AUTHOR=Kobeissi Hassan , Kallmes David F. , Benson John , Nagelschneider Alex , Madhavan Ajay , Messina Steven A. , Schwartz Kara , Campeau Norbert , Carr Carrie M. , Nasr Deena M. , Braksick Sherri , Scharf Eugene L. , Klaas James , Woodhead Zoe Victoria Joan , Harston George , Briggs James , Joly Olivier , Gerry Stephen , Kuhn Anna L. , Kostas Angelos A. , Nael Kambiz , AbdalKader Mohamad , Kadirvel Ramanathan , Brinjikji Waleed TITLE=Impact of e-ASPECTS software on the performance of physicians compared to a consensus ground truth: a multi-reader, multi-case study JOURNAL=Frontiers in Neurology VOLUME=14 YEAR=2023 URL=https://www.frontiersin.org/journals/neurology/articles/10.3389/fneur.2023.1221255 DOI=10.3389/fneur.2023.1221255 ISSN=1664-2295 ABSTRACT=Background

The Alberta Stroke Program Early CT Score (ASPECTS) is used to quantify the extent of injury to the brain following acute ischemic stroke (AIS) and to inform treatment decisions. The e-ASPECTS software uses artificial intelligence methods to automatically process non-contrast CT (NCCT) brain scans from patients with AIS affecting the middle cerebral artery (MCA) territory and generate an ASPECTS. This study aimed to evaluate the impact of e-ASPECTS (Brainomix, Oxford, UK) on the performance of US physicians compared to a consensus ground truth.

Methods

The study used a multi-reader, multi-case design. A total of 10 US board-certified physicians (neurologists and neuroradiologists) scored 54 NCCT brain scans of patients with AIS affecting the MCA territory. Each reader scored each scan on two occasions: once with and once without reference to the e-ASPECTS software, in random order. Agreement with a reference standard (expert consensus read with reference to follow-up imaging) was evaluated with and without software support.

Results

A comparison of the area under the curve (AUC) for each reader showed a significant improvement from 0.81 to 0.83 (p = 0.028) with the support of the e-ASPECTS tool. The agreement of reader ASPECTS scoring with the reference standard was improved with e-ASPECTS compared to unassisted reading of scans: Cohen's kappa improved from 0.60 to 0.65, and the case-based weighted Kappa improved from 0.70 to 0.81.

Conclusion

Decision support with the e-ASPECTS software significantly improves the accuracy of ASPECTS scoring, even by expert US neurologists and neuroradiologists.