A new perspective: Quantitative description of the Cupid's peak aesthetics essence.

Objectives: The Cupid's peak triangle theory was established to reveal the aesthetics essence of the Cupid's peak through golden ratio deviation to provide quantitative theoretical basis for lip plastic and cosmetic surgery.

Materials And Methods: Model the Cupid's peak line on the lip bow ridge and construct expressions for Cupid's peak parameters and their associated triangle theory using the angle circle (AC) and radius circle (RC) of the Cupid's peak line. Calculate and establish functional relationships for Cupid's peak parameters and the concept of the Cupid's peak index (CPI) golden ratio deviation (GRD).

Quantifying the reproducibility and longitudinal repeatability of radiomics features in magnetic resonance Image-Guide accelerator Imaging: A phantom study.

Objective: This study aimed to quantitatively evaluate the inter-platform reproducibility and longitudinal acquisition repeatability of MRI radiomics features in Fluid-Attenuated Inversion Recovery (FLAIR), T2-weighted (T2W), and T1-weighted (T1W) sequences on MR-Linac systems using an American College of Radiology (ACR) phantom.

Materials And Methods: This study used two MR-Linac systems (A and B) in different cancer centers. The ACR phantom was scanned on system A daily for 30 consecutive days to evaluate longitudinal repeatability.

Comprehensive three-dimensional cone beam computed tomography assessment unilateral alveolar cleft reconstruction using autologous iliac cancellous bone combined with deproteinized bovine bone: A clinical retrospective evaluation.

Large-volume autologous iliac cancellous bone grafting for alveolar cleft may lead to undesirable bone resorption and susceptible donor-site morbidity, whereas the addition of deproteinized bovine bone (DBB) could optimize outcomes. This study aimed to evaluate the effectiveness of combining autologous iliac bone with DBB using three-dimensional cone beam computed tomography (3D-CBCT) for better analysis of bone generation than conventional evaluation methods. Thirty-six patients with unilateral alveolar cleft were assigned into two groups.

Altered Brain Glymphatic Function at Diffusion-Tensor MRI in Pre-cirrhotic Metabolic Dysfunction-Associated Fatty Liver Disease.

Rationale And Objectives: To evaluate glymphatic function changes and their relationships with clinical features in patients with metabolic dysfunction-associated fatty liver disease (MAFLD), thereby facilitating early intervention before this disease progresses to cirrhosis.

Materials And Methods: A cross-sectional cohort of 46 pre-cirrhotic MAFLD patients and 30 age-, sex-, and education-matched controls was enrolled, with diffusion-tensor imaging (DTI) data, laboratory and neurocognitive scores collected. The DTI analysis along the perivascular space (DTI-ALPS) index was computed for qualifying glymphatic function.

Gut Microbiota Moderates Multimodal Brain Structure-Function Integration and Behavioral Cognition in Growth Hormone Deficient Children.

Introduction: Previous brain studies of growth hormone deficiency (GHD) often used single-modal neuroimaging, missing the complexity captured by multimodal data. Growth hormone affects gut microbiota and metabolism in GHD. However, from a gut-brain axis (GBA) perspective, the relationship between abnormal GHD brain development and microbiota alterations remains unclear.

Altered cerebral white matter network topology and cognition in children with obstructive sleep apnea.

Objectives: The study aimed to explore the underlying mechanisms of OSA-related cognitive impairment by investigating the altered topology of brain white matter networks in children with OSA.

Methods: Graph theory was used to examine white matter networks' network topological properties in 46 OSA and 31 non-OSA children. All participants underwent MRI, polysomnography, and cognitive testing.

Clinical efficacy of Hogan posterior pharyngeal flap in repairing velopharyngeal insufficiency secondary to cleft palate in older patients.

Objectives: The clinical effects and surgical procedures of Hogan posterior pharyngeal flap in the treatment of the older patients with velopharyngeal insufficiency (VPI) after cleft palate repair were investigated.

Methods: A total of 33 patients (aged 10-35 years; average of 20.4 years) with VPI secondary to cleft palate were included.

Assembling High-Quality Lymph Node Clinical Target Volumes for Cervical Cancer Radiotherapy Using a Deep Learning-Based Approach.

Aim: The study aimed to explore an approach for accurately assembling high-quality lymph node clinical target volumes (CTV) on CT images in cervical cancer radiotherapy with the encoder-decoder 3D network.

Methods: 216 cases of CT images treated at our center between 2017 and 2020 were included as a sample, which were divided into two cohorts, including 152 cases and 64 controls, respectively. Para-aortic lymph node, common iliac, external iliac, internal iliac, obturator, presacral, and groin nodal regions were delineated as sub-CTV manually in the cohort including 152 cases.

Alterations of brain gray matter volume in children with obstructive sleep apnea.

Objective: Obstructive sleep apnea (OSA) seriously affects the children's cognitive functions, but the neuroimaging mechanism of cognitive impairment is still unclear. The purpose of our study was to explore the difference in brain local gray matter volume (GMV) between children with OSA and non-OSA, and the correlation between the difference regions of brain gray matter volume and cognitive, the severity of OSA.

Method: Eighty-three children aged 8-13 years were recruited in our study, 52 children were diagnosed as OSA by polysomnography, and 31 as the non-OSA.

CDC6 is a prognostic biomarker and correlated with immune infiltrates in glioma.

Background: Cell division cycle 6 (CDC6) has been proven to be associated with the initiation and progression of human multiple tumors. However, it's role in glioma, which is ranked as one of the common primary malignant tumor in the central nervous system and is associated with high morbidity and mortality, is unclear.

Methods: In this study, we explored CDC6 gene expression level in pan-cancer.

Quality Assurance based on Deep Learning for Pelvic OARs Delineation in Radiotherapy.

Background: Correct delineation of organs at risk (OARs) is an important step for radiotherapy and it is also a time-consuming process that depends on many factors.

Objective: An automatic quality assurance (QA) method based on deep learning (DL) was proposed to improve efficiency for detecting contouring errors of OARs.

Materials And Methods: A total of 180 planning CT scan sets at the pelvic site and the corresponding OARs contours from clinics were enrolled in this study.

Altered Spontaneous Brain Activity in Left-Behind Children: A Resting-State Functional MRI Study.

Background: Parental migration has been associated with a higher risk of cognitive and behavioral abnormalities in left-behind children (LBC). This study aimed to explore the spontaneous brain activity in LBC and reveal the mechanisms underlying behavioral and cognitive abnormalities.

Methods: Involved LBC ( = 36) and non-LBC ( = 22) underwent resting-state functional MRI (fMRI) examination and cognitive and behavioral assessment.

[The Effects of Different Adaptive Statistical Iterative Reconstruction-V and Convolution Kernel Parameters on Auto-Segmentation Stability in CT Images].

The study aims to investigate the effects of different adaptive statistical iterative reconstruction-V（ ASiR-V） and convolution kernel parameters on stability of CT auto-segmentation which is based on deep learning. Twenty patients who have received pelvic radiotherapy were selected and different reconstruction parameters were used to establish CT images dataset. Then structures including three soft tissue organs (bladder, bowelbag, small intestine) and five bone organs (left and right femoral head, left and right femur, pelvic) were segmented automatically by deep learning neural network.

Real-Time Image-Guided Navigation in the Management of Alveolar Cleft Repair.

To present the use of dynamic navigation system in the repair of alveolar cleft. A total of three non-syndromic patients with unilateral alveolar cleft were involved in this study. Real-time computer-aided navigation were used to achieve restoration and reconstruction with standardized surgical technique.

[Feasibility of Evaluating Result of Auto-segmentation of Target Volumes in Radiotherapy with Medical Consideration Index].

Objective: To explore the feasibility of using the bidirectional local distance based medical similarity index (MSI) to evaluate automatic segmentation on medical images.

Methods: Taking the intermediate risk clinical target volume for nasopharyngeal carcinoma manually segmented by an experience radiation oncologist as region of interest, using Atlas-based and deep-learning-based methods to obtain automatic segmentation respectively, and calculated multiple MSI and Dice similarity coefficient (DSC) between manual segmentation and automatic segmentation. Then the difference between MSI and DSC was comparatively analyzed.

Quantitative Comparisons of Deep-learning-based and Atlas-based Auto- segmentation of the Intermediate Risk Clinical Target Volume for Nasopharyngeal Carcinoma.

Background: Manual segment target volumes were time-consuming and inter-observer variability couldn't be avoided. With the development of computer science, auto-segmentation had the potential to solve this problem.

Objective: To evaluate the accuracy and stability of Atlas-based and deep-learning-based auto-segmentation of the intermediate risk clinical target volume, composed of CTV2 and CTVnd, for nasopharyngeal carcinoma quantitatively.

A novel red emission fluorescent probe for monitoring carbon monoxide in living cells and zebrafish.

Carbon monoxide (CO), a gaseous signal molecule, plays a crucial role in biological systems. With the aim of unraveling its biological functions, a novel fluorescent probe for sensing CO was rationally designed and synthesized based on a coumarin derivative fluorophore merging tetrahydroquinoxaline unit and five-membered pyrrolidine. This fluorescent probe demonstrated a large Stokes shift (Δλ = 132 nm), high quantum yield, red emission, high sensitivity and selectivity for CO with remarkable fluorescence turn-on.

Dosimetric evaluation of synthetic CT image generated using a neural network for MR-only brain radiotherapy.

Purpose And Background: The magnetic resonance (MR)-only radiotherapy workflow is urged by the increasing use of MR image for the identification and delineation of tumors, while a fast generation of synthetic computer tomography (sCT) image from MR image for dose calculation remains one of the key challenges to the workflow. This study aimed to develop a neural network to generate the sCT in brain site and evaluate the dosimetry accuracy.

Materials And Methods: A generative adversarial network (GAN) was developed to translate T1-weighted MRI to sCT.

[Application and Development Trend of Medical Image Automatic Segmentation Technology in Radiation Therapy].

The development of medical image segmentation technology has been briefly reviewed. The applications of auto-segmentation of organs at risk and target volumes based on Atlas and deep learning in the field of radiotherapy have been introduced in detail, respectively. Then the development direction and product model for general automatic sketching tools or systems based on solid clinical data are discussed.

Evaluation on Auto-segmentation of the Clinical Target Volume (CTV) for Graves' Ophthalmopathy (GO) with a Fully Convolutional Network (FCN) on CT Images.

Unlabelled: CDATA[Purpose: The aim of this study is to evaluate the accuracy and dosimetric effects for auto- segmentation of the CTV for GO in CT images based on FCN.

Methods: An FCN-8s network architecture for auto-segmentation was built based on Caffe. CT images of 121 patients with GO who have received radiotherapy at the West China Hospital of Sichuan University were randomly selected for training and testing.

Gray Matter Differences Between Premature Pubertal Girls With and Without the Reactivation of the Hypothalamic-Pituitary-Gonadal Axis.

The onset of puberty and related hormones exerts significant effects on brain morphometric and psychosocial development. The biological mechanisms underlying how the reactivation of the hypothalamic-pituitary-gonadal (HPG) axis and puberty-related hormonal maturation sculpts human brain architecture remain elusive. To address this question, 105 premature pubertal girls (age 8-11 years) without menstruation underwent brain structural scanning on a 3T MR system, and the luteinizing hormone releasing hormone (LHRH) stimulation test was used to identify the reactivation of the HPG axis.

[Using stacked neural network to improve the auto-segmentation accuracy of Graves' ophthalmopathy target volumes for radiotherapy].

Compared with the previous automatic segmentation neural network for the target area which considered the target area as an independent area, a stacked neural network which uses the position and shape information of the organs around the target area to regulate the shape and position of the target area through the superposition of multiple networks and fusion of spatial position information to improve the segmentation accuracy on medical images was proposed in this paper. Taking the Graves' ophthalmopathy disease as an example, the left and right radiotherapy target areas were segmented by the stacked neural network based on the fully convolutional neural network. The volume Dice similarity coefficient (DSC) and bidirectional Hausdorff distance (HD) were calculated based on the target area manually drawn by the doctor.

Abnormal Functional Connectivity Density in New-Onset Type 1 Diabetes Mellitus Children: A Resting-State Functional Magnetic Resonance Imaging Study.

Type 1 diabetes mellitus (T1DM) causes cognitive changes in children, which may be due to deficits in brain functions. It is unclear whether T1DM children will have brain functional changes during the initial stage of the disease. We aimed to investigate the changes in the functional brain network topology in children with new-onset T1DM.