Bone reporting and data system on CT (Bone-RADS-CT): a validation study by four readers on 328 cases from three local and two public databases.

Objective: To evaluate the reproducibility and effectiveness of the bone reporting and data system on CT (Bone-RADS-CT) for incidental solitary bone lesions in adults.

Materials And Methods: We retrospectively included 328 CT cases from three local and two public databases, respectively. All the cases were histopathologically or clinically confirmed bone lesions, "do not touch" lesions with typical appearance, and remained stable for at least 2 years.

Tunable Interlayer-Spacing Graphene Oxide Membrane: Efficient Osmotic Energy Conversion Toward Metal Recovery.

2D material membranes show promise in osmotic energy (OE) conversion and separation technologies. However, low ion flux and swelling limit their applications. Herein, a polydopamine-crosslinked graphene oxide membrane (PDA@GO) with tunable interlayer spacing is developed to address these challenges.

Bone Reporting and Data System on MRI (Bone-RADS-MRI): a validation study by four readers on 275 cases from three local and two public databases.

Objective: To evaluate the reproducibility and effectiveness of the Bone Reporting and Data System on MRI (Bone-RADS-MRI) for incidental solitary bone lesions in adults.

Materials And Methods: We retrospectively included 275 MRI cases from three local and two public databases, respectively. All the cases were histopathologically or clinically confirmed bone lesions, or "do not touch" lesions with typical appearance and remained stable for at least two years.

Assessment of Robustness of MRI Radiomic Features in the Abdomen: Impact of Deep Learning Reconstruction and Accelerated Acquisition.

The objective of this study is to investigate the impact of deep learning reconstruction and accelerated acquisition on reproducibility and variability of radiomic features in abdominal MRI. Seventeen volunteers were prospectively included to undergo abdominal MRI on a 3-T scanner for axial T2-weighted, axial T2-weighted fat-suppressed, and coronal T2-weighted sequences. Each sequence was scanned for four times using clinical reference acquisition with standard reconstruction, clinical reference acquisition with deep learning reconstruction, accelerated acquisition with standard reconstruction, and accelerated acquisition with deep learning reconstruction, respectively.

Nanochannels with Varied Outer Surface Charges for Protein Discrimination.

Solid-state nanochannels with probe modification demonstrate effective spontaneous charge modulation and selective ionic current regulation. Outer-surface functionalization of these nanochannels enables tunable ionic current signals before and after analyte detection. To modulate local charge distributions, we designed sensing nanochannels with significant ion rectification properties for protein detection.

Overlooked and underpowered: a meta-research addressing sample size in radiomics prediction models for binary outcomes.

Objectives: To investigate how studies determine the sample size when developing radiomics prediction models for binary outcomes, and whether the sample size meets the estimates obtained by using established criteria.

Methods: We identified radiomics studies that were published from 01 January 2023 to 31 December 2023 in seven leading peer-reviewed radiological journals. We reviewed the sample size justification methods, and actual sample size used.

Node-RADS: a systematic review and meta-analysis of diagnostic performance, category-wise malignancy rates, and inter-observer reliability.

Objective: To perform a systematic review and meta-analysis to estimate diagnostic performance, category-wise malignancy rates, and inter-observer reliability of Node Reporting and Data System 1.0 (Node-RADS).

Methods: Five electronic databases were systematically searched for primary studies on the use of Node-RADS to report the possibility of cancer involvement of lymph nodes on CT and MRI from January 1, 2021, until April 15, 2024.

Mechanically durable plant-based composite surface towards enhanced antifouling properties.

The biofouling adhering to underwater facilities has a negative impact on the environment, energy, and economic development. However, conventional anti-adhesion organic silicon and organic fluorine materials often have poor adhesion properties and mechanical stability when combined with substrates. This work presents a novel strategy for preparing composite antifouling coatings that low surface energy plant-based carnauba wax (CW) covering through rough substrates and chemically bond with flexible polydimethylsiloxane (PDMS) oligomers or polymers.

The policies on the use of large language models in radiological journals are lacking: a meta-research study.

Objective: To evaluate whether and how the radiological journals present their policies on the use of large language models (LLMs), and identify the journal characteristic variables that are associated with the presence.

Methods: In this meta-research study, we screened Journals from the Radiology, Nuclear Medicine and Medical Imaging Category, 2022 Journal Citation Reports, excluding journals in non-English languages and relevant documents unavailable. We assessed their LLM use policies: (1) whether the policy is present; (2) whether the policy for the authors, the reviewers, and the editors is present; and (3) whether the policy asks the author to report the usage of LLMs, the name of LLMs, the section that used LLMs, the role of LLMs, the verification of LLMs, and the potential influence of LLMs.

Deep learning image reconstruction for low-kiloelectron volt virtual monoenergetic images in abdominal dual-energy CT: medium strength provides higher lesion conspicuity.

Background: The best settings of deep learning image reconstruction (DLIR) algorithm for abdominal low-kiloelectron volt (keV) virtual monoenergetic imaging (VMI) have not been determined.

Purpose: To determine the optimal settings of the DLIR algorithm for abdominal low-keV VMI.

Material And Methods: The portal-venous phase computed tomography (CT) scans of 109 participants with 152 lesions were reconstructed into four image series: VMI at 50 keV using adaptive statistical iterative reconstruction (Asir-V) at 50% blending (AV-50); and VMI at 40 keV using AV-50 and DLIR at medium (DLIR-M) and high strength (DLIR-H).

Deep learning image reconstruction generates thinner slice iodine maps with improved image quality to increase diagnostic acceptance and lesion conspicuity: a prospective study on abdominal dual-energy CT.

Background: To assess the improvement of image quality and diagnostic acceptance of thinner slice iodine maps enabled by deep learning image reconstruction (DLIR) in abdominal dual-energy CT (DECT).

Methods: This study prospectively included 104 participants with 136 lesions. Four series of iodine maps were generated based on portal-venous scans of contrast-enhanced abdominal DECT: 5-mm and 1.

Just give the contrast? Appraisal of guidelines on intravenous iodinated contrast media use in patients with kidney disease.

Objective: To appraise the quality of guidelines on intravenous iodinated contrast media (ICM) use in patients with kidney disease, and to compare the recommendations among them.

Methods: We searched four literature databases, eight guideline libraries, and ten homepages of radiological societies to identify English and Chinese guidelines on intravenous ICM use in patients with kidney disease published between January 2018 and June 2023. The quality of the guidelines was assessed with the Scientific, Transparent, and Applicable Rankings (STAR) tool.

Outer-Surface Functionalized Solid-State Nanochannels for Enhanced Sensing Properties: Progress and Perspective.

Solid-state nanochannel-based sensing systems have been established as vigorous tools for sensing plentiful biomarkers due to their label-free, highly sensitive, and high-throughput screening. However, research on solid-state nanochannels has predominantly centered on the functional groups modified on the inner wall, neglecting investigations into the outer surface. Actually, the outer surface, as a part of the nanochannels, also plays a key role in regulating ionic current.

Bioinformatics and Experimental Study Revealed LINC00982/ miR-183-5p/ABCA8 Axis Suppresses LUAD Progression.

Background: Lung adenocarcinoma (LUAD) is a major health challenge worldwide with an undesirable prognosis. LINC00982 has been implicated as a tumor suppressor in diverse human cancers; however, its role in LUAD has not been fully characterized.

Methods: Expression level and prognostic value of LINC00982 were investigated in pan-cancer and lung cancer from The Cancer Genome Atlas (TCGA) project.

Robustness of Quantitative Diffusion Metrics from Four Models: A Prospective Study on the Influence of Scan-Rescans, Voxel Size, Coils, and Observers.

Background: Quantitative diffusion metrics provide additional microstructural information of diseases. The robustness of quantitative diffusion metrics should be established before clinical application.

Purpose: To evaluate the variability and reproducibility of quantitative diffusion MRI metrics.

The endorsement of general and artificial intelligence reporting guidelines in radiological journals: a meta-research study.

Background: Complete reporting is essential for clinical research. However, the endorsement of reporting guidelines in radiological journals is still unclear. Further, as a field extensively utilizing artificial intelligence (AI), the adoption of both general and AI reporting guidelines would be necessary for enhancing quality and transparency of radiological research.

An overview of meta-analyses on radiomics: more evidence is needed to support clinical translation.

Objective: To conduct an overview of meta-analyses of radiomics studies assessing their study quality and evidence level.

Methods: A systematical search was updated via peer-reviewed electronic databases, preprint servers, and systematic review protocol registers until 15 November 2022. Systematic reviews with meta-analysis of primary radiomics studies were included.

A systematic review of radiomics in giant cell tumor of bone (GCTB): the potential of analysis on individual radiomics feature for identifying genuine promising imaging biomarkers.

Purpose: To systematically assess the quality of radiomics research in giant cell tumor of bone (GCTB) and to test the feasibility of analysis at the level of radiomics feature.

Methods: We searched PubMed, Embase, Web of Science, China National Knowledge Infrastructure, and Wanfang Data to identify articles of GCTB radiomics until 31 July 2022. The studies were assessed by radiomics quality score (RQS), transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) statement, checklist for artificial intelligence in medical imaging (CLAIM), and modified quality assessment of diagnostic accuracy studies (QUADAS-2) tool.

Evaluation of Image Quality and Detectability of Deep Learning Image Reconstruction (DLIR) Algorithm in Single- and Dual-energy CT.

This study is aimed to evaluate effects of deep learning image reconstruction (DLIR) on image quality in single-energy CT (SECT) and dual-energy CT (DECT), in reference to adaptive statistical iterative reconstruction-V (ASIR-V). The Gammex 464 phantom was scanned in SECT and DECT modes at three dose levels (5, 10, and 20 mGy). Raw data were reconstructed using six algorithms: filtered back-projection (FBP), ASIR-V at 40% (AV-40) and 100% (AV-100) strength, and DLIR at low (DLIR-L), medium (DLIR-M), and high strength (DLIR-H), to generate SECT 120kVp images and DECT 120kVp-like images.

Improving lesion conspicuity in abdominal dual-energy CT with deep learning image reconstruction: a prospective study with five readers.

Objectives: To evaluate image quality, diagnostic acceptability, and lesion conspicuity in abdominal dual-energy CT (DECT) using deep learning image reconstruction (DLIR) compared to those using adaptive statistical iterative reconstruction-V (Asir-V) at 50% blending (AV-50), and to identify potential factors impacting lesion conspicuity.

Methods: The portal-venous phase scans in abdominal DECT of 47 participants with 84 lesions were prospectively included. The raw data were reconstructed to virtual monoenergetic image (VMI) at 50 keV using filtered back-projection (FBP), AV-50, and DLIR at low (DLIR-L), medium (DLIR-M), and high strength (DLIR-H).

A systematic review of radiomics in chondrosarcoma: assessment of study quality and clinical value needs handy tools.

Objective: To evaluate the study quality and clinical value of radiomics studies on chondrosarcoma.

Methods: PubMed, Embase, Web of Science, China National Knowledge Infrastructure, and Wanfang Data were searched for articles on radiomics for evaluating chondrosarcoma as of January 31, 2022. The study quality was assessed according to Radiomics Quality Score (RQS), Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) checklist, Image Biomarker Standardization Initiative (IBSI) guideline, and modified Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool.

An updated systematic review of radiomics in osteosarcoma: utilizing CLAIM to adapt the increasing trend of deep learning application in radiomics.

Objective: To update the systematic review of radiomics in osteosarcoma.

Methods: PubMed, Embase, Web of Science, China National Knowledge Infrastructure, and Wanfang Data were searched to identify articles on osteosarcoma radiomics until May 15, 2022. The studies were assessed by Radiomics Quality Score (RQS), Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement, Checklist for Artificial Intelligence in Medical Imaging (CLAIM), and modified Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool.

A systematic review of radiomics in pancreatitis: applying the evidence level rating tool for promoting clinical transferability.

Background: Multiple tools have been applied to radiomics evaluation, while evidence rating tools for this field are still lacking. This study aims to assess the quality of pancreatitis radiomics research and test the feasibility of the evidence level rating tool.

Results: Thirty studies were included after a systematic search of pancreatitis radiomics studies until February 28, 2022, via five databases.