Radiomics, which integrates the comprehensive characterization of imaging phenotypes with machine learning algorithms, is increasingly recognized for its potential in the diagnosis and prognosis of oncological conditions. However, the repeatability and reproducibility of radiomic features are critical challenges that hinder their widespread clinical adoption. This review aims to address the paucity of discussion regarding the factors that influence the reproducibility and repeatability of radiomic features and their subsequent impact on the application of radiomic models. We provide a synthesis of the literature on the repeatability and reproducibility of CT/MR-based radiomic features, examining sources of variation, the number of reproducible features, and the availability of individual feature repeatability indices. We differentiate sources of variation into random effects, which are challenging to control but can be quantified through simulation methods such as perturbation, and biases, which arise from scanner variability and inter-reader differences and can significantly affect the generalizability of radiomic model performance in diverse settings. Four suggestions for repeatability and reproducibility studies are suggested: (1) detailed reporting of variation sources, (2) transparent disclosure of calculation parameters, (3) careful selection of suitable reliability indices, and (4) comprehensive reporting of reliability metrics. This review underscores the importance of random effects in feature selection and harmonizing biases between development and clinical application settings to facilitate the successful translation of radiomic models from research to clinical practice.

The Cr ion doped Y-type hexaferrite Ba_0.5Sr_1.5Zn₂Fe_11.4Cr_0.6O₂₂ has been found to be a promising magnetoelectric material for the non-zero spontaneous electric polarization. A newly emerging transition at 183 K separates the low-field ferroelectric phase into two regions with reversal and non-reversal polarization respectively.

The pursuit of multifunctional photodetectors (PDs) that combine broadband responsivity, high specific detectivity under low‐light conditions, and robust operation across extreme temperatures is a cornerstone for advancing next‐generation optical communication and imaging systems. Herein, we report a self‐powered PD FTO/CdS/Sb ₂ (S,Se) ₃ /Au via a low‐cost solution‐processed method. At zero bias, the Sb ₂ (S,Se) ₃ ‐based PD exhibits a responsivity of 0.6 A/W, a specific detectivity of 7.68 × 10 ¹² Jones, ultrafast response/recovery times of 1.13/1.90 µs, and a 3 dB bandwidth of 175 kHz under 785 nm illumination (4.09 µW/cm ² ). Most strikingly, the unencapsulated device exhibits excellent stability from 10 to 575 K, which is rarely reported for Sb ₂ (S,Se) ₃ ‐based PDs. The practical multifunctional applicability of this single PD is further validated by its successful integration as a high‐speed receiver in a visible light communication system and a sensing pixel for high‐resolution imaging. Compared with the reference Sb ₂ (S,Se) ₃ sample, the performance enhancement of the Sb ₂ (S,Se) ₃ /CdS heterojunction PD arises from the built‐in electric field ( E _bi ) that enables the effective carrier separation/extraction, and the heterojunction structure that reduces the interface/bulk trap densities of the Sb ₂ (S,Se) ₃ film. This work opens a promising avenue in near‐infrared imaging, light communication and extreme‐environment sensing.

Using the linear-response method, we investigate the phonon properties of β-cristobalite crystal under electronic excitation effect. We find that the transverse-acoustic phonon frequency becomes imaginary as the electron temperature is increased, which means that the lattice of β-cristobalite becomes unstable under intense laser irradiation. In addition, for the optic phonon mode, the LO(H)–TO(H) splitting disappears when the electronic temperature reaches a certain value, corresponding to the whole transverse-acoustic phonon branches becoming negative. It means that the electronic excitation destroys the macroscopic electric field of β-cristobalite. Based on the calculated phonon band structures, some thermodynamic properties are calculated as a function of temperature at different electronic temperatures. These investigations provide evidence that non-thermal melting takes place during a femtosecond pulse laser interaction with β-cristobalite.

Objectives: To evaluate the impact of tumor volume segmentation variability on the repeatability of radiomic features (RFs) and to determine how RF repeatability influences the generalizability of radiomic models for predicting overall survival (OS) in patients with oropharyngeal carcinoma (OPC). Methods: We retrospectively analyzed CT images from 1017 patients with oropharyngeal carcinoma across three institutions. Perturbation methods were applied to simulate variations in gross tumor volume segmentation. RFs were extracted from both the original images and Laplacian of Gaussian‐filtered images using different perturbation masks. RF repeatability was quantified using intra‐class correlation coefficients (ICC). Repeatable RFs were progressively incorporated into the modeling process according to different ICC thresholds to assess the influence of feature repeatability on model generalizability. Results: Incorporation of RFs with ICC values between 0.7 and 0.8 improved the AUC index of the two‐year and three‐year OS models in external validation cohorts. Using an ICC threshold of 0.7, RFs were classified into high‐ and low‐repeatability groups, and OS models were trained and validated using the training, internal testing, and external validation cohorts. Across all cohorts, the OS model trained with high‐repeatability RFs demonstrated significantly superior performance compared to the model trained with low‐repeatability RFs. Conclusion: The findings demonstrate that selecting RFs with ICC values greater than 0.7 substantially enhances both the generalizability and predictive performance of CT‐based radiomic models for patients with OPC. This study further underscores the importance of considering RF repeatability, particularly in the presence of tumor volume segmentation variability, to improve the robustness and clinical reliability of radiomic models.