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Purpose: Diffusion-weighted (DW) and dynamic contrast-enhanced magnetic resonance imaging (MRI) are increasingly applied for the assessment of functional tissue biomarkers for diagnosis, lesion characterization, or for monitoring of treatment response. However, these techniques are vulnerable to the influence of various factors, so there is a necessity for a standardized MR quality assurance procedure utilizing a phantom to facilitate the reliable estimation of repeatability of these quantitative biomarkers arising from technical factors (e.g., B1 variation) affecting acquisition on scanners of different vendors and field strengths. The purpose of this study is to present a novel phantom designed for use in quality assurance for multicenter trials, and the associated repeatability measurements of functional and quantitative imaging protocols across different MR vendors and field strengths.
Methods: A cylindrical acrylic phantom was manufactured containing 7 vials of polyvinylpyrrolidone (PVP) solutions of different concentrations, ranging from 0% (distilled water) to 25% w/w, to create a range of different MR contrast parameters. Temperature control was achieved by equilibration with ice-water. Repeated MR imaging measurements of the phantom were performed on four clinical scanners (two at 1.5 T, two at 3.0 T; two vendors) using the same scanning protocol to assess the long-term and short-term repeatability. The scanning protocol consisted of DW measurements, inversion recovery (IR) T1 measurements, multiecho T2 measurement, and dynamic T1-weighted sequence allowing multiple variable flip angle (VFA) estimation of T1 values over time. For each measurement, the corresponding calculated parameter maps were produced. On each calculated map, regions of interest (ROIs) were drawn within each vial and the median value of these voxels was assessed. For the dynamic data, the autocorrelation function and their variance were calculated; for the assessment of the repeatability, the coefficients of variation (CoV) were calculated.
Results: For both field strengths across the available vendors, the apparent diffusion coefficient (ADC) at 0 °C ranged from (1.12 ± 0.01) × 10(-3) mm(2)/s for pure water to (0.48 ± 0.02) × 10(-3) mm(2)/s for the 25% w/w PVP concentration, presenting a minor variability between the vendors and the field strengths. T2 and IR-T1 relaxation time results demonstrated variability between the field strengths and the vendors across the different acquisitions. Moreover, the T1 values derived from the VFA method exhibited a large variation compared with the IR-T1 values across all the scanners for all repeated measurements, although the calculation of the standard deviation of the VFA-T1 estimate across each ROI and the autocorrelation showed a stability of the signal for three scanners, with autocorrelation of the signal over the dynamic series revealing a periodic variation in one scanner. Finally, the ADC, the T2, and the IR-T1 values exhibited an excellent repeatability across the scanners, whereas for the dynamic data, the CoVs were higher.
Conclusions: The combination of a novel PVP phantom, with multiple compartments to give a physiologically relevant range of ADC and T1 values, together with ice-water as a temperature-controlled medium, allows reliable quality assurance measurements that can be used to measure agreement between MRI scanners, critical in multicenter functional and quantitative imaging studies.
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http://dx.doi.org/10.1118/1.4948997 | DOI Listing |
JMIR Med Educ
December 2024
Department of Psychiatry, Osaka University Graduate School of Medicine, Suita, Japan.
This study evaluated the performance of ChatGPT with GPT-4 Omni (GPT-4o) on the 118th Japanese Medical Licensing Examination. The study focused on both text-only and image-based questions. The model demonstrated a high level of accuracy overall, with no significant difference in performance between text-only and image-based questions.
View Article and Find Full Text PDFMed Phys
December 2024
University Clinic for Medical Radiation Physics, Medical Campus Pius Hospital, Carl von Ossietzky University, Oldenburg, Germany.
Background: Modern radiation therapy techniques, such as intensity-modulated radiation therapy (IMRT) and volumetric-modulated arc therapy (VMAT), use complex fluence modulation strategies to achieve optimal patient dose distribution. Ensuring their accuracy necessitates rigorous patient-specific quality assurance (PSQA), traditionally done through pretreatment measurements with detector arrays. While effective, these methods are labor-intensive and time-consuming.
View Article and Find Full Text PDFArh Hig Rada Toksikol
December 2024
2University Hospital Centre Zagreb, Department for Quality Assurance and Improvement in Healthcare, Zagreb, Croatia.
The burnout syndrome has been in the focus of occupational health experts for several decades, and a new diagnostic tool - Burnout Assessment Tool (BAT-23) - has given a strong impetus to its research. The tool is designed to self-assess four core dimensions of the burnout syndrome: chronic exhaustion, cognitive and emotional impairment at work, and mental distancing from work. However, little is known about how burnout is assessed from the perspective of a colleague.
View Article and Find Full Text PDFPhys Imaging Radiat Oncol
October 2024
University of Newcastle, University Drive, Newcastle, 2308, New South Wales, Australia.
The aim of this work was to evaluate results of a remote electronic portal imaging based dosimetric auditing method using Task-Group 218 clinical gamma evaluation criteria (3%,2 mm, 10% dose threshold). For intensity modulated radiation therapy the results were (mean ± 1 SD) 97.9 ± 4.
View Article and Find Full Text PDFHealth Informatics J
December 2024
The University of Queensland, Brisbane, QLD, Australia.
Objective: This study aimed to assess the practicality and trustworthiness of explainable artificial intelligence (XAI) methods used for explaining clinical predictive models.
Methods: Two popular XAIs used for explaining clinical predictive models were evaluated based on their ability to generate domain-appropriate representations, impact clinical workflow, and consistency. Explanations were benchmarked against true clinical deterioration triggers recorded in the data system and agreement was quantified.
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