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Purpose: ACR and AAPM task group's guidelines addressing commissioning for dedicated MR simulators were recently published. The goal of the current paper is to present the authors' 2-year experience regarding the commissioning and introduction of a QA program based on these guidelines and an associated automated workflow.
Methods: All mandatory commissioning tests suggested by AAPM report 284 were performed and results are reported for two MRI scanners (MAGNETOM Sola and Aera). Visual inspection, vendor clinical or service platform, third-party software, or in-house python-based code were used. Automated QA and data analysis was performed via vendor, in-house or third-party software. QATrack+ was used for QA data logging and storage. 3D geometric distortion, B inhomogeneity, EPI, and parallel imaging performance were evaluated.
Results: Contrasting with AAPM report 284 recommendations, homogeneity and RF tests were performed monthly. The QA program allowed us to detect major failures over time (shimming, gradient calibration and RF interference). Automated QA, data analysis, and logging allowed fast ACR analysis daily and monthly QA to be performed in 3 h. On the Sola, the average distortion is 1 mm for imaging radii of 250 mm or less. For radii of up to 200 mm, the maximum, average (standard deviation) distortion is 1.2 and 0.4 mm (0.3 mm). Aera values are roughly double the Sola for radii up to 200 mm. EPI geometric distortion, ghosting ratio, and long-term stability were found to be under the maximum recommended values. Parallel imaging SNR ratio was stable and close to the theoretical value (ideal g-factor). No major failures were detected during commissioning.
Conclusion: An automated workflow and enhanced QA program allowed to automatically track machine and environmental changes over time and to detect periodic failures and errors that might otherwise have gone unnoticed. The Sola is more geometrically accurate, with a more homogenous B field than the Aera.
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http://dx.doi.org/10.1002/acm2.14185 | DOI Listing |
Cereb Cortex
December 2024
Donders Institute for Brain, Cognition and Behaviour, Radboud University and Radboud University Medical Center, Kapittelweg 29, 6525 EN Nijmegen, The Netherlands.
In this study, we explored the relationship between developmental differences in gray matter structure and grammar learning ability in 159 Dutch-speaking individuals (8 to 25 yr). The data were collected as part of a recent large-scale functional MRI study (Menks WM, Ekerdt C, Lemhöfer K, Kidd E, Fernández G, McQueen JM, Janzen G. Developmental changes in brain activation during novel grammar learning in 8-25-year-olds.
View Article and Find Full Text PDFMagnetic resonance imaging (MRI) is commonly used in healthcare for its ability to generate diverse tissue contrasts without ionizing radiation. However, this flexibility complicates downstream analysis, as computational tools are often tailored to specific MRI types and lack generalizability across the full spectrum of scans used in healthcare. Here, we introduce a versatile framework for the development and validation of pan-contrast AI models that can exhaustively cater to the full spectrum of scans achievable with MRI, enabling model deployment across scanner models, scan types, and age groups.
View Article and Find Full Text PDFAdvances in magnetic resonance imaging (MRI) have revolutionized disease detection and treatment planning. However, as the volume and complexity of MRI data grow with increasing heterogeneity between institutions in imaging protocol, scanner technology, and data labeling, there is a need for a standardized methodology to efficiently identify, characterize, and label MRI sequences. Such a methodology is crucial for advancing research efforts that incorporate MRI data from diverse populations to develop robust machine learning models.
View Article and Find Full Text PDFMagn Reson Imaging
December 2024
Department of Radiology, Iwate Medical University, Yahaba, Japan.
Objective: The total examination time can be reduced if high-quality two-dimensional (2D) cine images can be collected post-contrast to minimize non-scanning time prior to late gadolinium-enhanced imaging. This study aimed to assess the equivalency of the pre-and post-contrast performance of 2D deep learning-based highly accelerated cardiac cine (DL cine) imaging by evaluating the image quality and the quantification of biventricular volumes and function in the clinical setting.
Material And Methods: Thirty patients (20 men, mean age 53.
Lancet Neurol
January 2025
Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland.
Background: Spinal cord injury results in permanent neurological impairment and disability due to the absence of spontaneous regeneration. NG101, a recombinant human antibody, neutralises the neurite growth-inhibiting protein Nogo-A, promoting neural repair and motor recovery in animal models of spinal cord injury. We aimed to evaluate the efficacy of intrathecal NG101 on recovery in patients with acute cervical traumatic spinal cord injury.
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