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March 4, 2026Signals0 citationsOpen Access

Performance Evaluation of Displacement Estimation Methods for Early-Stage Breast Cancer Tumor Detection Using Strain Elastography

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APAlexey García PadillaITI Bazan TrujilloCCCarlos A. Negreira Casares

Key Result

The combined autocorrelation method (CAM) outperformed speckle tracking and Doppler methods in displacement estimation for breast tumors smaller than 5 mm across depths.

Key Points

  • The study aims to systematically evaluate and compare displacement estimation methods for detecting early-stage breast cancer tumors less than 5 mm.
  • Used three displacement estimation methods: speckle tracking, Doppler, and combined autocorrelation method (CAM).
  • Conducted simulations of elastography signals for accuracy assessment.
  • Measured performance using root mean square error (RMSE) across various tumor sizes and tissue layers.
  • CAM demonstrated superior accuracy in displacement estimation compared to other methods.
  • Best results were obtained across all tests involving small tumor sizes at superficial and intermediate depths.
  • An analysis of varying SNR/strain values showed consistent outperformance of CAM.

Structured PICO

Does the combined autocorrelation method (CAM) improve displacement estimation accuracy compared to speckle tracking and Doppler methods in simulated early-stage breast cancer lesions?

P
Population
Simulated elastography signals for early-stage breast cancer lesions smaller than 5 mm in a three-layer model (healthy tissue–tumor–healthy tissue)
I
Intervention
Combined autocorrelation method (CAM) for displacement estimation
C
Comparator
Speckle tracking and the Doppler method
O
Outcome
Root mean square error (RMSE) for displacement field, strain, and tumor size estimationsurrogate

The combined autocorrelation method (CAM) provides superior accuracy for displacement estimation in simulated early-stage breast cancer lesions compared to traditional methods.

Abstract

Displacement estimation methods in strain elastography use ultrasound signals to estimate displacements and strain in soft tissue. Although several methods exist, systematic comparisons under controlled simulation conditions for lesions smaller than 5 mm are limited. Evaluating axial accuracy for superficial and intermediate depths in small breast cancer lesions is clinically important, as early-stage detection with existing techniques remains challenging. In this study, speckle tracking, the Doppler method, and the combined autocorrelation method (CAM) were used to estimate axial displacements from simulated elastography signals. The performance of these methods was assessed using the root mean square error (RMSE) for displacement field, strain, and tumor size estimation in a three-layer model comprising healthy tissue–tumor–healthy tissue. An extended analysis considering anatomically realistic tissue and motion artifacts conditions for the case of smallest lesion is presented. Finally, the CAM method, which obtained the best results, was assessed varying SNR/strain values. Simulation results show that CAM outperforms the other methods in displacement estimation across early-stage tumor sizes at both superficial and intermediate depths in all performed tests.

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Cite This Study

Padilla et al. (2026) studied this question. The combined autocorrelation method (CAM) outperformed speckle tracking and Doppler methods in displacement estimation for breast tumors smaller than 5 mm across depths.

synapsesocial.com/papers/69a7ccd5d48f933b5eed8b91https://doi.org/10.3390/signals7020019
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