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. The association between the presence of policies and journal characteristic variables was evaluated. RESULTS: The LLM use policies were presented in 43.9% (83/189) of journals, and those for the authors, the reviewers, and the editor were presented in 43.4% (82/189), 29.6% (56/189) and 25.9% (49/189) of journals, respectively. Many journals mentioned the aspects of the usage (43.4%, 82/189), the name (34.9%, 66/189), the verification (33.3%, 63/189), and the role (31.7%, 60/189) of LLMs, while the potential influence of LLMs (4.2%, 8/189), and the section that used LLMs (1.6%, 3/189) were seldomly touched. The publisher is related to the presence of LLM use policies (p < 0.001). CONCLUSION: The presence of LLM use policies is suboptimal in radiological journals. A reporting guideline is encouraged to facilitate reporting quality and transparency. CRITICAL RELEVANCE STATEMENT: It may facilitate the quality and transparency of the use of LLMs in scientific writing if a shared complete reporting guideline is developed by stakeholders and then endorsed by journals. KEY POINTS: The policies on LLM use in radiological journals are unexplored. Some of the radiological journals presented policies on LLM use. A shared complete reporting guideline for LLM use is desired.

Semi-rational engineering of D-allulose 3-epimerase for simultaneously improving the catalytic activity and thermostability based on D-allulose biosensor.

BACKGROUND: D-Allulose is one of the most well-known rare sugars widely used in food, cosmetics, and pharmaceutical industries. The most popular method for D-allulose production is the conversion from D-fructose catalyzed by D-allulose 3-epimerase (DAEase). To address the general problem of low catalytic efficiency and poor thermostability of wild-type DAEase, D-allulose biosensor was adopted in this study to develop a convenient and efficient method for high-throughput screening of DAEase variants. RESULTS: The catalytic activity and thermostability of DAEase from Caballeronia insecticola were simultaneously improved by semi-rational molecular modification. Compared with the wild-type enzyme, DAEaseS37N/F157Y variant exhibited 14.7% improvement in the catalytic activity and the half-time value (t1/2) at 65°C increased from 1.60 to 27.56 h by 17.23-fold. To our delight, the conversion rate of D-allulose was 33.6% from 500-g L-1 D-fructose in 1 h by Bacillus subtilis WB800 whole cells expressing this DAEase variant. Furthermore, the practicability of cell immobilization was evaluated and more than 80% relative activity of the immobilized cells was maintained from the second to seventh cycle. CONCLUSION: All these results indicated that the DAEaseS37N/F157Y variant would be a potential candidate for the industrial production of D-allulose.

Low-dose Ultra-high-resolution Photon-Counting Detector CT for Visceral Artery CT Angiography: A Preliminary Study.

RATIONALE AND OBJECTIVES: To validate the image quality of low-dose ultra-high-resolution (UHR) scanning mode of photon-counting detector CT (PCD-CT) for visceral artery computed tomography angiography (CTA). MATERIAL AND METHODS: We prospectively enrolled 57 patients each in the full dose (FD) and low-dose (LD) protocols, respectively, to undergo abdominal CT scans using the UHR mode on a PCD-CT system (NAEOTOM Alpha), between April 2023 and September 2023. Both the FD data and LD data were then reconstructed into two series of images: (a) 0.2 mm slice thickness, reconstruction kernel Bv48, quantum iterative reconstruction (QIR) 4; (b)1 mm slice thickness, Bv40, QIR 3. The signal-to-noise ratios (SNRs) and contrast-to-noise ratios (CNRs) of seven arteries were objectively measured. The image noise, vessel sharpness, overall quality, and visibility of nine arteries were subjectively assessed by three radiologists. RESULTS: The SNRs and CNRs of 0.2 mm reconstruction set was inferior to that of 1 mm reconstruction set (p < 0.001 for all the arteries and noise), however, the image quality of 0.2 mm reconstruction set was higher than that of 1 mm reconstruction set in qualitative evaluation especially for tiny arteries in Volume-rendered (VR) image (p < 0.001). The SNRs and CNRs were not significantly higher for FD group than LD group on the same slice thickness except for SNRs of common hepatic artery, splenic artery and bilateral renal arteries in 0.2 mm reconstruction set. In the comparison on image quality between normal weight and overweight patients within the same reconstruction set, the results showed that low-dose scan did not significantly impact the image quality in overweight patients. The ratings of visibility of nine visceral arteries were not significantly different among FD and LD at the same thickness reconstruction set except for superior mesenteric artery (p = 0.002 and 0.007 for 0.2 mm and 1 mm reconstruction set in axial image; p = 0.002 and 0.007 for 0.2 mm and 1 mm reconstruction set in coronal image, respectively) and left gastric artery (p = 0.002 and p < 0.001 for 0.2 mm and 1 mm reconstruction set in VR image, respectively). CONCLUSION: The low-dose UHR scanning mode of PCD-CT has proven to be adequate for the clinical evaluation of visceral arteries. Utilizing a reconstruction with a slice thickness of 0.2 mm could enhance arterial depiction, particularly for small vessels.

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). The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of nine anatomical sites were calculated. Noise power spectrum (NPS) using homogenous region of liver, and edge rise slope (ERS) at five edges were measured. Five radiologists rated image quality and diagnostic acceptability, and evaluated the lesion conspicuity. RESULTS: The SNR and CNR values, and noise and noise peak in NPS measurements, were significantly lower in DLIR images than AV-50 images in all anatomical sites (all P < 0.001). The ERS values were significantly higher in 40-keV images than 50-keV images at all edges (all P < 0.001). The differences of the peak and average spatial frequency among the four reconstruction algorithms were significant but relatively small. The 40-keV images were rated higher with DLIR-M than DLIR-H for diagnostic acceptance (P < 0.001) and lesion conspicuity (P = 0.010). CONCLUSION: DLIR provides lower noise, higher sharpness, and more natural texture to allow 40 keV to be a new standard for routine VMI reconstruction for the abdomen and DLIR-M gains higher diagnostic acceptance and lesion conspicuity rating than DLIR-H.

Robustness of radiomics among photon-counting detector CT and dual-energy CT systems: a texture phantom study.

OBJECTIVES: To evaluate the robustness of radiomics features among photon-counting detector CT (PCD-CT) and dual-energy CT (DECT) systems. METHODS: A texture phantom consisting of twenty-eight materials was scanned with one PCD-CT and four DECT systems (dual-source, rapid kV-switching, dual-layer, and sequential scanning) at three dose levels twice. Thirty sets of virtual monochromatic images at 70 keV were reconstructed. Regions of interest were delineated for each material with a rigid registration. Ninety-three radiomics were extracted per PyRadiomics. The test-retest repeatability between repeated scans was assessed by Bland-Altman analysis. The intra-system reproducibility between dose levels, and inter-system reproducibility within the same dose level, were evaluated by intraclass correlation coefficient (ICC) and concordance correlation coefficient (CCC). Inter-system variability among five scanners was assessed by coefficient of variation (CV) and quartile coefficient of dispersion (QCD). RESULTS: The test-retest repeatability analysis presented that 97.1% of features were repeatable between scan-rescans. The mean ± standard deviation ICC and CCC were 0.945 ± 0.079 and 0.945 ± 0.079 for intra-system reproducibility, respectively, and 86.0% and 85.7% of features were with ICC > 0.90 and CCC > 0.90, respectively, between different dose levels. The mean ± standard deviation ICC and CCC were 0.157 ± 0.174 and 0.157 ± 0.174 for inter-system reproducibility, respectively, and none of the features were with ICC > 0.90 or CCC > 0.90 within the same dose level. The inter-system variability suggested that 6.5% and 12.8% of features were with CV < 10% and QCD < 10%, respectively, among five CT systems. CONCLUSION: The radiomics features were non-reproducible with significant variability in values among different CT techniques. CLINICAL RELEVANCE STATEMENT: Radiomics features are non-reproducible with significant variability in values among photon-counting detector CT and dual-energy CT systems, necessitating careful attention to improve the cross-system generalizability of radiomic features before implementation of radiomics analysis in clinical routine. KEY POINTS: CT radiomics stability should be guaranteed before the implementation in the clinical routine. Radiomics robustness was on a low level among photon-counting detectors and dual-energy CT techniques. Limited inter-system robustness of radiomic features may impact the generalizability of models.

Complete genome sequence of Rhodococcus sp. strain PD04, a pyridine-degrading bacterium under hypersaline condition.

We report the complete genome sequence of a pyridine-degrading Rhodococcus sp. strain PD04 under 4% salinity environment, isolated from wastewater of coking plant. The genome is 6.07 Mb with 5,767 annotated gene coding sequences.

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 1.25-mm using adaptive statistical iterative reconstruction-V (Asir-V) with 50% blending (AV-50), and 1.25-mm using DLIR with medium (DLIR-M), and high strength (DLIR-H). The iodine concentrations (IC) and their standard deviations of nine anatomical sites were measured, and the corresponding coefficient of variations (CV) were calculated. Noise-power-spectrum (NPS) and edge-rise-slope (ERS) were measured. Five radiologists rated image quality in terms of image noise, contrast, sharpness, texture, and small structure visibility, and evaluated overall diagnostic acceptability of images and lesion conspicuity. RESULTS: The four reconstructions maintained the IC values unchanged in nine anatomical sites (all p > 0.999). Compared to 1.25-mm AV-50, 1.25-mm DLIR-M and DLIR-H significantly reduced CV values (all p < 0.001) and presented lower noise and noise peak (both p < 0.001). Compared to 5-mm AV-50, 1.25-mm images had higher ERS (all p < 0.001). The difference of the peak and average spatial frequency among the four reconstructions was relatively small but statistically significant (both p < 0.001). The 1.25-mm DLIR-M images were rated higher than the 5-mm and 1.25-mm AV-50 images for diagnostic acceptability and lesion conspicuity (all P < 0.001). CONCLUSIONS: DLIR may facilitate the thinner slice thickness iodine maps in abdominal DECT for improvement of image quality, diagnostic acceptability, and lesion conspicuity.

Factors associated with family decision-making self-efficacy among family members of patients with advanced cancer in mainland China.

OBJECTIVES: In Chinese culture, family members are the main decision maker on end-of-life (EoL) issues for patients with advanced cancer. Yet little is known about Chinese families' confidence in making EoL decisions and its associated factors. This study aims to investigate the status and associated factors of Chinese family members' confidence in making EoL decisions for patients with advanced cancer. METHODS: This cross-sectional study used a convenience sample of 147 family members of patients with stage III or stage IV cancer from a tertiary cancer center in Guangzhou, China. The questionnaires included demographic information of patients and their family members, patients' EoL preferences, and the Chinese version of the Family Decision-Making Self-Efficacy (FDMSE) Scale. RESULTS: A total of145 family members (98.64%) completed the questionnaires. The average score of FDMSE was 3.92 ± 0.53. A multiple regression analysis showed that the factors associated with FDMSE included patients' duration of disease, health insurance, participation in EoL decision-making, the expression of unfilled wishes, and family members' employment status. SIGNIFICANCE OF RESULTS: Chinese family members were not confident enough in making EoL decisions for patients with advanced cancer. It is recommended to develop cultural-tailored advanced care planning models to clarify patient preferences and to enhance the family members' self-efficacy in making EoL decisions with or for patients with advanced cancer.

Discovery, optimization and biological activity evaluation of genipin derivatives as potential KRAS G12D inhibitors.

A series of genipin derivatives were designed and synthesized as potential inhibitors targeted KRAS G12D mutation. The majority of these compounds demonstrated potential antiproliferative effects against KRAS G12D mutant tumor cells (CT26 and A427). Notably, seven compounds exhibited the anticancer effects with IC50 values ranging from 7.06 to 9.21 µM in CT26 (KRASG12D) and A427 (KRASG12D) cells and effectively suppressed the colony formation of CT26 cells. One representative compound SK12 was selected for further investigation into biological activity and action mechanisms. SK12 markedly induced apoptosis in CT26 cells in a concentration-dependent manner. Moreover, SK12 elevated the levels of reactive oxygen species (ROS) in tumor cells and exhibited a modulatory effect on the KRAS signaling pathway, thereby inhibiting the activation of downstream phosphorylated proteins. The binding affinity of SK12 to KRAS G12D protein was further confirmed by the surface plasmon resonance (SPR) assay with a binding KD of 157 µM. SK12 also exhibited notable anticancer efficacy in a nude mice tumor model. The relative tumor proliferation rate (T/C) of the experimental group (50 mg/kg) was 31.04 % (P < 0.05), while maintaining a commendable safety profile.

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. RESULTS: Ten guidelines were included, with a median STAR score of 46.0 (range 28.5-61.5). The guidelines performed well in "Recommendations" domain (31/40, 78%), while poor in "Registry" (0/20, 0%) and "Protocol" domains (0/20, 0%). Nine guidelines recommended estimated glomerular filtration rate (eGFR) < 30 mL/min/1.73 m2 as the cutoff for referring patients to discuss the risk-benefit balance of ICM administration. Three guidelines further suggested that patients with an eGFR < 45 mL/min/1.73 m2 and high-risk factors also need referring. Variable recommendations were seen in the acceptable time interval between renal function test and ICM administration, and that between scan and repeated scan. Nine guidelines recommended to use iso-osmolar or low-osmolar ICM, while no consensus has been reached for the dosing of ICM. Nine guidelines supported hydration after ICM use, but their protocols varied. Drugs or blood purification therapy were not recommended as preventative means. CONCLUSION: Guidelines on intravenous ICM use in patients with kidney disease have heterogeneous quality. The scientific societies may consider joint statements on controversial recommendations for variable timing and protocols. CRITICAL RELEVANCE STATEMENT: The heterogeneous quality of guidelines, and their controversial recommendations, leave gaps in workflow timing, dosing, and post-administration hydration protocols of contrast-enhanced CT scans for patients with kidney diseases, calling for more evidence to establish a safer and more practicable workflow. KEY POINTS: • Guidelines concerning iodinated contrast media use in kidney disease patients vary. • Controversy remains in workflow timing, contrast dosing, and post-administration hydration protocols. • Investigations are encouraged to establish a safer iodinated contrast media use workflow.

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. Differential expression analysis based on the LINC00982 expression level was performed in LUAD followed by gene set enrichment analysis (GSEA) and functional enrichment analyses. The association between LINC00982 expression and tumor immune microenvironment characteristics was evaluated. A potential ceRNA regulatory axis was identified and experimentally validated. RESULTS: We found that LINC00982 expression was downregulated and correlated with poor prognosis in LUAD. Enrichment analyses revealed that LINC00982 could inhibit DNA damage repair and cell proliferation, but enhance tumor metabolic reprogramming. We identified a competing endogenous RNA network involving LINC00982, miR-183-5p, and ATP-binding cassette subfamily A member 8 (ABCA8). Luciferase assays confirmed that miR-183-5p can interact with LINC00982 and ABCA8. Forced miR-183-5p expression reduced LINC00982 transcript levels and suppressed ABCA8 expression. CONCLUSIONS: Our findings revealed the LINC00982/miR-183-5p/ABCA8 axis as a potential therapeutic target in LUAD.

Synthesis, biological activity evaluation and mechanism analysis of new ganglioside GM3 derivatives as potential agents for nervous functional recovery.

Neuronal regenerative ability is vital for the treatment of neurodegenerative diseases and neuronal injuries. Recent studies have revealed that Ganglioside GM3 and its derivatives may possess potential neuroprotective and neurite growth-promoting activities. Herein, six GM3 derivatives were synthesized and evaluated their potential neuroprotective effects and neurite outgrowth-promoting activities on a cellular model of Parkinson's disease and primary nerve cells. Amongst these derivatives, derivatives N-14 and 2C-12 demonstrated neuroprotective effects in the MPP + model in SH-SY5Y cells. 2C-12 combined with NGF (nerve growth factor) induced effecially neurite growth in primary nerve cells. Further action mechanism revealed that derivative 2C-12 exerts neuroprotective effects by regulating the Wnt signaling pathway, specifically involving the Wnt7b gene. Overall, this study establishes a foundation for further exploration and development of GM3 derivatives with neurotherapeutic potential.

Design and optimization of ε-poly-l-lysine with specific functions for diverse applications.

ε-Poly-l-lysine (ε-PL) is a natural homo-poly(amino acid) which can be produced by microorganisms. With the advantages in broad-spectrum antimicrobial activity, biodegradability, and biocompatibility, ε-PL has been widely used as a preservative in the food industry. Different molecular architectures endow ε-PL and ε-PL-based materials with versatile applications. However, the microbial synthesis of ε-PL is currently limited by low efficiencies in genetic engineering and molecular architecture modification. This review presents recent advances in ε-PL production and molecular architecture modification of microbial ε-PL, with a focus on the current challenges and solutions for the improvement of the productivity and diversity of ε-PL. In addition, we highlight recent examples where ε-PL has been applied to expand the versability of edible films and nanoparticles in various applications. Commercial production and the challenges and future research directions in ε-PL biosynthesis are also discussed. Currently, although the main use of ε-PL is as a food preservative, ε-PL and ε-PL-based polymers have shown excellent application potential in biomedical fields. With the development of synthetic biology, the design and synthesis of ε-PL with a customized molecular architecture are possible in the near future. ε-PL-based polymers with specific functions will be a new trend in biopolymer manufacturing.

Safety assessment, whole genome sequence, and metabolome analysis of Streptococcus thermophilus CICC 20372 for bone cement fermentation.

Bone is a kind of meat processing by-product with high nutritional value but low in calorie, which is a typical food in China and parts of East Asian countries. Microbial fermentation by lactic acid bacteria showed remarkable advantages to increase the absorption of nutrients from bone cement by human body. Streptococcus thermophilus CICC 20372 is proven to be a good starter for bone cement fermentation. No genes encoding virulence traits or virulence factors were found in the genome of S. thermophilus CICC 20372 by a thorough genomic analysis. Its notable absence of antibiotic resistance further solidifies the safety. Furthermore, the genomic analysis identified four types of gene clusters responsible for the synthesis of antimicrobial metabolites. A comparative metabolomic analysis was performed by cultivating the strain in bone cement at 37 °C for 72 h, with the culture in de Man, Rogosa, and Sharpe (MRS) medium as control. Metabolome analysis results highlighted the upregulation of pathways involved in 2-oxocarboxylic acid metabolism, ATP-binding cassette (ABC) transporters, amino acid synthesis, and nucleotide metabolism during bone cement fermentation. S. thermophilus CICC 20372 produces several metabolites with health-promoting function during bone cement fermentation, including indole-3-lactic acid, which is demonstrated ameliorative effects on intestinal inflammation, tumor growth, and gut dysbiosis. In addition, lots of nucleotide and organic acids were accumulated at higher levels, which enriched the fermented bone cement with a variety of nutrients. Collectively, these features endow S. thermophilus CICC 20372 a great potential strain for bone food processing.

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. This study aims to investigate the endorsement of general reporting guidelines and those for AI applications in medical imaging in radiological journals, and explore associated journal characteristic variables. METHODS: This meta-research study screened journals from the Radiology, Nuclear Medicine & Medical Imaging category, Science Citation Index Expanded of the 2022 Journal Citation Reports, and excluded journals not publishing original research, in non-English languages, and instructions for authors unavailable. The endorsement of fifteen general reporting guidelines and ten AI reporting guidelines was rated using a five-level tool: "active strong", "active weak", "passive moderate", "passive weak", and "none". The association between endorsement and journal characteristic variables was evaluated by logistic regression analysis. RESULTS: We included 117 journals. The top-five endorsed reporting guidelines were CONSORT (Consolidated Standards of Reporting Trials, 58.1%, 68/117), PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses, 54.7%, 64/117), STROBE (STrengthening the Reporting of Observational Studies in Epidemiology, 51.3%, 60/117), STARD (Standards for Reporting of Diagnostic Accuracy, 50.4%, 59/117), and ARRIVE (Animal Research Reporting of In Vivo Experiments, 35.9%, 42/117). The most implemented AI reporting guideline was CLAIM (Checklist for Artificial Intelligence in Medical Imaging, 1.7%, 2/117), while other nine AI reporting guidelines were not mentioned. The Journal Impact Factor quartile and publisher were associated with endorsement of reporting guidelines in radiological journals. CONCLUSIONS: The general reporting guideline endorsement was suboptimal in radiological journals. The implementation of reporting guidelines for AI applications in medical imaging was extremely low. Their adoption should be strengthened to facilitate quality and transparency of radiological study reporting.

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. STUDY TYPE: Prospective. POPULATION: 14 volunteers (7 men; median age, range, 28, 26-59 years). FIELD STRENGTH/SEQUENCE: 3.0-T/Diffusion spectrum imaging. ASSESSMENT: Brain MRI studies were performed four times per subject: involving different combinations of coil types and voxel sizes. Regions of interest of 13 brain anatomical sites were drawn by one observer twice and another observer once to allow interobserver and intraobserver reproducibility assessment. Twenty-five quantitative metrics were calculated using four diffusion models. STATISTICAL TESTS: The variability was evaluated with coefficients of variation (CV), and quartile coefficient of dispersion (QCD). The reproducibility was assessed with intraclass correlation coefficient (ICC), and concordance correlation coefficient (CCC). Wilcoxon signed rank test was used to compare the influence of factors on robustness of quantitative diffusion metrics. A two-tailed P < 0.05 was considered statistically significant. RESULTS: The variability of quantitative diffusion metrics showed CV of 2.4%-68.2%, and QCD of 0.6%-48.2%, respectively. The reproducibility of scans using 20-channel coils with voxels of 2 × 2 × 2 mm3 and 3 × 3 × 3 mm3 , respectively (ICC 0.03-0.84, CCC 0.03-0.84) was significantly worse than that of repeated scans using a 20-channel coil with a voxel size of 2 × 2 × 2 mm3 (ICC of 0.74-0.97, CCC 0.74-0.97) and that of scans using 20- and 64-channel coils, respectively, with a voxel size of 2 × 2 × 2 mm3 (ICC 0.59-0.95, CCC 0.59-0.95). The intraobserver reproducibility (ICC 0.49-0.94, CCC 0.49-0.94) was significantly better than the interobserver reproducibility (ICC 0.28-0.91, CCC 0.28-0.91). DATA CONCLUSION: Our study indicated that the voxel size has a greater influence on the reproducibility of quantitative diffusion metrics than scan-rescans and coils. The reproducibility within one observer was higher than that between two observers. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 1.

Fast-SNN: Fast Spiking Neural Network by Converting Quantized ANN.

Spiking neural networks (SNNs) have shown advantages in computation and energy efficiency over traditional artificial neural networks (ANNs) thanks to their event-driven representations. SNNs also replace weight multiplications in ANNs with additions, which are more energy-efficient and less computationally intensive. However, it remains a challenge to train deep SNNs due to the discrete spiking function. A popular approach to circumvent this challenge is ANN-to-SNN conversion. However, due to the quantization error and accumulating error, it often requires lots of time steps (high inference latency) to achieve high performance, which negates SNN's advantages. To this end, this paper proposes Fast-SNN that achieves high performance with low latency. We demonstrate the equivalent mapping between temporal quantization in SNNs and spatial quantization in ANNs, based on which the minimization of the quantization error is transferred to quantized ANN training. With the minimization of the quantization error, we show that the sequential error is the primary cause of the accumulating error, which is addressed by introducing a signed IF neuron model and a layer-wise fine-tuning mechanism. Our method achieves state-of-the-art performance and low latency on various computer vision tasks, including image classification, object detection, and semantic segmentation. Codes are available at: https://github.com/yangfan-hu/Fast-SNN.

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. The radiomic features selected for model development were documented. RESULTS: Nine articles were included. The average of the ideal percentage of RQS, the TRIPOD adherence rate and the CLAIM adherence rate were 26%, 56%, and 57%, respectively. The risk of bias and applicability concerns were mainly related to the index test. The shortness in external validation and open science were repeatedly emphasized. In GCTB radiomics models, the gray level co-occurrence matrix features (40%), first order features (28%), and gray-level run-length matrix features (18%) were most selected features out of all reported features. However, none of the individual feature has appeared repeatably in multiple studies. It is not possible to meta-analyze radiomics features at present. CONCLUSION: The quality of GCTB radiomics studies is suboptimal. The reporting of individual radiomics feature data is encouraged. The analysis at the level of radiomics feature has potential to generate more practicable evidence for translating radiomics into clinical application.

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. Their reporting transparency, methodological quality, and risk of bias were assessed by PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) 2020 checklist, AMSTAR-2 (A MeaSurement Tool to Assess systematic Reviews, version 2) tool, and ROBIS (Risk Of Bias In Systematic reviews) tool, respectively. The evidence level supporting the radiomics for clinical use was rated. RESULTS: We identified 44 systematic reviews with meta-analyses on radiomics research. The mean ± standard deviation of PRISMA adherence rate was 65 ± 9%. The AMSTAR-2 tool rated 5 and 39 systematic reviews as low and critically low confidence, respectively. The ROBIS assessment resulted low, unclear and high risk in 5, 11, and 28 systematic reviews, respectively. We reperformed 53 meta-analyses in 38 included systematic reviews. There were 3, 7, and 43 meta-analyses rated as convincing, highly suggestive, and weak levels of evidence, respectively. The convincing level of evidence was rated in (1) T2-FLAIR radiomics for IDH-mutant vs IDH-wide type differentiation in low-grade glioma, (2) CT radiomics for COVID-19 vs other viral pneumonia differentiation, and (3) MRI radiomics for high-grade glioma vs brain metastasis differentiation. CONCLUSIONS: The systematic reviews on radiomics were with suboptimal quality. A limited number of radiomics approaches were supported by convincing level of evidence. CLINICAL RELEVANCE STATEMENT: The evidence supporting the clinical application of radiomics are insufficient, calling for researches translating radiomics from an academic tool to a practicable adjunct towards clinical deployment.