Evidence map›Paper›PMID 42735155›Full record

ArticleIEEE transactions on ultrasonics2026

Comparing the Statistics of High-Resolution Time-of-Flight-Based Shear Wave Speed Estimation in the Presence of Speckle Bias Using Shear Wave Slowness or Velocity.

Wren E Wightman, Shruthi Srinivasan, Ned C Rouze, Mark L Palmeri, Kaden D Bock, Kathryn R Nightingale

Abstract readComparative Study
In one paragraph

Article in IEEE transactions on ultrasonics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Wren E Wightman
Shruthi Srinivasan
Ned C Rouze
Mark L Palmeri
Kaden D Bock
Kathryn R Nightingale

Funding

3D Shearwave Elasticity Biomarker Development for Neuromuscular DiseaseR01EB033064 · NIBIB · DUKE UNIVERSITY · PI NIGHTINGALE, KATHRYN RADABAUGH · 2022 to 2025
$2.3M
NIBIB NIH HHS R01 EB033064
6 · The paper itself

Abstract

Ultrasound shear wave elasticity imaging (SWEI) quantifies the mechanical properties of soft tissue by relating measurements of shear wave speed (SWS) to a material model. Many SWEI algorithms estimate the time of flight (TOF) over some fixed distance along a given trajectory and calculate the wave velocity as the ratio of that distance to the TOF. To balance spatial resolution and SWS precision, most high-resolution 2D-SWEI algorithms average together multiple noisy velocity estimates to generate the final SWS. However, velocity calculated over a fixed distance with an estimated TOF can be prone to divide-by-near-zero (DBNZ) errors, especially as the true TOF approaches zero. The reciprocal of velocity, slowness, will never experience DBNZ errors as long as the fixed distance over which the TOF is estimated is greater than zero. In this work, we modify an existing 2D-SWEI algorithm to be based on point estimates of slowness. We propose a statistical model assuming normal TOF distributions and use it to evaluate the accuracy and the precision of the velocity- and slowness-based SWS algorithms in Monte Carlo simulations. We then extend our analysis of TOF data to empirically describe the bounds of the proposed model in the presence of speckle bias. Finally, we evaluate both algorithms in heterogeneous media and quantify the achievable lesion conspicuity across a range of shear wave SNR and SWS algorithm reconstruction parameters. We conclude that slowness-based SWS can achieve similar accuracy and precision as velocity-based SWS at less than one-tenth of the TOF SNR with no additional computational cost. For a fixed shear wave and TOF SNR in isotropic homogeneous media, we experimentally demonstrate a reduction in bias greater than 5% and a reduction in variability greater than 15%. We also demonstrate that the slowness-based approach achieves superior or equal lesion conspicuity as the velocity-based approach, regardless of imaging condition or algorithm parameters.

Indexed as

Elasticity Imaging TechniquesImage Processing, Computer-AssistedAlgorithmsModels, StatisticalPhantoms, Imaging

Identifiers

PMID42735155
PMCPMC13245884

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.