Automatic segmentation of the midfacial bone surface from ultrasound images using deep learning methods.

With developments in computer science and technology, great progress has been made in three-dimensional (3D) ultrasound. Recently, ultrasound-based 3D bone modelling has attracted much attention, and its accuracy has been studied for the femur, tibia, and spine. The use of ultrasound allows data for bone surface to be acquired non-invasively and without radiation.

Automatic virtual reduction of unilateral zygomatic fractures based on ICP algorithm: A preliminary study.

Objective: To establish an automatic reduction method for unilateral zygomatic fractures based on Iterative Closes Point (ICP) algorithm.

Material And Methods: 60 patients with unilateral type B zygomatic fractures were included. After acquiring CT images, zygomatic fragments were segmented using self-developed software MICSys.

Flavonoids of Euphorbia hirta inhibit inflammatory mechanisms via Nrf2 and NF-κB pathways.

Euphorbia hirta has anti-inflammatory effects in traditional medicine, but its anti-inflammatory mechanism has not been explored at the cellular and molecular levels. To unravel these mechanisms, the main active components in the 65 and 95% ethanol extracts of Euphorbia hirta were first identified by UPLC-Q-TOF/MS. Subsequently, potential anti-inflammatory targets and signaling pathways were predicted using network pharmacology and experimentally validated using RT-PCR and flow cytometry in a lipopolysaccharide (LPS)-induced inflammation model of RAW264.

UTSRMorph: A Unified Transformer and Superresolution Network for Unsupervised Medical Image Registration.

Complicated image registration is a key issue in medical image analysis, and deep learning-based methods have achieved better results than traditional methods. The methods include ConvNet-based and Transformer-based methods. Although ConvNets can effectively utilize local information to reduce redundancy via small neighborhood convolution, the limited receptive field results in the inability to capture global dependencies.

Super-resolution landmark detection networks for medical images.

Craniomaxillofacial (CMF) and nasal landmark detection are fundamental components in computer-assisted surgery. Medical landmark detection method includes regression-based and heatmap-based methods, and heatmap-based methods are among the main methodology branches. The method relies on high-resolution (HR) features containing more location information to reduce the network error caused by sub-pixel location.

Identification of high-functioning autism spectrum disorders based on gray-white matter functional network connectivity.

In the field of autism spectrum disorder (ASD), research on functional connectivity between gray matter and white matter remains under-researched. To address this gap, this study innovatively introduced a nested cross-validation method that integrates gray-white matter functional connectivity with an F-Score algorithm. This method calculates the correlation based on signals extracted from functional magnetic resonance imaging data using gray matter and white matter brain region templates.

The difference in core-surface temperature indicates the prognosis of heart failure patients.

To evaluate the difference between core temperature and surface temperature (ΔT) as an index for the prognosis of heart failure (HF). Core temperature and surface temperature were measured in 253 patients with HF. The association of ΔT with prognostic indicators of HF was analyzed.

LCGNet: Local Sequential Feature Coupling Global Representation Learning for Functional Connectivity Network Analysis with fMRI.

Analysis of functional connectivity networks (FCNs) derived from resting-state functional magnetic resonance imaging (rs-fMRI) has greatly advanced our understanding of brain diseases, including Alzheimer's disease (AD) and attention deficit hyperactivity disorder (ADHD). Advanced machine learning techniques, such as convolutional neural networks (CNNs), have been used to learn high-level feature representations of FCNs for automated brain disease classification. Even though convolution operations in CNNs are good at extracting local properties of FCNs, they generally cannot well capture global temporal representations of FCNs.

Growth Evaluation After Costochondral Graft Combined With Functional Appliance in Children With Temporomandibular Joint Ankylosis.

The treatment of temporomandibular joint (TMJ) ankylosis in children is a great challenge for surgeons. Costochondral graft (CCG) is a common method of reconstructing the TMJ in children. However, the growth pattern of CCG is unpredictable.

Craniomaxillofacial Bone Segmentation and Landmark Detection Using Semantic Segmentation Networks and an Unbiased Heatmap.

Craniomaxillofacial (CMF) surgery always relies on accurate preoperative planning to assist surgeons, and automatically generating bone structures and digitizing landmarks for CMF preoperative planning is crucial. Since the soft and hard tissues of the CMF regions possess complicated attachment, segmenting the CMF bones and detecting the CMF landmarks are challenging problems. In this study, we proposed a semantic segmentation network to segment the maxilla, mandible, zygoma, zygomatic arch, and frontal bones.

Reconstruction of the temporomandibular joint using a vascularized medial femoral condyle osteocartilaginous flap: an experimental investigation in miniature pigs.

Background: Reconstruction of the temporomandibular joint (TMJ) is a significant challenge in maxillofacial surgery. A vascularized medial femoral condyle (MFC) osteocartilaginous flap is a good choice for TMJ reconstruction. In this study, we evaluated the radiographic and histological changes of MFC after TMJ reconstruction.

[Using changes of left cardiac functional parameters and CPET evaluated the clinical effectiveness of individualized precise exercise overall program management of chronic disease I --Analysis between groups].

To explore and study the clinical usefulness of continuous dynamic recording of left cardiac function changes forevaluation the improvement in patients with chronic disease after 3 months of intensive control of individualized precision exercise overall manage program. From 2018 to 2021, 21 patients with chronic cardiovascular and cerebrovascular metabolic diseases mainly controlled by our team were selected to complete the cardiopulmonary exercise test (CPET) and Non-invasive synchronous cardiac function detector (N-ISCFD), electrocardiogram, radial pulse wave, jugular pulse wave and cardiogram data were continuously recorded for 50s.According to the titration results under CPET and continuous functional parameters monitoring, a holistic plan with individualized moderate exercise intensity as the core was developed for 3 months of intensive management, and then N-ISCFD data collection was repeatedafter signing the informed consent.

Is Convolutional Neural Network Accurate for Automatic Detection of Zygomatic Fractures on Computed Tomography?

Purpose: Zygomatic fractures involve complex anatomical structures of the mid-face and the diagnosis can be challenging and labor-consuming. This research aimed to evaluate the performance of an automatic algorithm for the detection of zygomatic fractures based on convolutional neural network (CNN) on spiral computed tomography (CT).

Materials And Methods: We designed a cross-sectional retrospective diagnostic trial study.

Clinical outcomes of vinorelbine loading CalliSpheres beads in the treatment of previously treated advanced lung cancer with progressive refractory obstructive atelectasis.

Drug-eluting beads bronchial arterial chemoembolization (DEB-BACE) has been used in the treatment of locally advanced lung cancer and has the potential to improve outcomes and reduce recurrence. However, DEB-BACE shows a poor therapeutic effect in advanced lung cancer after failure of multiple therapies. This study assessed the effect of DEB-BACE in the treatment of progressive lung cancer with refractory obstructive atelectasis.

A Multifactor Quantitative Assessment Model for Safe Mining after Roof Drainage in the Liangshuijing Coal Mine.

To prevent coal mine roof water damage, the water generally needs to be evacuated in advance. It can be mined with the water inrush risk assessed as safe. However, a single index is often employed in the water safety evaluation after the roof drainage, which causes a large gap between the evaluation results and the actual situation.

Convolutional Recurrent Neural Network for Dynamic Functional MRI Analysis and Brain Disease Identification.

Dynamic functional connectivity (dFC) networks derived from resting-state functional magnetic resonance imaging (rs-fMRI) help us understand fundamental dynamic characteristics of human brains, thereby providing an efficient solution for automated identification of brain diseases, such as Alzheimer's disease (AD) and its prodromal stage. Existing studies have applied deep learning methods to dFC network analysis and achieved good performance compared with traditional machine learning methods. However, they seldom take advantage of sequential information conveyed in dFC networks that could be informative to improve the diagnosis performance.

Accurate Reconstruction of Mandibular Defects With Vascularized Bone Flaps Through Utilization of Mandible Space-Retention Guides.

Purpose: Comprehensive evaluation of the effects of using computer-aided design and space retention guide technology to reconstruct mandibular defects using vascularized autogenous bone flaps.

Method: This study included 8 patients who received autogenous bone flaps (2 cases of vascularized fibula flaps and 6 cases of vascularized iliac flaps) for mandibular defect reconstruction at Peking University School and Hospital of Stomatology, from July 2018 to May 2021. All patients received digital surgery planning, computer aided design/computer aided manufacture, surgical guide technique for the removal of diseased bone segments, as well as vascularized fibular flap/iliac flap reconstruction.

Electron structure modulation and bicarbonate surrounding enhance Fenton-like reactions performance of Co-Co PBA.

Although several strategies have been developed to improve the efficiency of heterogeneous Fenton-like reactions, investigating the relationship among the electronic properties of the catalyst surface, the complex water matrix and catalytic activity remains challenges. Herein, the electron density of the active site Co(II) in Co Prussian blue analogs (Co-PBAs) is proved to be modulated by the anion source method. The elevated electron density of Co(II) and the higher metallicity of the catalyst lead to an increase in electron transport efficiency as revealed by X-ray photoelectron spectra (XPS), Fourier transform infrared spectroscopy (FT-IR), and density functional theory (DFT) calculations.

Management of pulmonary arteriovenous malformations involves additional factors aside from the diameter of feeding arteries: a 3-year case-case retrospective analysis.

Background: Pulmonary arteriovenous malformations (PAVMs) are rare but cause various manifestations. Although the diameter of feeding arteries has been linked to treatment decisions, relationships among the characteristics of PAVMs, clinical symptoms, and treatment effect remain unclear. The present study was performed to investigate how collective characteristics of PAVMs relate to clinical symptoms and to provide proper treatment recommendations for patients with PAVMs.

Statistical and individual characteristics-based reconstruction for craniomaxillofacial surgery.

Purpose: In craniomaxillofacial (CMF) surgery planning, a preoperative reconstruction of the CMF reference model is crucial for surgical restoration, especially the reconstruction of bilateral defects. Current reconstruction algorithms mainly generate reference models from the image analysis aspect, however, clinical indicators of the CMF reference model mostly consider the distribution of anatomical landmarks. Generating a reference model with optimal clinical evaluation helps promote the feasibility of an algorithm.

Radiomics Nomogram Improves the Prediction of Epilepsy in Patients With Gliomas.

Purpose: To investigate the association between clinic-radiological features and glioma-associated epilepsy (GAE), we developed and validated a radiomics nomogram for predicting GAE in WHO grade II~IV gliomas.

Methods: This retrospective study consecutively enrolled 380 adult patients with glioma (266 in the training cohort and 114 in the testing cohort). Regions of interest, including the entire tumor and peritumoral edema, were drawn manually.

Chest high-resolution computed tomography can make higher accurate stages for thoracic sarcoidosis than X-ray.

Background: To explore if chest high-resolution computed tomography (HRCT) can make higher accurate stages for thoracic sarcoidosis stage than X-ray (CRX) only.

Methods: Clinical data from medical records of consecutive patients with a confirmed diagnosis of pulmonary sarcoidosis at Shanghai Pulmonary Hospital from January 1 2012 to December 31 2016 and consecutive patients treated at the Sarcoidosis Center of University of Cincinnati Medical Center, Ohio, USA from January 1 2010 to December 31 2015 were reviewed. The clinical records of 227 patients diagnosed with sarcoidosis (140 Chinese and 87 American) were reviewed.

The diagnostic value of transbronchial lung cryobiopsy combined with rapid on-site evaluation in diffuse lung diseases: a prospective and self-controlled study.

Background: The etiology of interstitial lung diseases (ILDs) is varied. Early diagnosis and a specific pathological type could significantly improve the prognosis. Mostly, it is difficult to make the etiology diagnosis of ILD through traditional biopsy methods.