Spatial analysis of cardiovascular imaging

Abstract

A system including a hierarchical analytics framework that can utilize a first set of machine learned algorithms to identify and quantify a set of biological properties utilizing medical imaging data is provided. System can segment the medical imaging data based on the quantified biological properties to delineate existence of perivascular adipose tissue. The system can also segment the medical imaging data based on the quantified biological properties to determine a lumen boundary and/or determine a cap thickness based on a minimum distance between the lumen boundary and LRNC regions.

1 . A system for implementing an analyzer module using intermediate processing steps that incrementally enrich the processed data, the system comprising:
 a processor configured to:   receive imaging data of Computed Tomography (CT), Magnetic resonance (MR), Ultrasound (US), Positron Emission Tomography (PET), or any combination thereof of a patient;   determine a first set of derived quantities, qualities or both of anatomic descriptors, plaque descriptors or both as biological properties based on the received imaging data, determine a second set of derived quantities, qualities or both that identify, characterize or both vascular disease burden as a medical condition based on the first set of derived quantities, qualities or both;   wherein the determination of the first set, the second set or both further comprises determining values based on one or more operations to identify or classify regions, one or more transformations to accentuate spatial or temporal context, or both; and   output the vascular disease burden.   
     
     
         2 . The system of  claim 1  wherein quantities or qualities that identify or characterize vascular disease burden as a medical condition comprise determining at least a minimum of quantities or qualities to obtain a comprehensive understanding of the vascular disease burden. 
     
     
         3 . The system of  claim 2  wherein the at least a minimum quantities or qualities are lipid core, fibrosis, calcification, hemorrhage, permeability, thrombosis, ulceration, remodeling ratio, percent stenosis, percent dilation, wall thickness or any combination thereof. 
     
     
         4 . The system of  claim 1  wherein the processor is further configured to receive a patient's clinical history, a patient's symptoms, one or more diagnostic tests, or any combination thereof; and use any of the received patient's clinical history, received patient's symptoms, or received one or more diagnostic tests to determine the first set, the second set or both. 
     
     
         5 . The system of  claim 1  wherein the processor is further configured to receive one or more inputs to adjust the first set, the second set, the vascular disease burden or any combination thereof. 
     
     
         6 . The system of  claim 1  wherein the processor is further configured to cause the one or more outputs of the analyzer module to be transmitted to a display and displayed using graphics and text. 
     
     
         7 . The system of  claim 1  wherein the analyzer module utilizes one or more automated deep-learning algorithms. 
     
     
         8 . The system of  claim 1  wherein the biological properties include physiological measurements. 
     
     
         9 . The system of  claim 1  wherein the second set of derived quantities, qualities or both identify, characterize or both risk assessment or stratification of disease as a medical condition based on the first set of derived quantities. 
     
     
         10 . The system of  claim 1  wherein the second set of derived quantities, qualities or both identify, characterize or both predicting a course of disease as a medical condition based on the first set of derived quantities, wherein the course of disease comprises adverse event outcomes. 
     
     
         11 . The system of  claim 1  wherein the second set of derived quantities, qualities or both identify, characterize or both indicate a potential effectiveness of one treatment over another in individual patient based on the first set of derived quantities. 
     
     
         12 . A system for implementing an analyzer module using intermediate processing steps that incrementally enrich the processed data, the system comprising:
 a processor configured to:   post-process received imaging data of Computed Tomography (CT), Magnetic resonance (MR), Ultrasound (US), Positron Emission Tomography (PET), or any combination thereof of a patient;   determine a set of segmentations including lumen, wall, perivascular space, or any combination thereof to determine biological properties based on the received imaging data,   determine a set of quantities or qualities that identify, characterize or both atherosclerotic plaque, coronary artery disease, other vasculopathy, or any combination thereof as a medical condition based on the set of segmentations;   wherein the set of segmentations, the set of quantities or qualities or both are based on one or more operations to identify or classify regions, one or more transformations to accentuate spatial or temporal context, or both; and   output the atherosclerotic plaque, the coronary artery disease, the other vasculopathy or any combination thereof.   
     
     
         13 . The system of  claim 12  wherein the analyzer module applies one or more deep learning methodologies. 
     
     
         14 . The system of  claim 12  wherein the processor is further configured to determine hemodynamic properties based on the set of segmentations. 
     
     
         15 . The system of  claim 12  wherein the processor is further configured to determine one or more of blood pressure, blood flow velocity, flow reserve, vessel wall shear stress or other properties that contribute to a condition of ischemia or infarction based on the set of segmentations. 
     
     
         16 . The system of  claim 12  wherein processor is further configured to determining treatment paths for patients. 
     
     
         17 . The system of  claim 12  wherein the processor is further configured to cause the atherosclerotic plaque, the coronary artery disease, the other vasculopathy or any combination thereof to be transmitted to be displayed as a visualization in a report. 
     
     
         18 . (canceled) 
     
     
         19 . The system of  claim 12  where the set of quantities or qualities that identify, characterize or both determine a presence or extent of atherosclerotic plaques, coronary artery disease, other vasculopathy, or any combination thereof. 
     
     
         20 . A system for implementing an analyzer module using intermediate processing steps that incrementally enrich the processed data, the system comprising:
 a processor configured to:
 receive imaging data of Computed Tomography (CT), Magnetic resonance (MR), Ultrasound (US), Positron Emission Tomography (PET), or any combination thereof of a patient; 
 determine a set of segmentations including lumen, wall, perivascular space, or any combination thereof to determine biological properties based on the received imaging data; 
 determine a set of quantities or qualities that identify or characterize permeability, neovascularization, necrosis, collagen breakdown, inflammation, or any combination thereof, as a medical condition based on the set of segmentations; 
 wherein the set of segmentations, the set of quantities that identify or characterize or both are based on one or more operations to identify or classify regions, one or more transformations to accentuate spatial or temporal context, or both; and 
 output the permeability, neovascularization, necrosis, collagen breakdown, inflammation, or any combination thereof. 
   
     
     
         21 . A system for implementing an analyzer module using intermediate processing steps that incrementally enrich the processed data, the system comprising:
 receive imaging data of Computed Tomography (CT), Magnetic resonance (MR), Ultrasound (US), Positron Emission Tomography (PET), or any combination thereof of a patient;   determine a set of segmentations including permeability, neovascularization, necrosis, collagen breakdown, or inflammation, or any combination thereof as biological properties based on the imaging data;   determine a set of quantities or qualities that identify or characterize atherosclerotic plaque, coronary artery disease, other vasculopathy or any combination thereof as a medical condition based on the set of segmentations;   wherein the set of segmentations, the set of derived quantities or qualities or both are based on one or more operations to identify or classify regions, one or more transformations to accentuate spatial or temporal context, or both; and   output the atherosclerotic plaque, coronary artery disease, other vasculopathy or any combination thereof.