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Soil salinization and selenium (Se) deficiency threaten global food security. This study developed a composite bioinoculant combining ACC deaminase-producing Serratia liquefaciens and biogenically synthesized nano-selenium (SeNPs) to alleviate saline–alkali stress and enhance Se nutrition in rice (Oryza sativa L.). A strain of S. liquefaciens with high ACC deaminase activity was isolated and used to biosynthesize SeNPs with stable physicochemical properties. Pot experiments showed that application of the composite inoculant (S3: S. liquefaciens + 40 mmol/L SeNPs) significantly improved seedling biomass (fresh weight +53.8%, dry weight +60.6%), plant height (+31.6%), and root activity under saline–alkali conditions. S3 treatment also enhanced panicle weight, seed-setting rate, and grain Se content (234.13 μg/kg), meeting national Se-enriched rice standards. Moreover, it increased rhizosphere soil N, P, and K availability and improved microbial α-diversity. This is the first comprehensive demonstration that a synergistic bioformulation of ACC deaminase PGPR and biogenic SeNPs effectively mitigates saline–alkali stress, enhances soil fertility, and enables safe Se biofortification in rice. Full article

(This article belongs to the Special Issue Nanomaterials in Plant Growth and Stress Adaptation—2nd Edition)

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17 pages, 1546 KiB

Open AccessArticle

Design and Optimization of Valve Lift Curves for Piston-Type Expander at Different Rotational Speeds

by Yongtao Sun, Qihui Yu, Zhenjie Han, Ripeng Qin and Xueqing Hao

Fluids 2025, 10(8), 204; https://doi.org/10.3390/fluids10080204 (registering DOI) - 1 Aug 2025

Abstract

The piston-type expander (PTE), as the primary output component, significantly influences the performance of an energy storage system. This paper proposes a non-cam variable valve actuation system for the PTE, supported by a mathematical model. An enhanced S-curve trajectory planning method is used to design the valve lift curve. The study investigates the effects of various valve lift design parameters on output power and efficiency at different rotational speeds, employing orthogonal design and SPSS Statistics 27 (Statistical Product and Service Solutions) simulations. A grey comprehensive evaluation method is used to identify optimal valve lift parameters for each speed. The results show that valve lift parameters influence PTE performance to varying degrees, with intake duration having the greatest effect, followed by maximum valve lift, while intake end time has the least impact. The non-cam PTE outperforms the cam-based PTE. At 800 rpm, the optimal design yields 7.12 kW and 53.5% efficiency; at 900 rpm, 8.17 kW and 50.6%; at 1000 rpm, 9.2 kW and 46.8%; and at 1100 rpm, 12.09 kW and 41.2%. At these speeds, output power increases by 18.37%, 11.42%, 11.62%, and 9.82%, while energy efficiency improves by 15.01%, 15.05%, 14.24%, and 13.86%, respectively. Full article

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16 pages, 1141 KiB

Open AccessArticle

Coordinated Roles of Osmotic Adjustment, Antioxidant Defense, and Ion Homeostasis in the Salt Tolerance of Mulberry (Morus alba L. ‘Tailai Sang’) Seedlings

by Nan Xu, Tiane Wang, Yuan Wang, Juexian Dong and Yu Shaopeng

Forests 2025, 16(8), 1258; https://doi.org/10.3390/f16081258 (registering DOI) - 1 Aug 2025

Abstract

Soil salinization severely limits plant growth and productivity. Mulberry (Morus alba L.), an economically and ecologically important tree, is widely cultivated, yet its salt-tolerance mechanisms at the seedling stage remain insufficiently understood. This study investigated the physiological and biochemical responses of two-year-old mulberry (‘Tailai Sang’) seedlings subjected to six NaCl treatments (0, 50, 100, 150, 200, and 300 mmol L⁻¹) for 28 days. Results showed that growth parameters and photosynthetic gas exchange exhibited dose-dependent declines. The reduction in net photosynthetic rate (Pn) was attributed to both stomatal limitations (decreased stomatal conductance) and non-stomatal limitations, as evidenced by a significant decrease in the maximum quantum efficiency of photosystem II (Fv/Fm) under high salinity. To cope with osmotic stress, seedlings accumulated compatible solutes, including soluble sugars, proteins, and proline. Critically, mulberry seedlings demonstrated effective ion homeostasis by sequestering Na⁺ in the roots to maintain a high K⁺/Na⁺ ratio in leaves, a mechanism that was compromised above 150 mmol L⁻¹. Concurrently, indicators of oxidative stress—malondialdehyde (MDA) and H₂O₂—rose significantly with salinity, inducing the activities of antioxidant enzymes (SOD, CAT, APX, and GR), which peaked at 150 mmol L⁻¹ before declining under extreme stress. A biomass-based LC₅₀ of 179 mmol L⁻¹ NaCl was determined. These findings elucidate that mulberry salt tolerance is a coordinated process involving three key mechanisms: osmotic adjustment, selective ion distribution, and a robust antioxidant defense system. This study establishes an indicative tolerance threshold under controlled conditions and provides a physiological basis for further field-based evaluations of ‘Tailai Sang’ mulberry for cultivation on saline soils. Full article

(This article belongs to the Special Issue Adaptive Mechanisms of Tree Seedlings to Adapt to Stress—Second Edition)

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55 pages, 4017 KiB

Open AccessReview

Sonchus Species of the Mediterranean Region: From Wild Food to Horticultural Innovation—Exploring Taxonomy, Cultivation, and Health Benefits

by Adrián Ruiz-Rocamora, Concepción Obón, Segundo Ríos, Francisco Alcaraz and Diego Rivera

Horticulturae 2025, 11(8), 893; https://doi.org/10.3390/horticulturae11080893 (registering DOI) - 1 Aug 2025

Abstract

The genus Sonchus (Asteraceae) comprises 98 species, including 17 predominantly herbaceous taxa native to the Mediterranean region. These plants have long been utilized as traditional wild food sources due to their high nutritional value, as they are rich in vitamins A, C, and K, essential minerals, and bioactive compounds with antioxidant and anti-inflammatory properties. This review aims to provide a comprehensive synthesis of the taxonomy, geographic distribution, phytochemical composition, traditional uses, historical significance, and pharmacological properties of Sonchus species. A systematic literature search was conducted using PubMed, Scopus, Web of Science, and Google Scholar, focusing on studies from 1980 to 2024. Inclusion and exclusion criteria were applied, and methodological quality was assessed using standardized tools. A bibliometric analysis of 440 publications (from 1856 to 2025) reveals evolving research trends, with S. oleraceus, S. arvensis, and S. asper being the most extensively studied species. The review provides detailed taxonomic insights into 17 species and 14 subspecies, emphasizing their ecological adaptations and biogeographical patterns. Additionally, it highlights the cultural and medicinal relevance of Sonchus since antiquity while underscoring the threats posed by environmental degradation and changing dietary habits. Sonchus oleraceus and S. tenerrimus dominate the culinary applications of the genus, likely due to favorable taste, wide accessibility, and longstanding cultural importance. The comprehensive nutritional profile of Sonchus species positions these plants as valuable contributors to dietary diversity and food security. Finally, the study identifies current knowledge gaps and proposes future research directions to support the conservation and sustainable utilization of Sonchus species. Full article

(This article belongs to the Special Issue Wild Plant Species as Potential Horticultural Crops: An Opportunity for Farmers and Consumers—2nd Edition)

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18 pages, 1769 KiB

Open AccessArticle

Students’ Perceptions of Effective Math Learning Strategies

by Marissa K. Hartwig and Doug Rohrer

Behav. Sci. 2025, 15(8), 1047; https://doi.org/10.3390/bs15081047 (registering DOI) - 1 Aug 2025

Abstract

Two highly effective math learning strategies are spaced practice (in which problems of the same kind are distributed across many sessions) and interleaved practice (in which problems of different kinds are mixed rather than blocked). Though these strategies are supported by data, students may be reluctant to use them if they perceive the strategies as ineffective or unpleasant. In Study 1, we surveyed 174 grade 7 math students about the efficacy and likability of spaced and interleaved practice. Spaced practice was often judged likable, but nearly half of students failed to recognize its efficacy. Interleaved practice was judged both unlikable and inefficacious by most students. In Study 2, we further explored perceptions of interleaving in a survey of 233 grade 7 math students. Again, students erroneously judged interleaved practice to have low efficacy. Compared to blocked practice, interleaved practice was judged less effective, less preferable, more time-consuming, and more difficult. This work identifies perceptions that may discourage students from using effective learning strategies and also shows that specific perceptions differ by strategy. Helping students overcome their negative perceptions of spacing and interleaving is an important future direction. Full article

(This article belongs to the Special Issue Educational Applications of Cognitive Psychology)

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16 pages, 3043 KiB

Open AccessArticle

Experimental Investigations on Sustainable Dual-Biomass-Based Composite Phase Change Materials for Energy-Efficient Building Applications

by Zhiwei Sun, Wei Wen, Jiayu Wu, Jingjing Shao, Wei Cai, Xiaodong Wen, Chaoen Li, Haijin Guo, Yin Tang, Meng Wang, Dongjing Liu and Yang He

Materials 2025, 18(15), 3632; https://doi.org/10.3390/ma18153632 (registering DOI) - 1 Aug 2025

Abstract

The incorporation of phase change material (PCM) can enhance wall thermal performance and indoor thermal comfort, but practical applications still face challenges related to high costs and potential leakage issues. In this study, a novel dual-biomass-based shape-stabilized PCM (Bio-SSPCM) was proposed, wherein waste cooking fat and waste reed straw were, respectively, incorporated as the PCM substance and supporting material. The waste fat (lard) consisted of both saturated and unsaturated fatty acid glycerides, exhibiting a melting point about 21.2–41.1 °C and a melting enthalpy value of 40 J/g. Reed straw was carbonized to form a sustainable porous biochar supporting matrix, which was used for the vacuum adsorption of waste fat. The results demonstrate that the as-prepared dual-Bio-SSPCM exhibited excellent thermal performance, characterized by a latent heat capacity of 25.4 J/g. With the addition of 4 wt% of expanded graphite (EG), the thermal conductivity of the composite PCM reached 1.132 W/(m·K), which was 5.4 times higher than that of the primary lard. The thermal properties of the Bio-SSPCM were characterized using an analog T-history method. The results demonstrated that the dual-Bio-SSPCM exhibited exceptional and rapid heat storage and exothermic capabilities. The dual-Bio-SSPCM, prepared from waste cooking fat and reed straw, can be considered as environmentally friendly construction material for energy storage in line with the principles of the circular economy. Full article

(This article belongs to the Special Issue Eco-Friendly Intelligent Infrastructures Materials)

23 pages, 10868 KiB

Open AccessArticle

Quantitative Analysis and Nonlinear Response of Vegetation Dynamic to Driving Factors in Arid and Semi-Arid Regions of China

by Shihao Liu, Dazhi Yang, Xuyang Zhang and Fangtian Liu

Land 2025, 14(8), 1575; https://doi.org/10.3390/land14081575 (registering DOI) - 1 Aug 2025

Abstract

Vegetation dynamics are complexly influenced by multiple factors such as climate, human activities, and topography. In recent years, the frequency, intensity, and diversity of human activities have increased, placing substantial pressure on the growth of vegetation. Arid and semi-arid regions are particularly sensitive to climate change, and climate change and large-scale ecological restoration have led to significant changes in the dynamic of dryland vegetation. However, few studies have explored the nonlinear relationships between these factors and vegetation dynamic. In this study, we integrated trend analysis (using the Mann–Kendall test and Theil–Sen estimation) and machine learning algorithms (XGBoost-SHAP model) based on long time-series remote sensing data from 2001 to 2020 to quantify the nonlinear response patterns and threshold effects of bioclimatic variables, topographic features, soil attributes, and anthropogenic factors on vegetation dynamic. The results revealed the following key findings: (1) The kNDVI in the study area showed an overall significant increasing trend (p < 0.01) during the observation period, of which 26.7% of the area showed a significant increase. (2) The water content index (Bio 23, 19.6%), the change in land use (15.2%), multi-year average precipitation (pre, 15.0%), population density (13.2%), and rainfall seasonality (Bio 15, 10.9%) were the key factors driving the dynamic change of vegetation, with the combined contribution of natural factors amounting to 64.3%. (3) Among the topographic factors, altitude had a more significant effect on vegetation dynamics, with higher altitude regions less likely to experience vegetation greening. Both natural and anthropogenic factors exhibited nonlinear responses and interactive effects, contributing to the observed dynamic trends. This study provides valuable insights into the driving mechanisms behind the condition of vegetation in arid and semi-arid regions of China and, by extension, in other arid regions globally. Full article

(This article belongs to the Section Land Use, Impact Assessment and Sustainability)

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20 pages, 10391 KiB

Open AccessArticle

Sustainable Substitution of Petroleum-Based Processing Oils with Soybean-Derived Alternatives in Styrene–Butadiene Rubber: Effects on Processing Behavior and Mechanical Properties

by Yang-Wei Lin, Tsung-Yi Chen, Chen-Yu Chueh, Yi-Ting Chen, Tsunghsueh Wu and Hsi-Ming Hsieh

Polymers 2025, 17(15), 2129; https://doi.org/10.3390/polym17152129 (registering DOI) - 1 Aug 2025

Abstract

This study evaluates the replacement of petroleum-based naphthenic oil with four types of soybean-derived alternatives—virgin soybean oil (SBO), epoxidized SBO (ESBO), expired SBO, and recycled SBO—in styrene–butadiene rubber (SBR) composites. The materials were tested in both staining rubber (SR) and non-staining rubber (NSR) systems to assess processing characteristics, mechanical performance, and environmental durability. Among the alternatives, SBO demonstrated the best overall performance, improving processability and tensile strength by over 10%, while ESBO enhanced ozone resistance by 35% due to its epoxide functionality. Expired and recycled SBOs maintained essential mechanical properties within 90% of virgin SBO values. The full replacement of CH450 with SBO in tire prototypes resulted in burst strength exceeding 1000 kPa and stable appearance after 5000 km of road testing. To validate industrial relevance, the developed green tire was exhibited at the 2025 Taipei International Cycle Show, attracting interest from international buyers and stakeholders for its eco-friendly composition and carbon footprint reduction potential, thereby demonstrating both technical feasibility and commercial viability. Full article

(This article belongs to the Special Issue Functional Polymers and Their Composites for Sustainable Development)

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26 pages, 3037 KiB

Open AccessArticle

Effectiveness of Firefighter Training for Indoor Intervention: Analysis of Temperature Profiles and Extinguishing Effectiveness

by Jan Hora

Fire 2025, 8(8), 304; https://doi.org/10.3390/fire8080304 (registering DOI) - 1 Aug 2025

Abstract

This study assessed the effectiveness of stress-based cognitive-behavioral training compared to standard training in firefighters, emphasizing their ability to distribute extinguishing water and cool environments evenly during enclosure fires. Experiments took place at the Zbiroh training facility with two firefighter teams (Team A with stress-based training and Team B with standard training) under realistic conditions. Using 58 thermocouples and 4 radiometers, temperature distribution and radiant heat flux were measured to evaluate water distribution efficiency and cooling performance during interventions. Team A consistently achieved temperature reductions of approximately 320 °C in the upper layers and 250–400 °C in the middle layers, maintaining stable conditions, whereas Team B only achieved partial cooling, with upper-layer temperatures remaining at 750–800 °C. Additionally, Team A recorded lower radiant heat flux densities (e.g., 20.74 kW/m² at 0°) compared to Team B (21.81 kW/m²), indicating more effective water application and adaptability. The findings confirm that stress-based training enhances firefighters’ operational readiness and their ability to distribute water effectively during interventions. This skill is essential for safer and effective management of indoor fires under extreme conditions. This study supports the inclusion of stress-based and scenario-based training in firefighter education to enhance safety and operational performance. Full article

(This article belongs to the Section Fire Research at the Science–Policy–Practitioner Interface)

30 pages, 939 KiB

Open AccessArticle

Electricity-Related Emissions Factors in Carbon Footprinting—The Case of Poland

by Anna Lewandowska, Katarzyna Joachimiak-Lechman, Jolanta Baran and Joanna Kulczycka

Energies 2025, 18(15), 4092; https://doi.org/10.3390/en18154092 (registering DOI) - 1 Aug 2025

Abstract

Electricity is a significant factor in the life cycle of many products, so the reliability of greenhouse gas (GHG) emissions data is crucial. The article presents publicly available sources of emission factors representative of Poland. The aim of the study is to assess their strengths and weaknesses in the context of the calculation requirements of carbon footprint analysis in accordance with the GHG Protocol. The article presents the results of carbon footprint calculations for different ranges of emissions in the life cycle of 1 kWh of electricity delivered to a hypothetical organization. Next, a discussion on the quality of the emissions factors has been provided, taking account of data quality indicators. It was concluded that two of the emissions factors that are compared—those based on the national consumption mix and the residual mix for Poland—have been recognized as suitable for use in carbon footprint calculations. Beyond the calculation results, the research highlights the significance of the impact of the selection of emissions factors on the reliability of environmental analysis. The article identifies methodological challenges, including the risk of double counting, limited transparency, methodological inconsistency, and low correlation of data with specific locations and technologies. The insights presented contribute to improving the robustness of carbon footprint calculations. Full article

(This article belongs to the Special Issue Energy Management Systems: Challenges, Techniques and Opportunities: 2nd Edition)

15 pages, 4435 KiB

Open AccessArticle

An Ultra-Robust, Highly Compressible Silk/Silver Nanowire Sponge-Based Wearable Pressure Sensor for Health Monitoring

by Zijie Li, Ning Yu, Martin C. Hartel, Reihaneh Haghniaz, Sam Emaminejad and Yangzhi Zhu

Biosensors 2025, 15(8), 498; https://doi.org/10.3390/bios15080498 (registering DOI) - 1 Aug 2025

Abstract

Wearable pressure sensors have emerged as vital tools in personalized monitoring, promising transformative advances in patient care and diagnostics. Nevertheless, conventional devices frequently suffer from limited sensitivity, inadequate flexibility, and concerns regarding biocompatibility. Herein, we introduce silk fibroin, a naturally occurring protein extracted from silkworm cocoons, as a promising material platform for next-generation wearable sensors. Owing to its remarkable biocompatibility, mechanical robustness, and structural tunability, silk fibroin serves as an ideal substrate for constructing capacitive pressure sensors tailored to medical applications. We engineered silk-derived capacitive architecture and evaluated its performance in real-time human motion and physiological signal detection. The resulting sensor exhibits a high sensitivity of 18.68 kPa⁻¹ over a broad operational range of 0 to 2.4 kPa, enabling accurate tracking of subtle pressures associated with pulse, respiration, and joint articulation. Under extreme loading conditions, our silk fibroin sensor demonstrated superior stability and accuracy compared to a commercial resistive counterpart (FlexiForce™ A401). These findings establish silk fibroin as a versatile, practical candidate for wearable pressure sensing and pave the way for advanced biocompatible devices in healthcare monitoring. Full article

(This article belongs to the Special Issue Wearable Biosensors and Health Monitoring)

27 pages, 6085 KiB

Open AccessArticle

Assessing Model Trade-Offs in Agricultural Remote Sensing: A Review of Machine Learning and Deep Learning Approaches Using Almond Crop Mapping

by Mashoukur Rahaman, Jane Southworth, Yixin Wen and David Keellings

Remote Sens. 2025, 17(15), 2670; https://doi.org/10.3390/rs17152670 (registering DOI) - 1 Aug 2025

Abstract

This study presents a comprehensive review and comparative analysis of traditional machine learning (ML) and deep learning (DL) models for land cover classification in agricultural remote sensing. We evaluate the reported successes, trade-offs, and performance metrics of ML and DL models across diverse agricultural contexts. Building on this foundation, we apply both model types to the specific case of almond crop field identification in California’s Central Valley using Landsat data. DL models, including U-Net, MANet, and DeepLabv3+, achieve high accuracy rates of 97.3% to 97.5%, yet our findings demonstrate that conventional ML models—such as Decision Tree, K-Nearest Neighbor, and Random Forest—can reach comparable accuracies of 96.6% to 96.8%. Importantly, the ML models were developed using data from a single year, while DL models required extensive training data spanning 2008 to 2022. Our results highlight that traditional ML models offer robust classification performance with substantially lower computational demands, making them especially valuable in resource-constrained settings. This paper underscores the need for a balanced approach in model selection—one that weighs accuracy alongside efficiency. The findings contribute actionable insights for agricultural land cover mapping and inform ongoing model development in the geospatial sciences. Full article

(This article belongs to the Special Issue Precision Agriculture and Crop Monitoring Based on Remote Sensing Methods)

22 pages, 3023 KiB

Open AccessArticle

Improving Grain Safety Using Radiation Dose Technologies

by Raushangul Uazhanova, Meruyert Ametova, Zhanar Nabiyeva, Igor Danko, Gulzhan Kurtibayeva, Kamilya Tyutebayeva, Aruzhan Khamit, Dana Myrzamet, Ece Sogut and Maxat Toishimanov

Agriculture 2025, 15(15), 1669; https://doi.org/10.3390/agriculture15151669 (registering DOI) - 1 Aug 2025

Abstract

Reducing post-harvest losses of cereal crops is a key challenge for ensuring global food security amid the limited arable land and growing population. This study investigates the effectiveness of electron beam irradiation (5 MeV, ILU-10 accelerator) as a physical decontamination method for various cereal crops cultivated in Kazakhstan. Samples were irradiated at doses ranging from 1 to 5 kGy, and microbiological indicators—including Quantity of Mesophilic Aerobic and Facultative Anaerobic Microorganisms (QMAFAnM), yeasts, and molds—were quantified according to national standards. Experimental results demonstrated an exponential decline in microbial contamination, with a >99% reduction achieved at doses of 4–5 kGy. The modeled inactivation kinetics showed strong agreement with the experimental data: R² = 0.995 for QMAFAnM and R² = 0.948 for mold, confirming the reliability of the exponential decay models. Additionally, key quality parameters—including protein content, moisture, and gluten—were evaluated post-irradiation. The results showed that protein levels remained largely stable across all doses, while slight but statistically insignificant fluctuations were observed in moisture and gluten contents. Principal component analysis and scatterplot matrix visualization confirmed clustering patterns related to radiation dose and crop type. The findings substantiate the feasibility of electron beam treatment as a scalable and safe technology for improving the microbiological quality and storage stability of cereal crops. Full article

(This article belongs to the Section Agricultural Product Quality and Safety)

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15 pages, 580 KiB

Open AccessArticle

Reliability and Inter-Device Agreement Between a Portable Handheld Ultrasound Scanner and a Conventional Ultrasound System for Assessing the Thickness of the Rectus Femoris and Vastus Intermedius

by Carlante Emerson, Hyun K. Kim, Brian A. Irving and Efthymios Papadopoulos

J. Funct. Morphol. Kinesiol. 2025, 10(3), 299; https://doi.org/10.3390/jfmk10030299 (registering DOI) - 1 Aug 2025

Abstract

Background: Ultrasound (U/S) can be used to evaluate skeletal muscle characteristics in clinical and sports settings. Handheld U/S devices have recently emerged as a cheaper and portable alternative to conventional U/S systems. However, further research is warranted on their reliability. We assessed the reliability and inter-device agreement between a handheld U/S device (Clarius L15 HD₃) and a more conventional U/S system (GE LOGIQ e) for measuring the thickness of the rectus femoris (RF) and vastus intermedius (VI). Methods: Cross-sectional images of the RF and VI muscles were obtained in 20 participants by two assessors, and on two separate occasions by one of those assessors, using the Clarius L15 HD₃and GE LOGIQ e devices. RF and VI thickness measurements were obtained to determine the intra-rater reliability, inter-rater reliability, and inter-device agreement. Results: All intraclass correlation coefficients (ICCs) were above 0.9 for intra-rater reliability (range: 0.94 to 0.97), inter-rater reliability (ICC: 0.97), and inter-device agreement (ICC: 0.98) when comparing the two devices in assessing RF and VI thickness. For the RF, the Bland–Altman plot revealed a mean difference of 0.06 ± 0.07 cm, with limits of agreement ranging from 0.21 to −0.09, whereas for the VI, the Bland–Altman plot showed a mean difference of 0.07 ± 0.10 cm, with limits of agreement ranging from 0.27 to −0.13. Conclusions: The handheld Clarius L15 HD₃was reliable and demonstrated high agreement with the more conventional GE LOGIQ e for assessing the thickness of the RF and VI in young, healthy adults. Full article

(This article belongs to the Section Kinesiology and Biomechanics)

14 pages, 2889 KiB

Open AccessArticle

Ensuring Reproducibility and Deploying Models with the Image2Radiomics Framework: An Evaluation of Image Processing on PanNET Model Performance

by Florent Tixier, Felipe Lopez-Ramirez, Emir A. Syailendra, Alejandra Blanco, Ammar A. Javed, Linda C. Chu, Satomi Kawamoto and Elliot K. Fishman

Cancers 2025, 17(15), 2552; https://doi.org/10.3390/cancers17152552 (registering DOI) - 1 Aug 2025

Abstract

Background/Objectives: To evaluate the importance of image processing in a previously validated model for detecting pancreatic neuroendocrine tumors (PanNETs) and to introduce Image2Radiomics, a new framework that ensures reproducibility of the image processing pipeline and facilitates the deployment of radiomics models. Methods: A previously validated model for identifying PanNETs from CT images served as the reference. Radiomics features were re-extracted using Image2Radiomics and compared to those from the original model using performance metrics. The impact of nine alterations to the image processing pipeline was evaluated. Prediction discrepancies were quantified using the mean ± SD of absolute differences in PanNET probability and the percentage of classification disagreement. Results: The reference model was successfully replicated with Image2Radiomics, achieving a Cohen’s kappa coefficient of 1. Alterations to the image processing pipeline led to reductions in model performance, with AUC dropping from 0.87 to 0.71 when image windowing was removed. Prediction disagreements were observed in up to 45% of patients. Even minor changes, such as switching the library used for spatial resampling, resulted in up to 21% disagreement. Conclusions: Reproducing image processing pipelines remains challenging and limits the clinical deployment of radiomics models. While this study is limited to one model and imaging modality, the findings underscore a common risk in radiomics reproducibility. The Image2Radiomics framework addresses this issue by allowing researchers to define and share complete processing pipelines in a standardized way, improving reproducibility and facilitating model deployment in clinical and multicenter settings. Full article

(This article belongs to the Special Issue Application of Artificial Intelligence-Based Approaches in Cancer Diagnosis, Treatment and Prognosis)

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