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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. [ABSTRACT FROM AUTHOR]

Background: A power injector is typically employed to deliver a contrast agent to a subject (e.g., humans, animals, phantoms) during MRI, but it is costly and cannot inject more than one subject at a time. Conventional syringe pumps housing multiple syringes are typically non‐MRI compatible and, thus, should be placed outside the MRI room. Purpose: To develop the prototype of a cost‐effective, easy‐to‐use, reliable syringe pump that could be deployed inside a clinical MRI bore and operated on during a scan. Methods: The MRI‐compatible syringe pump (MSP) was designed using Solidworks 3D modeling software and fabricated using a Raise3D Pro2 Printer. The MSP was designed to infuse up to three syringes simultaneously. The injection speed was mainly controlled with different gear sets in the escapement unit and further adjusted by changing the effective hairspring length via a pinch pin. The MSP was evaluated with three gear sets (gear ratios: 0.20:1, 0.56:1, and 1.09:1) and 10 different effective hairspring lengths at each gear ratio. A video was recorded while operating MSP at each injection speed to calculate the volume injection rate of a 5‐mL syringe (mL/s). The MSP was operated five times repeatedly at each injection speed, and the mean and standard deviation of the volume injection rate were calculated. Results: The volume injection rates produced by three gear ratios (0.20:1, 0.56:1, and 1.09:1) were 0.209 ± 0.003 mL/s, 0.411 ± 0.002 mL/s, and 0.625 ± 0.006 mL/s, respectively, at the full hairspring length. The injection rates of gear set 1 (gear ratio: 0.20:1) decreased from 0.273 ± 0.001 mL/s to 0.245 ± 0.001 mL/s with a decrement of 0.003 mL/s for 10 different effective hairspring lengths (r = 0.997, p < 0.001). The injection rates of gear set 2 (gear ratio: 0.56:1) decreased from 0.519 ± 0.003 mL/s to 0.469 ± 0.003 mL/s with a decrement of 0.006 mL/s (r = 0.987, p < 0.001), and that of gear set 3 (gear ratio: 1.09:1) decreased from 0.779 ± 0.012 mL/s to 0.709 ± 0.005 mL/s with a decrement of 0.007 mL/s (r = 0.963, p < 0.001). The coefficient of variation in the injection rate measurement was 0.727 ± 0.346%. Conclusions: The MSP is a portable device that can reliably deliver a liquid agent to multiple subjects inside a clinical MRI bore during a scan. [ABSTRACT FROM AUTHOR]

Purpose: To develop a disposable point‐of‐care portable perfusion phantom (DP4) and validate its clinical utility in a multi‐institutional setting for quantitative dynamic contrast‐enhanced magnetic resonance imaging (qDCE‐MRI). Methods: The DP4 phantom was designed for single‐use and imaged concurrently with a human subject so that the phantom data can be utilized as the reference to detect errors in qDCE‐MRI measurement of human tissues. The change of contrast‐agent concentration in the phantom was measured using liquid chromatography‐mass spectrometry. The repeatability of the contrast enhancement curve (CEC) was assessed with five phantoms in a single MRI scanner. Five healthy human subjects were recruited to evaluate the reproducibility of qDCE‐MRI measurements. Each subject was imaged concurrently with the DP4 phantom at two institutes using three 3T MRI scanners from three different vendors. Pharmacokinetic (PK) parameters in the regions of liver, spleen, pancreas, and paravertebral muscle were calculated based on the Tofts model (TM), extended Tofts model (ETM), and shutter speed model (SSM). The reproducibility of each PK parameter over three measurements was evaluated with the intraclass correlation coefficient (ICC) and compared before and after DP4‐based error correction. Results: The contrast‐agent concentration in the DP4 phantom was linearly increased over 10 min (0.17 mM/min, measurement accuracy: 96%) after injecting gadoteridol (100 mM) at a constant rate (0.24 ml/s, 4 ml). The repeatability of the CEC within the phantom was 0.997 when assessed by the ICC. The reproducibility of the volume transfer constant, Ktrans, was the highest of the PK parameters regardless of the PK models. The ICCs of Ktrans in the TM, ETM, and SSM before DP4‐based error correction were 0.34, 0.39, and 0.72, respectively, while those increased to 0.93, 0.98, and 0.86, respectively, after correction. Conclusions: The DP4 phantom is reliable, portable, and capable of significantly improving the reproducibility of qDCE‐MRI measurements. [ABSTRACT FROM AUTHOR]

Since the first report on the unexpected ferroelectricity of fluorite‐structure oxides in 2011, this topic has provided a pathway for new research directions and opportunities. Based on theoretical calculations and experimental demonstrations, it is now well known that fluorite‐structure ferroelectrics are compatible with complementary metal–oxide–semiconductor technology and exhibit ferroelectric properties at extremely thin (<10 nm) thicknesses. It should be noted that the noncentrosymmetric orthorhombic phase, which is responsible for ferroelectric behavior, is formed even at low temperatures (400 °C or less). Herein, the various factors such as doping effects, deposition method, annealing method and conditions, and substrate material are reviewed, focusing on thermal budget, especially the low‐temperature annealing process for formation of the ferroelectric phase. These low‐thermal‐budget processes facilitate not only the integration of ferroelectric circuits in the back‐end‐of‐line to increase the effective memory area and add more functionalities but also applications for flexible and wearable electronics. [ABSTRACT FROM AUTHOR]

Since HfO2‐based ferroelectric films were reported in 2011, several doping/alloying elements have been introduced to secure interesting ferroelectric/antiferroelectric properties of Hf‐based fluorite‐structured thin films. Using a conventional approach by atomic layer deposition (ALD), an enormous number of experiments would be required to reveal the compositional effects of doping/alloying components in ternary and quaternary systems. Therefore, for a comprehensive study of the ferroelectric properties of HfxZr1−xO2, a novel combinatorial ALD technique that enables the fabrication of multicomponent films with a different composition ratio and thickness via saturated/non‐saturated ALD without changing the supercycle of each material is reported. The gradient of the amount of HfO2 over a 100 mm substrate is achieved using a lower Hf‐precursor temperature that results in an insufficient Hf‐precursor dose for saturated deposition. Systematic study on the HfxZr1−xO2 combinatorial library is carried out by spectroscopic ellipsometry, X‐ray photoelectron spectroscopy, and X‐ray diffraction. Furthermore, TiN/HfxZr1−xO2/TiN capacitors are fabricated to measure the remnant polarization. The obtained results clearly show the ferroelectric–antiferroelectric transition according to continuous composition change instead of discrete research. Therefore, a highly productive method for studying ferroelectricity changes in terms of a doping and a composition of HfO2‐based ferroelectric thin films through a novel ALD combinatorial approach is proposed. [ABSTRACT FROM AUTHOR]

Physiological properties of tumors can be measured both in vivo and noninvasively by diffusion‐weighted imaging and dynamic contrast‐enhanced magnetic resonance imaging. Although these techniques have been used for more than two decades to study tumor diffusion, perfusion, and/or permeability, the methods and studies on how to reduce measurement error and bias in the derived imaging metrics is still lacking in the literature. This is of paramount importance because the objective is to translate these quantitative imaging biomarkers (QIBs) into clinical trials, and ultimately in clinical practice. Standardization of the image acquisition using appropriate phantoms is the first step from a technical performance standpoint. The next step is to assess whether the imaging metrics have clinical value and meet the requirements for being a QIB as defined by the Radiological Society of North America's Quantitative Imaging Biomarkers Alliance (QIBA). The goal and mission of QIBA and the National Cancer Institute Quantitative Imaging Network (QIN) initiatives are to provide technical performance standards (QIBA profiles) and QIN tools for producing reliable QIBs for use in the clinical imaging community. Some of QIBA's development of quantitative diffusion‐weighted imaging and dynamic contrast‐enhanced QIB profiles has been hampered by the lack of literature for repeatability and reproducibility of the derived QIBs. The available research on this topic is scant and is not in sync with improvements or upgrades in MRI technology over the years. This review focuses on the need for QIBs in oncology applications and emphasizes the importance of the assessment of their reproducibility and repeatability. Level of Evidence: 5 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2019;49:e101–e121. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study was to develop a portable perfusion phantom and validate its utility in quantitative dynamic contrast-enhanced magnetic resonance imaging of the abdomen. Methods: A portable perfusion phantom yielding a reproducible contrast enhancement curve (CEC) was developed. A phantom package including perfusion and static phantoms were imaged simultaneously with each of three healthy human volunteers in two different 3T MR scanners. Look-up tables correlating reference (known) contrast concentrations with measured ones were created using either the static or perfusion phantom. Contrast maps of image slices showing four organs (liver, spleen, pancreas, and paravertebral muscle) were generated before and after data correction using the look-up tables. The contrast concentrations at 4.5 min after dosing in each of the four organs were averaged for each volunteer. The mean contrast concentrations (4 organs × 3 volunteers = 12) were compared for the two scanners, and the intra-class correlation coefficient (ICC) was calculated. Also, the ICC of the mean Ktrans values between the two scanners was calculated before and after data correction. Results: The repeatability coefficient of CECs of perfusion phantom was higher than 0.997 in all measurements. The ICC of the tissue contrast concentrations between the two scanners was 0.693 before correction, but increased to 0.974 after correction using the look-up tables (LUTs) of perfusion phantom. However, the ICC was not increased after correction using static phantom (ICC: 0.617). Similarly, the ICC of the Ktrans values was 0.899 before correction, but increased to 0.996 after correction using perfusion phantom LUTs. The ICC of the Ktrans values, however, was not increased when static phantom LUTs were used (ICC: 0.866). Conclusions: The perfusion phantom reduced variability in quantitating contrast concentration and Ktrans values of human abdominal tissues across different MR units, but static phantom did not. The perfusion phantom has the potential to facilitate multi-institutional clinical trials employing quantitative DCE-MRI to evaluate various abdominal malignancies. [ABSTRACT FROM AUTHOR]