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An Automated Algorithm for Optic Nerve Sheath Diameter Assessment from B‐mode Ultrasound Images
Author(s) -
Stevens Raoul R. F.,
Huberts Wouter,
Gommer Erik D.,
Ertl Michael,
Aries Marcel,
Mess Werner H.,
Delhaas Tammo
Publication year - 2021
Publication title -
journal of neuroimaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.822
H-Index - 64
eISSN - 1552-6569
pISSN - 1051-2284
DOI - 10.1111/jon.12851
Subject(s) - medicine , ultrasound , algorithm , cutoff , mean difference , intracranial pressure , nuclear medicine , radiology , computer science , confidence interval , physics , quantum mechanics
BACKGROUND AND PURPOSE The optic nerve sheath diameter (ONSD) is a promising surrogate marker for the detection of raised intracranial pressure (ICP). However, inconsistencies in manual ONSD assessment are thought to affect ONSD and the corresponding ONSD cutoff values for the diagnosis of elevated ICP, hereby hampering the full potential of ONSD. In this study, we developed an image intensity‐invariant algorithm to automatically estimate ONSD from B‐mode ultrasound images at multiple depths. METHODS The outcomes of the algorithm were validated against manual ONSD measurements by two human experts. Each expert analyzed the images twice (M1 and M2) in unknown order. RESULTS The algorithm proved capable of segmenting the ONSD in 39 of 42 images, hereby showing mean differences of −.08 ± .45 and −.05 ± .41 mm compared to averaged ONSD values (M1 + M2/2) of Operator 1 and Operator 2, respectively, whereas the mean difference between the two experts was .03 ± .26 mm. Moreover, differences between algorithm‐derived and expert‐derived ONSD values were found to be much smaller than the 1 mm difference that is expected between patients with normal and elevated ICP, making it likely that our algorithm can distinguish between these patient groups. CONCLUSIONS Our algorithm has the potential to improve the accuracy of ONSD as a surrogate marker for elevated ICP because it has no intrinsic variability. However, future research should be performed to validate if the algorithm does indeed result in more accurate noninvasive ICP predictions.