학술논문

Assessing ASPECTS and ICH score reliability on NCCT scans via SMART INDIA App and PACS by neurologists and neuro-radiologists
Document Type
Original Paper
Source
Health and Technology: jointly published by Springer and the IUPESM in cooperation with the World Health Organization. 14(2):305-316
Subject
Inter-rater reliability
ASPECTS
ICH score
Smartphone app
Language
English
ISSN
2190-7188
2190-7196
Abstract
Purpose: Inter-rater reliability is a critical aspect of stroke image interpretation. This study aims to investigate inter-rater reliability between neurologists and neuro-radiologist when assessing Alberta Stroke Program Early CT Score (ASPECTS) and Intracerebral Haemorrhage (ICH) scores using a mobile application (SMART INDIA App – by neurologists) and the Picture Archiving and Communication System (PACS – by neuro-radiologist).Methods: Adult patients diagnosed with ischemic or haemorrhagic stroke were included in this study. Two Neurologists (R1 and R2) assessed the ASPECTS and ICH scores by viewing the SMART INDIA App. A neuroradiologist expert (R3) assessed the same using PACS. Kappa statistics are presented for agreement between the Raters.Results: 100 consecutive patients each of Acute Ischemic stroke (AIS) and ICH were included. A significant agreement in the total ASPECTS between the Raters 1 and 2 (0.85(95% CI—0.775,0.926)), Raters 1 and 3(0.76(95% CI—0.671,0.857)) and Raters 2 and 3(0.76(95% CI—0.673,0.857)) was noted. A good agreement was ascertained between Rater 1 and 3, even though the devices were different. A similar excellent agreement was also noted in assessing the ICH score. The study's findings indicate that neurologists using different devices and platforms demonstrated good to excellent agreement with the neuro-radiologist (considered the gold standard) when estimating ASPECTS and ICH scores.Conclusion: The interpretations of neurologists using the SMART INDIA App can be deemed valid and reliable from the neuroimaging viewpoint. These results contribute to our understanding of the feasibility and reliability of app-based image evaluation in the assessment of stroke.