD substrate. Simultaneous neutron and X-ray radiography are employed to observe the dynamic microstructural rearrangements that occur at this interface during the first 4 h of curing. Based on the differences in water movement and densification (particle compaction) that occur for the dry and SSD specimens, respectively, a hypothesis is formulated as to why different bond tests may favor one moisture state over the other, also dependent on their surface roughness. It is suggested that the compaction of particles at a dry substrate surface may increase the frictional resistance when tested under slant shear loading, but contribute relatively little to the bonding when the interface is submitted to pull-off forces. For maximizing bond performance, the fluidity of the repair material and the roughness and moisture state of the substrate must all be given adequate consideration.