| Autor: |
Vitus Gosch, Kersten Villringer, Ivana Galinovic, Ramanan Ganeshan, Sophie K. Piper, Jochen B. Fiebach, Ahmed Khalil |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
Frontiers in Neurology, Vol 14 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
1664-2295 |
| DOI: |
10.3389/fneur.2023.1203241 |
| Popis: |
PurposeAutomated lesion segmentation is increasingly used in acute ischemic stroke magnetic resonance imaging (MRI). We explored in detail the performance of apparent diffusion coefficient (ADC) thresholding for delineating baseline diffusion-weighted imaging (DWI) lesions.MethodsRetrospective, exploratory analysis of the prospective observational single-center 1000Plus study from September 2008 to June 2013 (clinicaltrials.org; NCT00715533). We built a fully automated lesion segmentation algorithm using a fixed ADC threshold (≤620 × 10–6 mm2/s) to delineate the baseline DWI lesion and analyzed its performance compared to manual assessments. Diagnostic capabilities of best possible ADC thresholds were investigated using receiver operating characteristic curves. Influential patient factors on ADC thresholding techniques’ performance were studied by conducting multiple linear regression.Results108 acute ischemic stroke patients were selected for analysis. The median Dice coefficient for the algorithm was 0.43 (IQR 0.20–0.64). Mean ADC values in the DWI lesion (β = −0.68, p |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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