Rapid prototyping and in vitro modeling of patient-specific coronary artery bypass grafts

A patient-customized, coronary-based technology with applications in character and pattern recognition, prosthetics, and recognition of medical/anatomical patterns

Active Publication Date: 2019-06-07
CORNELL UNIVERSITY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Determining volume geometry in response to at least one medical image

Method used

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  • Rapid prototyping and in vitro modeling of patient-specific coronary artery bypass grafts
  • Rapid prototyping and in vitro modeling of patient-specific coronary artery bypass grafts
  • Rapid prototyping and in vitro modeling of patient-specific coronary artery bypass grafts

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0051] Example 1: CTA of the coronary arteries can be a non-invasive alternative to invasive coronary angiography (ICA). In some implementations, dissection engine 124 is configured to receive motion-free images (eg, CTA images) at an isotropic spatial resolution of about 500 μm. In one example, system 100 performed CTA prior to ICA on 230 patients without regard to body mass index or heart rate. For stenosis severity, CTA showed 94%, 83%, 48% and 99% sensitivity, specificity, positive predictive value and negative predictive value compared with ICA, respectively.

[0052] Anatomy engine 124 may receive CTA data to generate 3D coronary artery geometry for image-based modeling of coronary artery anatomy. The dissection engine 124 determines an arterial centerline extraction 200 . Using centerline extraction, lumen segmentation and stenosis can be performed 202 . The dissection engine 124 may also perform vessel wall segmentation and plaque detection 204 and arterial co-regis...

example 2

[0053] Example 2: In some implementations, the anatomy engine 124 can generate anatomical information about a patient-customized SDVG. CFD engine 126 may generate hemodynamic curves by performing computational fluid dynamics on anatomical information. Typically, hemodynamic profiles can include clinical factors, design factors, or other factors such as flow oscillations, flow stagnation, flow energy loss, wall mechanics, shear levels, and graft-arterial compliance mismatch. The CFD engine 126 can compute hemodynamic (eg, physiological) data of aortic and coronary blood flow and pressure. image 3 The pressure, velocity and flow calculated by the CFD engine 126 in the patient-customized SDVG 122 are shown. In some embodiments, the CFD engine 126 can plan a "virtual" revascularization strategy by selecting coronary vessels and locations within vessels to revascularize flow characteristics and ischemia reduction. Figure 4 A patient-customized SDVG 122 after percutaneous corona...

Embodiment 4

[0060] Example 4: In vitro measurements in a benchtop flow circulator using a patient-customized SDVG physical model fabricated by the printing subsystem 102 (eg, a multi-material high-resolution 3D printing system). Experiments demonstrate that the system 100 can generate complex 3D arterial geometries with continuously spatially varying mechanical properties. Figure 5A A custom SDVG 122 is shown as a 3D printed physical model for a patient. 3D printed physical models allow the evaluation of patient-specific, graft-specific and surgical technique-related factors affecting SDVG hemodynamics and wall mechanics by 3 different methods: (i) intravascular pressure and flow sensors, (ii) particle Image velocimetry (PIV) and (iii) embedded soft strain sensors.

[0061] Figure 5B and 6 Shown is an extracorporeal flow circulatory system constructed to approximate coronary blood flow physiology to determine input defined flow velocity (Q), proximal (Pa) and distal (Pd) pressure and...

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Abstract

The present disclosure describes a system and a method for producing patient-specific small diameter vascular grafts (SDVG) for coronary artery bypass graft (CABG) surgery. In some embodiments, the method for producing SDVGs includes non-invasive quantification of patient-specific coronary and vascular physiology by applying computational fluid dynamics (CFD), rapid prototyping, and in vitro techniques to medical images and coupling the quantified patient-specific coronary and vascular physiology from the CFD to computational fluid-structure interactions and SDVG structural factors to design apatient-specific SDVG.

Description

[0001] Cross References to Related Applications [0002] This application claims priority to U.S. Provisional Patent Application 62 / 365,474, entitled "Computational Modeling and Rapid Prototyping of Patient-Customized Coronary Artery Bypass Grafts," filed July 22, 2016, the entire contents of which are incorporated by reference into this article. Background technique [0003] The following descriptions are provided to aid the reader in understanding. None of the information presented or references cited is admitted to be prior art to the present technology. [0004] Coronary artery disease (CAD) is an important cause of patient morbidity and mortality. In the United States, CAD affects more than 16 million adults, accounts for more than one-third of deaths, and causes more than 1.2 million hospitalizations each year. Despite medical therapy, more than 1.5 million people require coronary revascularization each year. Coronary artery bypass grafting (CABG) remains the mainst...

Claims

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Application Information

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IPC IPC(8): G06K9/00
CPCA61L27/16A61L27/18A61L27/38A61L27/507G06V2201/03C08L27/18C08L75/04C08L83/04A61L27/14G06T7/62A61B6/032A61B6/504G06T7/0012G06T2207/10072G06T2207/30104
Inventor 詹姆斯·K·敏熊光磊B·莫萨德西蒙·邓纳姆K·K·科拉尔
Owner CORNELL UNIVERSITY
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