Sunnybrook Research Institute

University Health Network

Sunnybrook Health Sciences Centre

Gregory J Czarnota

Michael D Sherar

John Hunt

Ali Sadeghi-Naini

Hadi Tadayyon

Michael C Kolios

Omar Falou

Lakshmanan Sannachi

Michael Kolios

William Tyler Tran

Adam Tunis

Mehrdad Gangeh

Systems and methods for using quantitative ultrasound ('QUS') techniques to generate imaging biomarkers that can be used to assess a prediction of tumor response to different chemotherapy treatment regimens are provided. For instance, the imaging biomarkers can be used to subtype tumors that have resistance to certain chemotherapy regimens prior to drug exposure. These imaging biomarkers can therefore be useful for predicting tumor response and for assessing the prognostic value of particular treatment regimens.

Systems and methods for prediction of tumor treatment response to using texture derivatives computed from quantitative ultrasound parameters

Systems and methods for prediction of tumor response to chemotherapy using pre-treatment quantitative ultrasound parameters

Systems and methods for classifying tissue using quantitative ultrasound techniques. Parameters are calculated directly from raw echo signal data acquired from a region-of-interest during an ultrasound scan and parametric maps are produced using these parameters. These parameters can be calculated after normalizing the echo signal data using reference data so as to mitigate the effects of variations in instruments settings, ultrasound beam diffraction, and attenuation effects. First-order and second-order statistical measures are computed from these parametric maps, and are used to classify the tissue or tissues in the region-of-interest. Using these systems and methods, tissue can be classified with different levels of classification. For example, a tissue characterized as malignant cancer can additionally be graded (e.g., Grade I, II, or III).

System and method for classifying and characterizing tissues using first-order and second-order statistics of quantitative ultrasound parametric maps

A method of detecting cellular damage within a subject comprises transmitting low frequency ultrasound (20 MHz or below) into a selected site within the subject wherein the selected site has been exposed to a stress capable of causing cellular death at the selected site. At least a portion of ultrasound backscattered from the ultrasound transmitted into the selected site is received. The received backscattered ultrasound is compared to a control backscatter measurement. An increase or a decrease in intensity or spectral slope of the received backscattered ultrasound when compared to the control backscatter measurement indicates cellular death or damage at the selected site within the subject.

Methods of monitoring cellular death using low frequency ultrasound

A non-invasive method of monitoring apoptosis in cell culture, ex-vivo tissues and in-vivo tissues using high frequency ultrasound imaging is provided. The method includes the steps of: 1) imaging a selected site of the cell culture or tissues using high frequency (above 20 MHz) ultrasound imaging (before image); 2) exposing the selected site to an apoptosis-inducing stress; 3) imaging the selected site or a portion thereof, using ultrasound imaging at subsequent timed intervals (after image(s)); 4) measuring the signal amplitude of a region of interest of the selected site in the before and after images; 5) comparing the signal amplitude measurements for the regions of interest in the before and after images and determining whether the after image regions exhibit an increase in amplitude as compared to the before image regions which is an indication that apoptosis has begun; and 6) measuring the change in the frequency spectrum of the radiofrequency ultrasound backscatter signal in the region of interest in the before and after images and confirming that apoptosis has begun when the slope of the frequency spectrum has increased.

Use of high frequency ultrasound imaging to detect and monitor the process of apoptosis in living tissues, ex-vivo tissues and cell-culture

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Oakville, Canada

Gregory J Czarnota