The Diagnostic Ability of rs-DWI to Detect Subtle Acute Infarction Lesion in the Different Regions of the Brain and the Comparison between Different b-Values

Design and Computational Validation of γ-Ray Shielding Effectiveness in Heavy Metal/Rare Earth Oxide-Natural Rubber Composites

This study involved the preparation of natural rubber-based composites incorporating varying proportions of heavy metals and rare earth oxides (Sm2O3, Ta2O5, and Bi2O3). The investigation analyzed several parameters of the samples, including mass attenuation coefficients (general, photoelectric absorption, and scattering), linear attenuation coefficients (μ), half-value layers (HVLs), tenth-value layers (TVLs), mean free paths (MFPs), and radiation protection efficiencies (RPEs), utilizing the Monte Carlo simulation software Geant4 and the WinXCom database across a gamma-ray energy spectrum of 40-150 keV. The study also compared the computational discrepancies among these measurements. Compared to rubber composites doped with single-component fillers, multi-component mixed shielding materials significantly mitigate the shielding deficiencies observed with single-component materials, thereby broadening the γ-ray energy spectrum for which the composites provide effective shielding. Subsequently, the simulation outcomes were juxtaposed with experimental data derived from a 133Ba (80 keV) γ-source. The findings reveal that the simulated results align closely with the experimental observations. When compared to the WinXCom database, the Geant4 software demonstrates superior accuracy in deriving radiation shielding parameters and notably enhances experimental efficiency.

Diagnostic Benefit of High b-Value Computed Diffusion-Weighted Imaging in Patients with Hepatic Metastasis

Diffusion-weighted imaging (DWI) has rapidly become an essential tool for the detection of malignant liver lesions. The aim of this study was to investigate the usefulness of high b-value computed DWI (c-DWI) in comparison to standard DWI in patients with hepatic metastases. In total, 92 patients with histopathologic confirmed primary tumors with hepatic metastasis were retrospectively analyzed by two readers. DWI was obtained with b-values of 50, 400 and 800 or 1000 s/mm² on a 1.5 T magnetic resonance imaging (MRI) scanner. C-DWI was calculated with a monoexponential model with high b-values of 1000, 2000, 3000, 4000 and 5000 s/mm². All c-DWI images with high b-values were compared to the acquired DWI sequence at a b-value of 800 or 1000 s/mm² in terms of volume, lesion detectability and image quality. In the group of a b-value of 800 from a b-value of 2000 s/mm², hepatic lesion sizes were significantly smaller than on acquired DWI (metastases lesion sizes b = 800 vs. b 2000 s/mm²: mean 25 cm³ (range 10-60 cm³) vs. mean 17.5 cm³ (range 5-35 cm³), p < 0.01). In the second group at a high b-value of 1500 s/mm², liver metastases were larger than on c-DWI at higher b-values (b = 1500 vs. b 2000 s/mm², mean 10 cm³ (range 4-24 cm³) vs. mean 9 cm³ (range 5-19 cm³), p < 0.01). In both groups, there was a clear reduction in lesion detectability at b = 2000 s/mm², with hepatic metastases being less visible compared to c-DWI images at b = 1500 s/mm² in at least 80% of all patients. Image quality dropped significantly starting from c-DWI at b = 3000 s/mm². In both groups, almost all high b-values images at b = 4000 s/mm² and 5000 s/mm² were not diagnostic due to poor image quality. High c-DWI b-values up to b = 1500 s/mm² offer comparable detectability for hepatic metastases compared to standard DWI. Higher b-value images over 2000 s/mm² lead to a noticeable reduction in imaging quality, which could hamper diagnosis.

Impact of different b-value combinations on radiomics features of apparent diffusion coefficient in cervical cancer

Background

The impact of variable b-value combinations on apparent diffusion coefficient (ADC)-based radiomics features has not been fully addressed in literature.

Purpose

To investigate the correlation between radiomics features extracted from ADC maps and various b-value combinations in cervical cancer.

Material and Methods

Diffusion-weighted images (b-values: 0, 600, 800, and 1000 s/mm2) of 20 patients with cervical cancer were included. Tumors were identified with the largest transversal cross-section and manually segmented by radiologist. For each b-value combination, 92 radiomics features were extracted and coefficient of variance (CV) was used to evaluate the robustness of radiomics features with different b-value combinations. Features with CV > 5% were normalized by the mean feature variation across the group.

Results

Out of a total of 92 radiomics features, 18 were classified as robust features with CV ≤5%. Among the rest (CV > 5%), 11, 23, and 40 features demonstrated 5%< CV ≤10%, 10%< CV ≤20%, and CV > 20%, respectively. A subset of features in each category (CV > 5%) showed strong correlation with the b-value combination variation, including 44% (7/16) features in gray level co-occurrence matrix, 62% (8/13) features in gray level dependence matrix, 64% (9/14) features in first order, 50% (8/16) features in gray level run length matrix, 57% (8/14) features in gray level size matrix, and 20% (1/5) features in neighborhood gray-tone difference matrix.

Conclusions

Variations in b-value combinations demonstrated impact on radiomics features extracted from ADC maps for cervical cancer. The radiomics features with CV <5% can be considered as robust features and are recommended to be used in multicenter radiomics studies.