Johan Koekkoek
Neurologist / Neuro-oncologist / Head of outpatient clinic
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Articles (10)
Arterial spin labeling (ASL) and dynamic susceptibility contrast (DSC) magnetic resonance imaging (MRI) have shown potential for differentiating tumor progression from pseudoprogression. For pseudocontinuous ASL with a single postlabeling delay, the presence of delayed arterial transit times (ATTs) could affect the evaluation of ASL‐MRI perfusion data. In this study, the influence of ATT artifacts on the perfusion assessment and differentiation between tumor progression and pseudoprogression were studied. This study comprised 66 adult patients (mean age 60 ± 13 years; 40 males) with a histologically confirmed glioblastoma who received postoperative radio (chemo)therapy. ASL‐MRI and DSC‐MRI scans were acquired at 3 months postradiotherapy as part of the standard clinical routine. These scans were visually scored regarding (i) the severity of ATT artifacts (%) on the ASL‐MRI scans only, scored by two neuroradiologists; (ii) perfusion of the enhancing tumor lesion; and (iii) radiological evaluation of tumor progression versus pseudoprogression by one neuroradiologist. The final outcome was based on combined clinical and radiological follow‐up until 9 months postradiotherapy. ATT artifacts were identified in all patients based on the mean scores of two raters. A significant difference between the radiological evaluation of ASL‐MRI and DSC‐MRI was observed only for ASL images with moderate ATT severity (30%–65%). The perfusion assessment showed ASL‐MRI tending more towards hyperperfusion than DSC‐MRI in the case of moderate ATT artifacts. In addition, there was a significant difference between the prediction of tumor progression with ASL‐MRI and the final outcome in the case of severe ATT artifacts (McNemar test, p = 0.041). Despite using ASL imaging parameters close to the recommended settings, ATT artifacts frequently occur in patients with treated brain tumors. Those artifacts could hinder the radiological evaluation of ASL‐MRI data and the detection of true disease progression, potentially affecting treatment decisions for patients with glioblastoma.
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2024
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2024
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2024
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2023
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2023
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2023
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2023
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2023
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2023
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2023
Collaborators (19)
Jeroen de Bresser
Leiden University Medical Center
Maarten Wijnenga
Erasmus University Rotterdam
Matthias J. P. van Osch
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Linda Dirven
Leiden University Medical Center
Guy M. McKhann
Columbia University Irving Medical Center
Tobias Walbert
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Elies Fuster-Garcia
Associate Professor (Profesor Titular)
Universitat Politècnica de València
Pim French
Assoc Prof
Erasmus MC
Steven Tobochnik
Dana-Farber Cancer Institute
Jessica Templer
Northwestern University
Ece Ercan
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Lydiane Hirschler
Leiden University Medical Center
Gilbert Hangel
Medical University of Vienna
Nico Sollmann
Technical University of Munich
Jan Petr
Amsterdam University Medical Centers
Matthew Grech-Sollars
University College London Hospitals NHS Foundation Trust
Marta Calvo-Imirizaldu
Clinica Universidad de Navarra
Vera C. Keil
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Florien Boele
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