Dielectric performance of composites of BaTiO 3 and polymers for capacitor applications under microwave frequency

Composites of nano‐sized barium titanate (BaTiO3) with volume fractions up to 0.5 and poly(butylene terephthalate) (PBT) or linear low‐density polyethylene (LLDPE) were made via extrusion. Scanning electron microscopy demonstrated that BaTiO3 is well dispersed in the polymer matrices. The crystalline content (DSC) and thermal stability (TGA) of both polymers decreased with increasing BaTiO3 loading. Dielectric properties of the composites were measured using a vector network analyzer. Both dielectric permittivity and tangent loss increased with increasing BaTiO3 content. At 2.45 GHz, the dielectric permittivity for 48 vol% BaTiO3‐filled LLDPE and 43 vol% BaTiO3‐filled PBT was 25 and 21.2, respectively. There was a good fit between the Lichtenecker model and experimental data obtained up to a certain value, with the permittivity variations being dependent on volume fraction. The improved dielectric performance achieved on inclusion of BaTiO3 confirms both composite systems as potential candidates for microwave frequency capacitor applications

The ISMRM Open Science Initiative for Perfusion Imaging (OSIPI): Results from the OSIPI–Dynamic Contrast-Enhanced challenge

Purpose: K trans has often been proposed as a quantitative imaging biomarker for diagnosis,prognosis,andtreatmentresponseassessmentforvarioustumors.Noneofthe many software tools for K trans quantification are standardized. The ISMRM OpenScience Initiative for Perfusion Imaging–Dynamic Contrast-Enhanced (OSIPI-DCE)challenge was designed to benchmark methods to better help the efforts to standardize K trans measurement. Methods: A framework was created to evaluate K trans values produced by DCE-MRI analysis pipelines to enable benchmarking. The perfusion MRI community was invited to apply their pipelines for K trans quantification in glioblastoma from clinical and synthetic patients. Submissions were required to include the entrants’ K trans values, the applied software, and a standard operating procedure. These were evaluated using the proposed OSIPIgold score defined with accuracy, repeatability, and reproducibility components. Results: Across the 10 received submissions, the OSIPIgold score ranged from28% to 78% with a 59% median. The accuracy, repeatability, and reproducibility scores ranged from 0.54 to 0.92, 0.64 to 0.86, and 0.65 to 1.00, respectively(0–1=lowest–highest). Manual arterial input function selection markedly affected the reproducibility and showed greater variability in K trans analysis than automated methods. Furthermore, provision of a detailed standard operating procedure was critical for higher reproducibility. Conclusions: This study reports results from the OSIPI-DCE challenge and high-lights the high inter-software variability within K trans estimation, providing a framework for ongoing benchmarking against the scores presented. Through this challenge, the participating teams were ranked based on the performance of their software tools in the particular setting of this challenge. In a real-world clinical setting, many of these tools may perform differently with different benchmarking methodology

The ISMRM Open Science Initiative for Perfusion Imaging (OSIPI): Results from the OSIPI-Dynamic Contrast-Enhanced challenge

purpose: Ktrans$${K}^{\mathrm{trans}}$$ has often been proposed as a quantitative imaging biomarker for diagnosis, prognosis, and treatment response assessment for various tumors. None of the many software tools for Ktrans$${K}^{\mathrm{trans}}$$ quantification are standardized. the ISMRM open science initiative for perfusion imaging-dynamic contrast-enhanced (OSIPI-DCE) challenge was designed to benchmark methods to better help the efforts to standardize Ktrans$${K}^{\mathrm{trans}}$$ measurement. methods: a framework was created to evaluate Ktrans$${K}^{\mathrm{trans}}$$ values produced by DCE-MRI analysis pipelines to enable benchmarking. the perfusion MRI community was invited to apply their pipelines for Ktrans$${K}^{\mathrm{trans}}$$ quantification in glioblastoma from clinical and synthetic patients. submissions were required to include the entrants' Ktrans$${K}^{\mathrm{trans}}$$ values, the applied software, and a standard operating procedure. These were evaluated using the proposed OSIPIgold$$\mathrm{OSIP}{\mathrm{I}}_{\mathrm{gold}}$$ score defined with accuracy, repeatability, and reproducibility components. results: across the 10 received submissions, the OSIPIgold$$\mathrm{OSIP}{\mathrm{I}}_{\mathrm{gold}}$$ score ranged from 28% to 78% with a 59% median. The accuracy, repeatability, and reproducibility scores ranged from 0.54 to 0.92, 0.64 to 0.86, and 0.65 to 1.00, respectively (0-1 = lowest-highest). manual arterial input function selection markedly affected the reproducibility and showed greater variability in Ktrans$${K}^{\mathrm{trans}}$$ analysis than automated methods. furthermore, provision of a detailed standard operating procedure was critical for higher reproducibility. conclusions: This study reports results from the OSIPI-DCE challenge and highlights the high inter-software variability within Ktrans$${K}^{\mathrm{trans}}$$ estimation, providing a framework for ongoing benchmarking against the scores presented. through this challenge, the participating teams were ranked based on the performance of their software tools in the particular setting of this challenge. In a real-world clinical setting, many of these tools may perform differently with different benchmarking methodology

The ISMRM Open Science Initiative for Perfusion Imaging (OSIPI):Results from the OSIPI-Dynamic Contrast-Enhanced challenge

Purpose: (Formula presented.) has often been proposed as a quantitative imaging biomarker for diagnosis, prognosis, and treatment response assessment for various tumors. None of the many software tools for (Formula presented.) quantification are standardized. The ISMRM Open Science Initiative for Perfusion Imaging–Dynamic Contrast-Enhanced (OSIPI-DCE) challenge was designed to benchmark methods to better help the efforts to standardize (Formula presented.) measurement. Methods: A framework was created to evaluate (Formula presented.) values produced by DCE-MRI analysis pipelines to enable benchmarking. The perfusion MRI community was invited to apply their pipelines for (Formula presented.) quantification in glioblastoma from clinical and synthetic patients. Submissions were required to include the entrants' (Formula presented.) values, the applied software, and a standard operating procedure. These were evaluated using the proposed (Formula presented.) score defined with accuracy, repeatability, and reproducibility components. Results: Across the 10 received submissions, the (Formula presented.) score ranged from 28% to 78% with a 59% median. The accuracy, repeatability, and reproducibility scores ranged from 0.54 to 0.92, 0.64 to 0.86, and 0.65 to 1.00, respectively (0–1 = lowest–highest). Manual arterial input function selection markedly affected the reproducibility and showed greater variability in (Formula presented.) analysis than automated methods. Furthermore, provision of a detailed standard operating procedure was critical for higher reproducibility. Conclusions: This study reports results from the OSIPI-DCE challenge and highlights the high inter-software variability within (Formula presented.) estimation, providing a framework for ongoing benchmarking against the scores presented. Through this challenge, the participating teams were ranked based on the performance of their software tools in the particular setting of this challenge. In a real-world clinical setting, many of these tools may perform differently with different benchmarking methodology.</p