Effects of iterative metal artifact reduction techniques on diagnostic performance in patients with dental artifacts on carotid computed tomography angiography.

Background: Metal artifacts (MAs) induced by dental prostheses in carotid computed tomography angiography (CTA) significantly impair diagnostic accuracy. This study aimed to assess the efficacy of the iterative metal artifact reduction (iMAR) technique in mitigating these artifacts.

Methods: Eighty-one patients with suspected vascular disorders and dental prostheses who underwent CTA imaging were retrospectively included.

Multitask Deep Learning for Automated Segmentation and Prognostic Stratification of Endometrial Cancer via Biparametric MRI.

Background: Endometrial cancer (EC) is a common gynecologic malignancy; accurate assessment of key prognostic factors is important for treatment planning.

Purpose: To develop a deep learning (DL) framework based on biparametric MRI for automated segmentation and multitask classification of EC key prognostic factors, including grade, stage, histological subtype, lymphovascular space invasion (LVSI), and deep myometrial invasion (DMI).

Study Type: Retrospective.

Effects of dietary nitrate supplementation on isometric performance and physiological responses in college bodybuilders: a randomized, double-blind, crossover study.

Introduction: In bodybuilding competitions, athletes are required to hold static poses for extended periods. This study aimed to evaluate the effects of acute beetroot juice (BJ) supplementation on isometric muscle endurance in college bodybuilding athletes.

Methods: Sixteen male college bodybuilding athletes participated in a randomized, double-blind, crossover study conducted over three weeks with four laboratory visits.

Predicting Postoperative Progression of Ossification of the Posterior Longitudinal Ligament in the Cervical Spine Using Interpretable Radiomics Models.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery.

Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart.

Low-dose tin-filtered computed tomography (CT) with iterative metal artifact reduction algorithm versus dual-energy CT for patients with lumbar metal implants.

Purpose: This study aimed to evaluate a low-dose tin-filtered (LD Sn) CT protocol with iterative metal artifact reduction (iMAR) to reduce metal artifacts and radiation dose compared to dual-energy CT (DECT) with iMAR in patients with lumbar metal implants.

Methods: The study included 70 patients, comprising 35 patients in the prospective LD Sn CT cohort and 35 matched patients in the retrospective DECT cohort, utilizing a hybrid design. Evaluations included DECT Mixed images, noise-optimized virtual monoenergetic imaging at 130 keV (DE Mono+), and LD Sn CT with and without iMAR.

Metallic 1T Phase MoS Nanosheets Covalently Functionalized with BBD Molecules for Enhanced Supercapacitor Performances.

Metallic 1T phase molybdenum disulfide (MoS) is among the most promising electrode materials for supercapacitors, but its capacitance and cyclability remain to be improved to meet the constantly increasing energy storage needs in portable electronics. In this study, we present a strategy, covalent functionalization, which achieves the improvement of capacitance of metallic 1T phase MoS. Covalently functionalized by the modifier 4-bromobenzenediazonium tetrafluoroborate, the metallic MoS membrane exhibits increased interlayer spacing, slightly curled layered architecture, enhanced charge transfer, and improved adsorption capabilities toward electrolyte molecules and ions.

Prediction of pathological response and lymph node metastasis after neoadjuvant therapy in rectal cancer through tumor and mesorectal MRI radiomic features.

Establishing predictive models for the pathological response and lymph node metastasis in locally advanced rectal cancer (LARC) treated with neoadjuvant chemoradiotherapy (nCRT) based on MRI radiomic features derived from the tumor and mesorectal compartment (MC). This study included 209 patients with LARC who underwent rectal MRI both before and after nCRT. The patients were divided into a training set (n = 146) and a test set (n = 63).

A comparison of 2D and 3D magnetic resonance imaging-based intratumoral and peritumoral radiomics models for the prognostic prediction of endometrial cancer: a pilot study.

Background: Accurate prognostic assessment is vital for the personalized treatment of endometrial cancer (EC). Although radiomics models have demonstrated prognostic potential in EC, the impact of region of interest (ROI) delineation strategies and the clinical significance of peritumoral features remain uncertain. Our study thereby aimed to explore the predictive performance of varying radiomics models for the prediction of LVSI, DMI, and disease stage in EC.

Broken-fat pad sign: a characteristic radiographic finding to distinguish between knee rheumatoid arthritis and osteoarthritis.

Objectives: Diagnostic imaging plays an important role in the pre-treatment workup of knee osteoarthritis (OA) and rheumatoid arthritis (RA). Herein, we identified a useful MRI sign of infrapatellar fat pad (IPFP) to improve diagnosis.

Methods: Eighty-one age- and sex-matched RA and OA patients each, with pathological diagnosis and pre-treatment MRI were retrospectively evaluated.

Assessment of axial spondyloarthritis activity using a magnetic resonance imaging-based multi-region-of-interest fusion model.

Background: Identifying axial spondyloarthritis (axSpA) activity early and accurately is essential for treating physicians to adjust treatment plans and guide clinical decisions promptly. The current literature is mostly focused on axSpA diagnosis, and there has been thus far, no study that reported the use of a radiomics approach for differentiating axSpA disease activity. In this study, the aim was to develop a radiomics model for differentiating active from non-active axSpA based on fat-suppressed (FS) T2-weighted (T2w) magnetic resonance imaging (MRI) of sacroiliac joints.

Removal of toxic metals using iron sulfide particles: A brief overview of modifications and mechanisms.

Growing mechanization has released higher concentrations of toxic metals in water and sediment, which is a critical concern for the environment and human health. Recent studies show that naturally occurring and synthetic iron sulfide particles are efficient at removing these hazardous pollutants. This review seeks to provide a concise summary of the evolution in the production of iron sulfide particles, specifically nanoparticles, through the years.

Application research of AI-assisted compressed sensing technology in MRI scanning of the knee joint: 3D-MRI perspective.

Objective: To investigate the potential applicability of AI-assisted compressed sensing (ACS) in knee MRI to enhance and optimize the scanning process.

Methods: Volunteers and patients with sports-related injuries underwent prospective MRI scans with a range of acceleration techniques. The volunteers were subjected to varied ACS acceleration levels to ascertain the most effective level.

One-step green synthesis of oil-dispersible carbonized polymer dots as eco-friendly lubricant additives with superior dispersibility, lubricity, and durability.

Chemical functionalization provides effective protocols for inorganic nanomaterials as oil-dispersible lubricant additives. Nevertheless, harsh reaction conditions and arduous post-processing are frequently encountered when adopting this approach. Herein, four types of carbonized polymer dots (CPDs) with admirable dispersibility and long-term stability (more than 6 months without any sediments) in polyethylene glycol (PEG200) were synthesized by a one-step and green solvothermal route using saccharides as the single precursors.

Nano ferric oxide adsorbents with self-acidification effect for efficient adsorption of Sb(V).

It is urgent and essential to remove antimony from wastewater due to its potential carcinogenicity. In this paper, a nano ferric oxide (NFO) adsorbent was synthesized in a one-step low temperature calcination (150 °C) process. It presents a surprising self-acidification behavior, could automatically adjust the pH to around 4 from different intimal pH values (4-9), which enable it to efficiently remove more than 99% of Sb(V) from wastewater in a wide pH range.

Simultaneous reduction and sequestration of hexavalent chromium by magnetic β-Cyclodextrin stabilized FeS.

In this study, β-Cyclodextrin (CD) modified FeS nanomaterials were synthesized by a one-step facile strategy and investigated for the removal of Cr(VI). The resulted CD-FeS exhibited enhanced removal efficiency toward Cr(VI) than bared FeS with a maximum capacity of 220.26 mg·g as the molar ratio of CD-to-FeS at 0.

Magnetic Adsorbents for Wastewater Treatment: Advancements in Their Synthesis Methods.

The remediation of water streams, polluted by various substances, is important for realizing a sustainable future. Magnetic adsorbents are promising materials for wastewater treatment. Although numerous techniques have been developed for the preparation of magnetic adsorbents, with effective adsorption performance, reviews that focus on the synthesis methods of magnetic adsorbents for wastewater treatment and their material structures have not been reported.

[Application of MRI Water-Fat Separation Technology in Patients with Multiple Myeloma].

Objective: To explore the clinical significance of magnetic resonance imaging water-fat separation (Dixon) technique in patients with multiple myeloma.

Methods: A total of 41 newly diagnosed patients with multiple myeloma who underwent Dixon in The Affiliated Hospital of Qingdao University from April 2019 to April 2021 were included in this study. Patients were divided into observation group and control group according to whether Dixon performance was normal or not.

Magnetic Resonance Imaging-Based Radiomics Nomogram for Prediction of the Histopathological Grade of Soft Tissue Sarcomas: A Two-Center Study.

Background: Preoperative prediction of soft tissue sarcoma (STS) grade is important for treatment decisions. Therefore, formulation an STS grade model is strongly needed.

Purpose: To develop and test an magnetic resonance imaging (MRI)-based radiomics nomogram for predicting the grade of STS (low-grade vs.