An ever-growing number of predictive models used to inform clinical decision making have included quantitative, computer-extracted imaging biomarkers, or “radiomic features.” Broadly generalizable ...validity of radiomics-assisted models may be impeded by concerns about reproducibility. We offer a qualitative synthesis of 41 studies that specifically investigated the repeatability and reproducibility of radiomic features, derived from a systematic review of published peer-reviewed literature.
The PubMed electronic database was searched using combinations of the broad Haynes and Ingui filters along with a set of text words specific to cancer, radiomics (including texture analyses), reproducibility, and repeatability. This review has been reported in compliance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. From each full-text article, information was extracted regarding cancer type, class of radiomic feature examined, reporting quality of key processing steps, and statistical metric used to segregate stable features.
Among 624 unique records, 41 full-text articles were subjected to review. The studies primarily addressed non-small cell lung cancer and oropharyngeal cancer. Only 7 studies addressed in detail every methodologic aspect related to image acquisition, preprocessing, and feature extraction. The repeatability and reproducibility of radiomic features are sensitive at various degrees to processing details such as image acquisition settings, image reconstruction algorithm, digital image preprocessing, and software used to extract radiomic features. First-order features were overall more reproducible than shape metrics and textural features. Entropy was consistently reported as one of the most stable first-order features. There was no emergent consensus regarding either shape metrics or textural features; however, coarseness and contrast appeared among the least reproducible.
Investigations of feature repeatability and reproducibility are currently limited to a small number of cancer types. Reporting quality could be improved regarding details of feature extraction software, digital image manipulation (preprocessing), and the cutoff value used to distinguish stable features.
•This study examined the stability of radiomic features from T2-weighted MRI of cervical cancer.•Three tests were applied: 1. test–retest; 2. diagnostic vs simulation MRI; and 3. inter-observer ...delineation.•The inter-observer cohort had the greatest number of reproducible features.•The diagnostic–simulation cohort had the fewest reproducible features.•Shape features were the most stable features in all three cohorts.
The aims of this study are to evaluate the stability of radiomic features from T2-weighted MRI of cervical cancer in three ways: (1) repeatability via test–retest; (2) reproducibility between diagnostic MRI and simulation MRI; (3) reproducibility in inter-observer setting.
This retrospective cohort study included FIGO stage IB-IVA cervical cancer patients treated with chemoradiation between 2005 and 2014. There were three cohorts of women corresponding to each aim of the study: (1) 8 women who underwent test–retest MRI; (2) 20 women who underwent MRI on different scanners (diagnostic and simulation MRI); (3) 34 women whose diagnostic MRIs were contoured by three observers. Radiomic features based on first-order statistics, shape features and texture features were extracted from the original, Laplacian of Gaussian (LoG)-filtered and wavelet-filtered images, for a total of 1761 features. Stability of radiomic features was assessed using intraclass correlation coefficient (ICC).
The inter-observer cohort had the most reproducible features (95.2% with ICC ≥0.75) whereas the diagnostic–simulation cohort had the fewest (14.1% with ICC ≥0.75). Overall, 229 features had ICC ≥0.75 in all three tests. Shape features emerged as the most stable features in all cohorts.
The diagnostic–simulation test resulted in the fewest reproducible features. Further research in MRI-based radiomics is required to validate the use of reproducible features in prognostic models.
•Dynamic analysis of sensible type thermal energy storage by two different approaches.•CFD model using ANSYS-FLUENT® code and a reduced-order model using TRANSEO.•Experimental validation of the ...simulation results from both models.•Comparison of modelling capability and scope of each model.•Estimation of total thermal losses from the storage vessel.
Integration of Thermal Energy Storage (TES) is one of the promising features of Concentrated Solar Power (CSP) technology which allows the Renewable Energy Sources (RES) to provide uninterrupted and dispatchable power supply, and thus facilitates the RES grid integration. Hybrid Solar Gas Turbine (HSGT) systems along with TES integration have gained great attention for the last decades. Numerical modelling and simulation tools are essential for the TES design optimization and analysis of its thermal behaviour during charging and discharging phases. This paper deals with the dynamic modelling and experimental validation of a TES at laboratory scale, which is part of the HSGT system. The TES is modelled with two different approaches: the CFD model using a commercial tool and a reduced-order model using the in-house transient simulation tool TRANSEO, which has been developed by Thermochemical Power Group (TPG) for the energy system dynamic analysis. The validation of both model results against the data obtained by the Authors through experimental investigation has highlighted that 2D discretization of the TES through the CFD model gives accurate representation of the thermal behaviour of the system, but it causes a significant computational expense. On the other side, 1D dynamic model reasonably predicts the time dependent thermal behaviour of TES, except some deviations from the experiments which are related to the simplified discretization scheme. However, due to its fast approach, the TRANSEO model can be effectively used to perform both TES initial design and sensitivity analysis, and also to develop or verify the control system at a later stage of HSGT system development.
Pumped thermal energy storage (PTES) is a promising long-duration energy storage technology. Nevertheless, PTES shows intermediate round-trip efficiency (RTE—0.5 ÷ 0.7) and significant CAPEX. sCO2 ...heat pumps and power cycles could reduce PTES CAPEX, particularly via reversible and flexible machines. Furthermore, the possibility to exploit freely available heat sources (such as waste heat and/or CSP inputs) could increase RTE, making the system capable of an apparent RTE > 100% as well as reducing CAPEX, avoiding the need for two TES systems. This paper analyses the potential valorization of industrial waste heat (WH) to enhance PTES thermodynamic performance as well as increase industrial energy efficiency, valorizing different levels of WH sources in the 100–400 °C temperature range. In fact, the use of additional heat, otherwise dumped into ambient surroundings, may contribute to avoiding the need for a second TES, thus enhancing plant competitiveness. Starting from an assessment of the most relevant industrial sectors to apply the proposed solution (looking at available WH and electric flexibility needed), this paper analyses the feasibility of a specific sCO2-based PTES case study, where the cycle is integrated into a cement production plant with a WH temperature of around 350 °C. It is demonstrated that the CAPEX of the proposed systems are still relevant and only a robust exploitation of the PTES in the ancillary service market could attract industrial customers’ interest in sCO2 PTES.
To develop and validate a radiomics nomogram based on ultrasound (US) to predict central cervical lymph node (LN) metastasis in patients with papillary thyroid carcinoma (PTC).
PTC patients with ...pathologically confirmed presence or absence of central cervical LN metastasis in our hospital between March 2021 and November 2021 were enrolled as the training cohort. Radiomics features were extracted from the preoperative US images, and a radiomics signature was constructed. Univariate and multivariate logistic regression analyses were used to screen out the independent risk factors, and a radiomics nomogram was established. The performance of the model was verified in the independent test cohort of PTC patients who underwent thyroidectomy and cervical LN dissection in our hospital from December 2021 to March 2022.
In the independent test cohort, the radiomics model based on long-axis cross-section and short-axis cross-section images outperformed the radiomics models based on either one of these sections (the area under the curve (AUC), 0.69 vs. 0.62 and 0.66). The radiomics signature consisted of 4 selected features. The US radiomics nomogram included the radiomics signature, age, gender, BRAF V600E mutation status, and extrathyroidal extension (ETE) status. In the independent test cohort, the AUC of the receiver operating curve(ROC) of this nomogram was 0.76, outperformingthe clinical model and the radiomics model (0.63 and 0.69, respectively), and also much better than preoperative US examination (AUC, 0.60). Decision curve analysis indicated that the radiomics nomogram was clinically useful.
This study presents an efficient and useful US radiomics nomogram that can provide comprehensive information to assist clinicians in the individualized preoperative prediction of central cervical LN metastasis in PTC patients.
•Different management systems are compared on the basis of experimental results.•Target system is a real smart microgrid composed by different co-generative systems.•A complex demand scenario was ...used to test decision-making of the controllers.•Experimental results were analyzed from both economic and reliability viewpoints.
In recent years, many different concepts to manage smart distributed systems were proposed and solutions developed. Smart grids and the increasing influence of renewable sources on energy production lead to concerns about grid stability and load balance. Combined Heat and Power (CHP) generators coupled with solar or other renewable sources offer the opportunity to satisfy both electric and thermal power economically. Both electric and thermal demand and supply change continuously, and sources such as solar and wind are not dispatchable or accurately predictable. At the same time, it is essential to use the most efficient and cost effective sources to satisfy the demand. This problem has been studied at the University of Genoa (UNIGE), Italy, using different generators and energy storage device that can supply both electric and thermal energy to consumer buildings. Here the problem is formulated as a constrained Multi-Input Multi-Output (MIMO) problem with sometimes conflicting requests that must be satisfied. The results come from experiments carried out on the test rig located at the Innovative Energy System Laboratories (IESL) of the Thermochemical Power Group (TPG) of UNIGE. This paper compares three different control approaches to manage the distributed generation system: Simplified Management Control (SMC), Model Predictive Control (MPC), and Multi-Commodity Matcher (MCM). Control systems and their control actions are evaluated through economic and performance key indicators.
Research exploring CycleGAN-based synthetic image generation has recently accelerated in the medical community due to its ability to leverage unpaired images effectively. However, a commonly ...established drawback of the CycleGAN, the introduction of artifacts in generated images, makes it unreliable for medical imaging use cases. In an attempt to address this, we explore the effect of structure losses on the CycleGAN and propose a generalized frequency-based loss that aims at preserving the content in the frequency domain. We apply this loss to the use-case of cone-beam computed tomography (CBCT) translation to computed tomography (CT)-like quality. Synthetic CT (sCT) images generated from our methods are compared against baseline CycleGAN along with other existing structure losses proposed in the literature. Our methods (
) quantitatively and qualitatively improve over the baseline CycleGAN (
) across all investigated metrics and are more robust than existing methods. Furthermore, no observable artifacts or loss in image quality were observed. Finally, we demonstrated that sCTs generated using our methods have superior performance compared to the original CBCT images on selected downstream tasks.
Tesla turbine rotor, a special case of the flow between two corotating disks, has been studied in the past analytically and the performance is discussed both qualitatively and quantitatively. ...However, there is no systematic design criteria/process given to design the rotor of a Tesla expander in the peer-reviewed literature. Such design procedure, presented in this article, allows researchers and engineers to design and optimise the rotor for a given fluid and design condition (Power, flow and rotational speed). In this article, we present a 0-D design methodology to calculate rotor design parameters such as disk diameters, the gap between disks, the number of disks and the rotational speed of the expander, and efficiency and power estimation. This design procedure is based on the correlations and optimal ranges present in the literature. The 0-D model discussed in this article is a promising design approach to the preliminary design of the Tesla rotor and then further fine-tuning could be done based on the CFD simulations when coupled with the stator. A case study is presented with a 3-kW air bladeless expander prototype in which the rotor is designed using the 0-D model approach and compared with 2D Computational Fluid Dynamics results.
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