Automated methods and systems for vascular plaque detection and analysis
First Claim
1. A fully automated method of determining whether a blood vessel of a patient'"'"'s vasculature contains plaque by classifying plaque components, comprising computationally processing at least a first processable data type and a second processable data type obtained using at least one non-invasive medical imaging system in order to analyze at least one cross section of a blood vessel of a patient'"'"'s vasculature using statistical classifiers developed using statistical modeling to determine if the blood vessel comprises at least one tissue correlated with the presence of plaque, in which event the blood vessel is determined to contain plaque, wherein the fully automated method does not require human intervention and wherein at least each of the first and second processable data types are processable magnetic resonance data generated by an MRI instrument and selected from the group consisting of T1-weighted data, T2-weighted data, PDW-weighted data, TOF-weighted data, and data generated by a combination of two or more of the foregoing.
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Accused Products
Abstract
Automated methods and systems for the detection and analysis of plaque in one or more regions of a patient'"'"'s vasculature are described.
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Citations
34 Claims
- 1. A fully automated method of determining whether a blood vessel of a patient'"'"'s vasculature contains plaque by classifying plaque components, comprising computationally processing at least a first processable data type and a second processable data type obtained using at least one non-invasive medical imaging system in order to analyze at least one cross section of a blood vessel of a patient'"'"'s vasculature using statistical classifiers developed using statistical modeling to determine if the blood vessel comprises at least one tissue correlated with the presence of plaque, in which event the blood vessel is determined to contain plaque, wherein the fully automated method does not require human intervention and wherein at least each of the first and second processable data types are processable magnetic resonance data generated by an MRI instrument and selected from the group consisting of T1-weighted data, T2-weighted data, PDW-weighted data, TOF-weighted data, and data generated by a combination of two or more of the foregoing.
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30. A fully automated method for analyzing patient data obtained using a non-invasive medical imaging system to determine whether a blood vessel of the patient contains plaque by classifying plaque components, comprising:
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a. obtaining processable data of at least one cross section of a blood vessel of a patient'"'"'s vasculature, wherein the processable data are derived from raw data collected using a medical imaging system that comprises an MRI instrument, wherein the processable data comprises at least a first processable magnetic resonance data type and a second processable magnetic resonance data type generated by an MRI instrument and selected from the group consisting of T1-weighted data, T2-weighted data, PDW-weighted data, TOF-weighted data, and data generated by a combination of two or more of the foregoing; b. communicating the processable data to a computer configured to receive and computationally process the processable data using statistical classifiers developed using statistical modeling to determine whether the blood vessel in the region of the cross section(s) comprises at least one tissue correlated with the presence of plaque, in which event the blood vessel is determined to contain plaque; and c. using the computer to computationally process the processable data and determine whether the blood vessel contains plaque, wherein the computational processing and determination of whether the blood vessel contains plaque does not require human intervention. - View Dependent Claims (31, 32, 33, 34)
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Specification