Combining Regional and Connectivity Metrics of Functional Magnetic Resonance Imaging and Diffusion Tensor Imaging for Individualized Prediction of Pain Sensitivity.

Characterization and prediction of individual difference of pain sensitivity are of great importance in clinical practice. MRI techniques, such as functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI), have been popularly used to predict an individual's pain sensitivity, but existing studies are limited by using one single imaging modality (fMRI or DTI) and/or using one type of metrics (regional or connectivity features). As a result, pain-relevant information in MRI has not been fully revealed and the associations among different imaging modalities and different features have not been fully explored for elucidating pain sensitivity.

The brain's structural differences between postherpetic neuralgia and lower back pain.

The purpose is to explore the brain's structural difference in local morphology and between-region networks between two types of peripheral neuropathic pain (PNP): postherpetic neuralgia (PHN) and lower back pain (LBP). A total of 54 participants including 38 LBP and 16 PHN patients were enrolled. The average pain scores were 7.

Mortality prediction for patients with acute respiratory distress syndrome based on machine learning: a population-based study.

Background: Traditional scoring systems for patients' outcome prediction in intensive care units such as Oxygenation Saturation Index (OSI) and Oxygenation Index (OI) may not reliably predict the clinical prognosis of patients with acute respiratory distress syndrome (ARDS). Thus, none of them have been widely accepted for mortality prediction in ARDS. This study aimed to develop and validate a mortality prediction method for patients with ARDS based on machine learning using the Medical Information Mart for Intensive Care (MIMIC-III) and Telehealth Intensive Care Unit (eICU) Collaborative Research Database (eICU-CRD) databases.

Predicting Individual Pain Thresholds From Morphological Connectivity Using Structural MRI: A Multivariate Analysis Study.

Pain sensitivity is highly variable among individuals, and it is clinically important to predict an individual's pain sensitivity for individualized diagnosis and management of pain. Literature has shown that pain sensitivity is associated with regional structural features of the brain, but it remains unclear whether pain sensitivity is also related to structural brain connectivity. In the present study, we investigated the relationship between pain thresholds and morphological connectivity (MC) inferred from structural MRI based on data of 221 healthy participants.

Abnormalities of Cortical Thickness in Pediatric Mesial Temporal Lobe Epilepsy with Hippocampal Sclerosis.

Objective: Mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE-HS) is the most common intractable seizure type of pediatric epilepsy, with alterations in the cortex across the whole brain. The aim of this study is to investigate the abnormalities of cortical thickness in pediatric MTLE-HS.

Methods: Subjects were recruited from Shenzhen Children's Hospital between September 2015 and December 2016.