A worldwide study of subcortical shape as a marker for clinical staging in Parkinson's disease.

Alterations in subcortical brain regions are linked to motor and non-motor symptoms in Parkinson's disease (PD). However, associations between clinical expression and regional morphological abnormalities of the basal ganglia, thalamus, amygdala and hippocampus are not well established. We analyzed 3D T1-weighted brain MRI and clinical data from 2525 individuals with PD and 1326 controls from 22 global sources in the ENIGMA-PD consortium.

A worldwide study of white matter microstructural alterations in people living with Parkinson's disease.

The progression of Parkinson's disease (PD) is associated with microstructural alterations in neural pathways, contributing to both motor and cognitive decline. However, conflicting findings have emerged due to the use of heterogeneous methods in small studies. Here we performed a large diffusion MRI study in PD, integrating data from 17 cohorts worldwide, to identify stage-specific profiles of white matter differences.

Cerebellar Volume and Disease Staging in Parkinson's Disease: An ENIGMA-PD Study.

Background: Increasing evidence points to a pathophysiological role for the cerebellum in Parkinson's disease (PD). However, regional cerebellar changes associated with motor and non-motor functioning remain to be elucidated.

Objective: To quantify cross-sectional regional cerebellar lobule volumes using three dimensional T1-weighted anatomical brain magnetic resonance imaging from the global ENIGMA-PD working group.

A fixel-based analysis of white matter reductions early detects Parkinson disease with mild cognitive impairment.

Background: White matter (WM) tract alterations are early signs of cognitive impairment in Parkinson disease (PD) patients. Fixel-based analysis (FBA) has advantages over traditional diffusion tensor imaging in managing complex and crossing fibers. We used FBA to measure fiber-specific changes in patients with PD mild cognitive impairment (PD-MCI) and PD normal cognition (PD-NC).

Neuroplastic Changes Associated With Hybrid Exercise-Cognitive Training in Stroke Survivors With Mild Cognitive Decline: A Randomized Controlled Trial.

Background: Exercise and cognitive training have been shown to induce neuroplastic changes and modulate cognitive function following stroke. However, it remains unclear whether hybridized exercise-cognitive training facilitates cortical activity and further influences cognitive function after stroke.

Objective: The study aimed to investigate the effects of 2 hybridized exercise-cognitive trainings on neuroplastic changes and behavioral outcomes in stroke survivors with mild cognitive decline.

Diffusion and structural MRI as potential biomarkers in people with Parkinson's disease and cognitive impairment.

Objective: To explore the neuroimage change in Parkinson's disease (PD) patients with cognitive impairments, this study investigated the correlation between plasma biomarkers and morphological brain changes in patients with normal cognition and mild cognitive impairment. The objective was to identify the potential target deposition regions of the plasma biomarkers and to search for the relevant early neuroimaging biomarkers on the basis of different cognitive domains.

Methods: Structural brain MRI and diffusion weighted images were analyzed from 49 eligible PD participants (male/female: 27/22; mean age: 73.

The Image-Histology Correlation of Subcutaneous mPEG-poly(Ala) Hydrogel-Embedded MIN6 Cell Grafts in Nude Mice.

Previously, we have successfully used noninvasive magnetic resonance (MR) and bioluminescence imaging to detect and monitor mPEG-poly(Ala) hydrogel-embedded MIN6 cells at the subcutaneous space for up to 64 days. In this study, we further explored the histological evolution of MIN6 cell grafts and correlated it with image findings. MIN6 cells were incubated overnight with chitosan-coated superparamagnetic iron oxide (CSPIO) and then 5 × 10 cells in the 100 μL hydrogel solution were injected subcutaneously into each nude mouse.

Fully automated segmentation and radiomics feature extraction of hypopharyngeal cancer on MRI using deep learning.

Objectives: To use convolutional neural network for fully automated segmentation and radiomics features extraction of hypopharyngeal cancer (HPC) tumor in MRI.

Methods: MR images were collected from 222 HPC patients, among them 178 patients were used for training, and another 44 patients were recruited for testing. U-Net and DeepLab V3 + architectures were used for training the models.

The neural basis of pain during labor.

Characterizing a labor pain-related neural signature is a key prerequisite for devising optimized pharmacologic and nonpharmacologic labor pain relief methods. The aim of this study was to describe the neural basis of labor pain and to provide a brief summary of how epidural anesthesia may affect pain-related neuronal activity during labor. Possible future directions are also highlighted.

Generalizable transfer learning of automated tumor segmentation from cervical cancers toward a universal model for uterine malignancies in diffusion-weighted MRI.

Purpose: To investigate the generalizability of transfer learning (TL) of automated tumor segmentation from cervical cancers toward a universal model for cervical and uterine malignancies in diffusion-weighted magnetic resonance imaging (DWI).

Methods: In this retrospective multicenter study, we analyzed pelvic DWI data from 169 and 320 patients with cervical and uterine malignancies and divided them into the training (144 and 256) and testing (25 and 64) datasets, respectively. A pretrained model was established using DeepLab V3 + from the cervical cancer dataset, followed by TL experiments adjusting the training data sizes and fine-tuning layers.

T1 and T2∗ relaxation time in the parcellated myocardium of healthy Taiwanese participants: A single center study.

Background: Quantitative maps from cardiac MRI provide objective information for myocardial tissue. The study aimed to report the T1 and T2∗ relaxation time and its relationship with clinical parameters in healthy Taiwanese participants.

Methods: Ninety-three participants were enrolled between 2014 and 2016 (Males/Females: 43/50; age: 49.

Diffusion tensor imaging for the differential diagnosis of Parkinsonism by machine learning.

Background: There are currently no specific tests for either idiopathic Parkinson's disease or Parkinson-plus syndromes. The study aimed to investigate the diagnostic performance of features extracted from the whole brain using diffusion tensor imaging concerning parkinsonian disorders.

Methods: The retrospective data yielded 625 participants (average age: 61.

Deep Learning-Based Brain Computed Tomography Image Classification with Hyperparameter Optimization through Transfer Learning for Stroke.

Brain computed tomography (CT) is commonly used for evaluating the cerebral condition, but immediately and accurately interpreting emergent brain CT images is tedious, even for skilled neuroradiologists. Deep learning networks are commonly employed for medical image analysis because they enable efficient computer-aided diagnosis. This study proposed the use of convolutional neural network (CNN)-based deep learning models for efficient classification of strokes based on unenhanced brain CT image findings into normal, hemorrhage, infarction, and other categories.

Magnetic Resonance Imaging of Transplanted Porcine Neonatal Pancreatic Cell Clusters Labeled with Exendin-4-Conjugated Manganese Magnetism-Engineered Iron Oxide Nanoparticles.

Recently, we have shown that manganese magnetism-engineered iron oxide nanoparticles (MnMEIO NPs) conjugated with exendin-4 (Ex4) act as a contrast agent that directly trace implanted mouse islet β-cells by magnetic resonance imaging (MRI). Here we further advanced this technology to track implanted porcine neonatal pancreatic cell clusters (NPCCs) containing ducts, endocrine, and exocrine cells. NPCCs from one-day-old neonatal pigs were isolated, cultured for three days, and then incubated overnight with MnMEIO-Ex4 NPs.

Deep learning based diagnosis of Parkinson's Disease using diffusion magnetic resonance imaging.

The diagnostic performance of a combined architecture on Parkinson's disease using diffusion tensor imaging was evaluated. A convolutional neural network was trained from multiple parcellated brain regions. A greedy algorithm was proposed to combine the models from individual regions into a complex one.

Exendin-4-Conjugated Manganese Magnetism-Engineered Iron Oxide Nanoparticles as a Potential Magnetic Resonance Imaging Contrast Agent for Tracking Transplanted β-Cells.

To specifically detect and trace transplanted islet β-cells by magnetic resonance imaging (MRI), we conjugated manganese magnetism-engineered iron oxide nanoparticles (MnMEIO NPs) with exendin-4 (Ex4) which specifically binds glucagon-like peptide-1 receptors on the surface of β-cells. The size distribution of MnMEIO and MnMEIO-Ex4 NPs were 67.8 ± 1.

Fixel-Based Analysis Effectively Identifies White Matter Tract Degeneration in Huntington's Disease.

Microstructure damage in white matter might be linked to regional and global atrophy in Huntington's Disease (HD). We hypothesize that degeneration of subcortical regions, including the basal ganglia, is associated with damage of white matter tracts linking these affected regions. We aim to use fixel-based analysis to identify microstructural changes in the white matter tracts.

International Multicenter Analysis of Brain Structure Across Clinical Stages of Parkinson's Disease.

Background: Brain structure abnormalities throughout the course of Parkinson's disease have yet to be fully elucidated.

Objective: Using a multicenter approach and harmonized analysis methods, we aimed to shed light on Parkinson's disease stage-specific profiles of pathology, as suggested by in vivo neuroimaging.

Methods: Individual brain MRI and clinical data from 2357 Parkinson's disease patients and 1182 healthy controls were collected from 19 sources.

Magnetic Resonance Imaging of Transplanted Porcine Neonatal Pancreatic Cell Clusters Labeled with Chitosan-Coated Superparamagnetic Iron Oxide Nanoparticles in Mice.

Neonatal pancreatic cell clusters (NPCCs) are potential tissues for the treatment of diabetes. Different from adult cells, they continuously proliferate and differentiate after transplantation. In this study, we utilized magnetic resonance imaging (MRI) to detect and monitor implanted NPCCs.

Fixel-Based Analysis of White Matter Degeneration in Patients With Progressive Supranuclear Palsy or Multiple System Atrophy, as Compared to Parkinson's Disease.

White matter degeneration may contribute to clinical symptoms of parkinsonism. We used fixel-based analysis (FBA) to compare the extent and patterns of white matter degeneration in different parkinsonian syndromes-including idiopathic Parkinson's disease (PD), multiple system atrophy (MSA), and progressive supranuclear palsy (PSP). This is a retrospective interpretation of prospectively acquired data of patients recruited in previous studies during 2008 and 2019.

Noninvasive Tracking of mPEG-poly(Ala) Hydrogel-Embedded MIN6 Cells after Subcutaneous Transplantation in Mice.

Recently, we demonstrated the feasibility of subcutaneous transplantation of MIN6 cells embedded in a scaffold with poly(ethylene glycol) methyl ether (mPEG)-poly(Ala) hydrogels. In this study, we further tracked these grafts using magnetic resonance (MR) and bioluminescence imaging. After being incubated overnight with chitosan-coated superparamagnetic iron oxide (CSPIO) nanoparticles and then mixed with mPEG-poly(Ala) hydrogels, MIN6 cells appeared as dark spots on MR scans.

Oxygen-sensitive T2* magnetic resonance imaging to correlate heart function and ischemic etiology of post-hospitalized chronic heart failure patients.

Purpose: Myocardial oxygenation imaging is a field-of-interest but its clinical utility largely unexplored. We aimed to investigate the myocardial oxygenation status via T2* imaging and compared with the left ventricular ejection fraction (LVEF) in chronic heart failure (HF) patients after hospitalization. Also, we sought to compare the differences in myocardial oxygenation status among patients with ischemic HF, non-ischemic HF and controls.

A Method for the Prediction of Clinical Outcome Using Diffusion Magnetic Resonance Imaging: Application on Parkinson's Disease.

Robust early prediction of clinical outcomes in Parkinson's disease (PD) is paramount for implementing appropriate management interventions. We propose a method that uses the baseline MRI, measuring diffusion parameters from multiple parcellated brain regions, to predict the 2-year clinical outcome in Parkinson's disease. Diffusion tensor imaging was obtained from 82 patients (males/females = 45/37, mean age: 60.

Left Ventricular Function and Myocardial Triglyceride Content on 3T Cardiac MR Predict Major Cardiovascular Adverse Events and Readmission in Patients Hospitalized with Acute Heart Failure.

Background: This prospective study was designed to investigate whether myocardial triglyceride (TG) content from proton magnetic resonance spectroscopy (MRS) and left ventricular (LV) function parameters from cardiovascular magnetic resonance imaging (CMR) can serve as imaging biomarkers in predicting future major cardiovascular adverse events (MACE) and readmission in patients who had been hospitalized for acute heart failure (HF).

Methods: Patients who were discharged after hospitalization for acute HF were prospectively enrolled. On a 3.

Functional human brain connectivity during labor and its alteration under epidural analgesia.

This study used functional magnetic resonance imaging to explore the neural networks of pain during labor and its relief. It was hypothesized that epidural analgesia would affect the neural activities and the underlying network connectivity. Analysis using dynamic causal modelling and functional connectivity was performed to investigate the spatial activity and network connection of labor pain with and without epidural analgesia.