Initial Simulated FFR Investigation Using Flow Measurements in Patient-specific 3D Printed Coronary Phantoms

Abstract

Purpose: Accurate patient-specific phantoms for device testing or endovascular treatment planning can be 3D printed. We expand the applicability of this approach for cardiovascular disease, in particular, for CT-geometry derived benchtop measurements of Fractional Flow Reserve, the reference standard for determination of significant individual coronary artery atherosclerotic lesions.

Materials and methods: Coronary CT Angiography (CTA) images during a single heartbeat were acquired with a 320×0.5mm detector row scanner (Toshiba Aquilion ONE). These coronary CTA images were used to create 4 patient-specific cardiovascular models with various grades of stenosis: severe, <75% (n=1); moderate, 50-70% (n=1); and mild, <50% (n=2). DICOM volumetric images were segmented using a 3D workstation (Vitrea, Vital Images); the output was used to generate STL files (using AutoDesk Meshmixer), and further processed to create 3D printable geometries for flow experiments. Multi-material printed models (Stratasys Connex3) were connected to a programmable pulsatile pump, and the pressure was measured proximal and distal to the stenosis using pressure transducers. Compliance chambers were used before and after the model to modulate the pressure wave. A flow sensor was used to ensure flow rates within physiological reported values.

Results: 3D model based FFR measurements correlated well with stenosis severity. FFR measurements for each stenosis grade were: 0.8 severe, 0.7 moderate and 0.88 mild.

Conclusions: 3D printed models of patient-specific coronary arteries allows for accurate benchtop diagnosis of FFR. This approach can be used as a future diagnostic tool or for testing CT image-based FFR methods.

Figures

Figure 1

Selected and segmented vessels from the CT image for Model A.

Figure 2

Curved Multiplanar Reconstruction (MPR) in CT image for Model A.

Figure 3

STL file imported into Meshmixer for advanced mesh manipulation.

Figure 4

A, B: Top view (A) and side view (B) of Model A after advanced mesh manipulation to smooth vessels and create a base for vessel support.

Figure 5

Patient-specific 3D printed coronary arteries used to collect FFR data. The reservoir door and Cole Parmer luers are attached for controlled flow and pressure data.

Figure 6

Benchtop set up of FFR models. Pictured is the flow damper with pump to add or remove air, 3D printed coronary arteries, and pressure sensors located proximal and distal to stenosis.

Figure 7

Flow diagram of water and pressure data throughout the benchtop system.

Figure 8

CT image 3D reconstruction and curved MPR for Model A.

Figure 9

CT image 3D reconstruction and curved MPR for Model B.

Figure 10

CT image 3D reconstruction and curved MPR for Model C.

Figure 11

CT image 3D reconstruction and curved MPR for Model D.

Figure 12

Normalized pressure graphs for Model A at a 50/50 %systole/%diastole ratio with low and high distal resistances.

Figure 13

Normalized pressure graphs for Model A at a 45/55 %systole/%diastole ratio with low and high distal resistances.

Figure 14

Normalized pressure graphs for Model A at a 40/60 %systole/%diastole ratio with low and high distal resistances.

Figure 15

Normalized pressure graphs for Model A at a 35/65 %systole/%diastole ratio with low and high distal resistances.

Figure 16

Normalized pressure graphs for Model A at a 30/70 %systole/%diastole ratio with low and high distal resistances.

Figure 17

Normalized pressure graphs for Model A at a 25/75 %systole/%diastole ratio with low and high distal resistances.

Figure 18

Correlation of FFR and Flow Rate for each model at %systole/%diastole of 50/50 and 45/55 respectively.

Figure 19

Correlation of FFR and Flow Rate for each model at %systole/%diastole of 40/60 and 35/65 respectively.

Figure 20

Correlation of FFR and Flow Rate for each model at %systole/%diastole of 30/70 and 25/75 respectively.