Three-Dimensional Magneto-Acousto-Electrical Computed Tomography (3D MAE-CT): A Preliminary Study Using Ultrasound Linear Array Transducer.

Magneto-acousto-electrical tomography (MAET) is a hybrid imaging method that combines the high spatial resolution of ultrasonography with the high contrast of electrical impedance tomography (EIT). While most previous studies on MAET have focused on two-dimensional imaging, our recent research proposed a novel three-dimensional (3D) MAET method using B-mode and translational scanning. This method has been the first to reconstruct a 3D volume image of conductivity interfaces.

Harmonizing three-dimensional MRI using pseudo-warping field guided GAN.

In pursuit of cultivating automated models for magnetic resonance imaging (MRI) to aid in diagnostics, an escalating demand for extensive, multisite, and heterogeneous brain imaging datasets has emerged. This potentially introduces biased outcomes when directly applied for subsequent analysis. Researchers have endeavored to address this issue by pursuing the harmonization of MRIs.

Freehand 3D Ultrasound Imaging Based on Probe-mounted Vision and IMU System.

Objectives: Freehand three-dimensional (3D) ultrasound (US) is of great significance for clinical diagnosis and treatment, it is often achieved with the aid of external devices (optical and/or electromagnetic, etc.) that monitor the location and orientation of the US probe. However, this external monitoring is often impacted by imaging environment such as optical occlusions and/or electromagnetic (EM) interference.

Development of a novel six DNA damage response-related prognostic signature in osteosarcoma.

DNA damage response (DDR) plays a vital role in the development of cancer. Nevertheless, in osteosarcoma, the potential of DDR-related genes (DDRGs) remains unclear. Thus, the current research is intended to investigate the mechanisms of DDRGs in the development of osteosarcoma and to explore potential DDR-related biomarkers in forecasting the prognosis of osteosarcoma patients.

Association of Different Types of Osteoarthritis with Different Immune-Related Subtypes and Hub Genes.

Background: Osteoarthritis (OA) is a diverse disorder that most frequently affects elderly people and makes them disabled. Many investigations have shown that the etiology of OA depends on cartilage wear, but immunology also plays a significant role. Thus, the goal of this study was to define the immune-related etiology of OA.

Development of a Quantitative Digital Urinalysis Tool for Detection of Nitrite, Protein, Creatinine, and pH.

This paper presents a cost-effective, quantitative, point-of-care solution for urinalysis screening, specifically targeting nitrite, protein, creatinine, and pH in urine samples. Detecting nitrite is crucial for the early identification of urinary tract infections (UTIs), while regularly measuring urinary protein-to-creatinine (UPC) ratios aids in managing kidney health. To address these needs, we developed a portable, transmission-based colorimeter using readily available components, controllable via a smartphone application through Bluetooth.

Brain age predicted using graph convolutional neural network explains neurodevelopmental trajectory in preterm neonates.

Objectives: Dramatic brain morphological changes occur throughout the third trimester of gestation. In this study, we investigated whether the predicted brain age (PBA) derived from graph convolutional network (GCN) that accounts for cortical morphometrics in third trimester is associated with postnatal abnormalities and neurodevelopmental outcome.

Methods: In total, 577 T1 MRI scans of preterm neonates from two different datasets were analyzed; the NEOCIVET pipeline generated cortical surfaces and morphological features, which were then fed to the GCN to predict brain age.

Clinical and radiographic outcomes of oblique lumbar interbody fusion with anterolateral screw and rod instrumentation in osteopenia patients: a retrospective study.

Purpose: The purpose of this paper is to evaluate the clinical and radiographic outcomes of oblique lumbar interbody fusion (OLIF) to perform in L4/5 degenerative lumbar spondylolisthesis (DLS) patients who diagnosed with osteopenia.

Methods: From December 2018 to 2021 March, 94 patients were diagnosed with degenerative spondylolisthesis underwent OLIF and divided into two groups with different bone mineral density. Anterolateral screw and rod instrumentation was applied in two groups.

Incorporation of trans-rectal color doppler flow imaging and risk-stratification nomogram reduce unnecessary prostate biopsies in suspected prostate cancer patients: a bi-centered retrospective validation study.

Background: To explore the role of Trans-rectal Color Doppler Flow Imaging (TR-CDFI) and risk-stratification nomogram in a MRI-directed biopsy pathway and examine its clinical performance, via comparisons between existing four biopsy pathways.

Methods: A Bi-centered retrospective cohort study on biopsy-naïve male population who received ultrasound-guided prostate biopsy from Jan. 2015 to Feb.

Advanced Fourier migration for Plane-Wave vector flow imaging.

Ultrafast ultrasound imaging modalities have been studied extensively in the ultrasound community. It breaks the compromise between the frame rate and the region of interest by imaging the whole medium with wide unfocused waves. Continuously available data allow monitoring fast transient dynamics at hundreds to thousands of frames per second.

Contrastive Multi-View Composite Graph Convolutional Networks Based on Contribution Learning for Autism Spectrum Disorder Classification.

The resting-state functional magnetic resonance imaging (rs-fMRI) faithfully reflects the brain activities and thus provides a promising tool for autism spectrum disorder (ASD) classification. Up to now, graph convolutional networks (GCNs) have been successfully applied in rs-fMRI based ASD classification. However, most of these methods were developed based on functional connectivities (FCs) that only reflect low-level correlation between brain regions, without integrating both high-level discriminative knowledge and phenotypic information into classification.

Toward a Quantitative Colorimeter for Point-of-Care Nitrite Detection.

This paper reports on a low-cost, quantitative, point-of-care solution for the early detection of nitrite, a common biomarker for urinary tract infections (UTIs). In a healthy individual, nitrite is not found in the urine. However, a subject with a suspected UTI will produce nitrite in their urine since the bacteria present will convert nitrate into nitrite.

Jointly Composite Feature Learning and Autism Spectrum Disorder Classification Using Deep Multi-Output Takagi-Sugeno-Kang Fuzzy Inference Systems.

Autism spectrum disorder (ASD) is characterized by poor social communication abilities and repetitive behaviors or restrictive interests, which has brought a heavy burden to families and society. In many attempts to understand ASD neurobiology, resting-state functional magnetic resonance imaging (rs-fMRI) has been an effective tool. However, current ASD diagnosis methods based on rs-fMRI have two major defects.

Considerable effects of imaging sequences, feature extraction, feature selection, and classifiers on radiomics-based prediction of microvascular invasion in hepatocellular carcinoma using magnetic resonance imaging.

Background: Microvascular invasion (MVI) has a significant effect on the prognosis of hepatocellular carcinoma (HCC), but its preoperative identification is challenging. Radiomics features extracted from medical images, such as magnetic resonance (MR) images, can be used to predict MVI. In this study, we explored the effects of different imaging sequences, feature extraction and selection methods, and classifiers on the performance of HCC MVI predictive models.

Rapid rotational magneto-acousto-electrical tomography with filtered back-projection algorithm based on plane waves.

Magneto-acousto-electrical tomography (MAET) is designed to produce conductivity images with high spatial resolution for a conducting object. In a previous study, for an irregular conductor, transverse scanning and rotational methods with a focus transducer were combined to collect complete electrical information. This kind of method, however, is time-consuming because of the transverse scanning procedure.

A new deep learning method for displacement tracking from ultrasound RF signals of vascular walls.

It is necessary to monitor the mechanical properties of arteries which directly related to cardiovascular diseases (CVDs) in the early stages. In this study, we proposed a new method based on deep learning (DL) to track the displacement of the vessel wall from the ultrasound radio-frequency (RF) signals, which is a key technique to achieve quantitative measurement of vascular biomechanics. In comparison with traditional method, both results on simulation and experimental carotid artery data demonstrated that the DL method has higher accuracy for motion tracking of artery walls.

Treatment of pediatric femoral shaft fractures with elastic stable intramedullary nails versus external fixation: A meta-analysis.

Background: There is currently a debate about whether elastic stable intramedullary nails (ESIN) or external fixation (EF) is the best surgical method for treating pediatric femoral shaft fractures. We performed a meta-analysis to determine which surgical method leads to higher treatment satisfaction, lower complication rates, and reduced treatment time, to investigate whether ESIN is the preferred surgical method for treatment of pediatric femoral shaft fractures.

Patients And Methods: Relevant databases were searched for comparative studies of ESIN versus EF for the treating pediatric femoral shaft fractures.

A novel transcranial ultrasound imaging method with diverging wave transmission and deep learning approach.

Real time brain transcranial ultrasound imaging is extremely intriguing because of its numerous applications. However, the skull causes phase distortion and amplitude attenuation of ultrasound signals due to its density: the speed of sound is significantly different in bone tissue than in soft tissue. In this study, we propose an ultrafast transcranial ultrasound imaging technique with diverging wave (DW) transmission and a deep learning approach to achieve large field-of-view with high resolution and real time brain ultrasound imaging.

A novel transcranial ultrasound imaging method with diverging wave.

Real time transcranial ultrasound imaging of brain can be extremely intriguing because of its numerous applications. In this study, we proposed an ultrafast transcranial ultrasound imaging technique with diverging wave (DW) transmission, which has been a promising technique to image moving objects, such as complex blood flow field and transient elastography. However, diverging waves are all unfocused waves, which makes their image quality, especially the lateral resolution and contrast, has not yet been satisfactory.

Coherence Plane-Wave Compounding with Angle Coherence Factor for Ultrafast Ultrasound Imaging.

Ultrafast ultrasound imaging with plane wave transmission has been a promising technique to image moving objects, however, implies compromises among resolution, contrast and sensitivity. Coherence plane-wave compounding (CPWC) can balance the image quality and frame rate. The image quality, especiallyin terms of the suppression of artifacts stemmed from side lobes, is greatly comprised by reducing the number of the tilted plane-waves.

Impact and Predictive Value of Prostate Weight on the Outcomes of Nerve Sparing Laparoscopic Radical Prostatectomy in Patients with Low Risk Prostate Cancer.

Purpose: To investigate the impact of prostate weight on outcomes of nerve sparing laparoscopic radical prosta-tectomy (LRP) and assess its predictive value on postoperative continence and potency recovery.

Materials And Methods: We conducted a retrospective study on the clinical data of 165 patients with low risk prostate cancer (PCa) who underwent nerve sparing LRP. All the patients included had normal preoperative uri-nary and sexual function.

Combined analysis of CRMP4 methylation levels and CAPRA-S score predicts metastasis and outcomes in prostate cancer patients.

The present study analyzed the predictive value of combined analysis of collapsin response mediator protein 4 (CRMP4) methylation levels and the Cancer of the Prostate Risk Assessment (CAPRA-S) Postsurgical score of patients who required adjuvant hormone therapy (AHT) after radical prostatectomy (RP). We retrospectively analyzed 305 patients with prostate cancer (PCa) who received RP and subsequent androgen deprivation therapy (ADT). Two hundred and thirty patients with clinically high-risk PCa underwent immediate ADT, and 75 patients with intermediate risk PCa underwent deferred ADT.

Semianalytical Solution for the Deformation of an Elastic Layer under an Axisymmetrically Distributed Power-Form Load: Application to Fluid-Jet-Induced Indentation of Biological Soft Tissues.

Fluid-jet-based indentation is used as a noncontact excitation technique by systems measuring the mechanical properties of soft tissues. However, the application of these devices has been hindered by the lack of theoretical solutions. This study developed a mathematical model for testing the indentation induced by a fluid jet and determined a semianalytical solution.