: Radiomics has become a valuable tool in medical imaging, but its clinical use is limited by data variability and a lack of reproducibility between centers. This study aims to assess the differences between two scanners and provide guidance on image acquisition methods to reduce variations between images obtained from different centers. : This study utilized medical images obtained in two different imaging centers, with two different 3T MRI scanners. For each scanner, 3D T2 FLAIR sequences were acquired in two forms: the raw and the clinical practice images typically used in diagnostic workflows. The differences between images were analyzed regarding resolution, SNR, CNR, and radiomic features. To facilitate comparison, bias field correction was applied, and the data were standardized to the same scale using Z-score normalization. Descriptive and inferential statistical methods were used to analyze the data. : The results show that there are significant differences between centers. Filtering and zero-padding significantly influence the resolution, SNR, CNR values, and radiomics features. Applying Z-score normalization has resolved variations in features sensitive to scale differences, but features reflecting dispersion and extreme values remain significantly different between scanners. Some feature differences may be resolved by analyzing the raw images in both centers. : Variations arise due to different acquisition parameters and the differing quality and sensitivity of the equipment. In multi-center studies, acquiring raw images and then applying standardized post-processing methods across all images can enhance the robustness of results. This approach minimizes technical differences, and preserves the integrity of the information, reflecting a more accurate representation of reality and contributing to more reliable and reproducible findings.
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http://dx.doi.org/10.3390/diagnostics15040485 | DOI Listing |
Anal Chim Acta
May 2025
School of Chemistry and Chemical Engineering, Jiangsu University, Zhenjiang, Jiangsu, 212013, PR China; Key Laboratory of Modern Agricultural Equipment and Technology (Ministry of Education), Jiangsu University, Zhenjiang, Jiangsu, 212013 PR China. Electronic address:
Background: Hypochlorous acid (HClO) is a crucial disinfectant in the food industry. It can be used to soak perishable foods like vegetables, fruits, eggs, fish, and raw meat before processing and storage, eliminating microorganisms, bacteria, fungi, and pathogens to ensure food safety. HClO also helps preserve vegetables and fruits by reducing ethylene production, delaying rotting, decreasing cell membrane permeability, inhibiting polyphenol oxidase activity, and postponing discoloration.
View Article and Find Full Text PDFMed Image Anal
March 2025
Vall d'Hebron Institute of Oncology (VHIO), Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain. Electronic address:
Diffusion Magnetic Resonance Imaging (dMRI) sensitises the MRI signal to spin motion. This includes Brownian diffusion, but also flow across intricate networks of capillaries. This effect, the intra-voxel incoherent motion (IVIM), enables microvasculature characterisation with dMRI, through metrics such as the vascular signal fraction f or the vascular Apparent Diffusion Coefficient (ADC) D.
View Article and Find Full Text PDFPhys Med Biol
March 2025
Grupo de Física Nuclear & IPARCOS, Universidad Complutense de Madrid, Facultad de CC. Físicas, Avda. Complutense s/n, Madrid, 28040, SPAIN.
Clinical implementation of in-beam PET monitoring in proton therapy requires the integration of an online fast and reliable dose calculation engine. This manuscript reports on the achievement of real-time reconstruction of 3D dose and activity maps with proton range verification from experimental in-beam PET measurements. Approach: Several cylindrical homogeneous PMMA phantoms were irradiated with a monoenergetic 70-MeV proton beam in a clinical facility.
View Article and Find Full Text PDFObjective: To enable fast and stable neonatal brain MR imaging by integrating learned neonate-specific subspace model and model-driven deep learning.
Methods: Fast data acquisition is critical for neonatal brain MRI, and deep learning has emerged as an effective tool to accelerate existing fast MRI methods by leveraging prior image information. However, deep learning often requires large amounts of training data to ensure stable image reconstruction, which is not currently available for neonatal MRI applications.
Radiol Med
March 2025
Department of Radiology, Suez Canal University, Ismailia, Egypt.
Background: The purpose of this study is to assess the usefulness of the novel abbreviated MR (AB-MR) protocol in the screening of women with an intermediate risk of breast cancer. Sixty women with a Tyrer-Cuzick model-determined intermediate risk of breast cancer underwent AB-MR, mammography, and tomosynthesis examinations; as an auxiliary procedure, ultrasound imaging was carried out. Every modality was allocated a final BI-RADS category.
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