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.
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.
Authors: Man Zhang; Benjamin Castaneda; Zhe Wu; Priya Nigwekar; Jean V Joseph; Deborah J Rubens; Kevin J Parker Journal: Ultrasound Med Biol Date: 2007-07-02 Impact factor: 2.998
Authors: Joshua R Doherty; Gregg E Trahey; Kathryn R Nightingale; Mark L Palmeri Journal: IEEE Trans Ultrason Ferroelectr Freq Control Date: 2013-04 Impact factor: 2.725