Dataset Information

Adaptive Maximal Blood Flow Velocity Estimation From Transcranial Doppler Echos.

ABSTRACT: OBJECTIVE:Novel applications of transcranial Doppler (TCD) ultrasonography, such as the assessment of cerebral vessel narrowing/occlusion or the non-invasive estimation of intracranial pressure (ICP), require high-quality maximal flow velocity waveforms. However, due to the low signal-to-noise ratio of TCD spectrograms, measuring the maximal flow velocity is challenging. In this work, we propose a calibration-free algorithm for estimating maximal flow velocities from TCD spectrograms and present a pertaining beat-by-beat signal quality index. METHODS:Our algorithm performs multiple binary segmentations of the TCD spectrogram and then extracts the pertaining envelopes (maximal flow velocity waveforms) via an edge-following step that incorporates physiological constraints. The candidate maximal flow velocity waveform with the highest signal quality index is finally selected. RESULTS:We evaluated the algorithm on 32 TCD recordings from the middle cerebral and internal carotid arteries in 6 healthy and 12 neurocritical care patients. Compared to manual spectrogram tracings, we obtained a relative error of -1.5%, when considering the whole waveform, and a relative error of -3.3% for the peak systolic velocity. CONCLUSION:The feedback loop between the signal quality assessment and the binary segmentation yields a robust algorithm for maximal flow velocity estimation. Clinical Impact: The algorithm has already been used in our ICP estimation pipeline. By making the code and the data publicly available, we hope that the algorithm will be a useful building block for the development of novel TCD applications that require high-quality flow velocity waveforms.

SUBMITTER: Wadehn F

PROVIDER: S-EPMC7398472 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Adaptive Maximal Blood Flow Velocity Estimation From Transcranial Doppler Echos.

Wadehn Federico F Heldt Thomas T

IEEE journal of translational engineering in health and medicine 20200723

<h4>Objective</h4>Novel applications of transcranial Doppler (TCD) ultrasonography, such as the assessment of cerebral vessel narrowing/occlusion or the non-invasive estimation of intracranial pressure (ICP), require high-quality maximal flow velocity waveforms. However, due to the low signal-to-noise ratio of TCD spectrograms, measuring the maximal flow velocity is challenging. In this work, we propose a calibration-free algorithm for estimating maximal flow velocities from TCD spectrograms and ...[more]

PMID: 33033664

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Project description:BackgroundDual-venc 4D flow MRI, recently introduced for the assessment of intracranial hemodynamics, may provide a promising complementary approach to well-established tools such as transcranial Doppler ultrasound (TCD) and overcome some of their disadvantages. However, data comparing intracranial flow measures from dual-venc 4D flow MRI and TCD are lacking.PurposeTo compare cerebral blood flow velocity measures derived from dual-venc 4D flow MRI and TCD.Study typeProspective cohort.SubjectsA total of 25 healthy participants (56 ± 4 years old, 44% female).Field strength/sequenceA 3 T/dual-venc 4D flow MRI using a time-resolved three-dimensional phase-contrast sequence with three-dimensional velocity encoding.AssessmentPeak velocity measurements in bilateral middle cerebral arteries (MCA) were quantified from dual-venc 4D flow MRI and TCD. The MRI data were quantified by two independent observers (S.M and Y.M.) and TCD was performed by a trained technician (A.L.M.). We assessed the agreement between 4D flow MRI and TCD measures, and the interobserver agreement of 4D flow MRI measurements.Statistical testsPeak velocity from MRI and TCD was compared using Bland-Altman analysis and coefficient of variance. Intraclass correlation coefficient (ICC) was used to assess MRI interobserver agreement. A P value < 0.05 was considered statistically significant.ResultsThere was excellent interobserver agreement in dual-venc 4D flow MRI-based measurements of peak velocity in bilateral MCA (ICC = 0.97 and 0.96 for the left and right MCA, respectively). Dual-venc 4D flow MRI significantly underestimated peak velocity in the left and right MCA compared to TCD (bias = 0.13 [0.59, -0.33] m/sec and 0.15 [0.47, -0.17] m/sec, respectively). The coefficient of variance between dual-venc 4D flow MRI and TCD measurements was 26% for the left MCA and 22% for the right MCA.Data conclusionThere was excellent interobserver agreement for the assessment of MCA peak velocity using dual-venc 4D flow MRI, and ≤20% under-estimation compared with TCD.Evidence level3 TECHNICAL EFFICACY: Stage 2.

Dataset Information

Adaptive Maximal Blood Flow Velocity Estimation From Transcranial Doppler Echos.

Publications

Adaptive Maximal Blood Flow Velocity Estimation From Transcranial Doppler Echos.

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