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Medical Physics / Volume 38 / Issue 5 / ULTRASOUND PHYSICS

Med. Phys. 38, 2563 (2011); http://dx.doi.org/10.1118/1.3569578 (9 pages)

Crawling wave detection of prostate cancer: Preliminary in vitro results

Liwei An, Bradley Mills, Zaegyoo Hah, Shuo Mao, and Kevin J. Parker

University of Rochester, Rochester, New York 14627

Jorge Yao, Jean Joseph, Deborah J. Rubens, and John Strang

University of Rochester Medical Center,Rochester New York 14642

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(Received 7 December 2010; accepted 23 February 2011; revised 17 February 2011; published online 5 May 2011)

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Purpose: The focus of this article is to develop signal and imaging processing methods to derive an accurate estimation of local tissue elasticity using the crawling wave (CrW) sonoelastography method. The task is to reduce noise and to improve the contrast of the elasticity map.
Methods: The protocol of the CrW approach was first tested on heterogeneous elastic phantoms as a model of prostate cancers. Then, the contrast-to-noise ratio of the estimation was calculated iteratively with various sequences of algorithms to determine the optimal signal processing settings. Finally, the optimized signal processing was applied to ex vivo prostate cancer detection. The comparison of the segmented elasticity map and the histology tumor outline was made by quadrants to evaluate the diagnostic performance of the protocol. Furthermore, the CrW approach was combined with amplitude-sonoelastography to achieve a higher specificity.
Results: This study demonstrated the feasibility of the proposed approach for clinical applications. In the application to ex vivo prostate cancer detection, the established approach was tested on 43 excised prostate glands. The combination of the CrW approach and amplitude-sonoelastography achieved an accuracy of over 80% for finding tumors larger than 4 mm in diameter. The elasticity values and contrast found by the CrW approach were in agreement with the previous results derived from mechanical testing.
Conclusions: Crawling waves can be applied to detect prostate cancer with accuracy approaching 80% and can quantify the stiffness or shear modulus of both cancerous and noncancerous tissues. The technique therefore shows promise for guiding biopsies to suspect regions that are otherwise difficult to identify.

© 2011 American Association of Physicists in Medicine

ACKNOWLEDGMENTS

This research was supported by the NIH Grant No. 5 R01 AG016317-06. The authors greatly acknowledge Laurie Baxter and LeeAnn Kushner from the Surgical Pathology Department at University of Rochester Medical Center for acquiring the histology slices. The authors also thank the reviewers for their constructive comments.

Article Outline

  1. INTRODUCTION
  2. THEORY
    1. Crawling wave model
    2. Local autocorrelation estimator
    3. Amplitude sonoelastography
  3. EXPERIMENTAL
  4. METHODS
  5. RESULTS
    1. The CrW approach
    2. Combination of CrW sonoelastography and amplitude-sonoelastography
    3. Elasticity contrast
  6. CONCLUSIONS
Digital Object Identifier
http://dx.doi.org/10.1118/1.3569578

KEYWORDS and PACS

Keywords

biological tissues, biomechanics, cancer, elastic waves, elasticity, mechanical testing, medical image processing, noise, phantoms, tumours, crawling waves, elasticity imaging, shear velocity estimation, shear wave interference patterns, prostate cancer

PACS

PUBLICATION DATA

ISSN

0094-2405 (print)  

Publisher

$abstract.society.value is a Member of CrossRef American Association of Physicists in Medicine

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