Herein, the effect of the Ru:Ni bimetallic composition in dual-function materials (DFMs) for the integrated CO2 capture and methanation process (ICCU-Methanation) is systematically evaluated and combined with a thorough material characterization, as well as a mechanistic (in-situ diffuse reflectance infrared fourier-transform spectroscopy (in-situ DRIFTS)) and computational (computational fluid dynamics (CFD) modelling) investigation, in order to improve the performance of Ni-based DFMs. The bimetallic DFMs are comprised of a main Ni active metallic phase (20 wt%) and are modified with low Ru loadings in the 0.1–1 wt% range (to keep the material cost low), supported on Na2O/Al2O3. It is shown that the addition of even a very low Ru loading (0.1–0.2 wt%) can drastically improve the material reducibility, exposing a significantly higher amount of surface-active metallic sites, with Ru being highly dispersed over the support and the Ni phase, while also forming some small Ru particles. This manifests in a significant enhancement in the CH4 yield and the CH4 production kinetics during ICCU-Methanation (which mainly proceeds via formate intermediates), with 0.2 wt% Ru addition leading to the best results. This bimetallic DFM also shows high stability and a relatively good performance under an oxidizing CO2 capture atmosphere. The formation rate of CH4 during hydrogenation is then further validated via CFD modelling and the developed model is subsequently applied in the prediction of the effect of other parameters, including the inlet H2 concentration, inlet flow rate, dual-function material weight, and reactor internal diameter.@en

Background
To improve lifestyle guidance within cardiac rehabilitation (CR), a comprehensive understanding of the motivation and lifestyle-supporting needs of patients with cardiovascular disease (CVD) is required.

Objectives
This study's purpose is to evaluate patients’ lifestyle and their motivation, self-efficacy and social support for change when starting CR.

Methods
1782 CVD patients (69 % male, mean age 62 years) from 7 Dutch outpatient CR centers participated between 2020 and 2022. Modifiable risk factors were assessed with a survey and interviews by healthcare professionals during CR intake.

Results
Most patients exhibited an elevated risk in 3–4 domains. Elevated risks were most prominent in domains of (1) waist circumference and BMI (2) physical exercise (3) healthy foods intake and (4) sleep duration. Most patients chose to focus on increasing physical exercise, but about 20 % also wanted to focus on a healthy diet and/or decrease stress levels. Generally, motivation, self-efficacy and social support to reach new lifestyle goals were high. However, patients with an unfavorable risk profile had lower motivation and self-efficacy to work on lifestyle changes, while patients with lower social support had a higher chance to quit the program prematurely.

Conclusions
Our results underscore the need to begin CR with a comprehensive lifestyle assessment and highlight the importance of offering lifestyle interventions tailored to patients’ specific modifiable risk factors and lifestyle-supporting needs, targeting multiple lifestyle domains. Expanding the current scope of CR programs to address diverse patient needs and strengthening support may enhance motivation and adherence and lead to significant long-term benefits for cardiovascular health.@en

The development of soft electronic devices capable of autonomous self-healing (SH) holds immense potential across various endeavours, promising to revolutionize product durability, reliability, and maintenance practices. Despite some progress has been made, underwater stable SH continues to be an active area of research. Herein, SH polymer PDMS-MDI0.4-TFB0.6 (SHP) with excellent mechanical property was composited with MXene to investigate the piezoelectric nature under various circumstance. By leveraging MXene into SHP not only improves the material properties of mechanical stress but also permittivity of the elastomer. Thus, MXene incorporated SHP (mSHP) induce high polarized charges under mechanical pressure. The fabrication of mSHP piezoelectric nanogenerator (mSHP-PENG) device via spray coating AgNWs on the surface forms ohmic contact, which facilitate high sensitivity and flexibility. Nevertheless, the generated piezoelectricity (30 V, 4.2 μA: 3 Hz) upon mechanical pressure gives maximum power density of 128 μW/m2 indicating that our device can act as a reliable power source for portable electronic gadgets. In addition, SHP with amphiphilic functional groups sustain the original shape even after immerse into water for so long. Taking this into account, our device undergoes effective deformation even at low pressures, thus render to fabricate touch sensitive piezo-switches for both atmospheric and aquatics environments.@en

In this article Reference 10 was incorrect as ‘van der Zwanenburg LC, Koldenhof JJ, Suijkerbuijk KPM, Schellekens MPJ (2024) What patients with advanced cancer experience as helpful in navigating their life with a long-term response: a qualitative study. Support Care Cancer 32(4):222’ and should have been ‘Zwanenburg LC, van der Lee ML, Koldenhof JJ, Suijkerbuijk KPM, Schellekens MPJ (2024) What patients with advanced cancer experience as helpful in navigating their life with a long-term response: a qualitative study. Support Care Cancer. 32(4):222. PMID: 38470541.’@en

Organic Rankine cycle (ORC) systems are a class of distributed power-generation systems that are suitable for the efficient conversion of low-to-medium temperature thermal energy to useful power. These versatile systems have significant potential to contribute in diverse ways to future clean and sustainable energy systems through, e.g., deployment for waste-heat recovery in industrial facilities, but also the utilisation of renewable-heat sources, thereby improving energy access and living standards, while reducing primary energy consumption and the associated emissions. The energetic and economic performance, but also environmental sustainability of ORC systems, all depend strongly on the working fluid employed, and therefore a significant effort has been made in recent years to select, but also to design novel working fluids for ORC systems. In this context, computer-aided molecular design (CAMD) techniques have emerged as highly promising approaches with which to explore the key role of working fluids, and present an opportunity, by focusing on the design of new eco-friendly fluids with low environmental footprints, to identify alternatives to traditional refrigerants with improved characteristics. In this review article, an overview of working-fluid and system optimisation methodologies that can be used for the design and operation of next-generation ORC systems is provided. With reference to wide-ranging applications from waste-heat recovery in industrial and automotive applications, to biomass, geothermal and solar-energy conversion and/or storage, this review represents a comprehensive, forward-looking exposition of the application of CAMD to the design of ORC technology.

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In the collaborative effort towards standardisation of out-of-plane permeability measurement, an international benchmarking exercise was carried out whereby 19 participants worldwide were instructed to measure the out-of-plane permeability following a number of strict guidelines, informed by the outcomes of the first international benchmarking exercise completed in 2021. This paper presents the results of the exercise and an assessment of the reproducibility of the data and the suitability of the proposed test method. The data returned were subjected to a number of statistical analysis methods, which showed that adherence to the test guidelines resulted in a high likelihood of a participant not being an outlier and therefore providing evidence that the test method proposed in this paper is a suitable way forward for a standardised test method.@en

Introduction
The field of forensic DNA analysis has undergone rapid advancements in recent decades. The integration of massively parallel sequencing (MPS) has notably expanded the forensic toolkit, moving beyond identity matching to predicting phenotypic traits and biogeographical ancestry. This shift is of particular significance in cases where conventional DNA profiling fails to identify a single suspect. Supplementing forensic analyses with estimated biological age may be valuable but involves a complex and time-consuming DNA methylation analysis. This study explores and validates the performance of a comprehensive forensic third-generation sequencing assay utilizing Oxford Nanopore Technologies (ONT) in an adaptive and direct sequencing approach. We incorporated the most widely used forensic markers, i.e., STRs, SNPs, InDels, mitochondrial DNA (mtDNA), and two methylation-based clock classifiers, thereby combining forensic genetic and epigenetic analysis in one single workflow.

Methods and results
In our investigation, DNA from six anonymous individuals was sequenced using the ONT standard adaptive direct sequencing approach, reaching a mean percentage of on-target reads ranging from 6.6 % to 7.7 % per sample. ONT data was compared to standard MPS data and Illumina EPIC DNA methylation profiles. Basecalling employed recommended ONT software packages. TREAT was used for ONT-based analysis of autosomal and Y-chromosome STRs, achieving 90–92 % correct calls depending on allelic read depth thresholds. InDel analyses for two lower-quality samples proved challenging due to inadequate read depth, while the remaining four samples significantly contributed to the observed percentage markers (60.9 %) and correct calls (97.8 %). SNP analysis achieved a 98 % call rate, with only two mismatches and two missed alleles. ONT-generated DNA methylation data demonstrated Pearson’s correlation coefficients with EPIC data ranging from 0.67 to 0.97 for Horvath’s clock. Additional age-associated markers exhibited Pearson’s correlation coefficients with chronological age between 0.14 (ELOVL2) and 0.96 (FHL2) at read depths of <30 and <20, respectively. Despite excluding mtDNA from our targeted sequencing approach, adaptive proof-reading fragments covered the complete mtDNA with an average read depth of 21–72, showing 100 % concordance with reference data.

Discussion
Our exploratory study using ONT adaptive sequencing for conventional forensic and age associated DNA methylation markers showed high sequencing accuracy for a significant number of markers, showcasing ONT as a promising (epi)genetic forensic method. Future studies must address three critical aspects: determining clear quantity and quality measures and detection thresholds for accuracy, optimizing input DNA quantity for forensic casework expectations, and addressing ethical considerations associated with phenotype and ancestry analysis to prevent ethnic biases.@en

In this study, the deposition, annealing process, and oxidation properties of HfNbTaTiZr high-entropy alloy thin films were thoroughly investigated. The films, approximately 250 nm thick, were deposited on MgO substrates by DC magnetron sputtering using a single target. The preparation temperature was identified as a key factor influencing the resulting structure. Amorphous films formed at room temperature, whereas nanocrystalline films, characterized by multiple intermetallic phases, were obtained either by deposition at elevated temperatures (600 °C – 750 °C) or through in situ annealing of amorphous films (600 °C – 700 °C). Positron annihilation spectroscopy revealed that nanocrystalline films predominantly contain vacancy-like misfit defects, with concentration decreasing as the preparation temperature increases. Additionally, amorphous films exhibited a high concentration of large vacancy clusters. X-ray photoelectron spectroscopy showed greater oxygen absorption in amorphous films due to their defective structure, with preferential oxidation of Zr and Hf. Further annealing of naturally oxidized films in a vacuum at temperatures up to 1400 °C led to films' recrystallization and eventually the formation of complex oxides, including ZrO2, HfO2, and various Mg-containing oxides, indicating a reaction with the MgO substrate. This work demonstrates the ability to fine-tune the microstructure and defect characteristics of high-entropy alloy films and highlights their direct correlation with oxidation properties.@en

This paper presents a framework for the derivation of a noise budget and the subsequent utilization in the optimization of the control design, using the laser frequency stabilization loop in the Virgo interferometer, which is a complex nested feedback system, as an experimental case study. First, the system dynamics and noise sources are modeled and experimentally verified to produce the noise budget, after which an optimization problem using the H2 norm is formulated and tailored to the specific design requirements for the detector. The structure of the synthesized controller is then used to produce an improved control design. Experimental verification of the developed controller on the Virgo interferometer shows roughly a factor 3 reduction in root-mean-square error, illustrating the effectiveness of the presented method.@en

Dynamic susceptibility contrast (DSC) MRI is commonly part of brain tumor imaging. For quantitative analysis, measurement of the arterial input function and tissue concentration time curve is required. Usually, a linear relationship between the MR signal changes and contrast agent concentration ([Gd]) is assumed, even though this is a known simplification. The aim of this study was to develop a realistic 3D simulation model as an efficient method to assess the relationship between ΔR2(*) and [Gd] both in whole blood and brain tissue. We modified an open-source 3D simulation model to study different red blood cell configurations for assessing whole-blood ΔR2(*) versus [Gd]. The results were validated against previously obtained 2D data and in vitro data. Furthermore, hematocrit levels (30%–50%) and field strengths (1.5–3.0–7.0 T) were varied. Subsequently, realistic tumor vascular networks were derived from intraoperative high framerate Doppler ultrasound data to study the influence of vascular structure and orientation with respect to the main magnetic field (1.5–3.0–7.0 T) for the calculation of ΔR2(*) versus [Gd] in brain tissue. For whole blood, good agreement of the 3D model was found with in vitro and 2D simulation data when red blood cells were aligned with the blood flow. For brain tissue, minor differences were found between the vascular networks. The effect of vessel direction with respect to B0 was apparent in case of clear directionality of the main vessels. The dependency on field strength agreed with previous reports. In conclusion, we have shown that the relationship between ΔR2(*) and [Gd] is affected by the organization of red blood cells and orientation of blood vessels with respect to the main magnetic field, as well as the field strength. These findings are important for further optimization of the realistic 3D model that could eventually be used to improve the estimation of hemodynamic parameters from DSC-MRI.@en

An implementation strategy for high-power, high resolution, fully digital transmitters (DTX) is proposed. It is based on a high-speed CMOS controller featuring a high-density flip-chip interconnect to an LDMOS power MMIC containing large arrays of custom low-VT LDMOS gate segments configured in RF-power switch banks. Using a two-level thermometer approach and a novel symmetric control scheme for the activation of the gate segments, a high-resolution 11-bit DTX switch bank is realized. It can provide peak RF powers >10 W at 45/40% peak drain/system efficiency at 3.525 GHz.@en

The main objectives of bioprocesses are to reliably deliver drugs in a relatively short time frame with high quality within a tight regulatory framework. Bioprocesses are highly complex, the level of automation is moderate, and there is constant pressure to improve efficiency and costs. In addition, climate change and resource scarcity mandate a reduction in the environmental footprint of bioprocesses and production facilities. In the biopharmaceutical industry, two extreme production scenarios are applied: a fully disposable factory with the characteristics of full flexibility and speed, or a fixed large-scale plant with high capacity. Forward-looking solutions and ideas will be discussed how to combine new processes and environmental friendliness for the benefit of the patient, security of supply and profitability. The concept will be extended to large scale production of proteins for food and non-pharma applications, e.g., in material science and a roadmap towards a future plant will be laid out.

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Purpose: The value of integrating clinical variables, radiomics, and tumor-derived cell-free DNA (cfDNA) for the prediction of survival and response to chemoradiation of patients with resectable esophageal adenocarcinoma is not yet known. Our aim was to investigate if radiomics and cfDNA metrics combined with clinical variables can improve personalized predictions. Methods and Materials: A cohort of 111 patients with resectable esophageal adenocarcinoma from 2 centers treated with neoadjuvant chemoradiation therapy was used for exploratory retrospective analyses. Models combining the clinical variables of the SOURCE survival model with radiomic features and cfDNA were built using elastic net regression and internally validated using 5-fold cross-validation. Model performance for overall survival (OS) and time to progression (TTP) were evaluated with the C-index and the area under the curve for pathologic complete response. Results: The best-performing baseline models for OS and TTP were based on the combination of SOURCE-cfDNA that reached a C-index of 0.55 and 0.59 compared with 0.44 to 0.45 with SOURCE alone. The addition of restaging positron emission tomography radiomics to SOURCE was the most promising addition for predicting OS (C-index: 0.65) and TTP (C-index: 0.60). Baseline risk stratification was achieved for OS and TTP by combining SOURCE with radiomics or cfDNA, log-rank P < .01. The best-performing combination model for the prediction of pathologic complete response reached an area under the curve of 0.61 compared with 0.47 with SOURCE variables alone. Conclusions: The addition of radiomics and cfDNA can improve the performance of an established survival model. External validity needs to be further assessed in future studies together with the optimization of radiomic pipelines.

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This paper presents the results of the 2022 Groundwater Time Series Modelling Challenge, where 15 teams from different institutes applied various data-driven models to simulate hydraulic-head time series at four monitoring wells. Three of the wells were located in Europe and one was located in the USA in different hydrogeological settings in temperate, continental, or subarctic climates. Participants were provided with approximately 15 years of measured heads at (almost) regular time intervals and daily measurements of weather data starting some 10 years prior to the first head measurements and extending around 5 years after the last head measurement. The participants were asked to simulate the measured heads (the calibration period), to provide a prediction for around 5 years after the last measurement (the validation period for which weather data were provided but not head measurements), and to include an uncertainty estimate. Three different groups of models were identified among the submissions: lumped-parameter models (three teams), machine learning models (four teams), and deep learning models (eight teams). Lumped-parameter models apply relatively simple response functions with few parameters, while the artificial intelligence models used models of varying complexity, generally with more parameters and more input, including input engineered from the provided data (e.g. multi-day averages). The models were evaluated on their performance in simulating the heads in the calibration period and in predicting the heads in the validation period. Different metrics were used to assess performance, including metrics for average relative fit, average absolute fit, fit of extreme (high or low) heads, and the coverage of the uncertainty interval. For all wells, reasonable performance was obtained by at least one team from each of the three groups. However, the performance was not consistent across submissions within each group, which implies that the application of each method to individual sites requires significant effort and experience. In particular, estimates of the uncertainty interval varied widely between teams, although some teams submitted confidence intervals rather than prediction intervals. There was not one team, let alone one method, that performed best for all wells and all performance metrics. Four of the main takeaways from the model comparison are as follows: (1) lumped-parameter models generally performed as well as artificial intelligence models, which means they capture the fundamental behaviour of the system with only a few parameters. (2) Artificial intelligence models were able to simulate extremes beyond the observed conditions, which is contrary to some persistent beliefs about these methods. (3) No overfitting was observed in any of the models, including in the models with many parameters, as performance in the validation period was generally only a bit lower than in the calibration period, which is evidence of appropriate application of the different models. (4) The presented simulations are the combined results of the applied method and the choices made by the modeller(s), which was especially visible in the performance range of the deep learning methods; underperformance does not necessarily reflect deficiencies of any of the models. In conclusion, the challenge was a successful initiative to compare different models and learn from each other. Future challenges are needed to investigate, for example, the performance of models in more variable climatic settings to simulate head series with significant gaps or to estimate the effect of drought periods.

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The diagnostic spectrum for AML patients is increasingly based on genetic abnormalities due to their prognostic and predictive value. However, information on the AML blast phenotype regarding their maturational arrest has started to regain importance due to its predictive power for drug responses. Here, we deconvolute 1350 bulk RNA-seq samples from five independent AML cohorts on a single-cell healthy BM reference and demonstrate that the morphological differentiation stages (FAB) could be faithfully reconstituted using estimated cell compositions (ECCs). Moreover, we show that the ECCs reliably predict ex-vivo drug resistances as demonstrated for Venetoclax, a BCL-2 inhibitor, resistance specifically in AML with CD14+ monocyte phenotype. We validate these predictions using LUMC proteomics data by showing that BCL-2 protein abundance is split into two distinct clusters for NPM1-mutated AML at the extremes of CD14+ monocyte percentages, which could be crucial for the Venetoclax dosing patients. Our results suggest that Venetoclax resistance predictions can also be extended to AML without recurrent genetic abnormalities and possibly to MDS-related and secondary AML. Lastly, we show that CD14+ monocytic dominated Ven/Aza treated patients have significantly lower overall survival. Collectively, we propose a framework for allowing a joint mutation and maturation stage modeling that could be used as a blueprint for testing sensitivity for new agents across the various subtypes of AML.

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A rapidly growing population across mountain regions is pressuring expansion onto steeper slopes, leading to increased exposure of people and their assets to slow-moving landslides. These moving hillslopes can inflict damage to buildings and infrastructure, accelerate with urban alterations, and catastrophically fail with climatic and weather extremes. Yet, systematic estimates of slow-moving landslide exposure and their drivers have been elusive. Here, we present a new global database of 7,764 large (A ≥ 0.1 km²) slow-moving landslides across nine IPCC regions. Using high-resolution human settlement footprint data, we identify 563 inhabited landslides. We estimate that 9% of reported slow-moving landslides are inhabited, in a given basin, and have 12% of their areas occupied by human settlements, on average. We find the density of settlements on unstable slopes decreases in basins more affected by slow-moving landslides, but varies across regions with greater flood exposure. Across most regions, urbanization can be a relevant driver of slow-moving landslide exposure, while steepness and flood exposure have regionally varying influences. In East Asia, slow-moving landslide exposure increases with urbanization, gentler slopes, and less flood exposure. Our findings quantify how disparate knowledge creates uncertainty that undermines an assessment of the drivers of slow-moving landslide exposure in mountain regions, facing a future of rising risk, such as Central Asia, Northeast Africa, and the Tibetan Plateau.

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Solid-state batteries with lithium metal anodes are considered the next major technology leap with respect to today’s lithium-ion batteries, as they promise a significant increase in energy density. Expectations for solid-state batteries from the automotive and aviation sectors are high, but their implementation in industrial production remains challenging. Here, we report a solid-state lithium–metal battery enabled by a polymer electrolyte consisting of a poly(DMADAFSI) cationic polymer and LiFSI in Pyr13FSI as plasticizer. The polymer electrolyte is infiltrated and solidified in the pores of a commercial LiNi0.8Mn0.1Co0.1O2 (NMC811) cathode with up to 2.8 mAh cm–2 nominal areal capacity and in the pores of a 25 μm thin commercial polypropylene separator. Cathode and separator are finally laminated into a cell in combination with a commercial 20 μm thin lithium metal anode. Our demonstration of a solid-state polymer battery cycling at full nominal capacity employing exclusively commercially available components available at industrial scale represents a critical step forward toward the commercialization of a competitive all-solid-state battery technology.@en

The primary objective of the prospective, randomized, multicenter, phase 3 biomarker Microarray Analysis in breast cancer to Taylor Adjuvant Drugs Or Regimens trial (MATADOR: ISRCTN61893718) is to generate a gene expression profile that can predict benefit from either docetaxel, doxorubicin, and cyclophosphamide (TAC) or dose-dense scheduled doxorubicin and cyclophosphamide (ddAC). Patients with a pT1-3, pN0-3 tumor were randomized 1:1 between ddAC and TAC. The primary endpoint was a gene profile-treatment interaction for recurrence-free survival (RFS). We observed 117 RFS events in 664 patients with a median follow-up of 7 years. Hallmark gene set analyses showed significant association between enrichment in immune-related gene expression and favorable outcome after TAC in hormone receptor-negative, human epidermal growth factor receptor 2 (HER2)-negative breast cancer (BC) (triple-negative breast cancer [TNBC]). We validated this association in TNBC patients treated with TAC on H&E slides; stromal tumor-infiltrating lymphocytes (sTILs) ≥20% was associated with longer RFS (hazard ratio 0.18, p = 0.01), while in patients treated with ddAC no difference in RFS was seen (hazard ratio 0.92, p = 0.86, p_interaction = 0.02).

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Hydroelectric nanogenerators (HENGs) utilize the synergy between conductive nanomaterials and hydrodynamic flow to generate electricity, but their applications are limited by low output power density. Here, a high-performance HENG is developed by employing single-layer MXene (SMX) nanosheets on wool cloth. The SMX-based HENGs exhibit a maximum energy density of 0.683 mW cm−2, a current of 1.994 mA, and a voltage of 0.687 V, sufficient to power small wearable electronics. Moreover, the hydrophilicity of the HENGs is maintained due to the addition oxidized ketjen black nanoparticles to the SMX matrix. This is attributed to the functional groups (e.g., –COOH and –OH) on OKB, which are important for efficient ion transport and maintaining a high steady-state power density. Important insights into energy generation for the development of high-efficiency HENGs for practical applications have been gained from numerical simulation using COMSOL multiphysics.@en

This study investigated whether radiomic features extracted from pretreatment [18F]FDG PET could improve the prediction of both histopathologic tumor response and survival in patients with locally advanced cervical cancer (LACC) treated with neoadjuvant chemoradiotherapy followed by surgery compared with conventional PET parameters and histopathologic features. Methods: The medical records of all consecutive patients with LACC referred between July 2010 and July 2016 were reviewed. [18F]FDG PET/CT was performed before neoadjuvant chemoradiotherapy. Radiomic features were extracted from the primary tumor volumes delineated semiautomatically on the PET images and reduced by factor analysis. A receiver-operating-characteristic analysis was performed, and conventional and radiomic features were dichotomized with Liu’s method according to pathologic response (pR) and cancer-specific death. According to the study protocol, only areas under the curve of more than 0.70 were selected for further analysis, including logistic regression analysis for response prediction and Cox regression analysis for survival prediction. Results: A total of 195 patients fulfilled the inclusion criteria. At pathologic evaluation after surgery, 131 patients (67.2%) had no or microscopic (≤3 mm) residual tumor (pR0 or pR1, respectively); 64 patients (32.8%) had macroscopic residual tumor (>3 mm, pR2). With a median follow-up of 76.0 mo (95% CI, 70.7–78.7 mo), 31.3% of patients had recurrence or progression and 20.0% died of the disease. Among conventional PET parameters, SUVmean significantly differed between pathologic responders and nonresponders. Among radiomic features, 1 shape and 3 textural features significantly differed between pathologic responders and nonresponders. Three radiomic features significantly differed between presence and absence of recurrence or progression and between presence and absence of cancer-specific death. Areas under the curve were less than 0.70 for all parameters; thus, univariate and multivariate regression analyses were not performed. Conclusion: In a large series of patients with LACC treated with neoadjuvant chemoradiotherapy followed by surgery, PET radiomic features could not predict histopathologic tumor response and survival. It is crucial to further explore the biologic mechanism underlying imaging-derived parameters and plan a large, prospective, multicenter study with standardized protocols for all phases of the process of radiomic analysis to validate radiomics before its use in clinical routine.@en