Analyzing temporal imaging patterns in acute ischemic stroke via DICOM-timestamps
Abstract Acute stroke management is time-sensitive, making time data crucial for both research and quality management. However, these time data are often not reliably captured in routine clinical practice. In this proof-of-concept study we analysed image-based time data automatically captured in the...
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Nature Portfolio
2025-01-01
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| Online Access: | https://doi.org/10.1038/s41598-025-85315-5 |
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| author | Alexander Rau Marco Reisert Benedikt Frank Cornelius Deuschl Maximilian F Russe Samer Elsheikh Martin Köhrmann Horst Urbach Elias Kellner |
| author_facet | Alexander Rau Marco Reisert Benedikt Frank Cornelius Deuschl Maximilian F Russe Samer Elsheikh Martin Köhrmann Horst Urbach Elias Kellner |
| author_sort | Alexander Rau |
| collection | DOAJ |
| description | Abstract Acute stroke management is time-sensitive, making time data crucial for both research and quality management. However, these time data are often not reliably captured in routine clinical practice. In this proof-of-concept study we analysed image-based time data automatically captured in the DICOM format. We enrolled data from two separate stroke centers (n = 3136 and n = 2089). Data from the first center was additionally separated into groups with large-vessel-occlusion (LVO, n = 1.092), medium-vessel-occlusions (MVO, n = 416), and no occlusion (NVO, n = 1630). The DICOM-tag StudyTime was used to analyze the distribution of scan times throughout the day. Additionally, manually documented onset- and admission were extracted from the patients’ records in a subset of cases (n = 347). Timestamps were compared across centers and occlusion groups, and a probabilistic model was developed to illustrate and compare stroke occurrence patterns throughout the day. The temporal distribution of the scan times at both centers was exceptionally consistent with a peak around noon and a nighttime low. The groups with vessel occlusions showed an earlier peak compared to those without (p < 0.04). The median interval between admission and scan time was 23 min, while the median onset-to-imaging time was 1 h:54 min. This proof-of-concept study indicates that DICOM-timestamps can reveal insights into the temporal patterns of stroke imaging and may be a promising tool for quality control and stroke research in general since they are always automatically captured by imaging devices as opposed to manual data collection in routine clinical practice. |
| format | Article |
| id | doaj-art-6f825581e6444d3c8af1069752649e34 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
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| series | Scientific Reports |
| spelling | doaj-art-6f825581e6444d3c8af1069752649e342025-01-12T12:21:30ZengNature PortfolioScientific Reports2045-23222025-01-011511710.1038/s41598-025-85315-5Analyzing temporal imaging patterns in acute ischemic stroke via DICOM-timestampsAlexander Rau0Marco Reisert1Benedikt Frank2Cornelius Deuschl3Maximilian F Russe4Samer Elsheikh5Martin Köhrmann6Horst Urbach7Elias Kellner8Department of Neuroradiology, Medical Center – University of Freiburg, Faculty of Medicine, University of FreiburgMedical Physics, Department of Diagnostic and Interventional Radiology, Medical Center – University of Freiburg, Faculty of Medicine, University of FreiburgDepartment of Neurology and Center for Translational Neuro- and Behavioral Sciences (C-TNBS), University Hospital EssenFaculty of Medicine, Institute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital EssenDepartment of Diagnostic and Interventional Radiology, Medical Center – University of Freiburg, Faculty of Medicine, University of FreiburgDepartment of Neuroradiology, Medical Center – University of Freiburg, Faculty of Medicine, University of FreiburgDepartment of Neurology and Center for Translational Neuro- and Behavioral Sciences (C-TNBS), University Hospital EssenDepartment of Neuroradiology, Medical Center – University of Freiburg, Faculty of Medicine, University of FreiburgMedical Physics, Department of Diagnostic and Interventional Radiology, Medical Center – University of Freiburg, Faculty of Medicine, University of FreiburgAbstract Acute stroke management is time-sensitive, making time data crucial for both research and quality management. However, these time data are often not reliably captured in routine clinical practice. In this proof-of-concept study we analysed image-based time data automatically captured in the DICOM format. We enrolled data from two separate stroke centers (n = 3136 and n = 2089). Data from the first center was additionally separated into groups with large-vessel-occlusion (LVO, n = 1.092), medium-vessel-occlusions (MVO, n = 416), and no occlusion (NVO, n = 1630). The DICOM-tag StudyTime was used to analyze the distribution of scan times throughout the day. Additionally, manually documented onset- and admission were extracted from the patients’ records in a subset of cases (n = 347). Timestamps were compared across centers and occlusion groups, and a probabilistic model was developed to illustrate and compare stroke occurrence patterns throughout the day. The temporal distribution of the scan times at both centers was exceptionally consistent with a peak around noon and a nighttime low. The groups with vessel occlusions showed an earlier peak compared to those without (p < 0.04). The median interval between admission and scan time was 23 min, while the median onset-to-imaging time was 1 h:54 min. This proof-of-concept study indicates that DICOM-timestamps can reveal insights into the temporal patterns of stroke imaging and may be a promising tool for quality control and stroke research in general since they are always automatically captured by imaging devices as opposed to manual data collection in routine clinical practice.https://doi.org/10.1038/s41598-025-85315-5DICOM-timestampsAcute ischemic strokeProcess management |
| spellingShingle | Alexander Rau Marco Reisert Benedikt Frank Cornelius Deuschl Maximilian F Russe Samer Elsheikh Martin Köhrmann Horst Urbach Elias Kellner Analyzing temporal imaging patterns in acute ischemic stroke via DICOM-timestamps Scientific Reports DICOM-timestamps Acute ischemic stroke Process management |
| title | Analyzing temporal imaging patterns in acute ischemic stroke via DICOM-timestamps |
| title_full | Analyzing temporal imaging patterns in acute ischemic stroke via DICOM-timestamps |
| title_fullStr | Analyzing temporal imaging patterns in acute ischemic stroke via DICOM-timestamps |
| title_full_unstemmed | Analyzing temporal imaging patterns in acute ischemic stroke via DICOM-timestamps |
| title_short | Analyzing temporal imaging patterns in acute ischemic stroke via DICOM-timestamps |
| title_sort | analyzing temporal imaging patterns in acute ischemic stroke via dicom timestamps |
| topic | DICOM-timestamps Acute ischemic stroke Process management |
| url | https://doi.org/10.1038/s41598-025-85315-5 |
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