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. 2023 Aug 2;13(1):12551.
doi: 10.1038/s41598-023-39831-x.

Duration and accuracy of automated stroke CT workflow with AI-supported intracranial large vessel occlusion detection

Affiliations

Duration and accuracy of automated stroke CT workflow with AI-supported intracranial large vessel occlusion detection

Sander E Temmen et al. Sci Rep. .

Abstract

The Automation Platform (AP) is a software platform to support the workflow of radiologists and includes a stroke CT package with integrated artificial intelligence (AI) based tools. The aim of this study was to evaluate the diagnostic performance of the AP for the detection of intracranial large vessel occlusions (LVO) on conventional CT angiography (CTA), and the duration of CT processing in a cohort of acute stroke patients. The diagnostic performance for intracranial LVO detection on CTA by the AP was evaluated in a retrospective cohort of 100 acute stroke patients and compared to the diagnostic performance of five radiologists with different levels of experience. The reference standard was set by an independent neuroradiologist, with access to the readings of the different radiologists, clinical data, and follow-up. The data processing time of the AP for ICH detection on non-contrast CT, LVO detection on CTA, and the processing of CTP maps was assessed in a subset 60 patients of the retrospective cohort. This was compared to 13 radiologists, who were prospectively timed for the processing and reading of 21 stroke CTs. The AP showed shorter processing time of CTA (mean 60 versus 395 s) and CTP (mean 196 versus 243-349 s) as compared to radiologists, but showed lower sensitivity for LVO detection (sensitivity 77% of the AP vs mean sensitivity 87% of radiologists). If the AP would have been used as a stand-alone system, 1 ICA occlusion, 2 M1 occlusions and 8 M2 occlusions would have been missed, which would be eligible for mechanical thrombectomy. In conclusion, the AP showed shorter processing time of CTA and CTP as compared with radiologists, which illustrates the potential of the AP to speed-up the diagnostic work-up. However, its performance for LVO detection was lower as compared with radiologists, especially for M2 vessel occlusions.

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Conflict of interest statement

Author FM is member editorial board Neuroradiology, Speaker bureau Canon Medical Systems. Other authors: none.

Figures

Figure 1
Figure 1
Timelines of the duration of data processing for the Automation Platform and radiologists with different levels of experience (4 neuroradiologists, 4 non-neuroradiologists and 5 radiology residents). Each timeframe represents the mean duration of processing/reading, with the minimum and maximum times (range) provided in seconds. The durations were times manually. ICH: intracerebral hemorrhage, LVO: large vessel occlusion, ASPECTS: Alberta Stroke Program Early CT Score, CTP: CT perfusion.

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