Atherosclerosis, CoronaryNCT03149042
Validation of a Computed Tomography (CT) Based Fractional Flow Reserve (FFR) Software Using the 320 Detector Aquilion ONE CT Scanner.
An observational study of Atherosclerosis, Coronary, run by State University of New York at Buffalo at 1 site in United States.
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. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Atherosclerosis, Coronary
- What is being tested?
- CCTA
- How many people
- 75 participants
- Where
- 1 siteUnited States
- Study dates
- 28 May 2016to 21 Apr 2019
- Phase
- Observational
- Are there results?
- Yes, posted in the registrySummary in the doctors' view
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Patients who are (1) scheduled for clinically mandated elective invasive coronary angiography (ICA) at Buffalo General Hospital or Juntendo Hospital Japan (2) clinically mandated CTA will be screened.
Who may be able to join
- 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.
Who cannot join
- 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),
Show all 11Show fewer
- 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
Trial locations and contacts
1 site in 1 country.
United States1 site
Clinical and Translational Research Center Room 8052
Buffalo, New York, 14021
About this study
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.
Read the detailed 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.
- Conditions
- Atherosclerosis, Coronary
- Being tested
- CCTA
- Keywords
- FFR, Fractional Flow Reserve, Atherosclerosis, Coronary, stenosis
- Medical subject headings
- Coronary Artery Disease, Atherosclerosis, Constriction, Pathologic
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
CCTADiagnostic test
Diagnostic Test
| Study group | Role | What they receive |
|---|---|---|
| CCTA | Patients who are scheduled for clinically mandated elective invasive coronary angiography (ICA) at Buffalo General Hospital. Receives: Diagnostic Test: CCTA |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: 24 hours
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
Measured: 24 hours
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
Measured: 24 hours
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
Measured: 24 hours
Secondary outcomes (5)
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.
Measured: 4 weeks from baseline
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.
Measured: 4 weeks from baseline
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.
Measured: 4 weeks from baseline
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
Measured: 4 weeks from baseline
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
Measured: 4 weeks from baseline
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted11 May 2017
- Study start28 May 2016
- Primary completion31 Dec 2018
- Study completion21 Apr 2019
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Posted resultsParticipant flow, outcome measures and adverse events reported by the sponsor.
- Publications (9)Papers the sponsor has linked to this study.
- Other trials for Atherosclerosis, CoronaryStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 75 participants (actual)
Sponsor and investigators
- Lead sponsor
- State University of New York at Buffalo
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Ciprian Ionita, State University of New York at Buffalo
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03149042
- Sponsor's protocol ID
- 01
- Status last verified
- Nov 2020
- First submitted
- 8 May 2017
- Last updated
- 17 Nov 2020
- Results posted
- Yes, on ClinicalTrials.gov
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- Yes
- Individual data sharing
- No
Publications
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;10138:101380R. doi: 10.1117/12.2253711. Epub 2017 Mar 13.
PubMed 28663663Ionita, 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
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 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.
PubMed 30891468Sommer 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;10578:105780J. doi: 10.1117/12.2292736. Epub 2018 Mar 12.
PubMed 29899591Shepard 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;10138:101380S. doi: 10.1117/12.2253889. Epub 2017 Mar 13.
PubMed 28649159Kelsey 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
Sommer KN, Shepard LM, Mitsouras D, Iyer V, Angel E, Wilson MF, Rybicki FJ, Kumamaru KK, Sharma UC, Reddy A, Fujimoto S, Ionita CN. Patient-specific 3D-printed coronary models based on coronary computed tomography angiography volumes to investigate flow conditions in coronary artery disease. Biomed Phys Eng Express. 2020 May 14;6(4):045007. doi: 10.1088/2057-1976/ab8f6e.
PubMed 33444268Kumamaru KK, Angel E, Sommer KN, Iyer V, Wilson MF, Agrawal N, Bhardwaj A, Kattel SB, Kondziela S, Malhotra S, Manion C, Pogorzelski K, Ramanan T, Sawant AC, Suplicki MM, Waheed S, Fujimoto S, Sharma UC, Rybicki FJ, Ionita CN. Inter- and Intraoperator Variability in Measurement of On-Site CT-derived Fractional Flow Reserve Based on Structural and Fluid Analysis: A Comprehensive Analysis. Radiol Cardiothorac Imaging. 2019 Aug 29;1(3):e180012. doi: 10.1148/ryct.2019180012. eCollection 2019 Aug.
PubMed 33778507
Study at a glance
From the registry record, last updated by the sponsor on 17 Nov 2020. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Validation of a Computed Tomography (CT) Based Fractional Flow Reserve (FFR) Software Using the 320 Detector Aquilion ONE CT Scanner.
- ClinicalTrials.gov ID
- NCT03149042
- Acronym / sponsor ID
- 01
- Conditions
- Atherosclerosis, Coronary
- Keywords
- FFR, Fractional Flow Reserve, Atherosclerosis, Coronary, stenosis
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 75 participants (actual)
- Lead sponsor
- State University of New York at BuffaloUniversity, hospital or other
- Study start
- 28 May 2016 (actual)
- Primary completion
- 31 Dec 2018 (actual)
- Study completion
- 21 Apr 2019 (actual)
- First posted
- 11 May 2017 (actual)
- Results
- Posted 23 Jun 2020
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed 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.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| CCTA | – | Diagnostic Test: CCTAPatients who are scheduled for clinically mandated elective invasive coronary angiography (ICA) at Buffalo General Hospital. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Patients who are (1) scheduled for clinically mandated elective invasive coronary angiography (ICA) at Buffalo General Hospital or Juntendo Hospital Japan (2) clinically mandated CTA will be screened.
Key inclusion criteria (1 listed)
- 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.
Key exclusion criteria (11 listed)
- Adults unable to consent
- Individuals who are not yet adults (infants, children, teenagers)
- Pregnant women
- Prisoners
- atrial fibrillation,
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| CCTADiagnostic Test | Diagnostic test | CCTA |
Primary outcome
Comparison of CT Based FFR With Invasive FFR, ROC Analysis
Time frame: 24 hours
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.
Comparison of CT Based FFR With Invasive FFR, Correlation Analysis
Time frame: 24 hours
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
Comparison of CT Based FFR With Invasive FFR, Sensitivity
Time frame: 24 hours
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
Comparison of CT Based FFR With Invasive FFR, Specificity
Time frame: 24 hours
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
5 secondary outcomes
Comparison of CT Based FFR With Bench-top FFR Using 3D Printed Patient Specific Phantoms
Time frame: 4 weeks from baseline
Comparison of Bench-top FFR Using 3D Printed Patient Specific Phantoms With Invasive FFR, ROC Analysis
Time frame: 4 weeks from baseline
Comparison of Bench-top FFR Using 3D Printed Patient Specific Phantoms With Invasive FFR, Pearson Correlation
Time frame: 4 weeks from baseline
Comparison of Bench-top FFR Using 3D Printed Patient Specific Phantoms With Invasive FFR, Sensitivity
Time frame: 4 weeks from baseline
Comparison of Bench-top FFR Using 3D Printed Patient Specific Phantoms With Invasive FFR, Specificity
Time frame: 4 weeks from baseline
Results and safety
Loading the posted results from ClinicalTrials.gov…
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 17 Nov 2020.
- Posted resultsParticipant flow, baseline, all outcome measures and adverse events.
- Background: PubMed 28663663Sommer 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;10138:101380R. doi: 10.1117/12.2253711. Epub 2017 Mar 13.
- BackgroundIonita, 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
- BackgroundKelsey 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);
- Background: PubMed 30891468Shepard 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.
- Background: PubMed 29899591Sommer 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;10578:105780J. doi: 10.1117/12.2292736. Epub 2018 Mar 12.
- Background: PubMed 28649159Shepard 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;10138:101380S. doi: 10.1117/12.2253889. Epub 2017 Mar 13.
- BackgroundKelsey 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
- Results publication: PubMed 33444268Sommer KN, Shepard LM, Mitsouras D, Iyer V, Angel E, Wilson MF, Rybicki FJ, Kumamaru KK, Sharma UC, Reddy A, Fujimoto S, Ionita CN. Patient-specific 3D-printed coronary models based on coronary computed tomography angiography volumes to investigate flow conditions in coronary artery disease. Biomed Phys Eng Express. 2020 May 14;6(4):045007. doi: 10.1088/2057-1976/ab8f6e.
- Results publication: PubMed 33778507Kumamaru KK, Angel E, Sommer KN, Iyer V, Wilson MF, Agrawal N, Bhardwaj A, Kattel SB, Kondziela S, Malhotra S, Manion C, Pogorzelski K, Ramanan T, Sawant AC, Suplicki MM, Waheed S, Fujimoto S, Sharma UC, Rybicki FJ, Ionita CN. Inter- and Intraoperator Variability in Measurement of On-Site CT-derived Fractional Flow Reserve Based on Structural and Fluid Analysis: A Comprehensive Analysis. Radiol Cardiothorac Imaging. 2019 Aug 29;1(3):e180012. doi: 10.1148/ryct.2019180012. eCollection 2019 Aug.
- resultsLink provided by the sponsor.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Atherosclerosis, Coronary, run by State University of New York at Buffalo at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 11 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 17 Nov 2020. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Yes. Results are posted in the registry (first posted 23 Jun 2020). A summary is in the For doctors view, and the full results are on ClinicalTrials.gov.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Comparison of CT Based FFR With Invasive FFR, ROC Analysis (time frame: 24 hours). The study lists 4 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT03149042, which also lists 9 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 17 Nov 2020.