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Automated cerebral hemorrhage volume calculation and stability detection using automated software

INTRODUCTION: The measurement of intracerebral hemorrhage (ICH) volume is important for management, particularly in evaluating expansion on subsequent imaging. However manual volumetric analysis is time-consuming, especially in busy hospital settings. We aimed to use automated Rapid Hyperdensity sof...

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Detalles Bibliográficos
Autores principales: Sreekrishnan, Anirudh, Venkatasubramanian, Chitra, Heit, Jeremy J
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Journal Experts 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10246251/
https://www.ncbi.nlm.nih.gov/pubmed/37292654
http://dx.doi.org/10.21203/rs.3.rs-2944493/v1
Descripción
Sumario:INTRODUCTION: The measurement of intracerebral hemorrhage (ICH) volume is important for management, particularly in evaluating expansion on subsequent imaging. However manual volumetric analysis is time-consuming, especially in busy hospital settings. We aimed to use automated Rapid Hyperdensity software to accurately measure ICH volume across repeated imaging. METHODS: We identified ICH cases, with repeat imaging conducted within 24 hours, from two randomized clinical trials where enrollment was not based on ICH volume. Scans were excluded if there was (1) severe CT artifacts, (2) prior neurosurgical procedures, (3) recent intravenous contrast, or (4) ICH < 1 ml. Manual ICH measurements were conducted by one neuroimaging expert using MIPAV software and compared to the performance of automated software. RESULTS: 127 patients were included with median baseline ICH volume manually measured at 18.18 cc (IQR: 7.31 – 35.71) compared to automated detection of 18.93 cc (IQR: 7.55, 37.88). The two modalities were highly correlated (r = 0.994, p < 0.001). On repeat imaging, the median absolute difference in ICH volume was 0.68cc (IQR: −0.60–4.87) compared to automated detection at 0.68cc (IQR: −0.45–4.63). These absolute differences were also highly correlated (r = 0.941, p < 0.001), with the ability of the automated software to detect ICH expansion with a Sensitivity of 94.12% and Specificity 97.27%. CONCLUSION: In our proof-of-concept study, the automated software has high reliability in its ability to quickly determine IPH volume with high sensitivity and specificity and to detect expansion on subsequent imaging.