Mayo Foundation for Medical Education and Research

Azra Alizad

Mostafa Fatemi

Mahdi Bayat

Viksit Kumar

Marek Belohlavek

Alireza Nabavizadehrafsanjani

Redouane Ternifi

Yinong Wang

Mahdi Bayad

Seyed Siavash Ghavami Roudsari

Bae-Hyung Kim

Rohit Nayak

Juanjuan Gu

Described here are systems and method for using ultrasound to localize a medical device to which an active ultrasound element that can transmits ultrasound energy is attached. Doppler signal data of the medical device are acquired while the active element is transmitting acoustic energy, and the Doppler signal data are processed to detect symmetric Doppler shifts associated with the active element. The systems and methods described in the present disclosure enable tracking and display of one or more locations on or associated with the medical device.

Systems and methods for localizing a medical device using symmetric doppler frequency shifts measured with ultrasound imaging

Described here are systems and methods for quantifying vessel features in non-contrast microvasculature images obtained with an ultrasound imaging system. Vessel features that are quantified include, but are not limited to, vessel structure features (e.g., number of vessels, vessel density, number of branch points), vessel diameter, and vessel tortuosity. Morphological filtering is used to generate vessel segments from which the quantitative vessel features can be reliably quantified.

Systems and methods for quantifying vessel features in ultrasound doppler images

Systems and methods for reconstructing, estimating, or otherwise generating unacquired, undetected, unreconstructed, or otherwise unknown ultrasound data using machine learning algorithms are provided. Thus, the systems and methods described in the present disclosure provide for generating unacquired, undetected, unreconstructed, or otherwise unknown data that are not actually and physically acquired with an ultrasound transducer and/or front-end receiver of an ultrasound system.

Systems and methods for generating and estimating unknown and unacquired ultrasound data

Described here are systems and methods for generating microvessel images from image data acquired with an ultrasound system while analyzing the image data in realtime, or retrospectively, to generate a performance descriptor that can be used to assess data quality and/or motion correction quality; to adaptively suppress noise in the data; or both.

Systems and methods for microvessel ultrasound imaging

The present disclosure addresses a quantitative analysis of tumor vascularity patterns, with the goal of identifying biomarkers correlated with malignancy. Herein, we identify new types of quantitative ultrasound biomarkers of microvessel morphology that correlate with the state of the disease in question. We propose a novel method to automatically extract quantitative features related to the morphology and distribution of the vascular networks reconstructed from contrast-free ultrasound data. For instance, spatial vascularity pattern, bifurcation angle, Murray's deviation, fractal dimension and closet vessel distance were clearly depicted.

Methods for extracting and quantifying diagnostic biomarkers from ultrasound microvessel images

Ultrasound systems and methods are provided using mass characterization frequency methods that provide for predicting benign or malignant lesions, a response to treatment, tumor grading, and/or the expressions of immunohistochemical biomarkers, which are currently used for breast cancer classification and hormone therapy determination. The systems and methods are based on the shear wave parameter, mass characteristic frequency. The status of malignancy, treatment response, grade, and/or each immunohistochemical biomarker may be determined based on a corresponding mass characteristic frequency threshold.

Ultrasound systems and methods using mass characteristic frequency

System and method configured to characterize viscoelasticity of a target medium by directly determining phase difference between real and imaginary parts of the complex shear modulus of the tissue (determined as a result of applying a compression force to the tissue), without any fitting of data and independent from distribution of strain in the tissue caused by the application of compression force.

Loss-angle-based determination of a medium viscoelastic parameter in sub-hertz frequency range with the use of local creep response

Methods and systems for producing a visually-perceived representation of a sub-millimeter-sized blood vessel located at a depth of many centimeters in the biological tissue, in which the background clutter is suppressed (by at least 30 dB using SVT and additional 23 dB using a combination of morphology filtering and vessel enhancement filtering) as compared to an image obtained with the use of a B-mode ultrasound imaging, while at the same time maintaining the morphology of the blood vessel.

System and method for visualization of tissue microvasculature using ultrasound

Systems and methods for localizing a medical device using symmetric Doppler frequency shifts measured with ultrasound imaging

Methodology, with a programmable-processor imaging system, for control and determination of breast lesion viscoelastic properties with the use of a creep-like test. Two dimensional reconstruction maps are used for different parameters of a linear viscoelastic model. Description of different aspects of the test used on live subjects and suitability of a 1-D inversion model in capturing different viscoelasticity parameters. An automated methodology for the selection of a region of interest derived only from the appearance of the breast lesion on pre-compressed B-mode images. Based on the ROI and estimated viscoelasticity parameters, contrast values are determined that facilitate the enhanced differentiation of breast mass. Employing the methodology in a large group of patients provides better understanding of variations of different viscoelasticity parameters in different types of breast lesion and helps to identify new biomarkers for enhanced differentiation of benign from malignant cases.

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Rochester, MN, United States of America

Azra Alizad