Automated Segmentation and Diagnostic Measurement for the Evaluation of Cervical Spine Injuries Using X-Rays.

Accurate assessment of cervical spine X-ray images through diagnostic metrics plays a crucial role in determining appropriate treatment strategies for cervical injuries and evaluating surgical outcomes. Such assessment can be facilitated through the use of automatic methods such as machine learning and computer vision algorithms. A total of 852 cervical X-rays obtained from Gachon Medical Center were used for multiclass segmentation of the craniofacial bones (hard palate, basion, opisthion) and cervical spine (C1-C7), incorporating architectures such as EfficientNetB4, DenseNet201, and InceptionResNetV2. Diagnostic metrics automatically measured using computer vision algorithms were compared with manually measured metrics through Pearson's correlation coefficient and paired t-tests. The three models demonstrated high average dice coefficient values for the cervical spine (C1, 0.93; C2, 0.96; C3, 0.96; C4, 0.96; C5, 0.96; C6, 0.96; C7, 0.95) and lower values for the craniofacial bones (hard palate, 0.69; basion, 0.81; opisthion, 0.71). Comparison of manually measured metrics and automatically measured metrics showed high Pearson's correlation coefficients in McGregor's line (r = 0.89), space available cord (r = 0.94), cervical sagittal vertical axis (r = 0.99), cervical lordosis (r = 0.88), lower correlations in basion-dens interval (r = 0.65), basion-axial interval (r = 0.72), and Powers ratio (r = 0.62). No metric showed adjusted significant differences at P < 0.05 between manual and automatic metric measuring methods. These findings demonstrate the potential of multiclass segmentation in automating the measurement of diagnostic metrics for cervical spine injuries and showcase the clinical potential for diagnosing cervical spine injuries and evaluating cervical surgical outcomes.

Improving the Accuracy of Otitis Media with Effusion Diagnosis in Pediatric Patients Using Deep Learning.

Otitis media with effusion (OME), primarily seen in children aged 2 years and younger, is characterized by the presence of fluid in the middle ear, often resulting in hearing loss and aural fullness. While deep learning networks have been explored to aid OME diagnosis, prior work did not often specify if pediatric images were used for training, causing uncertainties about their clinical relevance, especially due to important distinctions between the tympanic membranes of small children and adults. We trained cross-validated ResNet50, DenseNet201, InceptionV3, and InceptionResNetV2 models on 1150 pediatric tympanic membrane images from otoendoscopes to classify OME. When assessed using a separate dataset of 100 pediatric tympanic membrane images, the models achieved mean accuracies of 92.9% (ResNet50), 97.2% (DenseNet201), 96.0% (InceptionV3), and 94.8% (InceptionResNetV2), compared to the seven otolaryngologists that achieved accuracies between 84.0% and 69.0%. The results showed that even the worst-performing model trained on fold 3 of InceptionResNetV2 with an accuracy of 88.0% exceeded the accuracy of the highest-performing otolaryngologist at 84.0%. Our findings suggest that these specifically trained deep learning models can potentially enhance the clinical diagnosis of OME using pediatric otoendoscopic tympanic membrane images.

Evaluation of U-Net models in automated cervical spine and cranial bone segmentation using X-ray images for traumatic atlanto-occipital dislocation diagnosis.

Segmentation of the cervical spine in tandem with three cranial bones, hard palate, basion, and opisthion using X-ray images is crucial for measuring metrics used to diagnose traumatic atlanto-occipital dislocation (TAOD). Previous studies utilizing automated segmentation methods have been limited to segmenting parts of the cervical spine (C3 ~ C7), due to difficulties in defining the boundaries of C1 and C2 bones. Additionally, there has yet to be a study that includes cranial bone segmentations necessary for determining TAOD diagnosing metrics, which are usually defined by measuring the distance between certain cervical (C1 ~ C7) and cranial (hard palate, basion, opisthion) bones. For this study, we trained a U-Net model on 513 sagittal X-ray images with segmentations of both cervical and cranial bones for an automated solution to segmenting important features for diagnosing TAOD. Additionally, we tested U-Net derivatives, recurrent residual U-Net, attention U-Net, and attention recurrent residual U-Net to observe any notable differences in segmentation behavior. The accuracy of U-Net models ranged from 99.07 to 99.12%, and dice coefficient values ranged from 88.55 to 89.41%. Results showed that all 4 tested U-Net models were capable of segmenting bones used in measuring TAOD metrics with high accuracy.

White Matter Microstructural Alterations in Newly Diagnosed Parkinson's Disease: A Whole-Brain Analysis Using dMRI.

Parkinson's disease (PD) is a neurodegenerative disorder characterized by cardinal motor symptoms and other non-motor symptoms. Studies have investigated various brain areas in PD by detecting white matter alterations using diffusion magnetic resonance imaging processing techniques, which can produce diffusion metrics such as fractional anisotropy and quantitative anisotropy. In this study, we compared the quantitative anisotropy of whole brain regions throughout the subcortical and cortical areas between newly diagnosed PD patients and healthy controls. Additionally, we evaluated the correlations between the quantitative anisotropy of each region and respective neuropsychological test scores to identify the areas most affected by each neuropsychological dysfunction in PD. We found significant quantitative anisotropy differences in several subcortical structures such as the basal ganglia, limbic system, and brain stem as well as in cortical structures such as the temporal lobe, occipital lobe, and insular lobe. Additionally, we found that quantitative anisotropy of some subcortical structures such as the basal ganglia, cerebellum, and brain stem showed the highest correlations with motor dysfunction, whereas cortical structures such as the temporal lobe and occipital lobe showed the highest correlations with olfactory dysfunction in PD. Our study also showed evidence regarding potential neural compensation by revealing higher diffusion metric values in early-stage PD than in healthy controls. We anticipate that our results will improve our understanding of PD's pathophysiology.

White Matter Connectivity between Structures of the Basal Ganglia using 3T and 7T.

Analysis of the basal ganglia has been important in investigating the effects of Parkinson's disease as well as treatments for Parkinson's disease. One method of analysis has been using MRI for non-invasively segmenting the basal ganglia, then investigating significant parameters that involve the basal ganglia, such as fiber orientations and positional markers for deep brain stimulation (DBS). Following enhancements to optimizations and improvements to 3T and 7T MRI acquisitions, we utilized Lead-DBS on human connectome project data to automatically segment the basal ganglia of 49 human connectome project subjects, reducing the reliance on manual segmentation for more consistency. We generated probabilistic tractography streamlines between each segmentation pair using 3T and 7T human connectome diffusion data to observe any major differences in tractography streamline patterns that can arise due to tradeoffs from different field strengths and acquisitions. Tractography streamlines generated between basal ganglia structures using 3T images showed less standard deviation in streamline count than using 7T images. Mean tractography streamline counts generated using 3T diffusion images were all higher in count than streamlines generated using 7T diffusion images. We illustrate a potential method for analyzing the structural connectivity between basal ganglia structures, as well as visualize possible differences in probabilistic tractography that can arise from different acquisition protocols.

Deterministic Tractography Analysis of Rat Brain Using SIGMA Atlas in 9.4T MRI.

Preclinical studies using rodents have been the choice for many neuroscience researchers due totheir close reflection of human biology. In particular, research involving rodents has utilized MRI to accurately identify brain regions and characteristics by acquiring high resolution cavity images with different contrasts non-invasively, and this has resulted in high reproducibility and throughput. In addition, tractographic analysis using diffusion tensor imaging to obtain information on the neural structure of white matter has emerged as a major methodology in the field of neuroscience due to its contribution in discovering significant correlations between altered neural connections and various neurological and psychiatric diseases. However, unlike image analysis studies with human subjects where a myriad of human image analysis programs and procedures have been thoroughly developed and validated, methods for analyzing rat image data using MRI in preclinical research settings have seen significantly less developed. Therefore, in this study, we present a deterministic tractographic analysis pipeline using the SIGMA atlas for a detailed structural segmentation and structural connectivity analysis of the rat brain's structural connectivity. In addition, the structural connectivity analysis pipeline presented in this study was preliminarily tested on normal and stroke rat models for initial observation.

Diffusion Measure Changes of Substantia Nigra Subregions and the Ventral Tegmental Area in Newly Diagnosed Parkinson's Disease.

Historically, studies have extensively examined the basal ganglia in Parkinson's disease for specific characteristics that can be observed with medical imaging. One particular methodology used for detecting changes that occur in Parkinson's disease brains is diffusion tensor imaging, which yields diffusion indices such as fractional anisotropy and radial diffusivity that have been shown to correlate with axonal damage. In this study, we compare the diffusion measures of basal ganglia structures (with substantia nigra divided into subregions, pars compacta, and pars reticula), as well as the diffusion measures of the diffusion tracts that pass through each pair of basal ganglia structures to see if significant differences in diffusion measures can be observed in structures or tracts in newly diagnosed Parkinson's disease patients. Additionally, we include the ventral tegmental area, a structure connected to various basal ganglia structures affected by dopaminergic neuronal loss and have historically shown significant alterations in Parkinson's disease, in our analysis. We found significant fractional anisotropy differences in the putamen, and in the diffusion tracts that pass through pairs of both substantia nigra subregions, subthalamic nucleus, parabrachial pigmental nucleus, ventral tegmental area. Additionally, we found significant radial diffusivity differences in diffusion tracts that pass through the parabrachial nucleus, putamen, both substantia nigra subregions, and globus pallidus externa. We were able to find significant diffusion measure differences in structures and diffusion tracts, potentially due to compensatory mechanisms in response to dopaminergic neuronal loss that occurs in newly diagnosed Parkinson's disease patients.

Truncated Neogenin Promotes Hippocampal Neuronal Death after Acute Seizure.

Protecting hippocampal neurons from death after seizure activity is critical to prevent an alteration of neuronal circuitry and hippocampal function. Here, we present a novel target, a truncated form of neogenin that is associated with seizure-induced hippocampal necroptosis, and novel use of the γ-secretase inhibitor N-[N-(3,5-difluorophenacetyl)-L-alanyl]-S-phenylglycine t-butyl ester (DAPT) as a pharmacological regulator of neogenin truncation. We show that 3 days after pilocarpine-induced status epilepticus in mice, when hippocampal cell death is detected, the level of truncated neogenin is increased, while that of full-length neogenin is decreased. Moreover, phosphorylation of mixed lineage kinase domain-like pseudokinase, a crucial marker of necroptosis, was also markedly upregulated at 3 days post-status epilepticus. In cultured hippocampal cells, kainic acid treatment significantly reduced the expression of full-length neogenin. Notably, treatment with DAPT prevented neogenin truncation and protected cultured neurons from N-methyl-D-aspartate (NMDA)-induced death. These data suggest that seizure-induced hippocampal necroptosis is associated with the generation of truncated neogenin, and that prevention of this by DAPT treatment can protect against NMDA-induced excitotoxicity.

Comparison of volumetric and shape changes of subcortical structures based on 3-dimensional image between obesity and normal-weighted subjects using 3.0 T MRI.

The morphological changes of the brain, particularly in the integrity of white and gray matter and the cortical thickness of brain, have been investigated extensively in obese patients. While there has been a growing amount of evidence indicating that subcortical structures are associated with obesity, studies on the volume of subregional level including shape alterations using high-field MRI are very sparse. The aim of this study was to evaluate and compare the volumes of 14 subcortical structures (bilateral thalamus, caudate, putamen, globus pallidus, hippocampus, amygdala, nucleus accumbens) in obese and normal-weighted subjects using 3T MRI for high resolution imaging. Fifty-four volunteers, 27 obesity (age = 23.15 ± 3.22, body mass index (BMI) = 30.12 ± 3.77) and 27 normal weighted controls (age = 26.1 ± 5.78, BMI = 21.76 ± 1.74) participated in the study. Through volumetric analysis, we found that the obese subjects had enlarged bilateral thalamus, putamen, pallidus and hippocampus, reduced bilateral caudate in obese groups in comparison to normal-weighted groups. Furthermore, we found that the medial-dorsal part of bilateral caudate significantly shrank while the lateral-dorsal part of bilateral thalamus significantly increased through vertex-based analysis (p < 0.05). Thus, based on our evidence, we suggest that subcortical structures are associated with feeding behavior and sensory function in obese patients.

Generation of Mouse Basal Ganglia Diffusion Tractography Using 9.4T MRI.

Over the years, diffusion tractography has seen increasing use for comparing minute differences in connectivity of brain structures in neurodegenerative diseases and treatments. Studies on connectivity between basal ganglia has been a focal point for studying the effects of diseases such as Parkinson's and Alzheimer's, as well as the effects of treatments such as deep brain stimulation. Additionally, in previous studies, diffusion tractography was utilized in disease mouse models to identify white matter alterations, as well as biomarkers that occur in the progression of disease. However, despite the extensive use of mouse models to study model diseases, the structural connectivity of the mouse basal ganglia has been inadequately explored. In this study, we present the methodology of segmenting the basal ganglia of a mouse brain, then generating diffusion tractography between the segmented basal ganglia structures. Additionally, we compare the relative levels of connectivity of connecting fibers between each basal ganglia structure, as well as visualize the shapes of each connection. We believe that our results and future studies utilizing diffusion tractography will be beneficial for properly assessing some of the connectivity changes that are found in the basal ganglia of various mouse models.

Volumetric Reductions of Subcortical Structures and Their Localizations in Alcohol-Dependent Patients.

Changes in brain morphometry have been extensively reported in various studies examining the effects of chronic alcohol use in alcohol-dependent patients. Such studies were able to confirm the association between chronic alcohol use and volumetric reductions in subcortical structures using FSL (FMRIB software library). However, each study that utilized FSL had different sets of subcortical structures that showed significant volumetric reduction. First, we aimed to investigate the reproducibility of using FSL to assess volumetric differences of subcortical structures between alcohol-dependent patients and control subjects. Second, we aimed to use Vertex analysis, a less utilized program, to visually inspect 3D meshes of subcortical structures and observe significant shape abnormalities that occurred in each subcortical structure. Vertex analysis results from the hippocampus and thalamus were overlaid on top of their respective subregional atlases to further pinpoint the subregional locations where shape abnormalities occurred. We analyzed the volumes of 14 subcortical structures (bilateral thalamus, caudate, putamen, globus pallidus, hippocampus, amygdala, nucleus accumbens) in 21 alcohol-dependent subjects and 21 healthy controls using images acquired with 3T MRI. The images were run through various programs found in FSL, such as SIENAX, FIRST, and Vertex analysis. We found that in alcohol-dependent patients, the bilateral thalamus (left: p < 0.01, right: p = 0.01), bilateral putamen (left: p = 0.02, right: p < 0.01), right globus pallidus (p < 0.01), bilateral hippocampus (left: p = 0.05, right: p = 0.03) and bilateral nucleus accumbens (left: p = 0.05, right: p = 0.03) were significantly reduced compared to the corresponding subcortical structures of healthy controls. With vertex analysis, we observed surface reductions of the following hippocampal subfields: Presubiculum, hippocampal tail, hippocampal molecular layer, hippocampal fissure, fimbria, and CA3. We reproduced the assessment made in previous studies that reductions in subcortical volume were negatively associated with alcohol dependence by using the FMRIB Software Library. In addition, we identified the subfields of the thalamus and hippocampus that showed volumetric reduction.

Resistive switching characteristics of manganese oxide nanoparticle assembly with crossbar arrays.

The fabrication of 3 x 3 crossbar arrays measuring 20 µm in width was demonstrated. The bipolar resistive switching characteristics in manganese oxide nanoparticles were investigated in the crossbar structure of top electrode (Au)/nanoparticle assembly/bottom electrode (Ti) on SiO2/Si substrate. The monodisperse manganese oxide nanoparticles measuring 13 nm in diameter were chemically synthesized by thermal decomposition of manganese acetate in the presence of oleic acid at high temperature. The nanoparticles were assembled as a layer measuring 30 nm thick by repeated dip-coating and annealing steps. The Au/nanoparticle assembly/Ti devices performed the bipolar behavior associated with the formation and sequential rupture of multiple conducting filaments in applying bias on Au electrode. When the voltage was swept from to +5 V to the Au top electrode, the reset voltage was observed at - 4.4 V. As the applied voltage swept from 0 to -5 V, the set voltage occurred at (-) -1.8 V.