TY - JOUR
T1 - Diagnostic Accuracy of an Algorithm for Discriminating Presumed Solid and Gaseous Microembolic Signals During Transcranial Doppler Examinations
AU - Keunen, Rudolf W.M.
AU - Daal, Sayonara M.
AU - Romers, Geert Jan
AU - Hoohenkerk, Gerard J.F.
AU - van Kampen, Paulien M.
AU - Suyker, Willem J.L.
N1 - Publisher Copyright:
© 2023 World Federation for Ultrasound in Medicine & Biology
PY - 2023/12
Y1 - 2023/12
N2 - Objective: The aim of the work described here was to assess the diagnostic accuracy of a new algorithm (SGA-a) for time-domain analysis of transcranial Doppler audio signals to discriminate presumed solid and gaseous microembolic signals and artifacts (SGAs). Methods: SGA-a was validated by human experts in an artifact cohort of 20 patients subjected to a 1-h transcranial Doppler exam before cardiac surgery (cohort 1). Emboli were validated in a cohort of 10 patients after aortic valve replacement in a 4-h monitoring period (cohort 2). The SGA misclassification rate was estimated by testing SGA-a on artifact-free test files of solid and gaseous emboli. Results: In cohort 1 (n = 24,429), artifacts were classified with an accuracy of 94.5%. In cohort 2 (n = 12,328), the accuracy in discriminating solid/gaseous emboli from artifacts was 85.6%. The 95% limits of agreement for, respectively, the numbers of presumed solids and gaseous emboli, artifacts and microembolic signals of undetermined origin were [−10, 10], [−14, 7] and [−9, 16], and the intra-class correction coefficients were 0.99, 0.99 and 0.99, respectively. The rate of misclassification of solid test files was 2%, and the rate of misclassification of gaseous test files was 12%. Conclusion: SGA-a can detect presumed solid and gaseous microembolic signals and differentiate them from artifacts. SGA-a could be of value when both solid and gaseous emboli may jeopardize brain function such as seen during cardiac valve and/or aortic arch replacement procedures.
AB - Objective: The aim of the work described here was to assess the diagnostic accuracy of a new algorithm (SGA-a) for time-domain analysis of transcranial Doppler audio signals to discriminate presumed solid and gaseous microembolic signals and artifacts (SGAs). Methods: SGA-a was validated by human experts in an artifact cohort of 20 patients subjected to a 1-h transcranial Doppler exam before cardiac surgery (cohort 1). Emboli were validated in a cohort of 10 patients after aortic valve replacement in a 4-h monitoring period (cohort 2). The SGA misclassification rate was estimated by testing SGA-a on artifact-free test files of solid and gaseous emboli. Results: In cohort 1 (n = 24,429), artifacts were classified with an accuracy of 94.5%. In cohort 2 (n = 12,328), the accuracy in discriminating solid/gaseous emboli from artifacts was 85.6%. The 95% limits of agreement for, respectively, the numbers of presumed solids and gaseous emboli, artifacts and microembolic signals of undetermined origin were [−10, 10], [−14, 7] and [−9, 16], and the intra-class correction coefficients were 0.99, 0.99 and 0.99, respectively. The rate of misclassification of solid test files was 2%, and the rate of misclassification of gaseous test files was 12%. Conclusion: SGA-a can detect presumed solid and gaseous microembolic signals and differentiate them from artifacts. SGA-a could be of value when both solid and gaseous emboli may jeopardize brain function such as seen during cardiac valve and/or aortic arch replacement procedures.
KW - Algorithm
KW - Artifacts
KW - Embolus detection
KW - Gaseous emboli
KW - Solid emboli
KW - Transcranial Doppler
UR - http://www.scopus.com/inward/record.url?scp=85171346271&partnerID=8YFLogxK
U2 - 10.1016/j.ultrasmedbio.2023.08.011
DO - 10.1016/j.ultrasmedbio.2023.08.011
M3 - Article
C2 - 37709563
AN - SCOPUS:85171346271
SN - 0301-5629
VL - 49
SP - 2483
EP - 2488
JO - Ultrasound in Medicine and Biology
JF - Ultrasound in Medicine and Biology
IS - 12
ER -