Analyzing temporal imaging patterns in acute ischemic stroke via DICOM-timestamps

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.