Validation of a Computed Tomography (CT) Based Fractional Flow Reserve (FFR) Software Using the 320 Detector Aquilion ONE CT Scanner.

Atherosclerosis, Coronary Clinical Trial

Official title:

Validation of a Computed Tomography (CT) Based Fractional Flow Reserve (FFR) Software Using the 320 Detector Aquilion ONE CT Scanner.

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT03149042
• Other study ID #: 01
• Status: Completed
• Start date: May 28, 2016
• Est. completion date: April 21, 2019

Study information

• Verified date: November 2020
• Source: State University of New York at Buffalo
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

Coronary Computed Tomography Angiography (CCTA) contrast opacification gradients and FFR-CT estimation can aid in the severity estimation of significant atherosclerotic lesions. Currently, FFR-CT algorithms can only be optimized using theoretical models and can only be validated in large multi-center clinical trials. Using patient specific 3D printed coronary phantoms would allow optimization of FFR-CT algorithms with a measured validation technique without the need for large clinical trials. Thus the investigators believe that this study will result in a FFR-CT algorithm/method with a better predictability for arterial lesion severity than those existing on the market today. Flow measurements will be compared with: CT-FFR for both patients and phantoms, angio lab FFR measurements and 30 days follow-up. This pilot clinical study includes ~50 patients over a year and half at GVI.

Description:

Coronary Computed Tomography Angiography (CCTA) contrast opacification gradients and FFR-CT estimation can aid in the severity estimation of significant atherosclerotic lesions. Following this trend, the investigators recently developed a collaboration between Brigham and Women's Hospital (BWH) and Gates Vascular Institute (GVI). The investigators 3D-printed patient specific coronary phantoms at (GVI) and scanned them with a Toshiba Aquilion scanner to test several aspects of the contrast opacification gradients using a method established at BWH. The initial results showed strong correlation between the flow in the phantom and opacification gradients. The investigators believe that this approach could be further developed to test and validate FFR-CT algorithms. Currently, FFR-CT algorithms can only be optimized using theoretical models and can only be validated in large multi-center clinical trials. This phantom approach would allow optimization of FFR-CT algorithms with a measured validation technique without the need for large clinical trials. Thus the investigators believe that this study will result in a FFR-CT algorithm/method with a better predictability for arterial lesion severity than those existing on the market today. The approach is to use the infrastructure at GVI to perform a detailed validation of the FFR-CT method using 3D printed patient specific phantoms. The subject enrollment criteria is: at least one CCTA, at least one lesion with >50% stenosis or 30-50% and an angio based FFR. Each patient will have a 3D phantom printed, containing the culprit lesion and used in a benchtop flow analysis. Flow measurements will be compared with: CT-FFR for both patients and phantoms, angio lab FFR measurements and 30 days follow-up. This pilot clinical study will include ~50 patients over a year and half at GVI. The investigators are confident that this approach performed via 3D-phantom testing will prove the validity of FFR-CT based measurements as well as develop a new standard for validating FFR-CT algorithms.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 75
• Est. completion date: April 21, 2019
• Est. primary completion date: December 31, 2018
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

• All the patients >18 yrs of age , who are undergoing CCTA and angio-FFR. Patients who are (1) scheduled for clinically mandated elective invasive coronary angiography (ICA) at Buffalo General Hospital or (2) clinically mandated CTA will be screened.

Exclusion Criteria:

• Adults unable to consent
• Individuals who are not yet adults (infants, children, teenagers)
• Pregnant women
• Prisoners
• atrial fibrillation,
• Renal insufficiency (estimated glomerular filtration rate (GFR) <60 ml/min/1.73 m2),
• Active Bronchospasm prohibiting the use of beta blockers
• Morbid obesity (body mass index 40 kg/m2)
• Contraindications to iodinated contrast.
• Emergencies requiring immediate intervention or patients unable to consent.
• Patients not showing coronary calcium during Calcium Scoring procedures

Related Conditions & MeSH terms

• Atherosclerosis
• Atherosclerosis, Coronary
• Coronary Artery Disease
• Myocardial Ischemia

Intervention

Diagnostic Test:
• CCTA
Diagnostic Test

Locations

Country	Name	City	State
United States	Clinical and Translational Research Center Room 8052	Buffalo	New York

Sponsors (1)

Lead Sponsor	Collaborator
State University of New York at Buffalo

Country where clinical trial is conducted

United States, 

References & Publications (9)

Ionita, C., Angel, E., Mitsouras, D., Rudin, S., Bednarek, D., Zaid, S., Wilson, M. and Rybicki, F. (2016), TU-H-CAMPUS-IeP2-03: Development of 3D Printed Coronary Phantoms for In-Vitro CT-FFR Validation Using Data from 320- Detector Row Coronary CT Angiography. Med. Phys., 43: 3781. doi:10.1118/1.4957681

Kanako K. Kumamaru , Erin Angel, Kelsey N. Sommer, Vijay Iyer, Michael F. Wilson, Nikhil Agrawal, Aishwarya Bhardwaj, Sharma B. Kattel, Sandra Kondziela, Saurabh Malhotra, Christopher Manion, Katherine Pogorzelski, Tharmathai Ramanan, Abhishek C. Sawant,

Kelsey N. Sommer, Lauren M. Shepard, Vijay Iyer, Erin Angel, Michael F. Wilson, Frank J. Rybicki, Dimitrios Mitsouras, Ciprian Ionita. Study of the effect of boundary conditions on fractional flow reserve using patient specific coronary phantoms. Proceedings Volume 11317, Medical Imaging 2020: Biomedical Applications in Molecular, Structural, and Functional Imaging; 113171J (2020) https://doi.org/10.1117/12.2548472

Kelsey N. Sommer, Lauren M. Shepard, Vijay Iyer, Erin Angel, Michael F. Wilson, Frank J. Rybicki, Dimitrios Mitsouras, Kanako Kunishima Kumamaru, Stephen Rudin, and Ciprian N. Ionita. Comparison of benchtop pressure gradient measurements in 3D printed patient specific cardiac phantoms with CT-FFR and computational fluid dynamic simulations, Proc. SPIE 10953, Medical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging, 109531P (15 March 2019);

Shepard L, Sommer K, Izzo R, Podgorsak A, Wilson M, Said Z, Rybicki FJ, Mitsouras D, Rudin S, Angel E, Ionita CN. Initial Simulated FFR Investigation Using Flow Measurements in Patient-specific 3D Printed Coronary Phantoms. Proc SPIE Int Soc Opt Eng. 2017 Feb 11;10138. pii: 101380S. doi: 10.1117/12.2253889. Epub 2017 Mar 13. — View Citation

Shepard LM, Sommer KN, Angel E, Iyer V, Wilson MF, Rybicki FJ, Mitsouras D, Molloi S, Ionita CN. Initial evaluation of three-dimensionally printed patient-specific coronary phantoms for CT-FFR software validation. J Med Imaging (Bellingham). 2019 Apr;6(2):021603. doi: 10.1117/1.JMI.6.2.021603. Epub 2019 Mar 12. — View Citation

Sommer K, Izzo RL, Shepard L, Podgorsak AR, Rudin S, Siddiqui AH, Wilson MF, Angel E, Said Z, Springer M, Ionita CN. Design Optimization for Accurate Flow Simulations in 3D Printed Vascular Phantoms Derived from Computed Tomography Angiography. Proc SPIE Int Soc Opt Eng. 2017 Feb 11;10138. pii: 101380R. doi: 10.1117/12.2253711. Epub 2017 Mar 13. — View Citation

Sommer KN, Shepard L, Karkhanis NV, Iyer V, Angel E, Wilson MF, Rybicki FJ, Mitsouras D, Rudin S, Ionita CN. 3D Printed Cardiovascular Patient Specific Phantoms Used for Clinical Validation of a CT-derived FFR Diagnostic Software. Proc SPIE Int Soc Opt Eng. 2018 Feb;10578. pii: 105780J. doi: 10.1117/12.2292736. Epub 2018 Mar 12. — View Citation

Sommer KN, Shepard LM, Mitsouras D, Iyer V, Angel E, Wilson MF, et al. Patient-specific 3d-printed coronary models based on coronary computed tomography angiography volumes to investigate flow conditions in coronary artery disease. Biomedical Physics & En

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Comparison of CT Based FFR With Invasive FFR, ROC Analysis	Patient CCTA images were imported into Vitrea segmentation software (Vital Images, Minnetonka, MN) for use in the research-based CT based FFR algorithm. The software analyzes four data volumes acquired a 70%, 80%, 90% and 99% of the R-R interval and computes the FFR based on the changes in vessel diameter and computational fluid dynamics. Within the algorithm, the aortic root and three main coronary arteries (LAD, LCX, and RCA) were automatically segmented, and then manually adjusted to obtain accurate centerline and contours. The CT based FFR was calculated and the user adjusted the location of the distal pressure measurement to calculate the CT basedFFR at the same location as Invasive-FFR, two lesion lengths below the distal end of the lesion.; Area under the Receiver Operator Characteristic were measured where an Invasive FFR<=0.8 was considered positive.	24 hours
Primary	Comparison of CT Based FFR With Invasive FFR, Correlation Analysis	Patient CCTA images were imported into Vitrea segmentation software (Vital Images, Minnetonka, MN) for use in the research-based CT based FFR algorithm. The software analyzes four data volumes acquired a 70%, 80%, 90% and 99% of the R-R interval and computes the FFR based on the changes in vessel diameter and computational fluid dynamics. Within the algorithm, the aortic root and three main coronary arteries (LAD, LCX, and RCA) were automatically segmented, and then manually adjusted to obtain accurate centerline and contours. The CT based FFR was calculated and the user adjusted the location of the distal pressure measurement to calculate the CT basedFFR at the same location as Invasive-FFR, two lesion lengths below the distal end of the lesion.; Pearson Correlation between Invasive FFR and CT based FFR was measured	24 hours
Primary	Comparison of CT Based FFR With Invasive FFR, Sensitivity	Patient CCTA images were imported into Vitrea segmentation software (Vital Images, Minnetonka, MN) for use in the research-based CT based FFR algorithm. The software analyzes four data volumes acquired a 70%, 80%, 90% and 99% of the R-R interval and computes the FFR based on the changes in vessel diameter and computational fluid dynamics. Within the algorithm, the aortic root and three main coronary arteries (LAD, LCX, and RCA) were automatically segmented, and then manually adjusted to obtain accurate centerline and contours. The CT based FFR was calculated and the user adjusted the location of the distal pressure measurement to calculate the CT basedFFR at the same location as Invasive-FFR, two lesion lengths below the distal end of the lesion.; Sensitivity were measured where an Invasive FFR<=0.8 was considered positive. Sensitivity reflects the percentage of true positive cases identified by CT-FFR compared to I-FFR	24 hours
Primary	Comparison of CT Based FFR With Invasive FFR, Specificity	Patient CCTA images were imported into Vitrea segmentation software (Vital Images, Minnetonka, MN) for use in the research-based CT based FFR algorithm. The software analyzes four data volumes acquired a 70%, 80%, 90% and 99% of the R-R interval and computes the FFR based on the changes in vessel diameter and computational fluid dynamics. Within the algorithm, the aortic root and three main coronary arteries (LAD, LCX, and RCA) were automatically segmented, and then manually adjusted to obtain accurate centerline and contours. The CT based FFR was calculated and the user adjusted the location of the distal pressure measurement to calculate the CT basedFFR at the same location as Invasive-FFR, two lesion lengths below the distal end of the lesion.; Specificity was measured, where an Invasive FFR<=0.8 was considered positive. Specificity reflects the percentage of true negative cases identified by CT-FFR compared to I-FFR	24 hours
Secondary	Comparison of CT Based FFR With Bench-top FFR Using 3D Printed Patient Specific Phantoms	CT images were used to measure CT-FFR and to generate patient-specific 3D printed models of the aortic root and three main coronary arteries. Each patient-specific 3D printed model was connected to a programmable pulsatile pump and bench-top FFR (B-FFR) was derived from pressures measured proximal and distal to coronary stenosis using pressure transducers. B-FFR was measured for hyperemic", 500 mL/min by adjusting the model's distal coronary resistance. Linear regression and Pearson correlation was calculated.	4 weeks from baseline
Secondary	Comparison of Bench-top FFR Using 3D Printed Patient Specific Phantoms With Invasive FFR, ROC Analysis	CT images were used to create patient specific 3d-printed phantom. Each patient-specific 3D printed model was connected to a programmable pulsatile pump and benchtop FFR (B-FFR) was derived from pressures measured proximal and distal to coronary stenosis using pressure transducers. B-FFR was measured for hyperemic", 500 mL/min by adjusting the model's distal coronary resistance. Benchtop-FFR was compared with Invasive-FFR. Area under the Receiver Operator Characteristic were measured where an Invasive FFR<=0.8 was considered positive.	4 weeks from baseline
Secondary	Comparison of Bench-top FFR Using 3D Printed Patient Specific Phantoms With Invasive FFR, Pearson Correlation	CT images were used to create patient specific 3d-printed phantom. Each patient-specific 3D printed model was connected to a programmable pulsatile pump and benchtop FFR (B-FFR) was derived from pressures measured proximal and distal to coronary stenosis using pressure transducers. B-FFR was measured for hyperemic", 500 mL/min by adjusting the model's distal coronary resistance. Benchtop-FFR was compared with Invasive-FFR. Pearson Correlation factor was calculated.	4 weeks from baseline
Secondary	Comparison of Bench-top FFR Using 3D Printed Patient Specific Phantoms With Invasive FFR, Sensitivity	CT images were used to create patient specific 3d-printed phantom. Each patient-specific 3D printed model was connected to a programmable pulsatile pump and benchtop FFR (B-FFR) was derived from pressures measured proximal and distal to coronary stenosis using pressure transducers. B-FFR was measured for hyperemic", 500 mL/min by adjusting the model's distal coronary resistance. Benchtop-FFR was compared with Invasive-FFR. Sensitivity was measure, where an Invasive FFR<=0.8 was considered positive.Sensitivity reflects the percentage of true positive cases identified by B-FFR compared to I-FFR	4 weeks from baseline
Secondary	Comparison of Bench-top FFR Using 3D Printed Patient Specific Phantoms With Invasive FFR, Specificity	CT images were used to create patient specific 3d-printed phantom. Each patient-specific 3D printed model was connected to a programmable pulsatile pump and benchtop FFR (B-FFR) was derived from pressures measured proximal and distal to coronary stenosis using pressure transducers. B-FFR was measured for hyperemic", 500 mL/min by adjusting the model's distal coronary resistance. Benchtop-FFR was compared with Invasive-FFR. Specificity was calculated, where an Invasive FFR<=0.8 was considered positive. Specificity reflects the percentage of true negative cases identified by B-FFR compared to I-FFR	4 weeks from baseline

External Links

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