Journal of Medical Internet Research (Jun 2020)

Reliability of Smartphone for Diffusion-Weighted Imaging–Alberta Stroke Program Early Computed Tomography Scores in Acute Ischemic Stroke Patients: Diagnostic Test Accuracy Study

  • Sakai, Kenichiro,
  • Komatsu, Teppei,
  • Iguchi, Yasuyuki,
  • Takao, Hiroyuki,
  • Ishibashi, Toshihiro,
  • Murayama, Yuichi

DOI
https://doi.org/10.2196/15893
Journal volume & issue
Vol. 22, no. 6
p. e15893

Abstract

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BackgroundHigh-quality neuroimages can be viewed using a medical app installed on a smartphone. Although interdevice agreement between smartphone and desktop PC monitor was found to be favorable for evaluating computed tomography images, there are no interdevice agreement data for diffusion-weighted imaging (DWI). ObjectiveThe aim of our study was to compare DWI interpretation using the Join smartphone app with that using a desktop PC monitor, in terms of interdevice and interrater agreement and elapsed interpretation time. MethodsThe ischemic change in the DWI of consecutive patients with acute stroke in the middle cerebral artery territory was graded by 2 vascular neurologists using the Join smartphone app and a desktop PC monitor. The vascular neurologists were blinded to all patient information. Each image was categorized as either Diffusion-Weighted Imaging–Alberta Stroke Program Early Computed Tomography Scores (DWI-ASPECTS) ≥7 or DWI-ASPECTS <7 according to the Japanese Society for Neuroendovascular Therapy. We analyzed interdevice agreement and interrater agreement with respect to DWI-ASPECTS. Elapsed interpretation time was compared between DWI-ASPECTS evaluated by the Join smartphone app and a desktop PC monitor. ResultsWe analyzed the images of 111 patients (66% male; median age=69 years; median National Institutes of Health Stroke Scale score on admission=4). Interdevice agreement regarding DWI-ASPECTS between the smartphone and the desktop PC monitor was favorable (vascular neurologist 1: κ=0.777, P<.001, vascular neurologist 2: κ=0.787, P<.001). Interrater agreement was also satisfactory for the smartphone (κ=0.710, P<.001) and the desktop PC monitor (κ=0.663, P<.001). Median elapsed interpretation time was similar between the smartphone and the desktop PC monitor (vascular neurologist 1: 1.7 min vs 1.6 min; P=.64); vascular neurologist 2: 2.4 min vs 2.0 min; P=.14). ConclusionsThe use of a smartphone app enables vascular neurologists to estimate DWI-ASPECTS accurately and rapidly. The Join medical smartphone app shows great promise in the management of acute stroke.