The major goal of this project is to predict thermal ablation-induced cell death in real time using ultrasound echo decorrelation imaging, a method for mapping rapid, ablation-induced changes in tissue over millisecond time scales. Preliminary research has shown a strong correlation between local echo decorrelation and thermal tissue coagulation. However, a direct link between local echo decorrelation and the desired clinical end effect, i.e., death of malignant tumor tissue, has not been established. We hypothesize that ultrasound echo decorrelation imaging can directly predict thermal ablation-induced cell death in real time. Our hypothesis will be tested using a novel ablation and imaging configuration with great advantages for precise, quantitative comparison of treatment plans, ultrasound images, and ablated tissue histology. Image- guided treatments will be performed using an image-treat ultrasound array capable of both thermal ablation and high-quality pulse-echo imaging, using the same piezoelectric array elements. As a result, all imaging and treatment takes place in the same plane, and image-based predictions of local ablation-induced cell death can be evaluated with high accuracy. A custom image-treat ultrasound array will perform ablation and imaging of rabbit liver with implanted VX2 carcinoma in a series of in vivo trials. Ultrasound exposure conditions will include both bulk thermal ablation (comparable to radiofrequency and microwave ablation, as currently used in the clinic for minimally-invasive cancer treatment), and high-intensity focused ultrasound ablation (comparable to noninvasive focused ultrasound ablation devices currently under development and clinical testing for cancer treatment). Experiments will initially test the capability of cumulative echo decorrelation images to predict ablation-induced cell death, as evaluated by vital and histologic staining, with prediction accuracy judged from pixel-by-pixel receiver-operating-characteristic curve analysis. The ability of echo decorrelation imaging to predict coagulative necrosis, partial tissue viability, and heat-induced apoptosis will be statistically assessed. Echo decorrelation will be correlated with local cell viability, mapped by quantitative image analysis of cell nuclear morphology. Further experiments will evaluate a procedure for real-time ablation control, in which treatments are continued until the spatially averaged echo decorrelation exceeds a prespecified threshold within a targeted region of interest. Accuracy of echo decorrelation imaging-controlled will be assessed, both for accurate prediction of cell death in the targeted ROI and for correspondence to the targeted ablation margins. If successful, this project will provide clinicians with a real-time, ultrasound-based imaging approach to predict thermal ablation-induced cell death in real time during thermal ablation. This new opportunity for real-time monitoring and control of thermal ablation procedures will ultimately result in greatly improved efficacy and safety for these clinically important, minimally invasive and noninvasive cancer treatments.

Public Health Relevance

Liver cancer is a major public health problem, accounting for the largest cancer-related mortality in the world, with only a small fraction of patients eligible or curative resection or transplantation. Minimally invasive and noninvasive thermal ablation methods provide an important alternative, but have significant problems with incomplete treatment, tumor recurrence, and complications caused by collateral tissue damage. Real-time prediction of thermal ablation-induced cell death, made possible by echo decorrelation imaging, will provide greatly improved monitoring and control of minimally invasive and noninvasive thermal ablation procedures, ultimately resulting in fewer complications, reduced tumor recurrence, and improved outcomes for cancer patients.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Research Project (R01)
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Biomedical Imaging Technology Study Section (BMIT)
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Farahani, Keyvan
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University of Cincinnati
Engineering (All Types)
Schools of Engineering
United States
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Abbass, Mohamed A; Garbo, Allison-Joy; Mahalingam, Neeraja et al. (2018) Optimized Echo Decorrelation Imaging Feedback for Bulk Ultrasound Ablation Control. IEEE Trans Ultrason Ferroelectr Freq Control 65:1743-1755
Abbass, Mohamed A; Killin, Jakob K; Mahalingam, Neeraja et al. (2018) Real-Time Spatiotemporal Control of High-Intensity Focused Ultrasound Thermal Ablation Using Echo Decorrelation Imaging in ex Vivo Bovine Liver. Ultrasound Med Biol 44:199-213
Fosnight, Tyler R; Hooi, Fong Ming; Keil, Ryan D et al. (2017) Echo Decorrelation Imaging of Rabbit Liver and VX2 Tumor during In Vivo Ultrasound Ablation. Ultrasound Med Biol 43:176-186
Haworth, Kevin J; Bader, Kenneth B; Rich, Kyle T et al. (2017) Quantitative Frequency-Domain Passive Cavitation Imaging. IEEE Trans Ultrason Ferroelectr Freq Control 64:177-191
Subramanian, Swetha; Schmidt, Daniel T; Rao, Marepalli B et al. (2016) Dependence of ultrasound echo decorrelation on local tissue temperature during ex vivo radiofrequency ablation. Phys Med Biol 61:2356-71
Haworth, Kevin J; Salgaonkar, Vasant A; Corregan, Nicholas M et al. (2015) Using passive cavitation images to classify high-intensity focused ultrasound lesions. Ultrasound Med Biol 41:2420-34
Rich, Kyle T; Mast, T Douglas (2015) Accuracy of a bistatic scattering substitution technique for calibration of focused receivers. J Acoust Soc Am 138:EL469-73
Subramanian, Swetha; Mast, T Douglas (2015) Optimization of tissue physical parameters for accurate temperature estimation from finite-element simulation of radiofrequency ablation. Phys Med Biol 60:N345-55
Hooi, Fong Ming; Nagle, Anna; Subramanian, Swetha et al. (2015) Analysis of tissue changes, measurement system effects, and motion artifacts in echo decorrelation imaging. J Acoust Soc Am 137:585-97
Rich, Kyle T; Mast, T Douglas (2015) Methods to calibrate the absolute receive sensitivity of single-element, focused transducers. J Acoust Soc Am 138:EL193-8

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