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Status: Bibliographieeintrag

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Verfasst von:Hirjak, Dusan [VerfasserIn]   i
 Brandt, Geva A. [VerfasserIn]   i
 Peretzke, Robin [VerfasserIn]   i
 Fritze, Stefan [VerfasserIn]   i
 Meyer-Lindenberg, Andreas [VerfasserIn]   i
 Maier-Hein, Klaus H. [VerfasserIn]   i
 Neher, Peter [VerfasserIn]   i
Titel:Microstructural white matter biomarkers of symptom severity and therapy outcome in catatonia
Titelzusatz:rationale, study design and preliminary clinical data of the whiteCAT study
Verf.angabe:Dusan Hirjak, Geva A. Brandt, Robin Peretzke, Stefan Fritze, Andreas Meyer-Lindenberg, Klaus H. Maier-Hein, Peter F. Neher
E-Jahr:2024
Jahr:January 2024
Umfang:9 S.
Illustrationen:Illustrationen
Fussnoten:Online verfügbar: 24. Mai 2023, Artikelversion: 18. Dezember 2023 ; Gesehen am 15.03.2024
Titel Quelle:Enthalten in: Schizophrenia research
Ort Quelle:Amsterdam [u.a.] : Elsevier Science, 1988
Jahr Quelle:2024
Band/Heft Quelle:263(2024) vom: Jan., Seite 160-168
ISSN Quelle:1573-2509
Abstract:The number of magnetic resonance imaging (MRI) studies on neuronal correlates of catatonia has dramatically increased in the last 10 years, but conclusive findings on white matter (WM) tracts alterations underlying catatonic symptoms are still lacking. Therefore, we conduct an interdisciplinary longitudinal MRI study (whiteCAT) with two main objectives: First, we aim to enroll 100 psychiatric patients with and 50 psychiatric patients without catatonia according to ICD-11 who will undergo a deep phenotyping approach with an extensive battery of demographic, psychopathological, psychometric, neuropsychological, instrumental and diffusion MRI assessments at baseline and 12 weeks follow-up. So far, 28 catatonia patients and 40 patients with schizophrenia or other primary psychotic disorders or mood disorders without catatonia have been studied cross-sectionally. 49 out of 68 patients have completed longitudinal assessment, so far. Second, we seek to develop and implement a new method for semi-automatic fiber tract delineation using active learning. By training supportive machine learning algorithms on the fly that are custom tailored to the respective analysis pipeline used to obtain the tractogram as well as the WM tract of interest, we plan to streamline and speed up this tedious and error-prone task while at the same time increasing reproducibility and robustness of the extraction process. The goal is to develop robust neuroimaging biomarkers of symptom severity and therapy outcome based on WM tracts underlying catatonia. If our MRI study is successful, it will be the largest longitudinal study to date that has investigated WM tracts in catatonia patients.
DOI:doi:10.1016/j.schres.2023.05.011
URL:Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.

kostenfrei: Volltext: https://doi.org/10.1016/j.schres.2023.05.011
 kostenfrei: Volltext: https://www.sciencedirect.com/science/article/pii/S0920996423001913
 DOI: https://doi.org/10.1016/j.schres.2023.05.011
Datenträger:Online-Ressource
Sprache:eng
Sach-SW:Catatonia
 DTI
 Longitudinal
 MRI
 Outcome
K10plus-PPN:188348085X
Verknüpfungen:→ Zeitschrift

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